Statistical Reliability Research Articles

ECG Tools for Cancer Screening

Various cancers can be screened quickly by detection of visible and invisible abnormal findings appearing at ECGs. Data were statistically processed using variation and regression analyses. Evaluation of statistical reliability for the groups studied was made according to the p-value for the meaning of chi-square, and differences were considered significant at р<0.05. In the group was included 31 individuals without cancer and 67 persons with different types of cancer. p- wave may be use with an insignificantly degree of probability as a predictor of cancer for women. QRS complex may be used as an additional indicator of cancer for men. Dividing the groups by sex showed the presence of statistically significant difference between the mathematical expectations for the groups. The results showed that obtained logistic regression model possessed good abilities for cancer prediction among men, based on the ECG.

Потоки інформації в мережі з обмеженнями кількості потоків, дозволених на кожному вузлі

This paper explores a classic problem in transport network research: the analysis of networks with specified total traffic values for each node. We employ linear algebraic methods to derive a comprehensive set of solutions, ensuring statistical reliability and enabling robust analysis of the results. A mathematical model is presented for determining solution sets in fully connected, loop-free networks with three and four nodes. Based on this model, we developed software to calculate the statistical distribution of entropy values within the network. Furthermore, we investigate the statistical properties of information flow entropy for networks with and without constraints that permit uniform flow distribution. This characteristic holds practical significance for analyzing network dynamics and predicting flow redistribution processes from initial unbalanced states, which inherently proceed towards higher entropy. The findings presented in this paper hold additional practical implications for network imbalance detection and adaptability to diverse network topologies. The results can serve as a foundation for algorithms designed to quantify the degree of network imbalance induced by substantial external influences that do not significantly alter the overall network load. This capability proves particularly valuable in identifying covert DDoS (Distributed Denial of Service) attacks that aim to reduce network bandwidth by supplanting legitimate traffic. While the proposed method has been demonstrated on fully connected networks, it demonstrates potential for adaptation to networks with a wide range of topological structures. This includes networks with partial connectivity or loosely connected networks, which constitute a significant proportion of real-world networks. The significance of the method is further amplified by advancements in cloud computing technologies, which offer substantial computational power and enable the accumulation of extensive statistics regarding information flow distributions across networks of diverse purposes. Such advancements create opportunities for the integration of the developed network analysis technique with machine learning and artificial intelligence technologies, fostering enhanced automation, scalability, and adaptability.

ANALYSIS OF SOME BIOMETRIC PARAMETERS IN THE CHARACTERIZATION OF CORN EAR

The study analyzed the variation of some biometric parameters in corn ears, the 'Oana' hybrid. The experiment was carried out within ARDS Lovrin, under non-irrigated crop system conditions. The ear samples were harvested at physiological maturity. The analyzed parameters were represented by: ear length (EL), row number (RN), grains number on rows (GNR), ear weight (CW), grains weight (GW) and cob weight (CW). Ear length varied between EL = 18.00 – 20.75±0.41 cm; row number presented values between RN = 16.00 – 16.50±0.11; grains number on rows presented values between GNR = 43.75 – 49.25±0.76; ear weight presented the values EW = 0.86 – 1.04±0.03 kg; grains weight varied between GW = 0.73 – 0.87±0.03 kg; cob weight varied between CW = 0.13 - 0.17±0.01 kg. The Anova test confirmed the presence of variance and the statistical reliability of the recorded data (F calculated > F crit, p<0.001; Alpha = 0.001). High variability was recorded in the case of cob weight (CV=10.1184), and low variability in the case of row number (CV=1.5971). Intermediate values were recorded for the other analyzed parameters, respectively CV = 4.0769 for GNR, CV = 5.3064 for EL, CV = 7.6181 for GW, respectively CV = 7.9539 for EW. Correlation of varying intensity levels was recorded between analyzed parameters (e.g. r=0.991 between EW and GW; r=0.949 between EL and GNR; r=0.845 between CW and EW). The regression analysis facilitated the finding of equations and graphic models that described the variation of EW and GW in relation to EL and RN parameters, under statistical safety conditions (R2=0.982 in the case of EW; R2=0.974 in the case of GW). From the equations obtained (values of the coefficients) as well as from the graphic models, it was found that the EL parameter had a determining influence (compared to RN) in the variation of the EW and GW parameters.

