Search results for: virtual service network

Authors: N. Ali, S. Nakayama, H. Yamaguchi, M. Nadeem

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Traffic congestion is a matter of prime concern in developing countries. This can be primarily attributed due to poor design practices and biased allocation of resources based on political will neglecting the technical feasibilities in infrastructure design. During the last decade, Lahore has expanded at an unprecedented rate as compared to surrounding cities due to more funding and resource allocation by the previous governments. As a result of this, people from surrounding cities and areas moved to the Lahore city for better opportunities and quality of life. This migration inflow inherited the city with an increased population yielding the inefficiency of the existing infrastructure to accommodate enhanced traffic demand. This leads to traffic congestion on major arterial roads of the city. In this simulation study, a major arterial road was selected to evaluate the performance of the five intersections by changing the geometry of the intersections or signal control type. Simulations were done in two software; Highway Capacity Software (HCS) and Synchro Studio and Sim Traffic Software. Some of the traffic management strategies that were employed include actuated-signal control, semi-actuated signal control, fixed-time signal control, and roundabout. The most feasible solution for each intersection in the above-mentioned traffic management techniques was selected with the least delay time (seconds) and improved Level of Service (LOS). The results showed that Jinnah Hospital Intersection and Akbar Chowk Intersection improved 92.97% and 92.67% in delay time reduction, respectively. These results can be used by traffic planners and policy makers for decision making for the expansion of these intersections keeping in mind the traffic demand in future years.

Keywords: traffic congestion, traffic simulation, traffic management, congestion problems

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Authors: Atefeh Omidkhah, Mohammadreza Bemanian

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The issue of way-finding earmarks a wide range of literature in architecture and despite the 50 year background of way-finding studies, it still lacks a comprehensive theory for indoor settings. Way-finding has a notable role in emergency evacuation as well. People in the panic situation of a fire emergency need to find the safe egress route correctly and in as minimum time as possible. In this regard the parameters of an appropriate way-finding are mentioned in the evacuation related researches albeit scattered. This study reviews the fire safety related literature to extract a way-finding related framework for architectural purposes of the design of a safe evacuation route. In this regard a research trend review in addition with applied methodological approaches review is conducted. Then by analyzing eight original researches related to way-finding parameters in fire evacuation, main parameters that affect way-finding in emergency situation of a fire incident are extracted and a framework was developed based on them. Results show that the issues related to exit route and emergency evacuation can be chased in task oriented studies of way-finding. This research trend aims to access a high-level framework and in the best condition a theory that has an explanatory capability to define differences in way-finding in indoor/outdoor settings, complex/simple buildings and different building types or transitional spaces. The methodological advances demonstrate the evacuation way-finding researches in line with three approaches that the latter one is the most up-to-date and precise method to research this subject: real actors and hypothetical stimuli as in evacuation experiments, hypothetical actors and stimuli as in agent-based simulations and real actors and semi-real stimuli as in virtual reality environment by adding multi-sensory simulation. Findings on data-mining of 8 sample of original researches in way-finding in evacuation indicate that emergency way-finding design of a building should consider two level of space cognition problems in the time of emergency and performance consequences of them in the built environment. So four major classes of problems in way-finding which are visual information deficiency, confusing layout configuration, improper navigating signage and demographic issues had been defined and discussed as the main parameters that should be provided with solutions in design and interior of a building. In the design phase of complex buildings, which face more reported problem in way-finding, it is important to consider the interior components regarding to the building type of occupancy and behavior of its occupants and determine components that tend to become landmarks and set the architectural features of egress route in line with the directions that they navigate people. Research on topological cognition of environmental and its effect on way-finding task in emergency evacuation is proposed for future.

