Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of The Internal Quality Assurance System in Improving School Quality

The Internal Quality Assurance System at SMP Darul Falah and SMP Negeri 02 Cililin has not been implemented optimally. school quality. The general objective of this study is to describe the implementation of school internal quality assurance in improving school quality and its specific objectives are to describe 1) quality mapping, 2) compilation of quality compliance plans, 3) implementation of quality compliance, 4) quality evaluation. 5) Determination of Quality Standards 6) Results of Quality Implementation 7) Obstacles in implementing SPMI. The implementation of SPMI itself according to Dirjendikdasmen (2016: 5) has the aim of ensuring that all elements, namely organization, policies, and processes related to educational units run by established standards to ensure the creation of a quality culture. This research procedure uses a qualitative approach with a case study method. The results of this study, in general, are that schools have implemented the SPMI implementation in improving the quality of schools in particular, namely: (1) Mapping, by carrying out school self-evaluation and school report cards. (2) Planning, schools carry out planning by the planning reference and format. (3) Implementation, the school has implemented SPMI starting at the initial stage, the core stage, and the final stage. (4) The school has carried out the SPMI evaluation by the monev team for each activity. (5) The school has developed a quality strategy for SPMI by the team using the formulation format, (6) The school has shown optimal learning outcomes through the application of SPMI with the satisfaction of various parties, (7) The school has resolved every problem with the right solution application of SPMI. The implementation of SPMI in schools is very helpful in improving the quality of the school, both academically and non-academically.
LOCATIVE MEDIA INTERVENTIONISM – A CONCEPTUAL FRAMEWORK FOR CRITICAL REVIEW OF AUGMENTED REALITY APPLICATIONS IN THE PARTICIPATORY SPATIAL DESIGN CONTEXT

This paper offers an analytical framework for a critical review of augmented reality visualisations in the domain of participatory spatial design in general and Participatory Architecture in particular. By offering this framework the paper aims to respond to the concern in published discourse that augmented reality visualisations are insufficient on their own to accomplish participation’s ultimate objective of social inclusion. To derive this framework the paper turns to augmented reality itself, that is, the realm of locative media practice as a whole. Illustrative examples have been reviewed to identify an overarching commonality of purpose, namely proactive spatial intervention for social inclusion. This common underpinning concept has been labelled as Locative Media Interventionism, or LMI. Finally, this compact framework has been used to evaluate augmented reality applications in participatory spatial design. A cursory evaluation of micro as well as macro scale examples indicates that the usage of this visualisation technology has yet to undergo the process of maturation that locative media in general has undergone. It has yet to evolve out from being a mere novelty to becoming a politically charged platform for delivering social inclusion
A Survey on FPGA-based Deep Neural Network Accelerators

Currently, deep learning technologies have achieved great success in applying deep neural networks(DNNs) to multiple domains. However, their high functional intensity, whether computational or memory, has become a heavy burden in the utilization of deep learning, especially in constrained resource platforms. A potential solution is FPGA, which provides eﬀective means for optimizing and accelerating DNNs. Therefore, an important of ﬁeld of research has been the development of DNN applications with FPGA accelerators. In this paper, existing optimization techniques are evaluated to provide a comprehensive overview of FPGA-based DNN accelerators. The review herein addresses software-and hardware-level acceleration techniques (including, but not limited to, model compression, parameter quantization, and energy-eﬃciency in structural design).
CPW fed miniaturized dual‐band short‐ended metamaterial antenna using modified split‐ring resonator for wireless application

A miniaturized dual‐band metamaterial (MTM) antenna has been designed in this article. The designed coplanar waveguide fed antenna has composed of inner split‐ring resonator and an outer open ring resonator with rectangular stub. The series parameter of the antenna is used to determine the zeroth order resonance frequency due to short‐ended boundary condition. The whole size of proposed structure is 20 × 25.5 mm2. This MTM antenna exhibits dual‐band operation at 3.17 GHz (3.1–3.22 GHz) and 5.39 GHz (5.27–5.47 GHz). The proposed MTM structure achieves measured peak gain of 0.71 and 1.89 dB at 3.17 and 5.39 GHz, respectively. The proposed antenna can be used for recent radio communication in form of S‐band application and Wi‐MAX.
Insulin/Enzyme Calculator “Gourmet” for Type 0 Diabetic Patients: Why, What for, and How?