Reliability statistics every orthodontist should know

It is essential to conduct a reliability examination even if the method was considered reliable in the past, as it may not be reliable in a new study conducted by different researchers using different materials. The current article highlights the importance of reliability examination in orthodontic studies and explains which assessment methods are more appropriate than others. Several fallacies in reporting and interpreting reliability are also discussed. In addition, the article presents examples of reliability examination for one-, two-, and three-dimensional data using graphic visualization in a tutorial format.

Long-Range SECCM Enables High-Throughput Electrochemical Screening of High Entropy Alloy Electrocatalysts at Up-To-Industrial Current Densities.

High-entropy alloys (HEAs), especially in the form of compositional complex solid solutions (CCSS), have gained attention in the field of electrocatalysis. However, exploring their vast composition space concerning their electrocatalytic properties imposes significant challenges. Scanning electrochemical cell microscopy (SECCM) offers high-speed electrochemical analysis on surface areas with a lateral resolution down to tens of nm. However, high-precision piezo positioners often used for the motion of the tip limit the area of SECCM scans to the motion range of the piezo positioners which is typically a few tens of microns. To bridge this experimental gap, the study proposes a long-range SECCM system with a rapid gas-exchange environmental cell for high-throughput electrochemical characterization of 100mm diameter HEA thin-film material libraries (ML) obtained by combinatorial co-sputtering. Due to the gas-liquid interface at the positioned SECCM droplet on the sample, high-throughput evaluation under industrial current density conditions becomes feasible. This allows the direct correlation between electrocatalytic activity and material composition with high statistical reliability. The multidimensional data obtained accelerates materials discovery, development, and optimization.

Meningkatkan Kualitas Official Statistics Melalui Integrasi Big Data

This paper delves into the transformative impact of incorporating big data into official statistical practices. The objective is to elevate the overall quality of data by leveraging the potential of big data analytics. The study employs a comprehensive methodology that encompasses data collection, processing, and analysis. The primary aim is to explore how the integration of big data can enhance the accuracy, timeliness, and relevance of official statistics. The research methodology involves the systematic collection of large-scale datasets, followed by advanced analytics techniques to extract meaningful insights. The findings underscore the substantial improvements achieved in the precision and reliability of official statistics through the infusion of big data methodologies. The transformative potential of integrating big data into official statistics is explored, offering valuable insights for policymakers, researchers, and practitioners in the field.

Bandwidth abstraction and service rate instantiation for latency-bounded reliability provisioning in 5th generation wireless networks

The provisioning of the statistical reliability regard to latency is crux for the bursty traffic in the 5th generation (5G) wireless network slicing. Based on martingale theory, a novel analysis framework of the latency-bounded reliability is proposed. For the queuing system with bursty traffic, a Queuing Length Martingale is constructed to reveal the impact of the entanglement between the arrival process and the service process on the latency performance, where these two stochastic processes are sharply heterogeneous. The complex martingale parameters are determined. Relying on the time shift feature of the Queuing Length Martingale, a Latency Martingale is defined, which enables to analyze the latency-bounded unreliability in the martingale domain. Leveraging the stopping time theory, a tight upper bound of the unreliability regard to latency is obtained. A bandwidth abstraction and service rate instantiation scheme is designed for wireless network slicing. Bandwidth abstraction facilitates to decouple the statistical reliability requirements as the desired bandwidth of the wireless node. In the 5G access network, a transmission power allocation problem is formulated with the constraint of abstracted bandwidth. According to the access states and channel characteristics, the demanded transmission power is captured dynamically to instantiate the service rates. Simulation results highlight the effectiveness of the bandwidth abstraction and service rate instantiation scheme.

