Abstract: Truck platooning refers to a convoy of digitally connected automated trucks traveling safely with a small inter-vehicle gap. It has been identified as one of the most promising and applicable technologies towards automated and sustainable freight transportation. Although truck platooning delivers significant energy-saving benefits, it cannot be realized without good coordination of drivers’ shifts to lead the platoons subject to their mandatory breaks. Therefore, this study aims to route a fleet of trucks to their destinations using the least amount of fuel by maximizing platoon opportunities under the regulations of drivers’ mandatory breaks. We formulate this platoon coordination problem as a mixed-integer linear programming problem and solve it by CPLEX. Numerical experiments are conducted to demonstrate the effectiveness and efficiency of our proposed model. In addition, we also explore the impacts of drivers’ compulsory breaks on the fuel-savings performance. The results show a slight increase in the total fuel costs in the presence of drivers’ compulsory breaks, thanks to driving-while-resting benefit provided for the trailing trucks. This study may serve as a guide for the operators of automated freight transportation.
Abstract: This systematic literature review sought to explore the dimensions of diversity that can affect classroom learning. This review is significant as it can aid educators in reaching more of their diverse student population and creating supportive classrooms for teachers and students. For this study, peer-reviewed articles were found and compiled using Google Scholar. Key terms used in the search include student individuality, classroom equality, student development, teacher development, and teacher individuality. Relevant educational standards such as Common Core and Partnership for the 21st Century were also included as part of this review. Student and teacher individuality and equality is discussed as well as methods to grow both within educational settings. Embracing student and teacher individuality was found to be key as it may affect how each person interacts with given information. One method to grow individuality and equality in educational settings included drafting and employing revised teaching standards which include various Common Core and US State standards. Another was to use educational theories such as constructivism, cognitive learning, and Experiential Learning Theory. However, barriers to growing individuality, such as not acknowledging differences in a population’s dimensions of diversity, still exist. Studies found preserving the dimensions of diversity owned by both teachers and students yielded more positive and beneficial classroom experiences.
Abstract: With the industrial revolution, global leaders must more rapidly become knowledgeable of and develop essential cross-cultural competencies to be effective. Ethnocentrism represents a hidden barrier of effective leadership and must be acknowledged and addressed proactively by global leaders. The article examines the impact of ethnocentrism in four critical areas (leadership strategy, cross-cultural competencies, intercultural communication, and adaptation to international contexts) and argues that by developing cross-cultural competencies, leaders might naturally reduce ethnocentrism levels. This paper will also offer few examples to support international managers in understanding how ethnocentrism can affect performance.
Abstract: The growing popularity of systems based on Unmanned Aerial Vehicles (UAVs) is highlighting their vulnerability particularly in relation to the positioning system used. Typically, UAV architectures use the civilian GPS which is exposed to a number of different attacks, such as jamming or spoofing. This is why it is important to develop alternative methodologies to accurately estimate the actual UAV position without relying on GPS measurements only. In this paper we propose a position estimate method for UAVs based on monocular visual odometry. We have developed a flight control system capable of keeping track of the entire trajectory travelled, with a reduced dependency on the availability of GPS signal. Moreover, the simplicity of the developed solution makes it applicable to a wide range of commercial drones. The final goal is to allow for safer flights in all conditions, even under cyber-attacks trying to deceive the drone.
Abstract: To obtain high mechanical performance, the fresh conditions of a mortar are decisive. Measuring the absorption of aggregates used in mortar mixes is a fundamental requirement for proper design of the mixes prior to their placement in construction sites. In this sense, absorption is a determining factor in the design of a mix because it conditions the amount of water, which in turn affects the water/cement ratio and the final porosity of the mortar. Thus, this work focuses on the mechanical behavior of recycled mortars manufactured from moisture correction using the Thermogravimetric Balancing Halogen Light (TBHL) technique in comparison with the traditional ASTM C 128 International Standard method. The advantages of using the TBHL technique are favorable in terms of reduced consumption of resources such as materials, energy and time. The results show that in contrast to the ASTM C 128 method, the TBHL alternative technique allows obtaining a higher precision in the absorption values of recycled aggregates, which is reflected not only in a more efficient process in terms of sustainability in the characterization of construction materials, but also in an effect on the mechanical performance of recycled mortars.
Abstract: The global warming crisis forced humans to consider their place in the world and the earth's future. In this regard, Electric Vehicles (EVs) are a significant step towards protecting the environment. By identifying factors that influence people's behavior intentions toward using EVs, we proposed a theoretical model by extending the Technology Acceptance Model (TAM), including three more concepts, Subjective Norm (SN), Self-Efficacy (SE), and Perceived Behavior Control (PBC). The study was conducted in South Korea, and a random sample was taken at a specific time. In order to collect data, a questionnaire was created in a Google Form and sent via Kakao Talk, a popular social media application used in Korea. There were about 220 participants in this survey. However, 201 surveys were completely done. The findings revealed that all factors in the TAM model and the other added concepts such as SNs, SE and PBC significantly affect the behavioral intention of using EVs.
