Search results for: cascaded H-bridge multilevel inverter

Authors: A. Assif

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This paper presents the modeling of a prototype distribution static compensator (D-STATCOM) for voltage sag and swell mitigation in an unbalanced distribution system. Here the concept that an inverter can be used as generalized impedance converter to realize either inductive or capacitive reactance has been used to mitigate power quality issues of distribution networks. The D-STATCOM is here supposed to replace the widely used StaticVar Compensator (SVC). The scheme is based on the Voltage Source Converter (VSC) principle. In this model PWM based control scheme has been implemented to control the electronic valves of VSC. Phase shift control Algorithm method is used for converter control. The D-STATCOM injects a current into the system to mitigate the voltage sags. In this paper the modeling of D¬STATCOM has been designed using MATLAB SIMULINIC. Accordingly, simulations are first carried out to illustrate the use of D-STATCOM in mitigating voltage sag in a distribution system. Simulation results prove that the D-STATCOM is capable of mitigating voltage sag as well as improving power quality of a system.

Keywords: D-STATCOM, voltage sag, voltage source converter (VSC), phase shift control

Procedia PDF Downloads 343

Authors: Vipresh Mehta , Aman Abhishek, Jatin Batra, Gautam Iyer

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Huge amount of solar radiation reaching the earth can be harnessed to provide electricity through Photo voltaic (PV) panels. The solar PV is an exciting technology but suffers from low efficiency. A study on low efficiency in multi MW solar power plants reveals that the electric yield of the PV modules is reduced due to reflection of the irradiation from the sun and when a module’s temperature is elevated, as there is decrease in the voltage and efficiency. We intend to alter the structure of the PV system, We also intend to improve the efficiency of the Solar Photo Voltaic Panels by active cooling to reduce the temperature losses considerably and decrease reflection losses to some extent. Reflectors/concentrators and anti-reflecting coatings are also used to intensify the amount of output produced from the system. Apart from this, transformer-less Grid-tied Inverter. And also, a T-LCL immitance circuit is used to reduce the harmonics and produce a constant output from the entire system.

Keywords: PV panels, efficiency improvement, active cooling, quantum dots, organic-inorganic hybrid 3D panel, ground water tunneling

Procedia PDF Downloads 772

Authors: Badache Messaoud

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Geothermal thermosyphons (GTs) are increasingly used in many heating and cooling geothermal applications owing to their high heat transfer performance. This paper proposes a response surface methodology (RSM) to investigate and optimize the performance of a CO2 geothermal thermosyphon. The filling ratio (FR), temperature, and flow rate of the heat transfer fluid are selected as the designing parameters, and heat transfer rate and effectiveness are adopted as response parameters (objective functions). First, a dedicated experimental GT test bench filled with CO2 was built and subjected to different test conditions. An RSM was used to establish corresponding models between the input parameters and responses. Various diagnostic tests were used to assess evaluate the quality and validity of the best-fit models, which explain respectively 98.9% and 99.2% of the output result’s variability. Overall, it is concluded from the RSM analysis that the heat transfer fluid inlet temperatures and the flow rate are the factors that have the greatest impact on heat transfer (Q) rate and effectiveness (εff), while the FR has only a slight effect on Q and no effect on εff. The maximal heat transfer rate and effectiveness achieved are 1.86 kW and 47.81%, respectively. Moreover, these optimal values are associated with different flow rate levels (mc level = 1 for Q and -1 for εff), indicating distinct operating regions for maximizing Q and εff within the GT system. Therefore, a multilevel optimization approach is necessary to optimize both the heat transfer rate and effectiveness simultaneously.

Keywords: geothermal thermosiphon, co2, Response surface methodology, heat transfer performance

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Authors: Emmanuel Chibuogu Asogwa, Tochukwu Sunday Belonwu

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An urgent demand for creative solutions has been created by the rapid expansion of medical knowledge, the complexity of patient care, and the requirement for more precise decision-making. As a solution to this problem, the creation of a Medical Intelligent Process Model (MIPM) utilizing ontology-based appears as a promising way to overcome this obstacle and unleash the full potential of healthcare systems. The development of a Medical Intelligent Process Model (MIPM) using ontology-based techniques is motivated by a lack of quick access to relevant medical information and advanced tools for treatment planning and clinical decision-making, which ontology-based techniques can provide. The aim of this work is to develop a structured and knowledge-driven framework that leverages ontology, a formal representation of domain knowledge, to enhance various aspects of healthcare. Object-Oriented Analysis and Design Methodology (OOADM) were adopted in the design of the system as we desired to build a usable and evolvable application. For effective implementation of this work, we used the following materials/methods/tools: the medical dataset for the test of our model in this work was obtained from Kaggle. The ontology-based technique was used with Confusion Matrix, MySQL, Python, Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), Cascaded Style Sheet (CSS), JavaScript, Dreamweaver, and Fireworks. According to test results on the new system using Confusion Matrix, both the accuracy and overall effectiveness of the medical intelligent process significantly improved by 20% compared to the previous system. Therefore, using the model is recommended for healthcare professionals.