Prevalence of Bacterial Keratitis in Contact Lens Wearing Female Medical Students in Sana'a, Yemen

Bacterial keratitis is bacterial infection of the cornea of eye and it is the fifth leading cause of blindness. Contact lens wearing is the most critical risk factor for microbial keratitis in developed countries and developing countries.In Yemen, females wear contact lens mainly for cosmetic purposes and there are no reliable statistics documenting the prevalence of Bacterial keratitis among contact lens wear especially among females. Amis: To find the prevalence of Bacterial keratitis and associated risk factors among female medical students at the National University who wear Contact Lenses in Sana'a city, Yemen. Methods: A cross-sectional structured questionnaire survey of 50 elements conducted to evaluate the behavioral and socio-demographic data.Corneal specimens were collected and cultured to isolate bacteria that cause keratitis. Results: the results revealed that, the prevalence rate of bacterial keratitis among participants was 72%. Staphylococcus aurous and coagulase negative staphylococci were the most common agents of bacterial keratitis.There were statistically significant differences between bacterial keratitis and age, extended wear contact lens wear, sharing contact lens with others, cleaning of contact lens and use eye drops. Conclusion: The major risk factors for bacterial keratitis include prolonged wear of contact lenses, sharing of lenses with others and poor hygiene practices when handling contact lenses. Female students aged 38–42 are the most at-risk group. Bacterial keratitis is preventable diseases.

Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems

Grant-free random access (RA) utilizing massive multiple-input multiple-output (MIMO) technology has attracted considerable attention in recent years due to its potential to enhance spectral efficiency. This paper introduces an innovative and advanced approach for the joint detection of users and estimation of channels in grant-free RA. The approach incorporates two distinct preamble structures: the single orthogonal preamble (SOP) and the concatenated orthogonal preamble (COP). The proposed algorithms make full use of the inherent quasiorthogonal characteristic of massive MIMO, thereby enabling the accurate estimation of user channels while effectively avoiding collisions in the preambles. As a result, these algorithms generate highly precise estimations of user channels. To substantiate the effectiveness of the proposed algorithms, this paper provides an extensive theoretical analysis and presents a comprehensive set of experimental results. These findings offer robust evidence for the efficacy of the algorithms in substantially bolstering the performance of grant-free RA. Additionally, we have conducted further research and analysis, which has led to additional insights and refinements in our proposed approach. Moreover, the experimental results validate the statistical significance and reliability of the performance enhancements achieved by these algorithms. Moreover, the proposed approach exhibits robustness in scenarios with different levels of user density and varying channel conditions. Through a thorough analysis of these scenarios, we showcase the versatility and applicability of our algorithms in real-world environments.

Long-term results of oncological endoprosthetics of the ankle joint: multicenter study

Introduction. The distal tibia and fibula are rare sites of involvement by primary and metastatic tumors. For a long time, amputation remained the standard surgical intervention for this location. Oncological ankle replacement is associated with a number of difficulties, including a lack of soft tissue necessary to cover the implant, close proximity of anatomical structures, a high probability of vascular and infectious complications, and difficulties in restoring the biomechanics of the lost joint. Currently, due to the small number of analyzed groups and short-term observations, there is no generalized data on primary and revision oncological ankle replacement, and there is no developed approach to treatment and prevention of complications.Aim. To generalize the analysis of long-term results, the structure of complications, and functional results in a group of patients after primary and revision oncological ankle replacement in a statistically significant group of patients.Materials and methods. The study included 40 patients with benign bone tumors, primary localized sarcomas of bone and soft tissue, and metastatic lesions, which, since 2008, until 2023 56 primary and revision endoprosthetics of postresection defect of the distal tibia were performed. Over a period of 15 years, the study group included 40 (71.4 %) surgeries in the scope of primary endoprosthetics and 16 (28.6 %) surgeries in the scope of revision oncological endoprosthetics of the ankle joint.Results. Over a 15-year follow-up period, the overall incidence of complications, structured according to the International Society of limb Salvage (ISOLS) 2013 classification, after primary and revision arthroplasty was 50 %. The average time until detection of oncological and non-oncological complications was 16.1 months. The leading complication after endoprosthetics was aseptic instability (Type II; 21.4 %) and tumor recurrence (Type V) – 20 %. The average functional outcome after primary and revision ankle replacement was assessed using the MSTS scale and was 72 % after 6 months and ranged from 43 to 97 %. After 12 months, this figure was 78 % and ranged from 49 to 97 %.Conclusion. An objective assessment and increase in the statistical reliability of the results of oncological ankle replacement requires a larger number of surgeries, a longer observation period and joint consolidation of data from various clinics. Development of indications for such reconstructive operations, careful selection of patients taking into account the effect of conservative treatment allows to reduce the total number of complications, the number of local relapses and achieve a good functional result.

