Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisiting 'revisiting supervised methods for effort-aware cross-project defect prediction'

Effort ‐ aware cross ‐ project defect prediction (EACPDP), which uses cross ‐ project software modules to build a model to rank within ‐ project software modules based on the defect density, has been suggested to allocate limited testing resource efficiently. Recently, Ni et al. proposed an EACPDP method called EASC, which used all cross ‐ project modules to train a model without considering the data distribution difference between cross ‐ project and within ‐ project data. In addition, Ni et al. employed the different defect density calculation strategies when comparing EASC and baseline methods. To explore the effective defect density calculation strategies and methods on EACPDP, the authors compare four data filtering methods and five transfer learning methods with EASC using four commonly used defect density calculation strategies. The authors use three classification evaluation metrics and seven effort ‐ aware metrics to assess the performance of methods on 11 PROMISE datasets comprehensively. The results show that (1) The classification before sorting (CBS + ) defect density calculation strategy achieves the best overall performance. (2) Using balanced distribution adaption (BDA) and joint distribution adaptation (JDA) with the K ‐ nearest neighbour classifier to build the EACPDP model can find 15% and 14.3% more defective modules and 11.6% and 8.9% more defects while achieving the acceptable initial false alarms (IFA). (3) Better comprehensive classification performance of the methods can bring better EACPDP performance to some extent. (4) A flexible adjustment of the defect threshold λ of the CBS + strategy contribute to different goals. In summary, the authors recommend researchers and practitioners use to BDA and JDA with the CBS + strategy to build the EACPDP model.
Accounting for Locational, Temporal, and Physical Similarity of Residential Sales in Mass Appraisal Modeling: Introducing the Development and Application of Geographically, Temporally, and Characteristically Weighted Regression (GTCWR)

Geographically weighted regression (GWR) has been recognized in the assessment community as a viable automated valuation model (AVM) to help overcome, at least in part, modeling hurdles associated with location, such as spatial heterogeneity and spatial autocorrelation of error terms. Although previous researchers have adjusted the GWR weights matrix to also weight by time of sale or by structural similarity of properties in AVMs, the research described in this paper is the first that has done so by all three dimensions (i.e., location, structural similarity, and time of sale) simultaneously. Using 24 years of single-family residential sales in Fairfax, Virginia, we created a new locally weighted regression (LWR) AVM called geographically, temporally, and characteristically weighted regression (GTCWR) and compared it with GWR-based models with fewer weighting dimensions.GTCWR was the only model to achieve IAAO-accepted levels of the coefficient of dispersion (COD), price-related differential (PRD), price-related bias (PRB), and median assessment-to-sale price ratio in both the training and testing samples, although it did not fully correct the existence of heteroscedasticity. With lower PRD and PRB levels, the application of temporal weighting to this data set did appear to help reduce indicators of vertical inequity. Along with an equitable, uniform, and defensible methodology that mirrors the sales comparison, GTCWR presents a new AVM that demonstrates an ability to value over 24 years of sales at IAAO standard levels, without the creation and implementation of time-based variables, the trimming of outliers, and time-intensive model specification and calibration
The entrepreneurial process in social enterprises

The present study examines the evolving nature of social enterprise and identiﬁes the most significant factors related to individuals and institutions. Organisations that pursue both profit and non-proﬁt objectives, thus maintaining a mix of market- and mission-oriented practices and beliefs for addressing social and ecological issues, are known as “social enterprises. ” The present study examines the methods of identifying, evaluating, and exploiting the principal factors related to social entrepreneurial opportunities. For this purpose, a qualitative research process applying the Delphi technique was conducted. A Delphi sample of 25 experts from Spain and Latin America was included. This study contributes to building a framework of reference for academics and practitioners regarding the key factors inﬂuencing the different stages of the social entrepreneurial process. The empirical results of the study offer a testimony of the most signiﬁcant, both contextual and individual, factors in each stage of the social entrepreneurial process.
Mechanisms of Meridional-Propagating High-Frequency Intraseasonal Oscillation Associated with a Persistent Rainfall over South China