Keywords: ontology-based, model, database, OOADM, healthcare

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Authors: Yanrong Song, Zikai Dong, Runqin Xu, Jinrong Tian, Kexuan Li

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Nonlinear polarization rotation (NPR) technique has become one of the main techniques to achieve mode-locked fiber lasers for its compactness, implementation, and low cost. In this paper, we demonstrate a compact mode-locked Yb-doped fiber laser based on NPR technique in the all normal dispersion (ANDi) regime. In the laser cavity, there are no physical filter and polarization controller in laser cavity. Mode-locked pulse train is achieved in ANDi regime based on NPR technique. The fiber birefringence induced filtering effect is the mainly reason for mode-locking. After that, an extra 20 m long single-mode fiber is inserted in two different positions, dissipative soliton operation and noise like pulse operations are achieved correspondingly. The nonlinear effect is obviously enhanced in the noise like pulse regime and broadband spectrum generated owing to enhanced stimulated Raman scattering effect. When the pump power is 210 mW, the central wavelength is 1030 nm, and the corresponding 1st order Raman scattering stokes wave generates and locates at 1075 nm. When the pump power is 370 mW, the 1st and 2nd order Raman scattering stokes wave generate and locate at 1080 nm, 1126 nm respectively. When the pump power is 600 mW, the Raman continuum is generated with cascaded multi-order stokes waves, and the spectrum extends to 1188 nm. The total flat spectrum is from 1000nm to 1200nm. The maximum output average power and pulse energy are 18.0W and 14.75nJ, respectively.

Keywords: fiber laser, mode-locking, nonlinear polarization rotation, Raman scattering

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Authors: William Xiu Shun Wong, Myungsu Lim, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Kee-Young Kwahk, Namgyu Kim

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Recently, many users have begun to frequently share their opinions on diverse issues using various social media. Therefore, numerous governments have attempted to establish or improve national policies according to the public opinions captured from various social media. In this paper, we indicate several limitations of the traditional approaches to analyze public opinion on science and technology and provide an alternative methodology to overcome these limitations. First, we distinguish between the science and technology analysis phase and the social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we successively apply a start list and a stop list to acquire clarified and interesting results. Finally, to identify the most appropriate documents that fit with a given subject, we develop a new logical filter concept that consists of not only mere keywords but also a logical relationship among the keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discover core issues and public opinions from 1,700,886 documents comprising SNS, blogs, news, and discussions.

Keywords: big data, social network analysis, text mining, topic modeling

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Authors: Hailu Dessalegn, T. Srinivas

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We propose new multiple-channel piezoelectric (PZT) actuated tunable optical filter based on racetrack multi-ring resonators for wavelength de-multiplexing network applications. We design tunable eight-channel wavelength de-multiplexer consisting of eight cascaded PZT actuated tunable multi-ring resonator filter with a channel spacing of 1.6 nm. The filter for each channel is basically structured on a suspended beam, sandwiched with piezoelectric material and built in integrated ring resonators which are placed on the middle of the beam to gain uniform stress and linearly varying longitudinal strain. A reference single mode serially coupled multi stage racetrack ring resonator with the same radii and coupling length is designed with a line width of 0.8974 nm with a flat top pass band at 1dB of 0.5205 nm and free spectral range of about 14.9 nm. In each channel, a small change in the perimeter of the rings is introduced to establish the shift in resonance wavelength as per the defined channel spacing. As a result, when a DC voltage is applied, the beams will elongate, which involves mechanical deformation of the ring resonators that induces a stress and a strain, which brings a change in refractive index and perimeter of the rings leading to change in the output spectrum shift providing the tunability of central wavelength in each channel. Simultaneous wave length shift as high as 45.54 pm/V has been achieved with negligible tunability variation in the eight channel tunable optical filter proportional to the DC voltage applied in the structure, and it is capable of tuning up to 3.45 nm in each channel with a maximum loss difference of 0.22 dB in the tuning range and out of band rejection ratio of 35 dB, with a low channel crosstalk ≤ 30 dB.

