Miracle-dz/UniFAR-FTUs huggingface dataset:
An integrated material flow system approach for determining the economic production quantity (EPQ)

Traditionally, the analysis of material flow systems has focused on each of the individual components of the system separately (i.e. material handling, production lot size, unit load size, flow path, layout, space, etc). Even though each component is difficult to address on its own, it is imperative that they be addressed concurrently due to their interactions. This paper explores the relationships between the components in the material flow system with respect to determining the economic production quantity (EPQ). This is in contrast to the traditional EPQ model, which considers only set-up cost, inventory cost, and demand, while ignoring other material flow system issues. A multi-item economic production quantity model under a storage space limit is considered with respect to material handling equipment selection and requirements, unit load size, and flow path selection. The integrated material flow system problem is mathematically formulated as a large scale, nonlinear integer programming model, and a heuristic solution procedure is developed. The impact of using an integrated approach to determine the EPQ is illustrated and solutions are compared to both a lower bound and a traditional sequential approach. It is found that an integrated approach provides consistent and significant improvement in the overall solution quality.
The Right Arrangement of Positioning, Differentiation, and Brand Based on Value-Driven Marketing

ABSTRACT The background in this research was the target number of registrant in The Midwifery Academy Bojonegoro’s District among 2009-2011 has not yet reached as big as more 200’s registrants. The objectives of research are arrangement of positioning, differentiation and brand according to Value-Driven Marketing in The Midwifery Academy Bojonegoro’s District. The design implementation of research is survei and cross sectional. Sampling was done by stratified random sampling, simple random sampling on lecturers and students of The Midwifery Academy Bojonegoro’s District. , 11th class students of SMAN 3 Bojonegoro, alumnus of The Midwifery Academy Bojonegoro’s District using accidental sampling method. Quantity of sample in this research are 219’s respondents and 9th for Delphi’s respondents using descriptive analysis, modus and frequency. The result of this research, the respondent’s assessment dominantly choose permission-to-play values as basic point for determining Value-Driven Marketing. The result of respondent’s assessment was confirmed to the Delphi’s respondent are dominantly choosed permission-to-play values in 77,8 percentages. The results FGD 1 show that the selected elements of permission-to-play values are professionalism, accountability, and integrity. The result FGD 2 to arrangement of positioning, differentiation and brand based on Value-Driven Marketing at The Midwifery Academy Bojonegoro’s District. Keywords marketing 3.0, positioning, differentiation, brand, value-driven marketing
Analysis of emitter-coupled multivibrators by singularly perturbed systems

Emitter-coupled multivibrators play a decisive role in electrical engineering, especially for phase locked loops which are key-building blocks of analogue RF front-ends. Since multivibrators correspond to relaxation oscillators, in the following the modelling and analysis by the theory of singularly perturbed systems is presented. Models for fast and slow phenomena are derived, and the fast transients of emitter-coupled multivibrators are analysed for the first time. The results of our analysis lead to significant advantages for the design of electrical multivibrators.
Plastic Biodegradation through Insects and their Symbionts Microbes: A Review

Plastic waste has recently been identified as one of the most serious environmental issues, affecting all life forms, natural habitats, and the economy, and is one of the most serious global environmental problems, second only to climate change. Seeking alternative environmentally sustainable options, such as biodegradation instead of conventional disposal, is critical in the face of this challenge. However, there is currently a lack of information about the mechanisms and efficacy of plastic biodegradation. From this perspective, this study aims to illustrate the negative environmental impacts of the plastic waste. It also addresses the role of insects and gut microbiota in the degradation of plastics, emphasizing the important role they will play in the future.
Direct Torque Control Strategy for Doubly Fed Induction Machine under Low Voltage Dips

This paper proposes a control strategy of generating a rotor flux amplitude reference for Doubly Fed Induction Machine (DFIM) based wind turbines. In addition to that a Direct Torque Control (DTC) strategy that provides fast dynamic response accompanies the overall control of the wind turbine. It is specially designed to address perturbations, such as voltage dips, keeping controlled the torque of the wind turbine, considerably reducing the stator and rotor over currents during faults. Despite the fact that the proposed control does not totally eliminate the necessity of the typical crowbar protection for this kind of turbines, it eliminates the activation of this protection during low depth voltage dips. DOI: http://dx.doi. org/10.11591/ijpeds.v2i4. 710
Transit’s Value-Added Effects: Light and Commuter Rail Services and Commercial Land Values