AbstractThe present study divides the intraseasonal variations into high-frequency intraseasonal oscillation (HF-ISO) with a 5–20-day period and low-frequency ISO (LF-ISO) with a 30–60-day period. Here, defined HF-ISO is heavily different from some previous work, because, over south China, persistent rainfall (PR) is not only related to the quasi-biweekly oscillation (10–20-day period), but also connected with the quasi-weekly oscillation (5–10-day period). Associated with a PR over south China during the first half of June 2016 (PR1606), the propagating components of the convections are largely attributed to the HF-ISOs. Moreover, both southward- and northward-propagating HF-ISOs are found in this case. Over southern China, the moisture advection dominated by anomalous flow and mean water vapor plays an important role in the southward propagation of the HF-ISO, and the cloud–radiation effect may be also, at least partially, responsible for the southward shift of the associated convective zone. Neverthele.
High Availability Design and Information Technology Architecture Optimization of Data Center Network

: With the rapid development of the Internet, enterprise informatization construction is becoming more and more important, and the rationality of data center network design has become the top priority of enterprise informatization construction. This paper mainly analyzes the high-availability design of the data center network and the optimization of the information technology architecture. When designing a data center network, it is necessary to analyze and plan the network architecture in combination with the specific conditions of the enterprise data center, so as to maximize the reliability of the network system, thereby improving the availability of the data center network. The optimization of information technology architecture also needs to comprehensively consider various factors such as system architecture, equipment functions, performance, and cost, so as to establish an information technology architecture suitable for its own development. Experimental results show that the bandwidth of the optimized data center network can reach 11.5TB/s.
PENERAPAN INOVASI SISTEM INFORMASI MANAJEMEN GUNA MEWUJUDKAN KETERBUKAAN INFORMASI PUBLIK

Abstrak: Seluruh informasi yang terkait dengan pengelolaan negara harus berani dipublikasikan secara transparan, terkecuali di dalamnya terdapat rahasia negara yang memang tidak boleh diketahui publik dan diatur di dalam UU. Masalah yang ditemui di Desa Arjowilangun adalah kurangnya pemahaman aparatur desa terhadap UU KIP 2008 dan SLIP Desa, kedua adalah kurangnya pemanfaatan sistem informasi untuk menyediakan informasi public desa. Berdasarkan latar belakang tersebut, kegiatan pengabdian ini bertujuan untuk berkontribusi terhadap upaya pemerintah desa Arjowilangun dalam mewujudkan keterbukaan informasi publik desa. Kegiatan ini difokuskan kepada pemahaman aparatur desa serta masyarakat terhadap UU KIP 2008 dan Peraturan Komisi Informasi Nomor 1 Tahun 2018 Tentang SLIP Desa serta peningkatan kapasitas aparatur desa dalam pemanfaatan system informasi manajemen. Terdapat tiga program yang dilakukan adalah sosialisasi, pelatihan dan focus group discussion (FGD). Peserta terbukti memahami materi mengenai UU KIP 2008 dan SLIP Desa dari sesi tanya jawab dan diskusi yang dilakukan setelah penyampaian materi. Selain pemahaman materi, peserta juga terbuki mampu menjalankan website dengan baik. Abstract: All information related to state management must dare to be published in a transparent manner, unless it contains state secrets which are not publicly known and are regulated in law. The problem encountered in Arjowilangun Village is the lack of understanding of the village apparatus towards the Information Disclosure law year 2008 and Village SLIP, the second is the lack of use of information systems to provide village public information. Based on this background, this service activity aims to contribute to the efforts of the Arjowilangun village government in realizing village public information disclosure. This activity focus on understanding the village apparatus and the community towards the 2008 KIP Law and Information Commission Regulation Number 1 of 2018 concerning Village SLIP and increasing the capacity of village officials in the use of management information systems. There are three programs carried out: socialization, training and focus group discussions (FGD). Participants proved to understand the material regarding Information Disclosure law year 2008 and Village SLIP from the question and answer session and discussion that was held after the presentation of the material. In addition to understanding the material, participants were also shown to be able to run the website well.
Does Good Nebulization Therapy in the Emergency Room Reduce the Need for Hospitalization in Asthmatic Children?