Keywords: optical MEMS, piezoelectric (PZT) actuation, tunable optical filter, wavelength de-multiplexer

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Authors: Yiwei Li, Boyu Tian, Mingyu Gao

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Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant metadata storage and lookup overheads for flexibly remapping data blocks between the two memory tiers. To alleviate the inefficiencies of existing designs, we propose Trimma, the combination of a multi-level metadata structure and an efficient metadata cache design. Trimma uses a multilevel metadata table to only track truly necessary address remap entries. The saved memory space is effectively utilized as extra DRAM cache capacity to improve performance. Trimma also uses separate formats to store the entries with non-identity and identity mappings. This improves the overall remap cache hit rate, further boosting the performance. Trimma is transparent to software and compatible with various types of hybrid memory systems. When evaluated on a representative DDR4 + NVM hybrid memory system, Trimma achieves up to 2.4× and on average 58.1% speedup benefits, compared with a state-of-the-art design that only leverages the unallocated fast memory space for caching. Trimma addresses metadata management overheads and targets future scalable large-scale hybrid memory architectures.

Keywords: memory system, data cache, hybrid memory, non-volatile memory

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Authors: Frie Ayalew, Seada Hussen

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Ethio-telecom holds a variety of telecom devices that needs a consistent power source to be operational. The company got this power mainly from the national grid and used this power source alone or with a generator and/or batteries as a backup. In addition, for off-grid or remote areas, the company commonly uses generators and batteries. But unstable diesel prices, huge expenses of fuel and transportation, and high carbon emissions are the main problems associated with fuel energy. So, the design of solar power with battery backup is a highly recommended and advantageous source for the next coming years. This project designs the AC and DC standalone photovoltaic supply to Ethio-telecom access layer devices for the case of multi-service access gateway in Adama. The design is done by using Homer software for both AC and DC loads. The project shows that the design of a solar based microgrid is the best option for the designed area.

Keywords: solar power, battery, inverter, Ethio-telecom, solar radiation

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Authors: V. S. Klimash, Ye Min Thu

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Thyristor rectifiers, inverters grid-tied, and AC voltage regulators are widely used in industry, and on electrified transport, they have a lot in common both in the power circuit and in the control system. They have a common mathematical structure and switching processes. At the same time, the rectifier, but the inverter units and thyristor regulators of alternating voltage are considered separately both theoretically and practically. They are written about in different books as completely different devices. The aim of this work is to combine them into one class based on the unity of the equations describing electromagnetic processes, and then, to show this unity on the mathematical model and experimental setup. Based on research from mathematics to the product, a conclusion is made about the methodology for the rapid conduct of research and experimental design work, preparation for production and serial production of converters with a unified bundle. In recent years, there has been a transition from thyristor circuits and transistor in modular design. Showing the example of thyristor rectifiers and AC voltage regulators, we can conclude that there is a unity of mathematical structures and grid-tied thyristor converters.

Keywords: direct current, alternating current, rectifier, AC voltage regulator, generalized mathematical model

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Authors: Benjamas Penboon, Zachary Zimmer, Aree Jampaklay

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Cambodia is a country where labor migration has been consistently high. Coupled with advancing labor opportunities in urban areas, a function partly of globalization, this is resulting in massive migration out of rural areas. This is particularly true in Cambodia where there are high migration and a very large proportion of adult children living some distant from their parents. This paper explores characteristics associated with migrant providing support to parents in rural Cambodia. With reference to perspectives of family altruism and solidarity, this analysis particularly focusses on how a series of variables representing family integration and residential location associates with intergenerational monetary and instrumental support from migrants. The study hypothesizes that migrants are more likely to provide support when parents are in need, and there are no alternative means of support. Data come from The Rural Household Survey (N=3,713), part of the 2011 Cambodian Rural Urban Migration Project (CRUMP). Multilevel multinomial models indicate international migrants are likely to give money, while internal migrants are likely to provide both money and instrumental support, especially when migrants have no sibling and their parent in poor health status. In addition, employed migrants are two times providing monetary compared to those unemployed. Findings elucidate the decision to which and why support occurs more often when no other source of support exists and also depends on the ability to provide of migrants themselves.

