Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect Of Government Expenditure On Health Performance

This study aims to evaluate the impact of the government's role in the health sector. An evaluation with Logic Model assesses the use of inputs in the form of government spending on health functions toward the outcome in the form of a health index. This study uses quantitative methods with data in the form of unbalanced panels from 10 districts / cities in NTB in 2010-2016. The independent variable is the government expenditure on the health function, and the control variable in the form of household consumption expenditure while the dependent variable is the health index. Analysis was carried out by panel regression with the random effect estimation method. The result shows that the government expenditure on the health function has no effect on the health index. ————————————————————
Review of model predictive control strategies for matrix converters

Matrix converters are a well-known class of direct AC-AC power converter topologies that can be used in applications, where compact volume and low weight are necessary. For good performance, special attention should be paid to the control scheme used for these converters. The model predictive control strategy is a promising, straightforward and flexible choice for controlling various different matrix converter topologies. This work provides a comprehensive study and detailed classification of several predictive control methods and techniques, discussing special capabilities they each add to the operation and control scheme for different matrix converter topologies. This study also considers the issues regarding the implementation of model predictive control strategies for matrix converters. This survey and comparison are intended to be a useful guide for solving the related drawbacks of each topology and to enable the application of this control scheme for matrix converters in practical applications.
Automatic Bridge Crack Detection Using a Convolutional Neural Network

Concrete bridge crack detection is critical to guaranteeing transportation safety. The introduction of deep learning technology makes it possible to automatically and accurately detect cracks in bridges. We proposed an end-to-end crack detection model based on the convolutional neural network (CNN), taking the advantage of atrous convolution, Atrous Spatial Pyramid Pooling (ASPP) module and depthwise separable convolution. The atrous convolution obtains a larger receptive field without reducing the resolution. The ASPP module enables the network to extract multi-scale context information, while the depthwise separable convolution reduces computational complexity. The proposed model achieved a detection accuracy of 96.37% without pre-training. Experiments showed that, compared with traditional classification models, the proposed model has a better performance. Besides, the proposed model can be embedded in any convolutional network as an effective feature extraction structure.
Optimization of Duties in Railway Traffic

This thesis discusses crew scheduling in railway transportation. A case of Finnish railway operator is used as an example. Literature review discusses crew scheduling in other countries. Finally, two crew scheduling problems are solved. The objective of crew scheduling is to form duties from all the tasks, which need to be performed. There are multiple constrains related to the duties, which make the crew scheduling a complex problem. Also, the problem sizes are usually really large. Traditionally duties were constructed by hand, but the rising demands of the modern world have forced railway operators to acquire planning software. In literature the crew scheduling problem is often modeled as a set covering problem with additional constraints. Objective is to minimize the total cost so that every task is covered at least once. Usually solution methods rely on column generation and different kinds of heuristics, because set covering problem is NP-hard. The problem is often solved in two phases, duty generation and duty selection. Two crew scheduling problems, based on real railway data from the Finnish operator, are solved using the planning software of the operator. The effect of different optimization parameters on the final solution is tested. The objective is to find solutions that minimize the total working hours and the amount of duties, while the amount of tasks, which are used multiple times, is as low as possible. Some clearly bad values for the parameters are found, but there is not a single parameter combination that would produce best results in every case. Date: 6.5. 2014 Language: English Number of pages: 17 + 4
Training-based frequency synchronisation and highly frequency selective channel estimation for OFDM/OQAM systems

This work addresses frequency synchronisation and channel estimation for highly frequency selective orthogonal frequency division multiplexed systems with offset quadrature amplitude modulation. A two-step approach is proposed, wherein a coarse carrier frequency offset (CFO) estimator, which does not require channel knowledge, is designed in the first step by exploiting the correlation between the received and training signals. A time-domain model is derived for the joint estimation of fine CFO (FCFO) and highly frequency selective channel in the second step. In contrast to the frequency domain model in the literature, the derived time-domain model does not require the channel to be frequency flat. Based on the time-domain model, the weighted least squares and minimum mean square error estimators are investigated to jointly estimate the FCFO and frequency selective channel. The Cramer-Rao lower bounds (CRLBs) are derived for the proposed estimators, and are used to evaluate the performance of the joint FCFO and channel estimation in the presence of inter-symbol-interference due to the overlapping of adjacent time-domain orthogonal frequency division multiplexing/offset quadrature amplitude modulation (OFDM/OQAM) symbols. Simulation results demonstrate achievability of the CRLB bounds and performance gain of the proposed estimators over the state-of-the-art existing estimators.
Does Managerial Ability Drive Firm Innovativeness?

