Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the Potential for Resilience of Integrated Oil & Gas Operations in Brazil

Resilience is presented in literature as the capacity of a system to disarm, adapt and recover from unexpected events. Despite the increase of interest of industries and academia in the subject, there are a lack of models that describes the elements that condition and determines resilient performance. This article presents a knowledge model that characterizes intangibles which determine resilient responses and is a central piece in a data science strategy supporting monitoring and analysis of potential for resilience in high-risk industries. Through an interdisciplinary approach, this model was established using an integrative review of the literature and the contribution of experts from several areas. The potential for resilience is represented by a set of leading indicators that allows continuous monitoring of both static characteristics of complex operations and dynamic resource mobilization in the face of unexpected events. Knowledge engineering and data science techniques are applied to treat data from various sources. The established approach addresses several elements that are not traditionally explored in safety management systems, including those related to knowledge that determine resilient responses, as well as factors related to human, structural and relational capital that condition resilient performance. Results of the application of the model are presented, including how the analytical model supports the definition of knowledge management and safety investment strategies in oil and gas companies in Brazil. The approach supports the prioritization of actions and investments to promote safety and enable strategies to learn from accidents and positive conditions that make operations safer despite unpredictability in daily operational routine.
Multitarget Multisensor Motion Tracking of Vehicles with Vehicle Based Multilayer 2D Laser Range Finders

For tracking, autonomous vehicles often use 3D laser range finders (LRFs), which are expensive. In order to make autonomous cars affordable as a mass product, we use multiple, more affordable 2D LRFs for tracking and implement an algorithm with the goal of achieving a similar performance. Our tracking algorithm comprises the following steps: Data preprocessing, segmentation, classification, feature extraction, data association, and track management. To compensate the information reduction, we re-use track information and focus on reducing over-segmentation and effects of the shape change problem. We test the algorithm on own labeled data and training data sets of “The KITTI Vision Benchmark Suite” with the CLEARMOT and MT/PT/ML metrics. In addition, we test specific properties with specific scenarios. Our algorithm obtains a MOT accuracy, which reflects the amount of correctly detected objects, of 0.79 on our own and negative values on the KITTI data sets. Obtained MOT precision, which is an averaged detection precision, is around 60 percent on all data sets. Out of all tracks, 47.83 percent are mostly tracked on our own data and zero percent on KITTI data sets. Our algorithm for tracking multiple objects with multiple moving 2D LRFs does not reach 3D performance. Improvements of feature extraction and especially classification to distinguish between vehicle and non-vehicle objects would boost its performance.
Has Smartphone Use Influenced Loneliness during the COVID-19 Pandemic in Japan?

The influence of smartphone use on increased risk of feeling lonely has been recognized as a global public health concern. However, it is unclear whether this influence has changed during the ongoing COVID-19 pandemic, during which smartphones have become a particularly important means of communication due to health safety measures restricting personal interactions. We used Hiroshima University’s online survey data collected from 18–28 February 2022, to assess the impact of smartphone use on loneliness in Japan. The final sample included 2630 participants aged over 20 years, with loneliness measured using the UCLA scale and smartphone use calculated as the duration of usage in minutes/day. Weighted logit regression analysis was used to examine the association between smartphone use and loneliness, with other demographic, socioeconomic, and psychological characteristics as explanatory variables. Contrary to conventional evidence, our findings show that smartphone use mitigated the risk of loneliness during the pandemic. This was especially true among females under 65 years old. We found that age, subjective health status, future anxiety, and depression impacted this relationship. The findings of this study can help guide policymaking by showing the importance of providing adequate digital platforms to manage loneliness and mental health during times of isolation.
Robust autocovariance estimation based on sign and rank correlation coefficients

This paper addresses the problem of estimating autocorrelation coefficients in the presence of outliers. Tools for characterizing the robustness are developed as well. Autocorrelation coefficients are obtained recursively by computing partial correlation (PARCOR) coefficients first. In order to achieve robustness, product-moment correlation coefficients are replaced by correlations computed using rank and sign correlation coefficients. Transformations relating rank and sign correlations and conventional correlations are exploited in the process. Finally, robust estimates of autocorrelation coefficients are obtained. They are used to construct an autocovariance matrix. Examples of the performance of the method are given by using a matrix constructed from autocorrelation coefficients and MUSIC subspace frequency estimator. The influence of outliers on conventional estimators and the robustness of the proposed method are illustrated in simulations as well.
Monitoring of pavement deflections using geophones