Keywords: architectural design, egress route, way-finding, fire safety, evacuation

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Authors: Zhuohan Li, Jing Yang, Yaoyuan Cui

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The gut-brain axis (GBA), a communication network between gut microbiota and the brain, benefits for investigation of brain diseases. Currently, organ chips are considered one of the potential tools for GBA research. However, most of the available GBA chips have limitations in replicating the three-dimensional (3D) growth environment of cells and lack the required cell types for barrier function. In the present study, a microfluidic chip was developed for GBA interaction. Blood-brain barrier (BBB) module was prepared with HBMEC, HBVP, U87 cells and decellularized matrix (dECM). Intestinal epithelial barrier (IEB) was prepared with Caco-2 and vascular endothelial cells and dECM. GBA microfluidic device was integrated with IEB and BBB modules using 3D printing interconnecting microchannel scaffolds. BBB and IEB interaction on this GBA chip were evaluated with lipopolysaccharide (LPS) exposure. The present GBA chip achieved multicellular three-dimensional cultivation. Compared with the co-culture cell model in the transwell, fluorescein was absorbed more slowly by 5.16-fold (IEB module) and 4.69-fold (BBB module) on the GBA chip. Accumulation of Rhodamine 123 and Hoechst33342 was dramatically decreased. The efflux function of transporters on IEB and BBB was significantly increased on the GBA chip. After lipopolysaccharide (LPS) disrupted the IEB, and then BBB dysfunction was further observed, which confirmed the interaction between IEB and BBB modules. These results demonstrated that this GBA chip may offer a promising tool for gut-brain interaction study.

Keywords: decellularized matrix, gut-brain axis, organ-on-chip, three-dimensional printing.

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Authors: Bircan Demiral

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Cognitive radio (CR) is the promising technology that addresses the spectrum scarcity problem for future wireless communications. Orthogonal Frequency Division Multiplexing (OFDM) technology provides more power band ratios for cognitive radio networks (CRNs). While CR is a solution to the spectrum scarcity, it also brings up the capacity problem. In this paper, a novel power allocation algorithm that aims at maximizing the sum capacity in the OFDM based cognitive radio networks is proposed. Proposed allocation algorithm is based on the previously developed water-filling algorithm. To reduce the computational complexity calculating in water filling algorithm, proposed algorithm allocates the total power according to each subcarrier. The power allocated to the subcarriers increases sum capacity. To see this increase, Matlab program was used, and the proposed power allocation was compared with average power allocation, water filling and general power allocation algorithms. The water filling algorithm performed worse than the proposed algorithm while it performed better than the other two algorithms. The proposed algorithm is better than other algorithms in terms of capacity increase. In addition the effect of the change in the number of subcarriers on capacity was discussed. Simulation results show that the increase in the number of subcarrier increases the capacity.

Keywords: cognitive radio network, OFDM, power allocation, water filling

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Authors: Ana Belon Hercilla

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The study is developed in “Reactivos Jeans” company, in the city of Arequipa, whose main business is the laundry of garments at an industrial level. In 2012 the company initiated actions to provide a dry cleaning service of alpaca fiber garments, recognizing that this item is in a growth phase in Peru. Additionally this company took the initiative to use a new greenwashing technology which has not yet been developed in the country. To accomplish this, a redesign of both the process and the plant layout was required. For redesigning the plant, the methodology used was the Systemic Layout Planning, allowing this study divided into four stages. First stage is the information gathering and evaluation of the initial situation of the company, for which a description of the areas, facilities and initial equipment, distribution of the plant, the production process and flows of major operations was made. Second stage is the development of engineering techniques that allow the logging and analysis procedures, such as: Flow Diagram, Route Diagram, DOP (process flowchart), DAP (analysis diagram). Then the planning of the general distribution is carried out. At this stage, proximity factors of the areas are established, the Diagram Paths (TRA) is developed, and the Relational Diagram Activities (DRA). In order to obtain the General Grouping Diagram (DGC), further information is complemented by a time study and Guerchet method is used to calculate the space requirements for each area. Finally, the plant layout redesigning is presented and the implementation of the improvement is made, making it possible to obtain a model much more efficient than the initial design. The results indicate that the implementation of the new machinery, the adequacy of the plant facilities and equipment relocation resulted in a reduction of the production cycle time by 75.67%, routes were reduced by 68.88%, the number of activities during the process were reduced by 40%, waits and storage were removed 100%.

