Truck Routing Problem Considering Platooning and Drivers’ Breaks

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.

Possibilities for Testing User Experience and User Interface Design on Mobile Devices

In an era when everything is increasingly digital, consumers are always looking for new options in solutions to their everyday needs. In this context, mobile apps are developing at an exponential pace. One of the fastest growing segments of mobile technologies is, obviously, e-commerce. It can be predicted that mobile commerce will record nearly three times the global growth of e-commerce across all platforms, which indicates its importance in the given segment. The current coronavirus pandemic is also changing many of the existing paradigms both socially, economically, and technologically, which has a major impact on changing consumer behavior and the emphasis on simplification and clarity of mobile solutions. This is the area that User Experience (UX) and User Interface (UI) designers deal with. Their task is to design a sufficiently attractive and interesting solution that will be available on all mobile devices and at the same time will be easy enough for the customer/visitor to get to the destination or to get the necessary information in a few clicks. The basis for changes in UX design can now be obtained not only through online analytical tools, but also through neuromarketing, especially in the case of mobile devices. The paper highlights possibilities for testing UX design applications on mobile devices using a special platform that combines a stationary eye camera (eye tracking) and facial analysis (facial coding).

Cultivating Individuality and Equality in Education: Ideas on Respecting Dimensions of Diversity within the Classroom

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.

Ethnocentrism: The Hidden Adversary of Effective Global Leadership

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.

Visual Odometry and Trajectory Reconstruction for UAVs

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.

Time Series Forecasting Using Various Deep Learning Models

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.

Atherosclerosis Prevalence within Populations of the Southeastern United States

A prevalence cohort study of atherosclerotic lesions within cadavers was performed to better understand and characterize the prevalence of atherosclerosis among Georgia residents within body donors in the Philadelphia College of Osteopathic Medicine (PCOM) - Georgia body donor program. We procured specimens from cadavers used for medical student, physical therapy student, and biomedical science student cadaveric anatomical dissection at PCOM - South Georgia and PCOM - Georgia. Tissues were prepared using hematoxylin and eosin (H&E) stain as histological slides by Colquitt Regional Medical Center Laboratory Services. One section from each of the following arteries was taken after cadaveric dissection at the site of most calcification palpated grossly (if present): left anterior descending coronary artery, left internal carotid artery, abdominal aorta, splenic artery, and hepatic artery. All specimens were graded and categorized according to the American Heart Association’s Modified and Conventional Standards for Atherosclerotic Lesions using x4, x10, x40 microscopic magnification. Our study cohort included 22 cadavers, with 16 females and 6 males. The average age was 72.54 and median age was 72, with a range of 52 to 90 years old. The cause of death determination listing vascular and/or cardiovascular causes were present on 6 of the 22 death certificates. 19 of 22 (86%) cadavers had at least a single artery grading > 5. Of the cadavers with at least a single artery graded at greater than 5, only 5 of 19 (26%) cadavers had a vascular or cardiovascular cause of death reported. Malignancy was listed as a cause of death on 7 (32%) of death certificates. The average atherosclerosis grading of the common hepatic, splenic and left internal carotid arteries (2.15, 3.05, and 3.36 respectively) were lower than the left anterior descending artery and the abdominal aorta (5.16 and 5.86 respectively). This prevalence study characterizes atherosclerosis found in five medium and large systemic arteries within cadavers from the state of Georgia.

Automated Driving Deep Neural Network Model Accuracy and Performance Assessment in a Simulated Environment

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.

Matrix Completion with Heterogeneous Observation Cost Using Sparsity-Number of Column-Space

The matrix completion problem has been studied broadly under many underlying conditions. In many real-life scenarios, we could expect elements from distinct columns or distinct positions to have a different cost. In this paper, we explore this generalization under adaptive conditions. We approach the problem under two different cost models. The first one is that entries from different columns have different observation costs, but, within the same column, each entry has a uniform cost. The second one is any two entry has different observation cost, despite being the same or different columns. We provide complexity analysis of our algorithms and provide tightness guarantees.

Design and Analysis of Low-Power, High Speed and Area Efficient 2-Bit Digital Magnitude Comparator in 90nm CMOS Technology Using Gate Diffusion Input

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.

Contribution of the SidePlate Beam-Column Connections to the Seismic Responses of Special Moment Frames

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.

Whooeaism: A Concept of Origin of Religion among the Jarawas of Andaman Islands, India

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.

Attitudes of Gratitude: An Analysis of 30 Cancer Narratives Published by Leading U.S. Cancer Care Centers

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.  

Vocational Skills, Recognition of Prior Learning and Technology: The Future of Higher Education

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.

A Deep Learning Framework for Polarimetric SAR Change Detection Using Capsule Network

The Earth's surface is constantly changing through forces of nature and human activities. Reliable, accurate, and timely change detection is critical to environmental monitoring, resource management, and planning activities. Recently, interest in deep learning algorithms, especially convolutional neural networks, has increased in the field of image change detection due to their powerful ability to extract multi-level image features automatically. However, these networks are prone to drawbacks that limit their applications, which reside in their inability to capture spatial relationships between image instances, as this necessitates a large amount of training data. As an alternative, Capsule Network has been proposed to overcome these shortcomings. Although its effectiveness in remote sensing image analysis has been experimentally verified, its application in change detection tasks remains very sparse. Motivated by its greater robustness towards improved hierarchical object representation, this study aims to apply a capsule network for PolSAR image Change Detection. The experimental results demonstrate that the proposed change detection method can yield a significantly higher detection rate compared to methods based on convolutional neural networks.

Domestic Violence against Children and Trafficking in Human Beings: Two Worrying Phenomena in Kosovo

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.

Quantifying the Second-Level Digital Divide on Sub-National Level

Digital divide, the gap in the access to the world of digital technologies and the socio-economic opportunities that they create is an important phenomenon of the XXI century. This gap may exist between countries, regions within a country or socio-demographic groups, creating the classes of “digital have and have nots”. While the 1st-level divide (the difference in opportunities to access the digital networks) was demonstrated to diminish with time, the issues of 2nd level divide (the difference in skills and usage of digital systems) and 3rd level divide (the difference in effects obtained from digital technology) may grow. The paper offers a systemic review of literature on the measurement of the digital divide, noting the certain conceptual stagnation due to the lack of effective instruments that would capture the complex nature of the phenomenon. As a result, many important concepts do not receive the empiric exploration they deserve. As a solution the paper suggests a composite Digital Life Index, that studies separately the digital supply and demand across seven independent dimensions providing for 14 subindices. The Index is based on Internet-borne data, a distinction from traditional research approaches that rely on official statistics or surveys. The application of the model to the study of the digital divide between Russian regions and between cities in China have brought promising results. The paper advances the existing methodological literature on the 2nd level digital divide and can also inform practical decision-making regarding the strategies of national and regional digital development.

Efficient Alias-free Level Crossing Sampling

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.

Detection of Arcobacter and Helicobacter pylori Contamination in Organic Vegetables by Cultural and PCR Methods

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.

Dielectric Recovery Characteristics of High Voltage Gas Circuit Breakers Operating with CO2 Mixture

CO₂-based gas mixtures exhibit huge potential as the interruption medium for replacing SF₆ in high voltage switchgears. In this paper, the recovery characteristics of dielectric strength of CO₂-O₂ mixture in the post arc phase after the current zero are presented. As representative examples, the dielectric recovery curves under conditions of different gas filling pressures and short-circuit current amplitudes are presented. A series of dielectric recovery measurements suggests that the dielectric recovery rate is proportional to the mass flux of the blowing gas, and the dielectric strength recovers faster in the case of lower short circuit currents.