In this paper, we investigate the impact of managerial ability on firm innovativeness. We further investigate how managerial ability impacts the association between firm innovativeness and competitive advantage. We employ two measures of managerial ability, namely strategic managerial ability and operational managerial ability. We find that firm innovativeness rises with strategic ability at an increasing rate. However, firm innovativeness initially falls and then rises with an increase in operational ability. Our results are consistent with the notion that a firm's innovation activity is a tradeoff between opportunity exploration and exploitation in that explorative and exploitative activities compete for manager's fixed attention. The greater the strategic ability of management, the more opportunity-focused they are, the greater is their risk tolerance, and the greater is the investment in research and development. Strategic managers seek and cultivate growth opportunities to resolve the uncertainty associated with the growth opportunities in the firm's favor, which enhances the firm's competitive advantage.
Comparison of two intelligent transportation systems Wrong-Way driving countermeasures currently deployed on Florida toll roads

Abstract Wrong way driving (WWD) crashes on high-speed limited access facilities often cause severe injuries and deaths. Conventional “Wrong Way” signs can reduce WWD events but can be insufficient in some cases. Intelligent Transportation Systems (ITS) WWD countermeasures can more effectively notify wrong-way drivers of their mistake. This paper compares the safety performance of two types of ITS WWD countermeasures implemented in Florida: Light-Emitting Diode (LED) signs in South Florida (which include one set of signs and one camera) and Rectangular Flashing Beacon (RFB) signs in Central Florida (which include two sets of signs and three cameras). The reduction in WWD events (911 calls and citations) and the percentage of wrong-way drivers who self-corrected their WWD behavior were used as surrogate safety performance measures instead of crashes, since WWD crashes are rare. Chi-squared tests revealed a significant reduction in WWD events at the LED and RFB treated sites compared to control sites without these countermeasures. Comparison group analyses indicated that the LED and RFB countermeasures reduced WWD events by 48.1% and 69.4%, respectively. Additionally, photographs taken by cameras on the countermeasures and/or closed-circuit television cameras monitored by the traffic management centers showed that over 16% of the 72 detected wrong-way vehicles self-corrected at the LED sites and 81% of the 353 detected wrong-way vehicles self-corrected at the RFB sites. The methods and results in this paper can help transportation agencies throughout the United States identify the most suitable WWD countermeasures and evaluate their performance.
Capital Structure And Profitability Of Foreign Direct Investment Companies In The Indian Manufacturing Sector

This study investigates the relationship between Capital Structure and Profitability of Foreign Direct Investment Companies in the Indian Manufacturing Sector India by employing firm level data (a sample of 54 Foreign Direct Investment companies from S&P BSE 500 Index) for a study period of 9 years from 2010 to 2018. Multiple Regression model has been employed for studying the impact of Capital Structure on Profitability. Three profitability measures are employed as indicators of profitabilityROA, ROE and ROTI. Four debt measures are employed to study the impact of capital structure on profitabilityTOL/TNA, LTD/TNA, STD/TNA and Debt/Equity ratio. The control variables included in the study are Size, Growth, Liquidity, Tangibility and Age. Empirical results indicate that debt ratios have significant negative impact on profitability and confirm the prediction of Pecking-Order Theory. It is found out that that the sample companies have low debt levels in their capital structure. Short term debt funds are an important mode of financing adopted by sample Foreign Direct Investment companies. Liquidity has a positive and significant impact on ROTI but significant and negative impact on ROE. Tangibility has significant negative impact on ROE. Growth, Size and Age indicators has no significant impact on profitability. The study concludes that Capital structure does have a significant impact on profitability and the right choice of financing the assets may have an effect on the performance of Foreign Direct Investment companies in the Indian Manufacturing sector.
Industry 4.0: a supply chain innovation perspective