Transit-oriented development has gained favor as a means of reducing traffic congestion, promoting affordable housing, and curbing sprawl. The effects of proximity to light and commuter rail stations are modeled as are the effects of freeway interchanges on commercial-retail and office properties in fast-growing Santa Clara County, California. From hedonic price models, substantial capitalization benefits were found, on the order of 23% for a typical commercial parcel near a light rail transit stop and more than 120% for commercial land in a business district and within 0.25 mi of a commuter rail station. Such evidence is of use not only to developers and lenders but also to transit agencies facing lawsuits over purported negative externalities associated with being near rail. It can also help in the design of creative financing, such as value-capture programs.
A generalized steady-state analysis of resonant converters using two-port model and Fourier-series approach

A generalized steady-state analysis of resonant power converters using a two-port model and the Fourier-series approach is presented. Analysis is presented for both voltage-source and current-source type loads. Analysis can also be used either for variable frequency or for fixed-frequency (phase-shift control) operation. Steady-state solutions have also been obtained. Particular cases are considered to show the method of application in analyzing different schemes. A simple design procedure is given for a particular case ((LC)(LC)-type) to illustrate the use of analysis in obtaining design curves and in designing the power converter. Experimental results obtained from a MOSFET based 500 W power converter are presented to verify the analysis for this particular case. <<ETX>>
Image fusion technology for security and surveillance applications

Image fusion technology offers a range of potential benefits to the security and surveillance community, including increased situational awareness and enhanced detection capabilities. This paper reports on how image fusion technology is being adapted from the military arena (in which it is generally found today) to provide a new and powerful asset in the fight against crime and terrorism. The combination of detection and tracking processing with image fusion is discussed and assessed. Finally, a number of specific examples are presented which include land, air, and sea applications.
Cost-effectiveness analysis protocol of the Smart Triage program: A point-of-care digital triage platform for pediatric sepsis in Eastern Uganda

Background Sepsis is a clinical syndrome characterized by organ dysfunction due to presumed or proven infection. Severe cases can have case fatality ratio 25% or higher in low-middle income countries, but early diagnosis and timely treatment have a proven benefit. The Smart Triage program in Jinja Regional Referral Hospital in Uganda will provide expedited sepsis treatment in children through a data-driven electronic patient triage system. To complement the ongoing Smart Triage interventional trial, we propose methods for a concurrent cost-effectiveness analysis of the Smart Triage platform. Methods We will use a decision-analytic model taking a societal perspective, combining government and out-of-pocket costs, as patients bear a sizeable portion of healthcare costs in Uganda due to the lack of universal health coverage. Previously published secondary data will be used to link healthcare utilization with costs and intermediate outcomes with mortality. We will model uncertainty via probabilistic sensitivity analysis and present findings at various willingness-to-pay thresholds using a cost-effectiveness acceptability curve. Discussion Our proposed analysis represents a first step in evaluating the cost-effectiveness of an innovative digital triage platform designed to improve clinical outcomes in pediatric sepsis through expediting care in low-resource settings. Our use of a decision analytic model to link secondary costing data, incorporate post-discharge healthcare utilization, and model clinical endpoints is also novel in the pediatric sepsis triage literature for low-middle income countries. Our analysis, together with subsequent analyses modelling budget impact and scale up, will inform future modifications to the Smart Triage platform, as well as motivate scale-up to the district and national levels. Trial registration Trial registration of parent clinical trial: NCT04304235, https://clinicaltrials.gov/ct2/show/NCT04304235. Registered 11 March 2020.
AVOIDANCE FACTORS AGAINST ONLINE ADVERTISEMENTS

This study explains the factors related to the avoidance of an advertisement by consumers. Factors that contribute to the avoidance of advertisements are important, as they lead to helping designers to design better and more effective advertisements. The results of this study have affirmed the factors related to the avoidance of advertisements by consumers. These factors are a good guidance for stakeholders, such as designers, educators, students, etc., to design better advertisements. These factors also serve as a direction for stakeholders to take, in order to increase the effectiveness of information delivery to consumers.
Austroads repeated load triaxial test method: determination of permanent deformation and resilient modulus characteristics of unbound granular materials under drained conditions