ABSTRACT The paper presents tests performed on an instrumented motorway section, to monitor traffic and pavement deflections using geophones. Geophones are sensors used to measure displacement velocities, and by integrating their signal, it is possible to monitor vertical displacements. In this study, 4 geophones have been installed in the base layer of the pavement, and their measurements have been recorded under real traffic, during a period of approximately 18 months, using a remote control data acquisition system, transferring the data to a server. Different methods of treatment of the geophone measurements have been proposed: the first application concerns the detection of different heavy vehicle silhouettes, by analysing the number of peaks of the displacement signals; the second application concerns the measurement of vehicle speeds, by determining the time difference between the measurements of two geophones. The third application concerns the measurement of pavement deflections. To measure accurately the deflection, a procedure has been developed, to correct the geophone response, which is attenuated in the low frequency range. This procedure has been validated by measurements under controlled loading conditions, on the IFSTTAR accelerated pavement testing facility, and then applied to in situ measurements. In conclusion, the study shows that geophones, which present the advantage of being relatively inexpensive and robust sensors, offer interesting possibilities for pavement monitoring.
Matrix-free linear system solving and applications to symbolic computation

This thesis investigates the solution of large, sparse, linear systems over finite fields by matrix-free algorithms. A matrix-free algorithm treats the coefficient matrix as a black box and requires a technique to apply the matrix to a vector. The components of the matrix are never directly addressed or changed. Hence structural properties such as sparseness become unimportant. We studied the block Wiedemann algorithm due to Coppersmith and implemented it after parallelizing the output loop, in a distributed setting as an SPMD computation. We developed three complete differently-optimized solvers, for computing in GF(2), in GF(p) where p is a prime representable in less than 16 binary digits, and in GF(q) where q can be of arbitrary length. We conducted detailed investigations of their performance. Two of the largest systems solved are a system of 569,00 equations over GF(2), in 332 hours on 2 computers; and a system of 20,000 equations over GF(32749), in 28.5 hours using 8 computers. We designed the Black Box Berlekamp algorithm for the factorization of high-degree polynomials over finite fields. A key component of our algorithm is a matrix-free linear system solver based upon the Block Wiedemann algorithm. We have written a complete software package in C++ using a library of classes for fast polynomial arithmetic. In our algorithm the coefficient matrix is never instantiated and the matrix times vector product is effected by the modular exponentiation of polynomials. These features make it possible for us to factor polynomials of higher degree than hitherto possible. Our algorithm works best for high degree polynomials with coefficients from fields of small cardinality. We have factored polynomials of degree as large as 15001 in the field GF(127). Our experiments with the Block Wiedemann Algorithm supply strong evidence for its success over finite fields of small cardinality. The only existing probabilistic analysis, by Kaltofen, is valid for large fields only. Seeking the probability of success in small fields, we considered an intermediate subproblem of the Block Wiedemann algorithm involving the solution of a system of equations having Toeplitz structure. We examined, in particular, the condition that the leading principal minors of the coefficient matrix up to dimension equal to the rank of the original matrix must be nonzero. Randomly generated matrices having Toeplitz structure themselves can be used to precondition the given Toeplitz system so as to give it such a generic rank profile. We have proven that an n x n Toeplitz matrix whose first row and column are chosen uniformly at random from the elements of a field of q elements, has generic rank $r < n$ with probability $(1/q)(1 - 1/q)\sp2(1 - (q -1)/q\sp2)\sp{r-1}. $ Using concepts from the theory of subresultants and Pade approximants we also proved that there are $(q - 1)q\sp{n-2}$ non-singular order-n Toeplitz matrices over GF(q). From this it follows that a random Toeplitz matrix is non-singular with probability $1-1/q$. (Abstract shortened by UMI.)
Dental Age Estimation Standards for Hispanic Children and Adolescents in California

Background: In recent years, cross-border migrations have resulted in an increase in the number of unaccompanied children apprehended at the United States border, particularly in the state of California. The assessment of the chronological age of a child, in many instances, determines the type of services rendered within the medico-legal system. Age can be determined by using population-specific reference standards, preferably within a geographical area. However, such standards are not available for Hispanic children living in California. Aim: To present new standards by developing and validating a reference data set for dental age estimation in Hispanic children in California. Methods: For the reference dataset, a total of 705 dental panoramic radiographs of healthy children aged 7.00 to 13.99 years belonging to Hispanic ethnicity in California were obtained from the archives of a teaching hospital. All permanent teeth on the left side were scored in automated software, and the average at assessment was calculated for each stage of dental development. For the validation dataset, 133 radiographs that were not part of the reference dataset were obtained based on the above criteria. The difference between the chronological age (CA) and dental age (DA) estimated using the California Hispanic reference dataset was assessed using a paired t-test with a statistical significance of p < 0.05. Results: The overall difference between the chronological age and dental age (CA-DA) was 0.03 years (1.56 weeks) for females and −0.10 years (−5.26 weeks) for males, and the difference was not statistically significant for children aged 8.00 to 12.99 years (p > 0.05). Conclusions: The newly constructed dental reference data can be recommended for age estimation in children belonging to Hispanic ethnicity in California.
COVID-19 Vaccine Acceptance Level in Ethiopia: A Systematic Review and Meta-Analysis