Motivasi Masyarakat dalam Mengikuti Olahraga Senam Aerobik di Kabupaten Kudus

This research aims to find out the picture of the level of community motivation in following aerobic gymnastics in the holy regency. Considering the recent development of sports is very rapid and the many choices of sports that are in demand to fill daily leisure time. This type of research is quantitative research with descriptive shortness. The location of this study was conducted in Kudus Regency with this research sample is the community that participated in participating in aerobic gymnastics. The data collection technique in the study used questionnaires on a likert scale. Data analysis used includes validity tests, reliability and quantitative descriptive statistics. The results showed the level of community motivation in participating in aerobic gymnastics in Kudus Regency as many as 35 people (35%) belonged to a very high category, and as many as 65 people (65%) had motivation in participating in aerobic gymnastics in Kudus Regency included in the high category. So that it can be concluded that the level of community motivation in following aerobic gymnastics in Kudus Regency falls into the high category. As for the indicators that dominate the most community motivation in following aerobic gymnastics in Kudus Regency, namely physiological needs

Water resources in Saudi Arabia: trends in rainfall, water consumption, and analysis of agricultural water footprint

Saudi Arabia is one of the most arid countries in the world. Thus, freshwater availability and consumption are of crucial importance for the fast-growing population subjected to an escalating heat stress from climate change. We provide an overarching view of water resources in Saudi Arabia, in terms of supply, demand, vulnerabilities, and the associated implications on food supply and security. To estimate the effects of climate change on natural water supply, we use ERA5 for the reliable and complete statistics of the long term-precipitation (1950-2021) trends across the Kingdom’s territory. ERA5 is the latest generation of the reanalysis of global climate from the European Centre for Medium-Range Weather Forecasts. The average annual precipitation is about 50 mm/year and does not satisfy the freshwater needs of the country. Energy-intensive desalination, driven by fossil fuels, meets two thirds of municipal freshwater requirements, while non-renewable “fossil” groundwater addresses most of agricultural consumption needs. Total freshwater use has decreased in recent years due to a significant reduction of water use by agricultural sector. Nevertheless, this sector still accounts for 67% of the total freshwater consumption and provides a third of the country’s food supply. To understand efficiency of freshwater use in the agricultural sector, we have developed a novel methodology that allowed us to estimate the country-scale water consumption associated with crop production. Results indicate that water requirements for crop cultivation in Saudi Arabia are up to three times the global average. Date and cereal production consumes almost two thirds of the total freshwater supply, while mass production is dominated by forage crops.