There is a need for performance characterisation indices and performance-based specifications of unbound materials. In addition, there is a need to address issues associated with the non-uniformity of current empirical specifications adopted by different AUSTROADS Member Authorities, with a view to developing more uniform national performance-based specifications using a framework based on mechanistic design procedures. Repeat load triaxial (RLT) testing equipment and test procedures have been developed and evaluated in NSRP Project N&T 9529 - Stage 1) and current specifications for standard unbound materials (Project T&E P133) are being reviewed. The objective of the NSRP Project N.T. &E 9906 during 1999/2000 is to establish a framework for incorporating the RLT test method into performance-based specifications and pavement design of unbound pavement materials. This report describes the interim AUSTROADS test protocols for the determination of permanent deformation and resilient modulus characteristics of unbound pavement materials under drained conditions, which can be used for the purposes of material specifications and pavement design.
Small facial image dataset augmentation using conditional GANs based on incomplete edge feature input

Image data collection and labelling is costly or difficult in many real applications. Generating diverse and controllable images using conditional generative adversarial networks (GANs) for data augmentation from a small dataset is promising but challenging as deep convolutional neural networks need a large training dataset to achieve reasonable performance in general. However, unlabeled and incomplete features (e.g., unintegral edges, simplified lines, hand-drawn sketches, discontinuous geometry shapes, etc.) can be conveniently obtained through pre-processing the training images and can be used for image data augmentation. This paper proposes a conditional GAN framework for facial image augmentation using a very small training dataset and incomplete or modified edge features as conditional input for diversity. The proposed method defines a new domain or space for refining interim images to prevent overfitting caused by using a very small training dataset and enhance the tolerance of distortions caused by incomplete edge features, which effectively improves the quality of facial image augmentation with diversity. Experimental results have shown that the proposed method can generate high-quality images of good diversity when the GANs are trained using very sparse edges and a small number of training samples. Compared to the state-of-the-art edge-to-image translation methods that directly convert sparse edges to images, when using a small training dataset, the proposed conditional GAN framework can generate facial images with desirable diversity and acceptable distortions for dataset augmentation and significantly outperform the existing methods in terms of the quality of synthesised images, evaluated by Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) scores.
NLP and Deep Learning Methods for Curbing the Spread of Misinformation in India

ABSTRACT The current fight against COVID-19 is not only around its prevention and cure but it is also about mitigating the negative impact resulting from misinformation around it. The pervasiveness of social media and access to smartphones has propelled the spread of misinformation on such a large scale that it is considered as one of the main threats to our society by the World Economic Forum. This ‘Infodemic’ has caused widespread rumors, fueled practices that can jeopardize one’s health, and has even resulted in hate violence in certain parts of the world. We built an engine that has the ability to match incoming text, which may contain correct or incorrect information, with a known repository of misinformation. By matching texts on embeddings generated using BERT, we evaluated paraphrased texts to see if they matched texts previously labeled as misinformation. Further, we augmented an existing data corpus of texts by tagging each misinformation with one or more impact categories. We may be able to take specific actions to avert the consequence of misinformation if we can predict the particular ramification of a certain type of misinformation.
Box-like filter response and expansion of FSR by a vertically triple coupled microring resonator filter

The Lorentzian-shape filter response of a microring resonator filter is not suitable for practical use in wavelength division multiplexing (WDM) systems because of the lack of passband flatness, high crosstalk, and the large wing in the rejection band. Therefore, the tailoring of filter response shape is required to improve the performance. The series coupled microring resonator is one of the solutions. We designed and fabricated vertically triple coupled microring resonator add/drop filters with a stacked configuration. A box-like filter response with a flat passband was successfully obtained, and the free spectral range (FSR) was expanded to 25.8 nm owing to the Vernier effect.
Risk and Trust Models for the Cloud