Introduction: Asthma is a chronic inflammatory disorder characterized by obstruction, hyperresponsiveness, and inflammatory changes in the airways. The overall prevalence of asthma in Saudi Arabian children ranges from 8% to 25%. Studies have shown that children who did not respond adequately to treatment in the emergency room (ER) were admitted to hospital for additional treatment which increased the cost and risk of hospital-acquired infections. The quality of nebulization therapy is influenced by several factors such as the position, dose, oxygen flow rate, and duration of treatment. Objectives: In this study, we aimed to explore factors that affect nebulization therapy in ER and to assess the relation between nebulization technique in ER and hospital admission for asthmatic children, and these aims were achieved over the period from December 2021 to May 2023. Methodology: An observational cross-sectional study was conducted in Maternity and Children Hospital (MCH) in Medina at the ER over the period from December 2021 to May 2023 for all children admitted to ER with asthma exacerbation. The sample size used to include patients in the study is 289 calculated using the Openepi website. Data were collected by observation and using medical records of the patients and analyzed using Statistical Package for Social Sciences (SPSS) version 26.0 (IBM Corp., Armonk, NY, USA). Results: The total number of the sample was 289 children ages between two to 14 years. Sixty-four percent (n=185) reported as their gender as male while 36% (n = 104) as female. The median age of the children was four years old (interquartile range [IQR] = 4), and their median weight was 15 kg (IQR = 8.15). Also, more than 83% of the patients has mild asthma, while 16.3% of the sample were diagnosed with moderate to severe asthma. Besides, 92.4% of the sample was discharged from a hospital, and 76.5% received an appropriate dose of nebulization. Discussion: After reviewing the results of the statistical analysis, the main findings were that the severity of asthma exacerbation was the most important factor influencing the outcome. It was found that 0.4% of patients with mild asthma were admitted to the hospital, compared to 44.7% of patients with moderate to severe asthma. Conclusion: Our study assessed whether effective nebulization therapy in the ER will reduce the need for hospitalization in asthmatic children and the results indicate that the severity of asthma exacerbation was the most significant factor impacting hospital admission in asthmatic patients and influenced other factors of nebulization therapy. However, the other factors, such as the patient position, oxygen flow rate, and the dose of medications did not show any clinically significant impact on hospitalization rates.
Tunable pseudo-Zeeman effect in graphene

One of the fundamental properties of spin 1/2 particles is their interaction with magnetic fields. The exploration of this coupling can be quite elusive, for example in the case of neutrinos. Graphene has been shown to be a condensed matter platform for the study of such ultrarelativistic particles, with its neutrino-like charge carriers having a spin-like degree of freedom called pseudospin. Here we show that in analogy to the spin alignment of a fermion in a magnetic field, the pseudo-spin of graphene can be oriented by a strain induced pseudo-magnetic field through the Zeeman term. We reveal this pseudo-spin polarization as a sublattice symmetry breaking by tunably straining graphene using the tip of a scanning tunnelling microscope. The observed pseudo-spin polarization scales with the lifting height of the strained deformation and therefore with the pseudo-magnetic field strength. Its magnitude is quantitatively reproduced by analytic and tight-binding models. This adds a key ingredient to the celebrated analogy of graphene's charge carriers to ultra-relativistic Dirac fermions. Furthermore, the deduced fields of about 1000 T could provide an effective THz valley filter, as a basic element of valleytronics.
Salivary Immune Parameters as A Predictor of Oral Diseases

