Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of mass customized paratransit services

In the decades characterized by ageing population, many community transportation organizations face challenges to serve various needs of people sustainably because of limited social welfare expenditure. This research aims to design mass customized services that provide multiple types of paratransit service through better system design and optimization of vehicle resources. In this paper, we focus on integrating scheduler route (SR) service with dial-a-ride (DAR) service, along with the option of a shared ride program. In the first part, we study how different types of paratransit services can be represented systematically under the same family structure. The identified commonality of processes among different service types will lead to the optimization of vehicle scheduling. Then, in the second part, we will develop a mechanism for scheduling vehicles to serve different types of passengers. Illustrated in a numerical example, 20% more passengers could be served by the integrated model of two service types.
A Case Study of Value-Added Tax Issues on Customer Loyalty Programs in Korea

This research examines the issue of taxation on customer loyalty programs (so called “mileage programs”). We refer to a case in business practice in order to closely observe the appropriateness of the current taxation system. The Company addressed (hereafter “Company”) maintains both tax-exempt and taxable operations. The controversy arises when the points earned in the tax-exempt business are exchanged for services, provided by the taxable operations. While it is frequently argued that the transactions of such nature should be taxed, we conclude that they are not liable for taxation based on the related laws and regulations. Offers for free service in discussion contravenes the legally defined range of service provided and what’s more, the points earned do not carry monetary value. Furthermore, the current value-added tax laws confine property liable for taxation to goods under the article No. 48. Also, the revenue from service made by mileage (the points) should be excluded from the tax base according to the reinterpretation of the Ministry of Strategy and Finance Case No. 319 (March 29, 2006) However, here arises the controversy. When points are utilized as a means of payments, they are expected to be subject to taxation. The same logic is to be implemented in the light of tax equality. Meanwhile, once value-added tax is imposed on the revenue made by mileage (the points), it would largely impact the industry offering loyalty programs to its customers. Thus, it is necessary to establish tax laws and regulations concerning customer loyalty programs.
Efficient Modeling of Modular Multilevel HVDC Converters (MMC) on Electromagnetic Transient Simulation Programs

The number of semiconductor switches in a modular multilevel converter (MMC) for HVDC transmission is typically two orders of magnitudes larger than that in a two or three level voltage-sourced converter (VSC). The large number of devices creates a computational challenge for electromagnetic transient simulation programs, as it can significantly increase the simulation time. The paper presents a method based on partitioning the system's admittance matrix and deriving an efficient time-varying Thévenin's equivalent for the converter part. The proposed method does not make use of approximate interfaced models, and mathematically, is exactly equivalent to modelling the entire network (converter and external system) as one large network. It is shown to drastically reduce the computational time without sacrificing any accuracy. The paper also presents control algorithms and other modelling aspects. The efficacy of the proposed method is demonstrated by simulating a point-to-point VSC-MMC-based HVDC transmission system.
Searching for differential expression: a non-parametric approach

Microarray experiments are being widely used in medical and biological research. The main features of these studies are the large number of variables (genes) involved and the low number of replicates (arrays). It seems clear that the most appropriate models, when looking for detecting differences in gene expression are those that exploit the most useful information to compensate for the lack of replicates. On the other hand, the control of the error in the decision process plays an important role for the high number of simultaneous statistical tests (one for each gene), so that concepts such as the false discovery rate (FDR) take a special importance. One of the alternatives for the analysis of the data in these experiments is based on the calculation of statistics derived from modifications of the classical methods used in this type of problems (moderated-t, B-statistic). Nonparametric techniques have been also proposed [B. Efron, R. Tibshirani, J.D. Storey, and V. Tusher, Empirical Bayes analysis of a microarray experiment, J. Amer. Stat. Assoc. 96 (2001), pp. 1151–1160; W. Pan, J. Lin, and C.T. Le, A mixture model approach to detecting differentially expressed genes with microarray data, Funct. Integr. Genomics 3 (2003), pp. 117–124], allowing the analysis without assuming any prior condition about the distribution of the data, which make them especially suitable in such situations. This paper presents a new method to detect differentially expressed genes based on non-parametric density estimation by a class of functions that allow us to define a distance between individuals in the sample (characterized by the coordinates of the individual (gene) in the dual space tangent to the manifold of parameters) [A. Miñarro and J.M. Oller, Some remarks on the individuals-score distance and its applications to statistical inference, Qüestiió, 16 (1992), pp. 43–57]. From these distances, we designed the test to determine the rejection region based on the control of FDR.
A review of HELLP syndrome, in 17 patients