This paper is an introductive chapter in the Insulin/Enzyme Calculator series. The prototype of “Gourmet” was developed to assist diabetic patients in controlling blood sugar after a total pancreatectomy or Whipple procedure. Taking into consideration the causes and symptoms of different types of diabetes, it is proposed to classify the post-surgical cases as type 0 diabetes. Since such patients have a significantly modified digestive system, new approaches in blood sugar analysis and treatment should be developed. This paper reviews existing mathematical models of diabetes and indicates how “Gourmet” compares to available simulators. It specifies the main problems with precise insulin dose estimation and describes the basic operational principles of the proposed computer program. The processes that must be taken into account are as follows: dynamical blood sugar profile related to digestion of carbohydrates of different types, sugar contribution by the liver, fat/proteins long- and short-term contributions into blood sugar level, influence of the enzymes and bicarbonate on blood sugar behavior, difference in carbohydrates content and their relative portion in cooked and uncooked meals.
Private Equity Involvement and Earnings Quality

This paper examines the relation between private equity (PE) investors' involvement and their portfolio firms' earnings quality. We operationalize earnings quality through comparative analyses of conditional loss recognition timeliness. For a sample of unlisted Belgian firms, we find that PE involvement increases a firm's willingness to recognize losses more timely as compared to industry, size and life-cycle matched non-PE backed firms. Further, we document more powerful earnings quality effects for firms backed by independent and captive PE-investors as compared to firms backed by government-related PE-investors. Finally, we find no systematic variation in earnings quality across different levels of PE ownership. Our results are robust to the inclusion of various controls and remain unaffected when we consider the endogeneity of PE investments and compare pre- and post PE investment years. The current results provide novel evidence towards the understanding of PE investors' governance implications for portfolio firms' earnings quality.
Uncertainty Quantification for Cantilever Based MEMS Switches Considering Bouncing Dynamics

Design methods of MEMS switches are typically based on deterministic approaches, where the parameters such as geometrical and physical properties as well as the operating conditions that characterize the behavior of systems are assumed to be known precisely. However, in practice, due to the batch-production processes used in MEMS fabrication as well as the micron-scale dimensions of the structural elements, consideration of uncertainties in system parameters and an understanding of their effects are warranted and should be investigated in order to improve the switch performance and reliability. The primary purpose of the present paper is to perform uncertainty quantification predictions for MEMS switches based on the transient dynamic response, in particular, the bouncing behavior. A suitable mathematical model that captures the bouncing dynamics and previously validated via experiments is employed for this purpose. In particular, quantification of performance in terms of second order statistics is performed to predict propagation of uncertainties in Young’s modulus, beam width, beam thickness as well as actuation voltage. The influence of these uncertainties on significant switch performance parameters such as initial bounce time as well as maximum bounce height have been quantified.Copyright © 2016 by ASME
FPGA-based High Performance Diagnostics For Fusion

High performance diagnostics are an important aspect of fusion research. Increasing shot-lengths paired with the requirement for higher accuracy and speed make it mandatory to employ new technology to cope with the increasing demands on digitization and data handling. Field programmable gate arrays (FPGAs) are well known in high performance applications. Their ability to handle multiple fast data streams whilst remaining programmable make them an ideal tool for diagnostic development. Both the improvement of old and the design of new diagnostics can benefit from FPGA-technology and increase the amount of accessible physics significantly. In this work the developments on two FPGA-based diagnostics are presented. In the first part a new open-hardware low-cost FPGA-based digitizer is presented for the MAST-Upgrade (MAST-U) integral electron density interferometer. The system is shown to have an optically limited phase accuracy and a detection bandwidth of over 3.5 MHz. Data is acquired continuously at 20 MS/s and streamed to an acquisition PC via optical fiber. By employing a dual-FPGA approach real-time processing of the density signal can be achieved despite severly limited resources, thus providing a control signal for the MAST-U plasma control system system with less than 8 μs latency. Due to MAST-U being still inoperable, in-situ testing has been conducted on the ASDEX Upgrade, where fast wave physics up to 3.5 MHz could first be observed. The second part presents developments to the Synthetic Aperture Microwave Imaging (SAMI) diagnostic. In addition to improving the utilization of long shot-lengths and enabling dual-polarized acquisition the system has been enhanced to continuously acquire active probing profiles for 2D Doppler back-scattering (DBS), a technique recently developed using SAMI. The aim is to measure pitch angle profiles to derive the edge current density. SAMI has been transferred to the NSTX-Upgrade and integrated into the experiment’s infrastructure, where it has been acquiring data since May 2016. As part of this move an investigation into near-field effects on SAMI’s image reconstruction algorithms was conducted.
Investigation of a helicopter harsh landing based on signals from installed sensors