Keywords: migration, left-behind parent, intergenerational relations, support, rural, Cambodia

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Authors: Andreas Livera, Spyros Theocharides, Michalis Florides, Charalambos Anastassiou

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A main challenge in the quest for ensuring quality of operation, especially for photovoltaic (PV) systems, is to safeguard the reliability and optimal performance by detecting and diagnosing potential failures and performance losses at early stages or before the occurrence through real-time monitoring, supervision, fault detection, and predictive maintenance. The purpose of this work is to present the functionalities and results related to the development and validation of a software platform for PV assets diagnosis and maintenance. The platform brings together proprietary hardware sensors and software algorithms to enable the early detection and prediction of the most common and critical faults in PV systems. It was validated using field measurements from operating PV systems. The results showed the effectiveness of the platform for detecting faults and losses (e.g., inverter failures, string disconnections, and potential induced degradation) at early stages, forecasting PV power production while also providing recommendations for maintenance actions. Increased PV energy yield production and revenue can be thus achieved while also minimizing operation and maintenance (O&M) costs.

Keywords: failure detection and prediction, operation and maintenance, performance monitoring, photovoltaic, platform, recommendations, predictive maintenance

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Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Jannes Quer, Amir Niknejad, Marcus Weber

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Computational Drug Design is often based on Molecular Dynamics simulations of molecular systems. Molecular Dynamics can be used to simulate, e.g., the binding and unbinding event of a small drug-like molecule with regard to the active site of an enzyme or a receptor. However, the time-scale of the overall binding event is many orders of magnitude longer than the time-scale of simulation. Thus, there is a need to speed-up molecular simulations. In order to speed up simulations, the molecular dynamics trajectories have to be ”steared” out of local minimizers of the potential energy surface – the so-called metastabilities – of the molecular system. Increasing the kinetic energy (temperature) is one possibility to accelerate simulated processes. However, with temperature the entropy of the molecular system increases, too. But this kind ”stearing” is not directed enough to stear the molecule out of the minimum toward the saddle point. In this article, we give a new mathematical idea, how a potential energy surface can be changed in such a way, that entropy is kept under control while the trajectories are still steared out of the metastabilities. In order to compute the unsteared transition behaviour based on a steared simulation, we propose to use extrapolation methods. In the end we mathematically show, that our method accelerates the simulations along the direction, in which the curvature of the potential energy surface changes the most, i.e., from local minimizers towards saddle points.

Keywords: extrapolation, Eyring-Kramers, metastability, multilevel sampling

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Authors: Robyn Moloney, HuiLing Xu

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Many countries wish to produce Asia-literate citizens, through language education. International contexts of Chinese language education are seeking pedagogical innovation to meet local contextual factors frequently holding back learner success. In multicultural Australia, innovative pedagogy is urgently needed to support motivation in sustained study, with greater strategic integration of technology. This research took a qualitative approach to identify need and solutions. The paper analyses strategies that three secondary school teachers are adopting to meet specific challenges in the Australian context. The data include teacher interviews, classroom observations and student interviews. We highlight the use of task-based learning and differentiated teaching for multilevel classes, and the role which digital technologies play in facilitating both areas. The strategy examples are analysed in reference both to a research-based framework for describing quality teaching, and to current understandings of motivation in language learning. The analysis of data identifies learning featuring deep knowledge, higher-order thinking, engagement, social support, utilisation of background knowledge, and connectedness, all of which work towards the learners having a sense of autonomy and an imagination of becoming an adult Chinese language user.

Keywords: Chinese pedagogy, digital technologies, motivation, secondary school

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Authors: Armin Amindari

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Hermetic compressors are used widely for refrigeration, heat pump, and air conditioning applications. With the improvement of energy conservation and environmental protection requirements, inverter compressors that operates at different speeds have become increasingly attractive in the industry. Although speed change capability is more efficient, passing through resonant frequencies may lead to excessive vibrations. In this work, an integrated vibration control approach based on flexible multi-body dynamics theory is used for optimizing the vibration amplitudes of the compressor at different operating speeds. To examine the compressor vibrations, all the forces and moments exerted on the cylinder block were clarified and minimized using balancers attached to the upper and lower ends of the motor rotor and crankshaft. The vibration response of the system was simulated using Motionview™ software. In addition, mass-spring optimization was adopted to shift the resonant frequencies out of the operating speeds. The modal shapes of the system were studied using Optistruct™ solver. Using this approach, the vibrations were reduced up to 56% through dynamic simulations. The results were in high agreement with various experimental test data. In addition, the vibration resonance problem observed at low speeds was solved by shifting the resonant frequencies through optimization studies.

