Bilingual Publishing Co. (BPC): E-Journals
Not a member yet
2424 research outputs found
Sort by
Supply and Demand, Tax, Income, Profit and Proof of Goldbach’s Conjecture——Logic is the Basis of Correct Mathematical Measurement
No full textThis paper demonstrates that Marshall’s logic on the supply and demand curve is not rigorous enough, that Coase’s theorem is flawed, and that the “Okishio Theorem” and Sweezy s logic are inadequate through empirical proof. By the way, the Goldbach conjecture is proved through clever mathematical proof. It shows that beautiful curves and mathematical formulas cannot be separated from reality and logic, and correct logic can play a correct role in market theory. In this paper, the analysis of the actual supply and demand curve, as well as the concepts and models of tax, profit rate and income, has positive practical significance for economic depression and stagflation
Offline Trajectory Generation for Bipedal Robot Using Linear Inverted Pendulum Model
No full textReduced order model (ROM)-based controllers have proved to be effective to generate stable bipedal locomotion. However, it is important to understand the limitations and effectiveness of these models without implementing any controllers. This study highlights the versatility of the Linear Inverted Pendulum Model (LIPM) at various walking speeds. Firstly, the Centre of Mass (COM) trajectory has been generated using the LIPM model, and the foot motion trajectory has been created using a sixth-order polynomial function. The trajectory is generated using a predefined step length, speed of locomotion and COM height. Secondly, the task space trajectory has been converted into a joint space trajectory through inverse kinematics for a 6-degree-of-freedom leg. To facilitate the proper walking motion the contact between the foot sole and the ground is implemented. Finally, a simple bipedal robot in MATLAB/Simulink has been modelled and the generated trajectories were implemented
Strategic Planning for Equitable RWIS Implementation: A Comprehensive Study Incorporating a Multi-variable Semivariogram Model
No full textThis paper extends the previously developed method of optimizing Road Weather Information Systems (RWIS) station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers multiple vital road weather variables. Previous research primarily centered on single-variable analysis focusing on road surface temperature (RST). The study bridges this oversight by introducing a framework that integrates multiple critical weather variables into the RWIS location allocation framework. This novel approach ensures balanced and equitable RWIS distribution across zones and aligns the network with areas both prone to traffic accidents and areas of high uncertainty. To demonstrate the effectiveness of this refinement, the authors applied the framework to Maine’s existing RWIS network, conducted a gap analysis through varying planning scenarios and generated optimal solutions using a heuristic optimization algorithm. The analysis identified areas that would benefit most from additional RWIS stations and guided optimal resource utilization across different road types and priority locations. A sensitivity analysis was also performed to evaluate the effect of different weightings for weather and traffic factors on the selection of optimal locations. The location solutions generated have been adopted by MaineDOT for future implementations, attesting to the model’s practicality and signifying an important advancement for more effective management of road weather conditions
Innovation Empowerment in Construction 4.0 by the Corporate Digital Responsibility (CDR)—Approach. A New Field of Scientific Research for the Digital Breakthrough
No full textThe architecture, engineering and construction industry (AEC) undergoes digital transformation, one of the major drivers for technical innovation and dynamism to all working processes. Emerging technologies were only used to a limited extent due to the lack of will to innovate and the unavailability of appropriate orientation guiding users with a more comprehensible framework. The research defined a new gap in scientific research with the concept of Corporate Digital Responsibility (CDR) in Construction 4.0—a term representing the digitization of the branch. The traditionally conservative, highly fragmented industry is predestined for this given the advanced technology, human potential and appreciation of values. Understanding the complex possibilities of innovation and recognizing the potential impact on the sustainability of buildings and the built environment promotes the adoption of corporate responsibility. The implementation of digital strategies, secured by an adapted legal framework, would accelerate the overall human, societal and digital transformation. This primary research investigates the challenges affecting the adoption of Artificial Intelligence (AI). The study highlights in which fields CDR can significantly catalyze innovation to achieve efficient, economic construction life cycles. The study used a mix of methods with a structured literature analysis and expert interview surveys enabling a critical-reflexive analysis of key factors. It evaluates the key tasks to master technological feasibility. By assessing multiple expert perspectives, the study takes stock of the acceptance of new technologies. The findings are expected to inspire corporates, researchers and practitioners across disciplines. Necessary corporate steps are outlined in the study to lay the path for defining their own digital strategy. The study shows that new research questions require a holistic approach
Exploring “Enabling Behaviours” of Wives of Persons with Substance Use Disorder in Chapter 8 of the Big Book of Alcoholic Anonymous
No full textSubstance use disorder has a damaging effect on the family members of alcoholics and drug users. On the other hand, the reactions and behaviours of family members may negatively influence a person with substance use disorder. The behaviours of significant others of a person with substance use disorder that contribute to the maintenance of substance use disorder are called enabling. This study aimed to explore enabling behaviours of wives of persons with substance use disorder in Chapter 8 of Alcoholic Anonymous’ Big Book by utilising qualitative content analysis. Alcoholics Anonymous (AA) is one of the most commonly used programs for recovery from alcoholism. The current study sought to help mental health professionals get a better understanding of the views and premises of the AA program in reference to enabling behaviours of wives by conducting a qualitative content analysis of the AA Big Book. The study also discusses the healthy behaviours suggested by the authors of the Big Book and the comprehensiveness of the text for the readers
Cognitive Advancements across the Globe: Intelligence Research and Piagetian Psychology in Comparison