Full scale testing of actual aircraft structures is one of the important methods of structural design experimental validation. Such testing is also used to support creation of future use strategy of ageing aircraft. Influence of hard landings on the structural integrity is one of the key issues in the process of helicopter service life extension for ageing aircraft, such as the Polish Air Force Mi-8/17 helicopters. An experimental vertical drop test simulating a hard landing has been one of the tasks in the European Defense Agency’s „ASTYANAX” research project. The aim of the test was to verify the extent of structural damage for landings occurring in the permitted velocity range (i.e. below 3,05 m/s). A Mi-8 helicopter decommissioned from the Polish Air Force has been used for the test. Various measurement systems were used in the test: deformation measurements with strain gauges, Bragg gratings and PZT sensors as well accelerometer systems and landing gear cylinder displacement meters. In addition, after each drop test step, a visual NDI as well as comparative analysis of three-dimensional surface deformation (made with optical scanners) took place. A measurement of 3D coordinates of discrete control points has also been performed. Preliminary analysis of the experiment results is presented in the paper.
A comprehensive accuracy assessment of Samsung smartwatch heart rate and heart rate variability

Background Photoplethysmography (PPG) is a low-cost and easy-to-implement method to measure vital signs, including heart rate (HR) and heart rate variability (HRV). The method is widely used in various wearable devices. For example, Samsung smartwatches are PPG-based open-source wristbands used in remote well-being monitoring and fitness applications. However, PPG is highly susceptible to motion artifacts and environmental noise. A validation study is required to investigate the accuracy of PPG-based wearable devices used in free-living conditions. Objective We evaluate the accuracy of PPG signals -- collected by the Samsung Gear Sport smartwatch in free-living conditions -- in terms of HR and time-domain and frequency-domain HRV parameters against a medical-grade chest electrocardiogram (ECG) monitor. Methods We conducted 24-hours monitoring using a Samsung Gear Sport smartwatch and a Shimmer3 ECG device. The monitoring included 28 participants (14 male and 14 female), where they engaged in their daily routines. We evaluated HR and HRV parameters during the sleep and awake time. The parameters extracted from the smartwatch were compared against the ECG reference. For the comparison, we employed the Pearson correlation coefficient, Bland-Altman plot, and linear regression methods. Results We found a significantly high positive correlation between the smartwatch's and Shimmer ECG's HR, time-domain HRV, LF, and HF and a significant moderate positive correlation between the smartwatch's and shimmer ECG's LF/HF during sleep time. The mean biases of HR, time-domain HRV, and LF/HF were low, while the biases of LF and HF were moderate during sleep. The regression analysis showed low error variances of HR, AVNN, and pNN50, moderate error variances of SDNN, RMSSD, LF, and HF, and high error variances of LF/HF during sleep. During the awake time, there was a significantly high positive correlation of AVNN and a moderate positive correlation of HR, while the other parameters indicated significantly low positive correlations. RMSSD and SDNN showed low mean biases, and the other parameters had moderate mean biases. In addition, AVNN had moderate error variance while the other parameters indicated high error variances. Conclusion The Samsung smartwatch provides acceptable HR, time-domain HRV, LF, and HF parameters during sleep time. In contrast, during the awake time, AVNN and HR show satisfactory accuracy, and the other HRV parameters have high errors.
HematoNet: Expert Level Classification of Bone Marrow Cytology Morphology in Hematological Malignancy with Deep Learning

There have been few efforts made to automate the cytomorphological categorization of bone marrow cells. For bone marrow cell categorization, deep-learning algorithms have been limited to a small number of samples or disease classifications. In this paper, we proposed a pipeline to classify the bone marrow cells despite these limitations. Data augmentation was used throughout the data to resolve any class imbalances. Then, random transformations such as rotating between 0 to 90 degrees, zooming in/out, flipping horizontally and/or vertically, and translating were performed. The model used in the pipeline was a CoAtNet and that was compared with two baseline models, EfficientNetV2 and ResNext50. We then analyzed the CoAtNet model using SmoothGrad and Grad-CAM, two recently developed algorithms that have been shown to meet the fundamental requirements for explainability methods. After evaluating all three models' performance for each of the distinct morphological classes, the proposed CoAtNet model was able to outperform the EfficientNetV2 and ResNext50 models due to its attention network property that increased the learning curve for the algorithm which was represented using a precision-recall curve.
COST SAVINGS FROM PRIVATIZATION: A Compilation of Study Findings

SUMMARY Opponents of privatization and other methods of increasing competition in government-financed services frequently claim that privatization/competition rarely results in cost savings for government or society at large. In fact, some argue that privatization increases costs to the taxpayer. These claims are refuted by a substantial body of research that has documented significant savings from privatization/competition. More than 100 studies over the course of the last 20 years have demonstrated privatization/competition cost savings in service areas from airport operation to weather forecasting.
Network Disaster Response Effectiveness: The Case of ICTs and Hurricane Katrina