Abstract: Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed length window in the past as an explicit input. In this paper, we study how the performance of predictive models change as a function of different look-back window sizes and different amounts of time to predict into the future. We also consider the performance of the recent attention-based transformer models, which had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), Gated Recurrent Units (GRU), and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the website of University of California, Irvine (UCI), which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Absolute Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.
Abstract: The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling the human behaviour. However, the exclusive use of this technology still seems insufficient to control the vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.
Abstract: The use of technological innovations has been touted to be beneficial in the delivery of construction projects. Particularly, Radio Frequency Identification (RFID) technology is widely regarded to be of immense advantage for the management of construction projects. This study focused on evaluating the barriers to the use of RFID technology for the delivery of construction projects. Using Gauteng Province in South Africa as the study area, questionnaire was used in eliciting responses from construction professionals which made up the population of the study. Retrieved data were analyzed using Mean Item Score and One-Sample t-test. Findings from the study showed that the most significant barriers to the deployment of RFID for construction project delivery are high cost and lack of awareness. Conclusively, the study made recommendations that would aid in the abatement of the barriers to the use of RFID technology for construction project delivery.
Abstract: Digital magnitude comparators based on Gate Diffusion Input (GDI) implementation technique are high speed and area-efficient, and they consume less power as compared to other implementation techniques. However, they are less efficient for some logic gates and have no full voltage swing. In this paper, we made a performance comparison between the GDI implementation technique and other implementation methods, such as Static CMOS, Pass Transistor Logic (PTL), and Transmission Gate (TG) in 90 nm, 120 nm, and 180 nm CMOS technologies using BSIM4 MOS model. We proposed a methodology (hybrid implementation) of implementing digital magnitude comparators which significantly improved the power, speed, area, and voltage swing requirements. Simulation results revealed that the hybrid implementation of digital magnitude comparators show a 10.84% (power dissipation), 41.6% (propagation delay), 47.95% (power-delay product (PDP)) improvement compared to the usual GDI implementation method. We used Microwind & Dsch Version 3.5 as well as the Tanner EDA 16.0 tools for simulation purposes.
Abstract: The present study is an attempt to demonstrate the significant levels of contribution of the moment-resisting beam-column connections with side plates to the earthquake behavior of special steel moment frames. To this end, the moment-curvature relationships of a regular beam-column connection and its SidePlate counterpart were determined with the help of finite element analyses. The connection stiffness and deformability values from these finite element analyses were used in the linear time-history analyses of an example structural steel frame under three different seismic excitations. The top-story lateral drift, base shear, and overturning moment values in two orthogonal directions were obtained from these time-history analyses and compared to each other. The results revealed the improvements in the system response with the use of SidePlate connections. The paper ends with crucial recommendations for the plan and design of further studies on this very topic.
Abstract: The concept and practice of whooeaism exist among the Jarawas of Andaman Islands of India. The Jarawas are one of the simplest populations of the world and truly represent the hunting and food gathering stage. The study is conducted among the Jarawas of Kadamtala region, which is situated approximately in the western part of the south and middle Andaman Islands, India. The Jarawa tribe belongs to Negrito race and is one of the particularly vulnerable tribal groups of the Andaman Islands. The present study is based on 45 Jarawas of Kadamtala region. The observations have been conducted through the semi-participant observation method and informal interview method. It has been observed that there are neither any beliefs and practices related to supernatural power nor any concept related to the soul, manaism, demonology, totemism, animatism etc. They only have faith on Whooea, i.e., a small bone of their deceased ancestors and they wear it by the help of a bark band around the neck and shoulder or around the waist, especially during hunting or fishing and food gathering time. The Jarawas either keep the whooea in higher places or hang it and they make sure that it must not touch the earth. The beliefs and practices related to whooea may be designated as Whooeaism. It may be concluded that in of spite of various existing theories related to the origin of religion viz. Animism, Animatism, Manaism and totemism and others, the origin of religion initially developed from the Whooeaism and then other concepts of religion evolved gradually by the manifestation of human beliefs and assumptions.