Introduction Preeclampsia is a well known obstetric complication characterized with hypertension and proteinuria whereas HELLP syndrome (hemolysis, elevated liver enzymes, low platelet count) which was first stated by Prichard in 1954 and described by Weinstein in 1982, is a multisystemic disease usually seen in the third trimester and in the postpartum period, usually in 48 - 72 hours following delivery [1]. Aim In this study we aim to share our experience in 17 patients with HELLP syndrome treated in our clinic between January 2005 and March 2008 in regard of the current literature. Material and Methods 17 patients diagnosed with HELLP syndrome between January 2005 and March 2008 were retro-spectively re-evaluated in regard of symptoms, treatment options and prognosis. As such this is a retro-spective study focusing on case reports. Conclusion As noted before main focus of treatment should be on patient stability, in other words, palliative care under intensive care conditions.
Multi area load frequency control of interconnected power systems using JAYA

Load frequency control problem in interconnected multi area power system incorporating renewable energy generation has been investigated. Three area model with first area consisting of non-reheat synchronous generator, second with reheat synchronous generator based power plant and third with hydro generating unit is considered. In addition to synchronous generator, a DFIG-wind turbine unit is incorporated in first area. Jaya heuristic technique based controller design has been proposed to mitigate frequency deviations. The proposed controller has been compared with existing PSO based controller. Simulation results establish the efficacy of the proposed technique.
Contingent Capital: The Case of COERCs

Abstract This paper introduces and analyzes a new form of contingent convertible: a call option enhanced reverse convertible (COERC). If an issuing bank’s market value of capital breaches a trigger, COERCs convert to many new equity shares that would heavily dilute existing shareholders, except that shareholders have the option to purchase these shares at the bond’s par value. COERCs have low risk: They are almost always fully repaid in cash. Yet, they reduce government bailouts by replenishing a bank’s capital. COERCs’ design also avoids problems with market-value triggers, such as manipulation or panic, while reducing moral hazard and debt overhang.
Measuring Use and Cost of Care for Patients With Mood Disorders: The Utilization and Cost Inventory

Background:Researchers conducting cost-outcome studies must account for all materially relevant care that subjects receive from their care providers. However, access to provider records is often limited. This article describes and tests the Utilization and Cost Inventory (UAC-I), a structured patient interview designed to measure costs of care when access to provider records is limited. Methods:UAC-I was tested on 212 consenting adult veterans with mood disorder attending a VA medical center. Counts (inpatient days and outpatient encounters) and costs (dollars) computed from survey responses were compared with estimates from medical records and an alternative structured questionnaire. Results:The agreement between inpatient costs computed from provider records and from UAC-I responses, assessed using the intraclass correlation coefficient (ICC), was 0.66, 95% confidence interval (CI), 0.30–0.84; the bias was −3.7%, 95% CI, −48 to 41. The ICC for the service data (inpatient days) was 0.97, 95% CI, 0.95–0.99; the bias was <1%, 95% CI, −14 to 15. The ICC for outpatient costs computed from provider records and from UAC-I responses was 0.53 95% CI, 0.38–0.65; the bias was <1%, 95% CI, −27 to 27. The ICC for outpatient encounters was 0.74, 95% CI, 0.65–0.80; the bias was <1%, 95% CI, −16 to 18. Conclusions:These results indicate that it may be feasible for cost-outcome studies to compare patient groups for inpatient and outpatient costs computed from patient self-reports.
Metric Learning via Maximizing the Lipschitz Margin Ratio

In this paper, we propose the Lipschitz margin ratio and a new metric learning framework for classification through maximizing the ratio. This framework enables the integration of both the inter-class margin and the intra-class dispersion, as well as the enhancement of the generalization ability of a classifier. To introduce the Lipschitz margin ratio and its associated learning bound, we elaborate the relationship between metric learning and Lipschitz functions, as well as the representability and learnability of the Lipschitz functions. After proposing the new metric learning framework based on the introduced Lipschitz margin ratio, we also prove that some well known metric learning algorithms can be shown as special cases of the proposed framework. In addition, we illustrate the framework by implementing it for learning the squared Mahalanobis metric, and by demonstrating its encouraging results on eight popular datasets of machine learning.
Fraud Control in the Health Care Industry : Assessing the State of the Art

● Most insurers, public and private, have failed to measure systematically the fraud problem they face. Oblivious to the slightly more technical presentation of some of the material in this Research in Brief is found in the article “Health Care Fraud Control: Understanding the Challenge,” published in the Journal of Insurance Medicine, 28 (November 1996):2, 86–96. We are grateful to the publication’s managing editor, Dr. Nigel Roberts, for his permission to use information from the article in this Research in Brief.
Where are the Mycobacterium Ulcerans? Mapping the Risk and Vulnerable Areas of Mycobacterium Infection in the Amansie West District of Ghana