Microflora of atherosclerotic plaques and blood of patients with atherosclerosis

Background. Over the past decades, the role of the microbial factor in the development of atherosclerosis has been discussed. To date, data on the composition of the microflora of atherosclerotic plaques have been accumulated, but in these studies the blood microflora in atherosclerosis was not studied.
 Aim. To determine the contamination frequency of biopsy samples of atherosclerotic plaques and peripheral blood with cultured microorganisms in patients with atherosclerosis of the brachiocephalic arteries.
 Material and methods. A cross-sectional study in 35 patients with atherosclerosis of the carotid arteries; the average age of the patients was 58.2±8.3 years, was performed. Blood and atherosclerotic plaque samples from 23 men (mean age 58.6±10.3 years) and 12 women (mean age 57.3±14.3 years) were examined. Anaerobic flasks for blood cultivation were incubated at 35 °C for up to 6 months, from which they were regularly inoculated onto solid nutrient media to obtain culture growth. Cultures of tissues of atherosclerotic plaques of the carotid arteries in test tubes with thioglycollate medium were thermostated until visible growth of the culture was obtained; observation was carried out for up to 2 months. Identification of crops was carried out using commercial kits. For statistical analysis of the results obtained, the equality of the average values in two samples was checked using the Student’s statistical reliability test. Correlation analysis of the tightness of the connection was carried out using the Spearman rank correlation method.
 Results. The frequency of detection of microorganisms in samples of atherosclerotic plaques was 48.6% (17/35), including Cutibacterium acnes — in 31.4% (11/35), the genus Staphylococcus — in 22.9% (8/35), associations of these microorganisms — in 5.7% (2/35) of samples. C. acnes was cultured in the blood of 11.4% (4/35) of patients. In 5.7% (2/35) of patients, cultures of C. acnes bacteria were isolated from both atherosclerotic plaque biopsies and blood. Bacterial cultures exhibited slow growth on nutrient media. Correlation analysis of the closeness of the connection according to the Chaddock scale demonstrated the presence of a high and very high closeness of connection between the amount of high-density lipoproteins and the daily growth of C. acnes in atherosclerotic plaques (p=0.812) and blood (rxy=–0.969), the content of leukocytes showed a very high closeness of connection with days of growth of C. acnes in the blood (rxy=–0.957); Student's t-test revealed a statistically significant relationship with the fact of detection of C. acnes cultures in atherosclerotic plaques (p=0.013).
 Conclusion. Bacterial cultures isolated from blood samples and atherosclerotic plaques of patients with atherosclerosis had slow growth on nutrient media, and the period of their growth or the fact of detection correlated with the number of leukocytes and the level of high-density lipoproteins in the blood of patients.

Statistical Characteristics of Stress Changes in Tunnel Surrounding Rock Based on Random Discrete Variability of Geotechnical Materials

In the construction of underground engineering, the determination of surrounding rock stresses has important theoretical significance for the design of tunnel structure reliability. In this paper, the nonlinear criterion is introduced to modify and improve the friction resistance in the calculation formula of Bierbaumer’s loose surrounding rock stresses, and the improved application is carried out in view of the situation of composite formation. Due to the variability and discreteness of geotechnical parameters, combined with engineering examples, Monte Carlo random sampling is carried out for various geotechnical parameters in engineering, and the characteristics of loose surrounding rock stresses are analyzed from the perspective of statistical reliability by using the improved shallow tunnel formula. By using the standard regression coefficient, the weight influence of the parameters in various shallow surrounding rock stress formulas is analyzed, and the confidence degree of the calculated results of various formulas is analyzed from a statistical point of view, which verifies the rationality of the improved formula in the statistical sense.

Assessment of Level of Awareness, Current State of Knowledge, and Skills on Endocrown Technique Among Senior Saudi Dental Students and Interns.