Keywords: vibration, MBD, compressor, hermetic

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Authors: Marianne Dæhlen

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Periods of apprenticeships are characteristic of many vocational educational training (VET) systems. In many countries, becoming a skilled worker implies that the journey starts with an application for apprenticeships at a company or another relevant training establishment. In Norway, where this study is conducted, VET students start their journey with two years of school-based training before applying for two years of apprenticeship. Previous research has shown that access to apprenticeships differs by family background (socio-economic, immigrant, etc.), gender, school grades, and region. The question we raise in this study is whether the status, reputation, or position of the vocational school contributes to VET students’ access to apprenticeships. Data and methods: Register data containing information about schools’ and VET students’ characteristics will be analyzed in multilevel regression analyses. At the school level, the data will contain information on school size, shares of immigrants and/or share of male/female students, and grade requirements for admission. At the VET-student level, the register contains information on e.g., gender, school grades, educational program/trade, obtaining apprenticeship or not. The data set comprises about 3,000 students. Results: The register data is expected to be received in November 2024 and consequently, any results are not present at the point of this call. The planned article is part of a larger research project granted from the Norwegian Research Council and will, accordingly to the plan, start up in December 2024.

Keywords: apprenticeships, VET-students’ characteristics, vocational schools, quantitative methods

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Authors: Rajkumar Kolangarakandy

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Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

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Authors: N. P. Tien, S. Songsermpong, T. H. Quan

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Mung bean vermicelli is a popular food in Asian countries and is made from mung bean starch. The preparation process involves several steps, including drying, which affects the structure and quality of the vermicelli. This study aims to examine the effects of different drying technologies on the rehydration time and quality of mung bean vermicelli. Three drying technologies, namely hot air drying, microwave continuous drying, and microwave vacuum drying, were used for the drying process. The vermicelli strands were dried at 45°C for 12h in a hot air dryer, at 70 Hz of conveyor belt speed inverter in a microwave continuous dryer, and at 30 W.g⁻¹ of microwave power density in a microwave vacuum dryer. The results showed that mung bean vermicelli dried using hot air drying had the longest rehydration time of 12.69 minutes. On the other hand, vermicelli dried through microwave continuous drying and microwave vacuum drying had shorter rehydration times of 2.79 minutes and 2.14 minutes, respectively. Microwave vacuum drying also resulted in larger porosity, higher water absorption, and cooking loss. The tensile strength and elasticity of vermicelli dried using hot air drying were higher compared to microwave drying technologies. The sensory evaluation did not reveal significant differences in most attributes among the vermicelli treatments. Overall, microwave drying technology proved to be effective in reducing rehydration time and producing good-quality mung bean vermicelli.

Keywords: mung bean vermicelli, drying, hot air, microwave continuous, microwave vacuum

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Authors: Md. Rashed Aalm, Md. Nuruzzaman Khan, Yothin Sawangdee

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Background: Around 47% of the total pregnancies are unintended in Bangladesh, which lead to several adverse consequences, including maternal and child mortality. Use of menstrual regulation (MR) can help women to reduce unintended pregnancy related adverse consequences. We explored the prevalence and determinants of MR services among ever-married women in Bangladesh. Methods: Total of 14,346 ever-married women data were analysed from the 2017 Bangladesh Demographic and Health Survey. Our study variable was use or non-use of MR services. Individual, household, and community level factors were the explanatory factors. Multilevel mixed-effect Poisson regression model was used to determine the factors associated with MR services in Bangladesh. Results: Nearly 7% of the total women in Bangladesh use MR services. Use of MR services was found higher among women who were aged 20-30 ages (IRR 1.60, 95% CI: 1.17–2.17), who were overweight (IRR 1.43, 95% CI: 1.13–1.81), had at least 1 child (IRR 2.97, 95% CI: 2.34– 3.77) or > 2 children (IRR 3.22, 95% CI: 2.45–4.20), and the birth preceding birth interval was(2 – 4) years (IRR 1.56, 95% CI: 1.13–2.15). Around 1.39 times (95% CI: 1.11–1.73) higher likelihood of MR was found among women whose husbands were engage with business. At the community level, MR service was found lower among the women who resided in the community with higherilliteracy (IRR 0.67, 95% CI: 0.42–0.96) and the Mymensingh division (IRR 0.39, 95% CI: 0.31–0.91). Conclusion: Use of MR service is comparatively low, which indicate a significant proportion of unintended pregnancy continued toward life-birth. This could be responsible for higher adverse maternal and child health outcomes in Bangladesh. Initiatives should be taken to ensure MR services is available when women need this service.