Mycobacterium Ulcerans (MU) is the bacterium that causes Buruli ulcer (BU), a neglected tropical disease whose epidemiology has proven hard to pin down till date. This study was undertaken to map out the high and low risk areas of the disease in the Amansie West District, the most endemic constituency in Ghana. The disease affects people who live on less than a dollar a day and scourges mainly women and children. It is unclear where the bacterium lives in the environment and how it enters the human body. These slits in knowledge necessitated the study. Semivariograms were computed to determine the strength and the spatial dependency of the pattern of the disease. Kriging was chosen in the variogram modeling. The BU datasets exhibited a highly positively skewed histogram with possible outlying. The kriged map showed large patches of BU infections in the southern, eastern and western parts of the study area. Coincidentally, these areas are drained by the two major rivers, Oda and Offin and also characterized by intense mining and agricultural activity. The paper is of the view that the environmental characteristics and intense economic activity may be responsible for the high concentration of MU in the identified areas.
Eléments d"acoustique générale

Ce manuel d’enseignement presente les principaux elements de l’acoustique physique. Une approche didactique a ete privilegiee, les themes presentes etant abordes par le biais d’une description d’objets courants extraits par exemple de la lutherie, de l’environnement, de l’industrie ou de la physiologie. L’auteur introduit par ailleurs quelques methodes numeriques necessaires a la resolution de problemes plus complexes, tout en mettant l’accent a l’aide de calculs elementaires sur les bases essentielles de cette discipline. Cet ouvrage regroupe ainsi dans un ensemble coherent et synthetique les bases physiques et numeriques de l’acoustique et il sensibilise le lecteur a divers problemes d’optimisation illustres de cas pratiques.
Separation of occluded leaves using direction field

This paper proposes a method that separates the region of each leaf from an image of occluded leaves and produces a set of single-leaf images as an output. To identify the region of a single leaf, intersection points and direction field are required. An intersection point, which is defined as a concave point between leaves, is used as the starting position of leaf estimation process. Direction field, which describes the average direction of edges in a local area, is used to guide the estimation process. Leaf separation process applies the result of leaf estimation process to create an output. Experimental results show that 71.23% of testing leaf images were correctly separated from each other with a segmentation accuracy of 88.80%.
1 Adaptive df / dt Relay-A case study with reference to the Indian Power System

s: df/dt relays are used in the power industry to rescue systems facing extreme disturbances to avoid system collapse. Traditionally, many computations are repeated to seek the proper power system settings such that the df/dt relay provides the desired good performance for selected scenarios. In this paper a case study of tripping of Farakka Super Thermal Power Station and proposed adaptive df/dt method for
Wireless and Autonomous Sensor for Strut Load Monitoring

In case of hard landings, engine mounts or landing gears can be damaged and must be inspected as the severity of landing is not well estimated based on aircraft inertial system and models. Such inspections can be time consuming and generate delays, cancellations and inappropriate maintenance actions that could be avoided if a sensor is able to measure the accurate load level sustained by the equipment. The aim of the project is to develop an autonomous wireless sensor with local intelligence and storage capacity that can be downloaded upon request. A micro-mechanic MEMS sensor (chronoMEMS), using cogwheels, has been implemented: when a predefined level of load is reached, the sensor increments a counter. To validate the discrete information given by this sensor, strain gauges have been added. Interrogating the sensor must be easy and fast so that a wireless interrogating system based on RFID has been chosen. An Energy Harvesting system transforming Thermal and Vibration into electric power has been developed to supply the strain gauges and the memory (chronoMEMS does not require power). Lab tests have been done on thermal and vibration energy harvesters. RFID transmission in the engine area is yet under studies and tests. The next step is to develop a prototype of a full sensor integrating all these parts working together in the engine harsh environment. This technology could be used to monitor any kind of load charge for which real time surveillance is not necessary. Snecma (Safran Group) is the leader of this project allied to SilMach and SKF Aerospace. SilMach develops the chronoMEMS load sensor. SKF Aerospace is in charge of strain gauges, energy harvesting, RFID modules and complete system assembly.
Investigation of IR based topic models on issue tracking systems to infer software-specific semantic related term pairs

Software maintenance is a core component of any software development life-cycle. Contemporary software systems contain voluminous and complex information stored in software repositories. Software maintenance professionals spend significant amount of time in search and exploration of these repositories for common maintenance tasks like bug fixing, feature enhancements, code refactoring and reengineering. Therefore, tools and methods to facilitate search in software repositories can aid software maintenance professionals to have faster access to required information and increase productivity. A domain-specific lexical resource is an important tool to bridge the semantic gap existing between the information need and search query. In this work, we investigate the use of information retrieval (IR) based topic models (like LSI and LDA) to infer semantically related terms for a software context specific lexical resource. We perform our experiments on Google Chromium — a widely popular open-source browser — issue tracker system which contains 134,000+ bug reports. We divide our study into two parts — (1) In the first part, we apply our IR models on free form natural language textual data present in defect tracking systems. We perform qualitative analysis on the obtained output and uncover semantically related terms in the Google Chromium software context. We observe that we are able to infer semantically similar term pairs in four different contexts of English language, Software, Google Chromium and Code details. (2) In second part of this study, we utilize the semantically inferred terms obtained from the output of IR models to facilitate the software maintenance task of duplicate bug report detection. Our results demonstrate that the use of IR based topic models on defect tracking systems to automatically infer semantically related terms can help build a software domain-specific lexical resource and reduce the vocabulary gap.
The Using of Ionic Gelation Method Based on Polysaccharides for Encapsulating the Macromolecules – A Review