Abstract: This study examines the ways in which cancer patient narratives are portrayed and framed on the websites of three leading U.S. cancer care centers – The University of Texas MD Anderson Cancer Center in Houston, Memorial Sloan Kettering Cancer Center in New York, and Seattle Cancer Care Alliance. Thirty patient stories, 10 from each cancer center website blog, were analyzed using qualitative and quantitative textual analysis of unstructured data, documenting common themes and other elements of story structure and content. Patient narratives were coded using grounded theory as the basis for conducting emergent qualitative research. As part of a systematic, inductive approach to collecting and analyzing data, recurrent and unique themes were examined and compared in terms of positive and negative framing, patient agency, and institutional praise. All three of these cancer care centers are teaching hospitals, with university affiliations, that emphasize an evidence-based scientific approach to treatment that utilizes the latest research and cutting-edge techniques and technology. The featured cancer stories suggest positive outcomes based on anecdotal narratives as opposed to the science-based treatment models employed by the cancer centers. An analysis of 30 sample stories found skewed representation of the “cancer experience” that emphasizes positive outcomes while minimizing or excluding more negative realities of cancer diagnosis and treatment. The stories also deemphasize patient agency, instead focusing on deference and gratitude toward the cancer care centers, which are cast in the role of savior.
Abstract: The vocational education, enhanced by technology and Recognition of Prior Learning (RPL) is going to be the main ingredient of the future of education. This is coming from the various issues of the current educational system like cost, time, type of course, type of curriculum, unemployment, to name the major reasons. Most millennials like to perform and learn rather than learning how to perform. This is the essence of vocational education be it any field from cooking, painting, plumbing to modern technologies using computers. Even a more theoretical course like entrepreneurship can be taught as to be an entrepreneur and learn about its nuances. The best way to learn accountancy is actually keeping accounts for a small business or grocer and learn the ropes of accountancy and finance. The purpose of this study is to investigate the relationship between vocational skills, RPL and new technologies with future employability. This study implies that individual's knowledge and skills are essential aspects to be emphasized in future education and to give credit for prior experience for future employability. Virtual reality can be used to stimulate workplace situations for vocational learning for fields like hospitality, medical emergencies, healthcare, draughtsman ship, building inspection, quantity surveying, estimation, to name a few. All disruptions in future education, especially vocational education, are going to be technology driven with the advent of AI, ML, IoT, VR, VI etc. Vocational education not only helps institutes cut costs drastically, but allows all students to have hands-on experiences, rather than to be observers. The earlier experiential learning theory and the recent theory of knowledge and skills-based learning modified and applied to the vocational education and development of skills is the proposed contribution of this paper. Apart from secondary research study on major scholarly articles, books, primary research using interviews, questionnaire surveys have been used to validate and test the reliability of the suggested model using Partial Least Square- Structural Equation Method (PLS-SEM), the factors being assimilated using an existing literature review. Major findings have been that there exists high relationship between the vocational skills, RPL, new technology to the future employability through mediation of future employability skills.
Abstract: In the context of financial globalization, China has put forward the policy goal of high-quality development, and the digital economy, with its advantage of information resources, is driving China's export trade to achieve high-quality development. Due to the long-standing financing constraints of small and medium-sized export enterprises, how to expand the export scale of small and medium-sized enterprises has become a major threshold for the development of China's export trade. This paper firstly adopts the hierarchical analysis method to establish the evaluation system of high-quality development of China's export trade; secondly, the panel data of 30 provinces in China from 2011 to 2018 are selected for empirical analysis to establish the impact model of digital inclusive finance on the high-quality development of China's export trade; based on the analysis of the heterogeneous enterprise trade model, a mediating effect model is established to verify the mediating role of credit constraint in the development of high-quality export trade in China. Based on the above analysis, this paper concludes that inclusive digital finance, with its unique digital and inclusive nature, alleviates the credit constraint problem among SMEs, enhances the binary marginal effect of SMEs' exports, optimizes their export scale and structure, and promotes the high-quality development of regional and even national export trade. Finally, based on the findings of this paper, we propose insights and suggestions for inclusive digital finance to promote the high-quality development of export trade.