Background Awareness and knowledge about the endocrown technique contribute to the delivery of quality dental care and restorative long-term success. Dentists must be aware and knowledgeable about endocrowns as they offer a conservative approach, aid in maintaining tooth integrity, and have become a promising option in use recently. Aim This study evaluated the current state of knowledge, and the understanding of the endocrown technique as post-endodontic management among senior undergraduate dental students and interns who have studied the theoretical and laboratory procedures of endocrown as part of the curriculum. Materials and methods This cross-sectional investigation was conducted through an online questionnaire consisting of 21 questions in three parts. The first part consisted of demographic information; the second encompassed knowledge and attitude; and the third part evaluated skills regarding endocrown technique. A total of 164 voluntary dental students and dental intern questionnaires were evaluated.Factor analysis was used to identify the domains for knowledge and skill. Results In this study, the knowledge and skills of undergraduate dental students toward endocrowns were assessed. The reliability statistics showed favorable internal consistency (Cronbach's alpha values: 0.513 for knowledge and 0.729 for skill component 1). Significant correlations were noticed between knowledge component 1 and skill component 1 (r = 0.647, p < 0.001), knowledge component 1 and skill component 2 (r = 0.333, p < 0.001), and knowledge component 1 and skill component 3 (r = 0.260, p = 0.001). These findings emphasize the importance of evaluating students' understanding of endocrown. Significant differences were found among intern participants, fifth- and sixth-year dental students in component 1 of the knowledge (p-value<0.001), andall skills components. Conclusion Dental students have varying levels of knowledge and skills related to endocrown. Gaps in knowledge and skills have been detected, which dictates intervention actions, including curricular changes and training workshops.

Crime and Safety Concerns to Safe and Vibrant Parks and Open

This paper delves into the crucial relationship between safety, public parks, and crime prevention, exploring the various factors that contribute to a safe and vibrant park environment. It examines the impact of urban and built environments, crime statistics, safety audits, design, conditions, and other elements on overall park safety, with a focus on Koramangala's social morphology. The paper emphasizes the significance of safety in public parks, highlights the purpose and importance of safety audits, discusses the intricate connection between crime and safety, and underscores the role of user perceptions in shaping park safety. Additionally, it explores how park redesign can enhance safety, the reliability of crime statistics, the value of user experiences, strategies for public education, and the importance of maintenance in ensuring the safety and vibrancy of public parks. Key Words: crime, park, safety, green, public, socialize, neighbourhood

GENERAL PRINCIPLES OF FORECASTING THE RELIABILITY OF COMPLEX TECHNICAL SYSTEMS IN THE OIL AND GAS INDUSTRY

In the oil and gas industry, various high-risk facilities operate, among which pipeline systems occupy a leading position due to their specific characteristics (structural, technological, operational conditions, etc.).&#x0D; Pipeline systems, distributed over a large area, are characterized by a high level of risk of emergencies. Therefore, the risk analysis of accidents and failures, the main essence of which is to identify hazards and assess the possibility of their occurrence, is a crucial part of the industrial safety management system of technical systems (TS) [1]. One of the main tasks of this system is to prevent the possibility of accidents and failures, i.e., to ensure reliability. The authors emphasize the importance of assessing the reliability of high-risk objects, both when put into operation and during their operation. It is noted that reliability management during the operation stage can be carried out by determining the optimal allowable deviations of structural parameters of the technical condition and other measures. The paper provides an overview of key quantitative reliability indicators, such as the reliability function and the "unreliability function," and discusses their significance in determining failure probabilities and life-to-failure. Changes in failure intensity according to the Weibull distribution and the exponential distribution law are examined in detail. Reliability indicators for non-repairable systems include the probability of non-failure operation, failure intensity, and mean time to failure, while maintainability indicators for repairable systems are the probability of recovery and mean recovery time. The comprehensive indicator of the reliability of repairable systems is determined through the coefficient of operational readiness. The conclusions of the paper highlight the importance of using statistical data and reliability indicators to assess systems and components, in particular the oil and gas pipeline systems in Europe, which have significant importance for industrial safety and the reliability of technical facilities.

Firth's penalized logistic regression: A superior approach for analysis of data from India's National Mental Health Survey, 2016.