Keywords: menstrual regulation, pattern, risk, maternal health, Bangladesh

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Authors: X. Li, J. Sundquist, C. Sjöstedt, M. Winkleby, K. S. Kendler, K. Sundquist

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Aims: This study examines the association between the incidence of drug abuse (DA) and linking (communal) social capital, a theoretical concept describing the amount of trust between individuals and societal institutions. Methods: We present results from an 8-year population-based cohort study that followed all residents in Sweden, aged 15-44, from 2003 through 2010, for a total of 1,700,896 men and 1,642,798 women. Social capital was conceptualized as the proportion of people in a geographically defined neighborhood who voted in local government elections. Multilevel logistic regression was used to estimate odds ratios (ORs) and between-neighborhood variance. Results: We found robust associations between linking social capital (scored as a three level variable) and DA in men and women. For men, the OR for DA in the crude model was 2.11 [95% confidence interval (CI) 2.02-2.21] for those living in areas with the lowest vs. highest level of social capital. After accounting for neighborhood-level deprivation, the OR fell to 1.59 (1.51-1-68), indicating that neighborhood deprivation lies in the pathway between linking social capital and DA. The ORs remained significant after accounting for age, sex, family income, marital status, country of birth, education level, and region of residence, and after further accounting for comorbidities and family history of comorbidities and family history of DA. For women, the OR decreased from 2.15 (2.03-2.27) in the crude model to 1.31 (1.22-1.40) in the final model, adjusted for multiple neighborhood-level and individual-level variables. Conclusions: Our study suggests that low linking social capital may have important independent effects on DA.

Keywords: drug abuse, social linking capital, environment, family

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Authors: Malinwo Estone Ayikpa

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Electric power systems are likely to operate with minimum losses and voltage meeting international standards. This is made possible generally by control actions provide by automatic voltage regulators, capacitors and transformers with on-load tap changer (OLTC). With the development of photovoltaic (PV) systems technology, their integration on distribution networks has increased over the last years to the extent of replacing the above mentioned techniques. The conventional analysis and simulation tools used for electrical networks are no longer able to take into account control actions necessary for studying distributed PV generation impact. This paper presents an unbalanced optimal power flow (OPF) model that minimizes losses with association of active power generation and reactive power control of single-phase and three-phase PV systems. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The unbalance OPF is formulated by current balance equations and solved by primal-dual interior point method. Several simulation cases have been carried out varying the size and location of PV systems and the results show a detailed view of the impact of PV distributed generation on distribution systems.

Keywords: distribution system, loss, photovoltaic generation, primal-dual interior point method

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Authors: Damir Latypov

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A hybrid classical-quantum algorithm to solve boundary integral equations (BIE) arising in problems of electromagnetic and acoustic scattering is proposed. The quantum speed-up is due to a Quantum Linear System Algorithm (QLSA). The original QLSA of Harrow et al. provides an exponential speed-up over the best-known classical algorithms but only in the case of sparse systems. Due to the non-local nature of integral operators, matrices arising from discretization of BIEs, are, however, dense. A QLSA for dense matrices was introduced in 2017. Its runtime as function of the system's size N is bounded by O(√Npolylog(N)). The run time of the best-known classical algorithm for an arbitrary dense matrix scales as O(N².³⁷³). Instead of exponential as in case of sparse matrices, here we have only a polynomial speed-up. Nevertheless, sufficiently high power of this polynomial, ~4.7, should make QLSA an appealing alternative. Unfortunately for the QLSA, the asymptotic separability of the Green's function leads to high compressibility of the BIEs matrices. Classical fast algorithms such as Multilevel Fast Multipole Method (MLFMM) take advantage of this fact and reduce the runtime to O(Nlog(N)), i.e., the QLSA is only quadratically faster than the MLFMM. To be truly impactful for computational electromagnetics and acoustics engineers, QLSA must provide more substantial advantage than that. We propose a computational scheme which combines elements of the classical fast algorithms with the QLSA to achieve the required performance.