Recently, there has been a considerable research interest in the area of bioactives delivery system using polysaccharides as non toxic biodegradable encapsulates materials. The methode to obtain encapsulates particle from those materials was using ionic gelation that has some benefits i.e. very mild conditions and avoiding harmful organic solvents or high shear forces. The materials have been used to protect the bioavailability and functionality of bioactive from harsh condition of digestive system and to deliver on target site at controlled and sustained rate to the site action. Various biopolymer have been used in research on formulation of encapsulates particle to increase therapeutic benefit, while minimised the disadvantage. We review the using of ionic gelation methods on various formulations of materials and its characteristics, and their application in encapsulation of some important macromolecules.
Power-Efficient Modulation Formats in Coherent Transmission Systems

Coherent optical transmission systems have a four-dimensional (4-D) signal space (two quadratures in two polarizations). These four dimensions can be used to create modulation formats that have a better power efficiency (higher sensitivity) than the conventional binary phase shift keying/quadrature phase shift keying (BPSK/QPSK) signals. Several examples are given, with some emphasis on a 24-level format and an 8-level format, including descriptions of how they can be realized and expressions for their symbol and bit error probabilities. These formats are, respectively, an extension and a subset of the commonly used 16-level dual-polarization QPSK format. Sphere packing simulations in 2, 3, and 4 dimensions, up to 32 levels, are used to verify their optimality. The numerical results, as the number of levels increases, are shown to agree with lattice-theoretical results. Finally, we point out that the use of these constellations will lead to improved fundamental sensitivity limits for optical communication systems, and they may also be relevant as a way of reducing power demands and/or nonlinear influence.
Massless metric preheating

Can super-Hubble metric perturbations be amplified exponentially during preheating ? Yes. An analytical existence proof is provided by exploiting the conformal properties of massless inflationary models. The traditional conserved quantity \zeta is non-conserved in many regions of parameter space. We include backreaction through the homogeneous parts of the inflaton and preheating fields and discuss the role of initial conditions on the post-preheating power-spectrum. Maximum field variances are strongly underestimated if metric perturbations are ignored. We illustrate this in the case of strong self-interaction of the decay products. Without metric perturbations, preheating in this case is very inefficient. However, metric perturbations increase the maximum field variances and give alternative channels for the resonance to proceed. This implies that metric perturbations can have a large impact on calculations of relic abundances of particles produced during preheating.
Innovative Fault Detection, Isolation and Recovery Strategies On-Board Spacecraft: State of the Art and Research Challenges

This paper summarizes basic concepts and the current state of the art in spacecraft fault detection, isolation and recovery. A gap analysis focuses on drawbacks of classical fault diagnosis methods in deep space applications. Studies that propose innovative techniques are summarized and evaluated briefly with respect to enhanced spacecraft on-board fault diagnosis on system level. Research challenges for the introduction of these methods in spacecraft FDIR are outlined and a development roadmap is elaborated.
Phytoremediation-biorefinery tandem for effective clean-up of metal contaminated soil and biomass valorisation

ABSTRACT During the last few decades, phytoremediation process has attracted much attention because of the growing concerns about the deteriorating quality of soil caused by anthropogenic activities. Here, a tandem phytoremediation/biorefinery process was proposed as a way to turn phytoremediation into a viable commercial method by producing valuable chemicals in addition to cleaned soil. Two agricultural plants (Sinapis alba and Helianthus annuus) were grown in moderately contaminated soil with ca. 100 ppm of Ni and further degraded by a fungal lignin degrader—Phanerochaete chrysosporium. Several parameters have been studied, including the viability of plants, biomass yield, and their accumulating and remediating potentials. Further, downstream processing showed that up to 80% of Ni can be easily extracted from contaminated biomass by aqueous extraction at mild conditions. Finally, it was demonstrated that the growth of plants on the contaminated soil could be degraded by P. chrysosporium, and the effect of nickel and biomass pretreatment on the solid-state fermentation was studied. The proposed and studied methodology in this work could pave the way for successful commercialization of the phytoremediation process in the near future.