Background The coronavirus disease 2019 pandemic has had a devastating impact on the everyday lives of the world's population and to this end, the development of curative vaccines was upheld as a welcome panacea. Despite the undeniable negative impact of the disease on human beings, lower than expected proportions of people have taken up the vaccines, particularly in the developing non-Western world. Ethiopia represents an interesting case example, of a nation where COVID-19 vaccine acceptance levels have not been well investigated and a need exists to assess the overall level of vaccine acceptance. Methods A systematic multidatabase search for relevant articles was carried out across Google Scholar, Web of Science, Science Direct, Hinari, EMBASE, Boolean operator, and PubMed. Two reviewers independently selected, reviewed, screened, and extracted data by using a Microsoft Excel spreadsheet. The Joanna Briggs Institute prevalence critical appraisal tools and the modified NewcastleOttawa Scale (NOS) were used to assess the quality of evidence. All studies conducted in Ethiopia, reporting vaccine acceptance rates were incorporated. The extracted data were imported into the comprehensive meta-analysis version 3.0 for further analysis. Heterogeneity was confirmed using Higgins's method, and publication bias was checked by using Beggs and Eggers tests. A random-effects meta-analysis model with a 95% confidence interval was computed to estimate the pooled prevalence. Furthermore, subgroup analysis based on the study area and sample size was done. Results and Conclusion. After reviewing 67 sources, 18 articles fulfilled the inclusion criteria and were included in the meta-analysis. The pooled prevalence of COVID-19 vaccine acceptance in Ethiopia was 57.8% (95% CI: 47.2%–67.8%). The level of COVID-19 vaccine acceptance in Ethiopia was at a lower rate than necessary to achieve herd immunity. The highest level of vaccine acceptance rate was reported via online or telephone surveys followed by the southern region of Ethiopia. The lowest vaccine acceptance patterns were reported in Addis Ababa.
FDI Spillover Channel and its Effect on Innovation

In an increasingly globalized environment, one of the important aspects for knowledge development and usage has been the advantage of benefiting from knowledge spillover across international boundaries. The knowledge literature recognizes the importance of the combining internal and external knowledge in the innovation process. Knowledge spillover from abroad is an important channel of external knowledge needed to complement the innovation activities in the domestic economies of countries. However, the complementarities of external knowledge and domestic innovation activities also remains a thorny issue that remain unresolved in the knowledge literature. On one hand, there is a believe that combinatorial efforts of domestic and foreign knowledge activities are a good recipe for innovation. There are other strands of literature that are concerned that when foreign knowledge is not complementary with domestic innovation activities increased innovation may not be realized. Contrary to the widely held view of the positive impact of FDI on host economies, the literature shows a rather complex relationship between FDI and economic outcomes in V4 countries. OECD countries, being the main trading partners of V4 countries, the study therefore investigates the FDI channel for knowledge spillover from OECD countries and how such knowledge spillover complements V4 countries innovation activities to affect innovation outcomes. Data for the study is panel data on the V4 countries, spanning 2003 to 2012 which is sourced from the OECD database. The study applies panel regression analysis and controls for country and time fixed effect to determine the role of FDI knowledge spillover from OECD countries on innovation outcome in V4 countries. The findings of the study indicate that proportionate change in innovation is greater than a proportionate change in FDI knowledge spillover in the opposite direction. The results of the analysis show that knowledge spillover from FDI does not complement V4 countries’ internal R&D activities to improve innovation. FDI knowledge spillover channel is not a good complement to domestic R&D activities to enhance V4 countries’ innovation performance. It is concluded that, FDI knowledge spillover channel does not complement innovation activities to improve innovation outcome. The study provides useful practical implications and recommendations.
Effectiveness of a Water Disinfection Method Based on Osmosis and Chlorine Dioxide for the Prevention of Microbial Contamination in Dental Practices