Keywords: quantum linear system algorithm, boundary integral equations, dense matrices, electromagnetic scattering theory

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Authors: Shara Toibayeva, Irbulat Utepbergenov, Lyazzat Issabekova, Aidana Bodesova

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The article discusses the importance of quality assessment as a strategic tool in business and emphasizes the significance of the effectiveness of quality management systems (QMS) for enterprises. The evaluation of these systems takes into account the specificity of quality indicators, the multilevel nature of the system, and the need for optimal selection of the number of indicators and evaluation of the system state, which is critical for making rational management decisions. Methods and models of automated enterprise quality management are proposed, including an intelligent automated quality management system integrated with the Management Information and Control System. These systems make it possible to automate the implementation and support of QMS, increasing the validity, efficiency, and effectiveness of management decisions by automating the functions performed by decision makers and personnel. The paper also emphasizes the use of recurrent neural networks to improve automated quality management. Recurrent neural networks (RNNs) are used to analyze and process sequences of data, which is particularly useful in the context of document quality assessment and non-conformance detection in quality management systems. These networks are able to account for temporal dependencies and complex relationships between different data elements, which improves the accuracy and efficiency of automated decisions. The project was supported by a grant from the Ministry of Education and Science of the Republic of Kazakhstan under the Zhas Galym project No. AR 13268939, dedicated to research and development of digital technologies to ensure consistency of QMS regulatory documents.

Keywords: automated control system, quality management, document structure, formal language

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Authors: Ali Mashayekh, Mahdiye Khorasani, Thomas Weyh

Abstract:

The tendency to use the Battery-Electric vehicle (BEV) for the low and medium driving range or even high driving range has been growing more and more. As a result, higher safety, reliability, and durability of the battery pack as a component of electric vehicles, which has a great share of cost and weight of the final product, are the topics to be considered and investigated. Battery aging can be considered as the predominant factor regarding the reliability and durability of BEV. To better understand the aging process, offline battery characterization has been widely used, which is time-consuming and needs very expensive infrastructures. This paper presents the substitute method for the conventional battery characterization methods, which is based on battery Modular Multilevel Management (BM3). According to this Topology, the battery cells can be drained and charged concerning their capacity, which allows varying battery pack structures. Due to the integration of the power electronics, the output voltage of the battery pack is no longer fixed but can be dynamically adjusted in small steps. In other words, each cell can have three different states, namely series, parallel, and bypass in connection with the neighbor cells. With the help of MATLAB/Simulink and by using the BM3 modules, the battery string model is created. This model allows us to switch two cells with the different SoC as parallel, which results in the internal balancing of the cells. But if the parallel switching lasts just for a couple of ms, we can have a perturbation pulse which can stimulate the cells out of the relaxation phase. With the help of modeling the voltage response pulse of the battery, it would be possible to characterize the cell. The Online EIS method, which is discussed in this paper, can be a robust substitute for the conventional battery characterization methods.

Keywords: battery characterization, SoH estimation, RLS, BEV

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Authors: Karchung, S. Ruangsinchaiwanich

Abstract:

This paper presents open-loop vector control method of induction motor with space vector pulse width modulation (SVPWM) technique. Normally, the closed loop speed control is preferred and is believed to be more accurate. However, it requires a position sensor to track the rotor position which is not desirable to use it for certain workspace applications. This paper exhibits the performance of three-phase induction motor with the simplest control algorithm without the use of a position sensor nor an estimation block to estimate rotor position for sensorless control. The motor stator currents are measured and are transformed to synchronously rotating (d-q-axis) frame by use of Clarke and Park transformation. The actual control happens in this frame where the measured currents are compared with the reference currents. The error signal is fed to a conventional PI controller, and the corrected d-q voltage is generated. The controller outputs are transformed back to three phase voltages and are fed to SVPWM block which generates PWM signal for the voltage source inverter. The open loop vector control model along with SVPWM algorithm is modeled in MATLAB/Simulink software and is experimented and validated in TMS320F28335 DSP board.

Keywords: electric drive, induction motor, open-loop vector control, space vector pulse width modulation technique

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Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

Abstract:

In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Berger Aida

Abstract:

Social entrepreneurship has emerged as an active area of practice and research within the last three decades and has called for a focus on Social Entrepreneurship innovation. Areas such as academics, practitioners , institutions or governments have placed Social Entrepreneurship on the priority list of reflexion and action. It has been accepted that Social entrepreneurship (SE) shares large similarities with its parent, Traditional Entrepreneurship (TE). SE has grown over the past ten years exploring entrepreneurial cognition and the analysis of the ways of thinking of entrepreneurs. The research community believes that value exists in grounding entrepreneurship in neuroscience and notes that SE, like Traditional Entrepreneurship, needs to undergo efforts in clarification, definition and differentiation. Moreover, gaps in SE research call for integrative multistage and multilevel framework for further research. The cognitive processes underpinning entrepreneurial action are similar for SE and TE even if Social Entrepreneurship orientation shows an increased empathy value. Theoretically, there is a need to develop sound models of how to process functions and how to work more effectively as entrepreneurs and research on efficiency improvement calls for the analysis of the most common practices in entrepreneurship. Multitasking has been recognized as a daily and unavoidable habit of entrepreneurs. Hence, we believe in the need of analyzing the multiple task phenomena as a methodology for skill acquisition. We will conduct our paper including Social Entrepreneurship within the wider spectrum of Traditional Entrepreneurship, for the purpose of simplifying the neuroscientific lecture of the entrepreneurial cognition. A question to be inquired is to know if there is a way of developing multitasking habits in order to improve entrepreneurial skills such as speed of information processing , creativity and adaptability . Nevertheless, the direct link between the neuroscientific approach to multitasking and entrepreneurship effectiveness is yet to be uncovered. That is why an extensive Literature Review on Multitasking is a propos.

Keywords: cognitive, entrepreneurial, empathy, multitasking

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Authors: Oloruntegbe Kunle Oke, Alake Ese Monica, Odutuyi Olubu Musili

Abstract:

This research explores the differing effectiveness of cascade and cluster models in professional development programs for educators in Ondo State, Nigeria. The cascade model emphasizes a top-down approach, where training is cascaded from expert trainers to lower levels of teachers. In contrast, the cluster model, a bottom-up approach, fosters collaborative learning among teachers within specific clusters. Through a review of the literature and empirical studies of the implementations of the former in two academic sessions followed by the cluster model in another two, the study examined their effectiveness on teacher development, productivity and students’ achievements. The study also drew a comparative analysis of the strengths and weaknesses associated with each model, considering factors such as scalability, cost-effectiveness, adaptability in various contexts, and sustainability. 2500 teachers from Ondo State Primary Schools participated in the cascade with intensive training in five zones for a week each in two academic sessions. On the other hand, 1,980 and 1,663 teachers in 52 and 34 clusters, respectively, were in the first and the following session. The programs were designed for one week of rigorous training of teachers by facilitators in the former while the latter was made up of four components: sit-in-observation, need-based assessment workshop, pre-cluster and the actual cluster meetings in addition to sensitization, and took place one day a week for ten weeks. Validated Cluster Impact Survey Instruments, CISI and Teacher’s Assessment Questionnaire (TAQ) were administered to ascertain the effectiveness of the models during and after implementation. The findings from the literature detailed specific effectiveness, strengths and limitations of each approach, especially the potential for inconsistencies and resistance to change. Findings from the data collected revealed the superiority of the cluster model. Response to TAQ equally showed content knowledge and skill update in both but were more sustained in the cluster model. Overall, the study contributes to the ongoing discourse on effective strategies for improving teacher training and enhancing student outcomes, offering practical recommendations for the development and implementation of future professional development projects.

Keywords: cascade model, cluster model, teachers’ development, productivity, students’ achievement

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Authors: Aditya Patil, Arun Patil, Vaishali Patil, Sudhir Chitnis, Anjum Patel

Abstract:

Rapid growth has given e-commerce platforms a lot of client behavior and spending data. To maximize their strategy, businesses must understand how customers utilize online shopping platforms and what influences their purchases. Our research focuses on e-commerce user behavior and purchasing trends. This extensive study examines spending and user behavior. Regression and grouping disclose relevant data from the dataset. We can understand user spending trends via multilevel regression. We can analyze how pricing, user demographics, and product categories affect customer purchase decisions with this technique. Clustering groups consumers by spending. Important information was found. Purchase habits vary by user group. Our analysis illuminates the complex world of e-commerce consumer behavior and purchase trends. Understanding user behavior helps create effective e-commerce marketing strategies. This market can benefit from K-means clustering. This study focuses on tailoring strategies to user groups and improving product and price effectiveness. Customer buying behaviors across categories were shown via K-means clusters. Average spending is highest in Cluster 4 and lowest in Cluster 3. Clothing is less popular than gadgets and appliances around the holidays. Cluster spending distribution is examined using average variables. Our research enhances e-commerce analytics. Companies can improve customer service and decision-making with this data.

Keywords: e-commerce, regression, clustering, k-means

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