No full textSpatiotemporal Analysis of Land Use Land Cover Mapping and Change Detection in Dambatta Local Government Area
No full textThis research studied the spatiotemporal changes in land use (LU)/land cover (LC) in Dambatta local government area, with a view to identifying the effect arising from the observable changes in land use patterns. The imageries used in the study were obtained from the National Space Research and Development Agency (NARSDA), Abuja. Spatial analytical techniques and descriptive statistical techniques were employed to analyze the data. The results showed 66.8% reduction in agricultural lands, 45.5% reduction in vegetation cover, 223.2% increase in built-up areas, 269.1% increase in bare lands and 70% increase in water bodies within the 20 years. Spatio-temporal analysis of the three imageries revealed that agricultural lands were largely been taken over by urbanization while vegetation had rapidly given way to bare lands within the 20 years. It was observed that these changes resulted from anthropogenic activities, environmental factors and climate change. These result in the loss of farmlands, inadequate food supply, unemployment, inadequate industrial raw materials, reduction in revenue generated, forest depletion, desertification, wildlife extinction and temperature increase. While it is recommended that reforestation, land reclamation and irrigation agriculture should be promoted in the area, it is also suggested that further research should focus on the impact of climate change on land cover change in the area
Impacts on Bats by a Supertyphoon vs. Ordinary Typhoons along a Habitat Urbanization Gradient
No full textTwo major human-caused threats to ecosystems are habitat modification and the increasing frequency and intensity of extreme weather events. To study the combined effect of these threats, the authors used acoustic monitoring of bats along a habitat modification gradient on the island of Okinawa, Japan. During the observation period, the island experienced numerous typhoons and one supertyphoon. Native bat species remained active even at high wind speeds (up to 30 m/s in some cases). Milder typhoons had no observable effect on bat populations, with activity levels fully recovering within a few hours or days. The super typhoon also did not seem to affect bats in fully or partially forested habitats but caused their local disappearance at the urban site, which they have not re-colonized three years after the event. Notably, bats that disappeared at the urban site were species roosting in well-protected places such as caves and concrete structures. In all cases, the biomass of small flying insects and the acoustic activity of insects recovered within days after extreme weather events. Thus, the striking difference between habitats in supertyphoon effects on bats cannot be explained by the super typhoon directly killing bats, destroying their roosting sites, or decreasing the abundance of their prey. The results underscore the importance of preserving natural habitats in areas particularly affected by changing climate and show that the survival of species and ecosystems during the numerous episodes of climate change in the Earth’s history does not necessarily mean their ability to survive the accelerating climate change of our time
Carbon fiber from Biomass sources: A Comprehensive Review
No full textGlobal energy demand is rising, fossil fuel prices are rising, fossil fuel reserves are running out, and fossil fuel use contributes to the greenhouse effect. As a clean alternative source of energy to fossil fuels, biomass is becoming more and more essential. Carbon fiber (CF), often known as graphite fiber, is a thin, strong, and adaptable material utilized in both structural (capacity) and non-structural applications (e.g., thermal insulation).Precursors are the raw materials used to create carbon fiber, which is mostly derived from fossil fuels. Because of the high cost of precursors and manufacture, carbon fiber has only found employment in a few numbers of high-performance structural materials (e.g., aerospace). To reduce the price of CF and reliance on fossil fuels, numerous alternative precursors have been studied throughout the years, including biomass-derived precursors including rayon, lignin, glycerol, and lignocellulosic polysaccharides. This study's goal is to present a detailed study of biomass-derived CF precursors and their market potential. We look into the viability of producing CF from these precursors, as well as the state of technology, potential applications, and cost of production (when data are available). We go over their benefits and drawbacks. We also talk about the physical characteristics of CF made from biomass and contrast them with CF made from polyacrylonitrile (PAN). Additionally, we go into bio-based CF manufacturing and end-product concerns, logistics for biomass feedstock and plant sites, feedstock competition, and risk-reduction techniques. This paper offers a comprehensive overview of the CF potential from all biomass sources and can be used as a resource by both novice and seasoned professionals who are interested in producing CF from non-traditional sources
Users’ Evaluation of Traffic Congestion in LTE Networks using Machine Learning Techniques
No full textOver time, higher demand for data speed and quality of service by an increasing number of mobile network subscribers has been the major challenge in the telecommunication industry. This challenge is the result of an increasing population of human race and the continuous advancement in mobile communication industry, which has led to network traffic congestion. In an effort to solve this problem, the telecommunication companies released the Fourth Generation Long Term Evolution (4G LTE) network and afterwards the Fifth Generation Long Term Evolution (5G LTE) network that laid claims to have addressed the problem. However, machine learning techniques, which are very effective in prediction, have proven to be capable of great importance in the extraction and processing of information from the subscriber’s perceptions about the network. The objective of this work is to use machine learning models to predict the existence of traffic congestion in LTE networks as users perceived it. The dataset used for this study was gathered from some students over a period of two months using Google form and thereafter, analysed using the Anaconda machine learning platform. This work compares the results obtained from the four machine learning techniques employed that are k-Nearest Neighbour, Support Vector Machine, Decision Tree and Logistic Regression. The performance evaluation of the ML techniques was done using standard metrics to ascertain the real existence of congestion. The result shows that k-Nearest Neighbour outperforms all other techniques in predicting the existence of traffic congestion. This study therefore has shown that the majority of LTE network users experience traffic congestion