The Fourth Industrial Revolution – also known as Industry 4.0 (i4.0) – comprises the digitalisation of the industrial sector. This paper uses the theoretical lens of supply chain innovation (SCI) to investigate the implications of i4.0 on supply chain management. For these purposes, the method of structured content analysis is applied to more than 200 use cases of i4.0-enabled SCI introduced by both established and startup companies. i4.0-enabled SCI manifests along three dimensions: process, technology, and business architecture. The key findings of this study can be summarised as follows: first, i4.0-enabled SCI extends the initial focus on productivity improvements in SC processes towards scalability and flexibility. Second, extant i4.0 solutions rely mostly on analytics and smart things while omitting smart people technology and the human-centric approach associated with the i4.0 paradigm. Third, established companies adopt i4.0 merely to sustain their existing business architectures while startup companies radically change their operating models, relying heavily on data analytics and the platform economy. Consequently, established companies pursue a problem-driven, engineering-based approach to SCI while startup companies follow an ‘asset-light’, business-driven approach. Lastly, there are two distinct approaches to digitalising operational SC processes: platform-based crowdsourcing of standard processes and on-demand provision of customised services.
Congestion-Free Ant Traffic: Jam Absorption Mechanism in Multiple Platoons

In this paper, an agent-based model of ant traffic on a unidirectional single-lane ant trail is presented to provide better understanding of the jam-free traffic of an ant colony. On a trail, the average velocity of ants remains approximately constant irrespective of density, thereby avoiding jamming. Assuming chemotaxis, we analyze platoon-related scenarios to assess the marching-platoon hypothesis, which claims that ants on a trail form a single platoon in which they march synchronously, thereby reducing hindrances due to increasing density. Contrary to that hypothesis, our findings show that ants on a trail do not march synchronously and do experience stop-and-go motion. However, more interestingly, our study also indicates that the ants’ chemotaxis behavior leads to a peculiar jam absorption mechanism, which helps to maintain free flow on a trail and avoids jamming. Again, contrary to the marching-platoon hypothesis, our findings also indicate that, rather than assisting traffic flow, forming a single cluster actually triggers jamming.
Energy-efficient Interfaces for Vibration Energy Harvesting

Ultra low power wireless sensors and sensor systems are of increasing interest in a variety of applications ranging from structural health monitoring to industrial process control. Electrochemical batteries have thus far remained the primary energy sources for such systems despite the finite associated lifetimes imposed due to limitations associated with energy density. However, certain applications (such as implantable biomedical electronic devices and tire pressure sensors) require the operation of sensors and sensor systems over significant periods of time, where battery usage may be impractical and add cost due to the requirement for periodic re-charging and/or replacement. In order to address this challenge and extend the operational lifetime of wireless sensors, there has been an emerging research interest on harvesting ambient vibration energy. Vibration energy harvesting is a technology that generates electrical energy from ambient kinetic energy. Despite numerous research publications in this field over the past decade, low power density and variable ambient conditions remain as the key limitations of vibration energy harvesting. In terms of the piezoelectric transducers, the open-circuit voltage is usually low, which limits its power while extracted by a full-bridge rectifier. In terms of the interface circuits, most reported circuits are limited by the power efficiency, suitability to real-world vibration conditions and system volume due to large off-chip components required. The research reported in this thesis is focused on increasing power output of piezoelectric transducers and power extraction efficiency of interface circuits. There are five main chapters describing two new design topologies of piezoelectric transducers and three novel active interface circuits implemented with CMOS technology. In order to improve the power output of a piezoelectric transducer, a series connection configuration scheme is proposed, which splits the electrode of a harvester into multiple equal regions connected in series to inherently increase the open-circuit voltage generated by the harvester. This topology passively increases the rectified power while using a full-bridge rectifier. While most of piezoelectric transducers are designed with piezoelectric layers fully covered by electrodes, this thesis proposes a new electrode design topology, which maximizes the raw AC output power of a piezoelectric harvester by finding an optimal electrode coverage.
Design Optimisation of a Unidirectional Centrifugal Radial-Air-Turbine for Application in OWC Wave Energy Converters

Research on employing unidirectional air turbines for oscillating water columns (OWC) has received much attention in the last few years. Most unidirectional turbine topologies considered to date use axial flow unidirectional turbines. The radial turbine offers an alternative with increased resistance to backflow. However, in general, the efficiency of radial turbines is lower than axial turbines. This study describes a computational fluid dynamics (CFD)-based design optimisation of an outflow radial turbine for the intended application in an OWC system configured to enable primarily unidirectional flow through the turbine. The rotor blade geometry is parametrically described in addition to other turbine components. The central composite design (CCD) and genetic algorithm were used to explore an optimum design of a centrifugal radial turbine for a maximum total-to-static efficiency. Seven computer aided design (CAD) parameters were investigated as the design variables, and the optimum turbine design was identified in a population of 79 design points. The optimum outflow turbine was found to have a peak steady-state efficiency of 72%, and the leading-edge angle, guide vane angle, trailing edge angle, and the chord length were found to have the highest sensitivity. Compared to an inflow radial turbine, the geometrical features of the outflow turbine permit higher absolute velocities of the flow at the rotor entrance and increase the dynamic pressure changes across the rotor. Therefore, the optimised outflow radial turbine can obtain acceptable rotor energy transfer despite having a negative centrifugal energy transfer term.
Effect of Weather Conditions on Harmonic Performance of PV Inverters