The National Mental Health Survey of India (NMHS) was a ground-breaking nationwide study that harnessed a uniform, standardized methodology blending quantitative and qualitative approaches. Covering data from 12 states across diverse regions, its mission was to gauge the prevalence of psychiatric disorders, bridge treatment gaps, explore service utilization, and gauge the socioeconomic repercussions of these conditions. This initiative provided pivotal insights into the intricate landscape of mental health in India. One of the analyses planned for NMHS data was to undertake a logistic regression analysis with an aim to unravel how various sociodemographic factors influence the presence or absence of specific psychiatric disorders. Within this pursuit, two substantial challenges loomed. The first pertained to data separation, a complication that could perturb parameter estimation. The second challenge stemmed from the existence of disorders with lower prevalence rates, which resulted in datasets of limited density, potentially undermining the statistical reliability of our analysis. In response to these data-driven hurdles, NMHS recognized the critical necessity for an alternative to conventional logistic regression, one that could adeptly navigate these complexities, ensuring robust and dependable insights from the collected data. Traditional logistic regression, a widely prevalent method for modeling binary outcomes, has its limitations, especially when faced with limited datasets and rare outcomes. Here, the problem of "complete separation" can lead to convergence failure in traditional logistic regression estimations, a conundrum frequently encountered when handling binary variables. Firth's penalized logistic regression emerges as a potent solution to these challenges, effectively mitigating analytical biases rooted in small sample sizes, rare events, and complete separation. This article endeavors to illuminate the superior efficacy of Firth's method in managing small datasets within scientific research and advocates for its more widespread application. We provide a succinct introduction to Firth's method, emphasizing its distinct advantages over alternative analytical approaches and underscoring its application to data from the NMHS 2015-2016, particularly for disorders with lower prevalence.

Statistical inference of travelers’ route choice preferences with system-level data

Traditional network models encapsulate travel behavior among all origin–destination pairs based on a simplified and generic travelers’ utility function. Typically, the utility function consists of travel time solely, and its coefficients are equated to estimates obtained from discrete choice models and stated preference data. While this modeling strategy is reasonable, the inherent sampling bias in individual-level experimental data may be further amplified over network flow aggregation, leading to inaccurate flow estimates. In addition, individual-level data must be collected from surveys or travel diaries, which may be labor-intensive, costly, and limited to a small time horizon. To address these limitations, this study extends classical bi-level formulations to estimate travelers’ utility functions with multiple attributes using system-level data. This data tends to be less subject to sampling bias than individual-level data, it is cheaper to collect and it has become increasingly diverse and available. To leverage system-level data, we formulate a methodology grounded on non-linear least squares to statistically infer travelers’ utility function in the network context using traffic counts, traffic speeds, the number of traffic incidents, and sociodemographic information obtained from the US Census, among other attributes. The analysis of the mathematical properties of the optimization problem and its pseudo-convexity motivates the use of normalized gradient descent, an algorithm developed in the machine learning community that is suitable for pseudo-convex programs. More importantly, we develop a hypothesis test framework to examine the statistical properties of coefficients attached to utility terms and to perform attribute selection. Experiments on synthetic data show that the travelers’ utility function coefficients can be consistently recovered and that hypothesis tests are reliable statistics to identify which attributes are determinants of travelers’ route choices. Besides, a series of Monte-Carlo experiments showed that statistical inference is robust to various levels of sensor coverage and to noises in the Origin-Destination matrix and the traffic count measurements. The methodology is also deployed at a large scale using real-world multi-source data in Fresno, CA, collected before and during the COVID-19 outbreak.

Development trends of cross-border e-commerce In Kazakhstan

Today the global world is characterized by active development and widespread penetration of information and communication technologies in various spheres of life. This trend has also influenced the ways and formats of doing business: today e-commerce is already actively developing, which has provided new development prospects for business in the form of savings on transaction costs, the possibility of access to global markets without the need to be present on the spot, etc. The purpose of this article is to expand the coverage of balance of payments statistics on certain types of foreign economic transactions of individuals, to improve the quality and reliability of external sector statistics. The article presents trends in the development of cross-border electronic commerce and approaches to estimating its volumes in the balance of payments indicators.