Abstract This article assesses how information and communication technologies (ICTs) hindered the effectiveness of public sector organizational networks in the City of New Orleans following Hurricane Katrina. The analysis examines three disaster response networks responsible for disaster planning and preparedness whose primary tasks focused on evacuation, shelter, first response, and public protection. The temporal period under discussion is the immediate days prior to and after Hurricane Katrina made landfall in New Orleans, Friday, August 26, 2005 to Sunday, September 4, 2005. We discuss the status of policies instituted by the federal government, the status of local disaster planning in New Orleans, the theoretical underpinnings and empirical research on communication, ICTs, and the role of organizational networks in public administration, and summarize findings from the small corpus of research on organizational network effectiveness during and after Hurricane Katrina. Our study relies on grounded theory to document how failures of technology, communication, information sharing, and management contributed to reducing organizational network effectiveness and discusses some of the reasons for network failure during the response to Hurricane Katrina. We focus on the need for critical resources and structural conditions that prevented local organizational networks from operating effectively and efficiently. We conclude with an analysis of the continuing relevance of Hurricane Katrina by comparing events that took place following Hurricane Sandy and with series of recommendations for assessing the probability of future disasters including use of a different theoretical framework, social-ecological system thinking; a commitment to and investment in metrics, indicators, and data to measure progress towards resilience; significant investments to harden and redesign key infrastructure; and the adoption of an international perspective to inform national policies and practices.
Fuzzy logic based obstacle avoidance strategy for mobile robot

The application of mobile robot often used in an inappropriate place for human. Sometime, it would involve in unknown environment. Obstacle avoidance are the key feature to control the mobile robot in order to avoid collision which provide safety to the mobile robot and the environment object. Obstacle avoidance is basically a strategy to define an obstacle by processing the distance between it, decision making in controller and giving output which control the movement or motion of the mobile robot. In this research, an obstacle avoidance strategy is using fuzzy logic approach to control the action of mobile robot was designed. The simulation design and algorithms of the obstacle avoidance with fuzzy inference system is described. The consideration of obstacle are depend on the data calculated throughout the design. The result shown are included on three model which is the target driven model, obstacle avoidance target driven model and multiple obstacle avoidance target driven model. The mobile robot are able to avoid all obstacle that set on the simulation environment.
Non-destructive quality control of kiwi fruits by hyperspectral imaging

This study aimed to evaluate the possibility to perform a fast, reliable and robust non-destructive monitoring of kiwifruits characteristics adopting an HyperSpectral Imaging (HSI) based approach. HSI was thus utilized for two different purposes: i) to test whether the postharvest ripeness of kiwifruits could be non-destructively determined and ii) for the diagnosis of pseudomonas infection in the Kiwi orchards. To reach the 1st goal (i.e. fruit ripening evaluation) a NIR Spectral Camera acting in the range between 900 and 1700 nm has been used. To reach the 2nd goal a hyperspectral camera working in the VIS-NIR range (400 nm – 1000 nm) was used. For both the approaches "only" significance and robustness of the collected data, in respect of the selected operative conditions, was investigated and the results have been evaluated in terms of different Principal Components (PC) images.
Optimization of Algae Residues Gasification: Experimental and Theoretical Approaches

Gasification is one of the thermochemical pathways of biomass conversion that produces synthesis gas, tar, and char. This study aims to convert algal residues via gasification at different operating conditions; temperature, equivalence ratio, and biomass loading. The study was carried out in 3 steps; (1) testing the outcomes of temperature and loading effects on synthesis gas yield, (2) experimental optimization of gasification via Design Expert, and (3) theoretical optimization of gasification via Aspen Plus simulation. Temperature and equivalence ratio highly influenced synthesis gas composition, while loading demonstrated less effect on the synthesis gas composition. The experimental and simulated gasification outcomes were compared to obtain optimized conditions that produce high H2 and CO yields. The data were validated using root mean square error. The optimized temperature, loading, and equivalence ratio were found for both algal residues that produced 36.38 and 13.28mol% of H2 and CO, respectively for lipid extracted algae (LEA) and 47.99 and 26.05mol% of H2 and CO, respectively for fucoidan extracted seaweeds (FEA). There was a considerable variation between experimental and simulated data due to the simulation and experimental limitations. The average Carbon Conversion Efficiency values were 66.36 and 80.42% for LEA and FES, respectively, denoting that LEA produced less carbon-containing products, while FES produced more carbon-containing products. In conclusion, LEA gasification yielded more H2 while FEA produced more CO.