Diabetes mellitus (DM) is a metabolic and hormonal disorder in which the body does not produce sufficient or respond ordinarily to insulin, leading to an increase in blood sugar (glucose) levels. This disordered has many side effects on body health, one of them being oral health. This study aimed to find these effects on several oral immune parameters included (IL6, CRP, and alpha-amylase) and the possible use of these parameters in the prediction of oral health and further risk sequel. A total of 91 specimens including 51 DM patients and 40 apparently healthy individuals were enrolled in this study which was carried out from November/2021 to February/2022. The results revealed that, abnormal increase of both IL6 and CRP in the saliva of both experimental groups, with no significant differences between them. Simultaneously, alpha-amylase shows significant increases in the saliva of the patient's group than in the control. Receiver operating characteristic (ROC) analysis with Area under the curve (AUC) confirmed that alpha-amylase can be used as a predictor parameter reflected oral and body health.
Basu-Dhar's bivariate geometric distribution in presence of censored data and covariates: some computational aspects

Some computational aspects to obtain classical and Bayesian inferences for the Basu and Dhar (1995) bivariate geometric distribution in presence of censored data and covariates are discussed in this paper. The posterior summaries of interest are obtained using standard existing MCMC (Markov Chain Monte Carlo) simulation methods available in popular free softwares as the OpenBugs software and the R software. Numerical illustrations are introduced considering simulated and real datasets showing that the use of discrete bivariate distributions may be a good alternative to the use of continuous bivariate distributions, in many areas of application.
A framework for usability evaluation of automated driving human-machine interface in context of UAE

As a future mobility enabler, vehicle teleoperation offers a viable option for efficiently leveraging the benefits of driverless cars, whilst fully automated cars (SAE 5) are not completely viable. Despite the huge amount of research on self-driving technology, the notion of riding in a fully automated vehicle is still sceptical. Hence necessitating the presence of a remote operator who tele monitors the vehicle and acquire control in case of failure beyond the capabilities of vehicle automation, such as misuse, disuse or mode confusion and ensuring safety and reliability. Keeping the current inclination towards automated vehicles and the launch of the United Arab Emirates” ( UAE) first driverless, autonomous 12-seater shuttle, the researcher has suggested a low-fidelity basic prototype. To connect the vehicle’s automation and human teleoperation, the researcher has proposed a unique and interactive framework of Human-Machine Interface (HMI) to cater teleoperation in the context of automated vehicles (AVs) in the UAE. The design is optimised for the teleoperation of a highly automated shuttle by a public transportation control centre based on a logical and careful inquiry. After deriving a detailed analysis of requirements, a prototype is then created and refined until an interactive user-interface emerges. Fifteen control station experts are presented with a prototype for evaluation in a regular manner and solicited to work out three scenarios with disruptions in the system. The prototype is then evaluated using questionnaires and structured interviews. The results validate the suggested HMI design for the remote operation of a highly automated vehicle. Participants’ feedback shows a particularly high level of satisfaction in terms of perceived capacity, feasibility, usability approval and situational responsiveness. The findings also provide valuable information for an advanced interactive HMI design and pave the way for potential future directions in further research as well.
The Latent Scale Covariogram: A Tool for Exploring the Spatial Dependence Structure of Nonnormal Responses

ABSTRACT When modeling spatially distributed normal responses Yi in terms of vectors xi of explanatory variables, one may fit a linear model assuming independence, and then use the empirical variogram of the residuals to determine an appropriate parametric form for the autocorrelation function. Suppose, however, that the responses are not normally distributed—for example, Poisson or Bernoulli. One may model spatial dependence using a hierarchical generalized linear model in which, conditional on a latent Gaussian field Z = {Zi}, the Yi have independent distributions from the exponential family, with an appropriate link function connecting their conditional means with the linear predictors xtiβ + Zi. The question then is how to determine an appropriate model for the autocorrelation function of Z. The empirical variogram of the Yi is no longer appropriate, since (unless the link function is the identity) it is on the wrong scale. We propose here an alternative, the latent scale covariogram, whose graph reflects the autocorrelation structure of the underlying normal field. We illustrate its use on several real datasets, together with a simulated dataset, and obtain results quite different from those obtained using the variogram. Supplementary materials for this article are available online.
Load Frequency Control in Power Systems Using Improved Particle Swarm Optimization Algorithm