Abstract The effect of weather conditions on the generation of harmonics in PV systems is investigated. A PV model, including the inverting stage, is considered. The output of the equivalent PV model is fed to the load via an inverter and transformer. The analysis is conducted by using a dataset of weather conditions in a North American city. Two converter techniques, which form the basis for the majority of converters, are used to validate the proposed approach: a square-wave inverter with 60 Hz switching, and pulse width modulation (PWM). Probability density functions and probability distribution models with best fit are determined as aids for improving the quality of the power generated for different range of converter values and the best is selected in this article. The long-term effects of weather conditions on harmonics produced by PV inverters are considered. The results show the variability in amplitude of each harmonic component, the boundaries of each harmonic component, and which harmonic magnitudes occur more frequently. The classic PV DC-AC conversion system has been modeled using MATLAB. The work is validated by using different ranges of dataset for two different converters and the results improved the importance of the proposed work. Also, the results agree with previous studies that have been carried with a different method which could be considered as another way of validation for the proposed work. Based on the generated harmonic variation cases, the appropriate parameter values for dynamic adaptive circuit switching of the filtering system and determining the capacity of the storage system could be determined.
Torque Ripple Minimization and Control of a Permanent Magnet Synchronous Motor Using Multiobjective Extremum Seeking

In this paper, a multiobjective extremum-seeking (MOES) approach is proposed for torque control of a permanent magnet synchronous motor and minimization of its torque ripple. The latter aspect is important in human–machine interface applications such as haptic interfaces requiring smooth torque profiles at slow speeds. The proposed MOES scheme combines an adaptive iterative learning control method with an adaptive proportional-integral (PI) controller, which makes the system less sensitive to load disturbances and improves the control performance for torque regulation during transient events. Experiments are performed on a proof-of-concept exercise machine that generates desired torque profiles and mechanical impedance based on user's preference. The performance of the proposed controller is further compared with a recently proposed adaptive PI controller. The experimental results validate the effectiveness of the proposed controller in terms of torque ripple suppression, steady-state and transient performance, and load disturbance rejection.
High Gain Single Ended Primary Inductor Converter With Ripple Free Input Current for Solar Powered Water Pumping System Utilizing Cost-Effective Maximum Power Point Tracking Technique

This paper presents a new configuration of high gain (HG) single ended primary inductor converter (SEPIC) with a ripple-free input current to maximize the efficiency of the PV panel for standalone water pumping system (WPS). The ripple eliminating circuit combined with the HG SEPIC converter to achieve reduced ripples in photovoltaic (PV) current is independent to the duty cycle control and hence, it can be easily integrated to the main power circuit of configuration. This circuit does not need any active switches, control, or drive circuit for its execution. The ripple eliminating circuit yields a complete removal of the electrolytic capacitor connected across the PV array and significantly reduces the inductance of the HG SEPIC converter. It also improves the response and power density of the dc–dc converter. The large gain of dc–dc converter enables the use of low-voltage PV panel and minimizes the partial shading and parasitic capacitance effects on PV array source. Due to the substantial compatibility between natural characteristics of switched reluctance motor (SRM) drive and WPS, a four-phase SRM drive is utilized in the proposed scheme. In addition, a single current sensor based maximum power point tracking technique is utilized in the proposed system, which helps to reduce the cost and improve the accuracy of the overall system. Analytical, simulated, and experimental results of the developed system are presented to demonstrate the performance of the system.
Does Microfinance Affect Poverty Reduction and Inequality in Indonesia

This study is to discuss the question of whether microfinance (specifically micro-credit) can reduce poverty and income inequality in Indonesia. Using data from 33 provinces in Indonesia, we show that higher levels of micro-credit provision can indeed reduce poverty in Indonesia. However, it turns out that this cannot be done to reduce the income income inequality. The results of this study add to the discussion about the impact of microfinance on poverty and inequality in Indonesia. Because so far micro finance is considered a very effective tool to be applied in an effort to improve people's welfare by reducing the level of poverty and inequality in Indonesia. Although poverty can decline, but no less important is economic development must be followed by a decrease in the gap between the rich and poor.