In dental clinics, the infections may be acquired through contaminated devices, air, and water. Aerosolized water may contain bacteria, grown into the biofilm of dental unit waterlines (DUWLs). We evaluated a disinfection method based on water osmosis and chlorination with chlorine dioxide (O-CD), applied to DUWL of five dental clinics. Municipal water was chlorinated with O-CD device before feeding all DUWLs. Samplings were performed on water/air samples in order to research total microbial counts at 22–37 °C, Pseudomonas aeruginosa, Legionella spp. , and chlorine values. Water was collected from the taps, spittoons, and air/water syringes. Air was sampled before, during, and after 15 min of aerosolizing procedure. Legionella and P. aeruginosa resulted as absent in all water samples, which presented total microbial counts almost always at 0 CFU/mL. Mean values of total chlorine ranged from 0.18–0.23 mg/L. Air samples resulted as free from Legionella spp. and Pseudomonas aeruginosa. Total microbial counts decreased from the pre-aerosolizing (mean 2.1 × 102 CFU/m3) to the post-aerosolizing samples (mean 1.5 × 10 CFU/m3), while chlorine values increased from 0 to 0.06 mg/L. O-CD resulted as effective against the biofilm formation in DUWLs. The presence of residual activity of chlorine dioxide also allowed the bacteria reduction from air, at least at one meter from the aerosolizing source.
Approaching ABET Preparations as a Design Exercise

Much of the preparation of the self-study for an ABET accreditation visit is collecting and formatting data on faculty, courses, facilities, and equipment. This part of the preparation can be tedious, but it is not open to interpretation by those preparing the document. It is ABET Criterion 4 (Continuous Improvement) that creates the most confusion and most often leads to problems. Criterion 4 requires creation and implementation of processes for assessment of the degree of student attainment of specific Student Outcomes (SOs) and the use of this (and other) information in a continuous improvement of the program. There is often confusion about what data to collect, how to analyze it, and how to present the results in the program’s self-study. The goal of this paper is to provide engineering programs with a workable design-based example of a system that has successfully met the requirements of ABET Criterion 4. The author, an experienced ABET evaluator, developed the system for the aerospace engineering program at the University of Texas at Austin and evolved it during the 2010-2016 ABET cycle. The system resulted in a successful ABET visit in fall 2016 as no program deficiencies or weaknesses were cited by the ABET visitor at the end of the visit. The author’s experiences as an ABET evaluator and as a design instructor led to the decision to use design methodology in the satisfaction of Criterion 4.
Neoliberal Temporality: Cultural Practices of Time Management in Neoliberal Post-Communist Poland

The subject of this article is cultural practices of time management in Poland in the context of transformations of social time, such as compression, and multi-temporality. The author participated in a series of time-management workshops organized in Poland to understand specific time-management techniques and tools (such as the Eisenhower Matrix, the Pareto Principle, Parkinson’s Law, and Pomodoro) and to explore how the chosen Foucauldian techniques of the self may facilitate emergence of mechanisms which support neoliberalism. Participant observation revealed that such workshops not only serve to passively present time as an independent economic value but also actively contribute to changing an individual’s way of thinking and acting. Furthermore, time-management training workshops have a class-related character. People in a less favorable situation or those who are more subjugated and constrained by other social mechanisms (such as poverty, work obligations, or family obligations) appear less affected by the neoliberal logic.
Design and improvement of a soft switching high step-up boost converter with voltage multiplier

A new soft switching high step-up boost converter is proposed in this study. Coupled inductors technique is used along with voltage multiplier in order to provide high-voltage gain and reduce voltage stress across semiconducting elements. Using an active clamp circuit, soft switching condition is provided for both the main and auxiliary switch which reduces the switching losses and improves the circuit efficiency as well as power density. The reverse recovery problem of diodes is alleviated due to the existence of the leakage inductances of the coupled inductors in series with diodes. The circuit performance is investigated and theoretical analysis is provided. A 200 W 40 V input to 400 V output laboratory prototype of the proposed converter is implemented, and the experimental results show the proper performance of the proposed converter.
An empirical computational study of genetic algorithms to solve order based problems: an emphasis on TSP and VRPTC

This study explores the potential of genetic algorithms (GA) to solve order based problems with particular emphasis on solving the traveling salesman problem (TSP) and the time constrained vehicle routing problem (VRPTC). As a result of a thorough review of current literature, several issues related to developing GA to solve ordering problems are uncovered. An in-depth, empirically valid computational study using an a-priori statistical design is conducted to determine the best combination of parameter settings and design decisions to use when building GA to solve ordering problems. This test was conducted using the GA Testing System (GATS) developed as part of this effort. A suite of real world problems selected from literature and the TSPlib 1.2 were solved with 144 different GA designed to solve the tsp (GA-TSP), also developed as part of this study. More than 5,000 problems were solved by GA-TSP during this phase of the study. The results of the GA-TSP test were used to develop a GA to solve the VRPTC (GA-VRPTC). To evaluate GA-VRPTC, a set of VRPTC were solved and the results were compared with the results obtained when solving the same set of problems using traditional algorithms. We find that GA-VRPTC performs well in terms of solution quality; however, the amount of CPU time required to solve these problems exceeded that used by traditional methods by several orders of magnitude. After reporting and analyzing the results of the GA-VRPTC test, suggestions for further improvement and extensions are made.