Risk in itself is not bad, risk is essential to progress, and failure is often a key part of learning. But we must learn to balance the possible negative consequences of risk against the potential benefits of its associated opportunity. With the increase in the growth of cloud computing and the changes in technology that have resulted new ways for cloud providers to deliver their services to cloud consumers, the cloud consumers should be aware of the risks and vulnerabilities present in the current cloud computing environment. An information security risk assessment is designed specifically for that task. However, there is lack of structured risk assessment approach to do it. In this paper, firstly, I provide the definition of risk, also risk analysis, assessment, and management as well as their relationship and differences. Secondly, this paper will define the term “threat” and introduce the top threats and vulnerabilities for cloud computing by Cloud Security Alliance (CSA). Next, I present a cloud risk management by European Network and Information Security Agency (ENISA). The last section is about risk and trust models, and it also introduce two models developed by A4Cloud, which are Cloud adopted risk assessment model (CARAM) and the Joint risk and trust model (JRTM).
AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.
Appendix for “ MUSIQ : Multi-scale Image Quality Transformer ” A

We use the classic Transformer encoder [9] in our experiments. As illustrated in Figure 1, the Transformer block layer consists of multi-head self-attention (MSA), Layernorm (LN) and MLP layers. Residual connections are added in between the layers. In MST-IQA, the multi-scale patches are encoded as xk where k = 0 · · ·K is the scale index and n is the patch index in the scale. k = 0 represents the full-size image. We then add HSE and SCE to the patch embeddings, forming the multi-scale representation input. Similar to previous works [2], we prepend a learnable [class] token embedding to the sequence of embedded tokens (xclass). The Transformer encoder can be formulated as:
A Study of Factors Affecting Attitude Towards Using Mobile Cloud Service

As smart devices have proliferated and mobile networks have accelerated, various wired IT(Information Technology) services are transplanted in wireless environments. Cloud computing service, enabling individual users or firm users to download data from a server and upload data after manipulating data, is also available in mobile devices. Unlike cloud service in wired network environments, mobile cloud service provides differentiated aspects in mobility, security issues caused by persistent connection to networks. In this paper we aim to analyze the factors affecting the user attitude and their structural relationships towards mobile cloud service use. We extend TAM(Technology Acceptance Model) to consider the characteristics of mobile environments. Research findings, analyzed by SEM(Structural Equation Model), are explained and practical implications are presented with concluding remarks.
Active and passive spatial learning in a complex virtual environment: The effect of effcient exploration

In natural and virtual environments (VE) spatial learning depends on several factors including the spatial goal, environmental complexity and mode of learning. A factor influencing the mode of learning is the extent to which exploration is self-governed. The aim of this study was to investigate the effect of active (self-governed) vs. passive (avatar- guided) exploration on the organization of spatial knowledge of a large-scale VE in a wayfinding task. In particular, we wanted to test the hypothesis that self-governed explo- ration promotes the creation of a survey-type representation when participants are requested to explore efficiently (i.e. avoid repeatedly traversing the same paths). Twenty male participants were randomized to a passive group or an active group; both groups performed a two-phase task. In the first phase (learning phase), they learned an unfamiliar large-scale closed VE on two floors with a cross shaped ground plan. The pas- sive group learned by following an avatar; the active group explored at will. All were instructed to find, in the shortest possible time, target flags positioned through the VE. In the test phase, participants' spatial knowledge was assessed by three tasks: wayfinding (one session), pointing to the starting point of a traveled path (four sessions), and producing a sketch map of the VE. In the wayfinding task, 7 active participants found the way against 2 in the passive group. Among participants who found the way 5/7 in the active group have drawn a survey-type (hierarchically organized) map while none of the 2 in the passive group produced a map of this type. As expected, the groups did not differ in performance of the pointing tasks. These find- ings support the hypothesis that self-governed explorations in a VR are favored if spatial knowledge is organized in survey mode.
PrivGuard: Privacy Regulation Compliance Made Easier

Continuous compliance with privacy regulations, such as GDPR and CCPA, has become a costly burden for companies from small-sized start-ups to business giants. The culprit is the heavy reliance on human auditing in today’s compliance process, which is expensive, slow, and error-prone. To address the issue, we propose P RIV G UARD , a novel system design that reduces human participation required and improves the productivity of the compliance process. P RIV G UARD is mainly comprised of two components: (1) P RIV A NALYZER , a static analyzer based on abstract interpretation for partly enforcing privacy regulations, and (2) a set of components providing strong security protection on the data throughout its life cycle. To validate the effectiveness of this approach, we prototype P RIV G UARD and integrate it into an industrial-level data governance platform. Our case studies and evaluation show that P RIV G UARD can correctly enforce the encoded privacy policies on real-world programs with reasonable performance overhead.