Abstract: Domestic violence, trafficking with human beings especially violence against children, is a worldwide problem. Hence, it remains one of the most widespread forms of violence in Kosovo and which often continues to be described as a "closed door issue". Recognition, acceptance and prioritization of cases of domestic violence definitely require a much greater awareness of individuals in institutions for the risks, consequences and costs that the lack of such a well-coordinated response brings to the country. Considering that children are the future and the wealth of the country, violence and neglect against them should be treated as carefully as possible. The purpose of this paper is to identify steps towards prevention of the domestic violence and trafficking with human beings, so that the reflection of the consequences and the psychological flow do not reflect to a large extent in society. In this study is described: How is the phenomenon of domestic violence related to trafficking in human beings? The methods used are: historical, comparative, qualitative. Data derived from the relevant institutions were presented, i.e., by the actors who are the first reactors as well as the policy makers. Although these phenomena are present in all countries of the world, Kosovo is no exception and therefore comparisons of the development of child abuse have been made with other countries in the region as well. Since Kosovo is a country in transition, a country with a relatively high level of education, low economic development, high unemployment, political instability, dysfunctional legal infrastructure, it can be concluded that the potential for the development of negative phenomena is present and inevitable. Thus, during the research, the stages of development of these phenomena are analyzed, determining the causes and consequences which come from abuse, neglect of children and the impact on trafficking in human beings. The Kosovar family (parental responsibility), culture and religion, social services, the dignity of the abused child, etc. were analyzed. The review was also done on the legislation, educational institutions (curricula), governmental and non-governmental institutions their responsibilities and cooperation towards combating child abuse and trafficking. It is worth noting that during the work on paper, recommendations and conclusions have been drawn where it is concluded that we need an environment with educational reforms, stability in the political environment, economic development, a review of social policies, greater awareness of society, more adequate information through media, so that information and awareness could penetrate even in the most remote places of Kosovo society.
Abstract: This paper proposes strategies in level crossing (LC) sampling and reconstruction that provide alias-free high-fidelity signal reconstruction for speech signals without exponentially increasing sample number with increasing bit-depth. We introduce methods in LC sampling that reduce the sampling rate close to the Nyquist frequency even for large bit-depth. The results indicate that larger variation in the sampling intervals leads to alias-free sampling scheme; this is achieved by either reducing the bit-depth or adding a jitter to the system for high bit-depths. In conjunction with windowing, the signal is reconstructed from the LC samples using an efficient Toeplitz reconstruction algorithm.
Abstract: With the current increase in CO2 emissions and global warming, the sustainability of both existing and new solutions must be assessed on a wide scale. As the implementation of closed cavity façades (CCF) is on the rise, various factors must be included in the analysis of new types of CCF. This paper aims to cover the relevant factors included in the sustainability assessment of new types of CCF. Several mathematical models are being used to describe the physical behavior of CCF. Depending on the type of CCF, they cover the main factors which affect the durability of the façade: thermal behavior of various elements in the façade, stress and deflection of the glass panels, pressure and the moisture control in the cavity. CCF itself represents a complex system in which all mentioned factors must be considered mutually. Still, the façade is only an envelope of a more complex system, the building. Choice of the façade dictates the heat loss and the heat gain, thermal comfort of inner space, natural lighting, and ventilation. Annual energy consumption for heating, cooling, lighting, and maintenance costs will present the operational advantages or disadvantages of the chosen façade system in economic and environmental aspects. Still, the only operational viewpoint is not all-inclusive. As the building codes constantly demand higher energy efficiency as well as transfer to renewable energy sources, the ratio of embodied and lifetime operational energy footprint of buildings is changing. With the drop in operational energy CO2 emissions, embodied energy emissions present a larger and larger share in the lifecycle emissions of the building. Taking all into account, the sustainability assessment of a façade, as well as other major building elements, should include all mentioned factors during the lifecycle of an element. The challenge of such an approach is a timescale. Depending on the climatic conditions on the building site, the expected lifetime of a glazed façade can exceed 25 years. In such a timespan, some of the factors can be estimated more precisely than the others. However, the ones depending on the socio-economic conditions are more likely to be harder to predict than the natural ones like the climatic load. This work recognizes and summarizes the relevant factors needed for the assessment of a new type of CCF, considering the entire lifetime of a façade element in an environmental aspect.
Abstract: In global navigation satellite system (GNSS) denied settings, such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.
Abstract: The most demanded organic foods worldwide are those that are consumed fresh, such as fruits and vegetables. However, there is a knowledge gap about some aspects of organic food microbiological quality and safety. Organic fruits and vegetables are more exposed to pathogenic microorganisms due to surface contact with natural fertilizers such as animal manure, wastes and vermicompost used during farming. Therefore, the objective of this work was to study the contamination of organic fresh green leafy vegetables by two emergent pathogens, Arcobacter spp. and Helicobacter pylori. For this purpose, a total of 24 vegetable samples, 13 lettuce and 11 spinach were acquired from 10 different ecological supermarkets and greengroceries and analyzed by culture and PCR. Arcobacter spp. was detected in five samples (20%) by PCR, four spinach and one lettuce. One spinach sample was found to be also positive by culture. For H. pylori, the H. pylori VacA gene-specific band was detected in 12 vegetable samples (50%), 10 lettuces and two spinach. Isolation in the selective medium did not yield any positive result, possibly because of low contamination levels together with the presence of the organism in its viable but non-culturable form. Results showed significant levels of H. pylori and Arcobacter contamination in organic vegetables that are generally consumed raw, which seems to confirm that these foods can act as transmission vehicles to humans.