The purpose of load frequency control is to reduce transient oscillation frequencies than its nominal value and achieve zero steady-state error for it . A common technique used in real applications is to use the proportional integral controller (PI). But this controller has a longer settling time and a lot of Extra mutation in output response of system so it required that the parameters be adjusted as appropriate . In this paper, we aim to design a system based on PI controllers using improved particle swarm optimization algorithm for load frequency control . Multi-population approach and local search to improve the optimization algorithms is used and displayed. That this approach will lead to accelerating the achievement of results, preventing entrapment in a local minimum, and get better system output compared with similar methods .
Influencia de los valores locales en los diseños cD-óptimos para el modelo logístico

En el diseño de experimentos es común el no uso de criterios para determinar los tratamientos y el número de réplicas que se deben realizar para la obtención de una buena estimación de los parámetros del modelo, debido principalmente al desconocimiento de estos y en muchas otras ocasiones por la dificultad en implementarlos. Los diseños óptimos tratan de resolver esta falencia al dar condiciones experimentales óptimas y los niveles de los factores donde se debe medir la respuesta, con el fin de obtener una mejora en la calidad de la inferencia estadística a un menor costo. En la búsqueda de diseños óptimos se utilizan criterios de optimalidad, los cuales son función de la matriz de información de Fisher. Uno de los problemas de estimación más frecuente en los modelos no lineales es la especificación de los valores locales para los parámetros del modelo, necesarios para la optimización del criterio de optimalidad. En este artículo se realiza un estudio de robustez de los diseños óptimos obtenidos en el modelo logístico, al considerar perturbaciones en los valores locales de los parámetros, con el fin de proporcionar al investigador un rango de maniobrabilidad en la selección de los valores locales y garantizando que el diseño óptimo resultante no pierda una eficiencia considerable con respecto al valor de referencia. Para ello, a partir de los datos de un ejemplo, se encuentran las eficiencias de cada uno de los diseños obtenidos con relación al valor sin perturbar; se construyen los diseños cD-óptimos locales para la estimación de la varianza del logit, se determinó que la magnitud de la perturbación en los diseños cD-óptimos locales obtenidos alcanzan una eficiencia alrededor de un 70 %, con un radio de 0.04 de perturbación sobre el valor de referencia.
Bichromatic Synthetic Schlieren for surface measurement

We introduce Bichromatic Synthetic Schlieren (BiCSS) for instantaneous surface measurements, in where we use two simultaneous images taken at blue and near infrared wavelengths, making use of that refractive index variation depends on wavelength, rather than using a reference/dynamic image pair to measure the surface gradient. Experiments on solitary and periodic waves were used to test the method, showing that new method can produce good results. Using this method it might be possible to extend the wave steepness range of Synthetic Schlieren surface measurements by overcoming the Invertibility Condition caused by light ray crossing, but due to compromises in design of real lenses, it might be difficult to achieve in practice. It might also serve as a first step towards a synthetic Schlieren method without a reference image, making it possible to use these methods in experiments where taking the reference image is difficult or impossible.
Management of external reserves and economic growth in Nigeria

Despite the management of the Nigerian external reserves to support output over these years, the economic growth rate has not been improved. The study source data from the Central Bank of Nigeria Statistical Bulletin for real gross domestic product for economic growth as the dependent variable against external reserves rate, exchange rate and total exports rate that represented the explanatory variables from 1985-2019. The study adopted the Augmented Dickey-Fuller and the Ordinary Least Squares for the analysis. The results were stationary at first order differenced levels. The Johansen cointegration test indicated two co-integrating equations in long run. Further, the short run least squares results revealed that external reserves rate, and exchange rate had a positive but not significant, while total exports rate had a positive and significant relationships with the Nigerian economic growth. Finally, more innovative means of production to boost Nigeria’s exports and aid exchange rate/reserves management were recommended.