Keywords: redesign, time optimization, industrial laundry, greenwashing

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: Ping-Hung Chen, Han-Liang Lin

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Taiwan has formed diverse settlement patterns in different time and space backgrounds. Various socio-network links are created between individuals, families, communities, and societies, and different living cultures are also derived. But rapid urbanization and social structural change have caused the creation of densely-packed assembly housing complexes and made neighborhood community upward developed. This, among others, seemed to have affected neighborhood relationship and also created social problems. To understand the complex relations and socio-spatial structure of the community, it is important to use mixed methods. This research employs the theory of space syntax to analyze the layout and structural indicators of the selected communities in Tainan city. On the other hand, this research does the survey about residents' interactions and the sense of community by questionnaire of the selected communities. Then the mean values of the syntax measures from each community were correlated with the results of the questionnaire using a Pearson correlation to examine how elements in physical design affect the sense of community and neighborhood relationship. In Taiwan, most urban morphology research methods are qualitative study. This paper tries to use space syntax to find out the correlation between the community layout and the neighborhood relationship. The result of this study could be used in future studies or improve the quality of residential communities in Taiwan.

Keywords: community layout, neighborhood relationship, space syntax, mixed-method

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Authors: Parisa Mansour

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The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

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Authors: Noel Busch-Armendariz, Caitlin Sulley

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Introduction: This study investigated the development of college experiences, COVID-19 pandemic experiences, alcohol use, and sexual violence. The longitudinal study includes 656 college students living in the same dormitory. Students' alcohol use and social network structure were investigated to better understand the relationship with sexual violence risk. Basic Methodologies: Over two years, students repeated five web-based surveys, including a pre-college survey and surveys during four consecutive semesters. Questions were added in the fourth wave to assess students’ experiences of the COVID-19 pandemic, administered from November-January 2021, including mental and behavioral health. Analyses include the impact of COVID on living arrangements, drinking behaviors, and daily life; experiences of COVID symptoms, testing, and diagnosis, responses to COVID such as social distancing, quarantining, not working, increased health care needs; experience of fear, worry, stigma, emotional well-being, loneliness, and mental health; experiences of financial loss, lack of basic supplies, receiving emotional and financial support, and comparison with academic disengagement. Concluding Statement: Findings and discussion will include strategies to strengthen mental and behavioral health programs and policies.

Keywords: COVID, mental health, substance abuse, college students, sexual misconducts

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Authors: W. S. Barber, S. L. King

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This paper reports on a pilot project to develop a collaborative partnership between a community college in rural northern Ontario, Canada, and an urban university in the greater Toronto area in Oshawa, Canada. Partner institutions will collaborate to address learning needs of university applicants whose goals are to attain an undergraduate university BA in Educational Studies and Digital Technology degree, but who may not live in a geographical location that would facilitate this pathways process. The UOIT BA degree is attained through a 2+2 program, where students with a 2 year college diploma or equivalent can attain a four year undergraduate degree. The goals reported on the project are as: 1. Our aim is to expand the BA program to include an additional stream which includes serious educational games, simulations and virtual environments, 2. Develop fully (using both synchronous and asynchronous technologies) online learning modules for use by university applicants who otherwise are not geographically located close to a physical university site, 3. Assess the digital competencies of all students, including members of local, distance and Indigenous communities using a validated tool developed and tested by UOIT across numerous populations. This tool, the General Technical Competency Use and Scale (GTCU) will provide the collaborating institutions with data that will allow for analyzing how well students are prepared to succeed in fully online learning communities. Philosophically, the UOIT BA program is based on a fully online learning communities model (FOLC) that can be accessed from anywhere in the world through digital learning environments via audio video conferencing tools such as Adobe Connect. It also follows models of adult learning and mobile learning, and makes a university degree accessible to the increasing demographic of adult learners who may use mobile devices to learn anywhere anytime. The program is based on key principles of Problem Based Learning, allowing students to build their own understandings through the co-design of the learning environment in collaboration with the instructors and their peers. In this way, this degree allows students to personalize and individualize the learning based on their own culture, background and professional/personal experiences. Using modified flipped classroom strategies, students are able to interrogate video modules on their own time in preparation for one hour discussions occurring in video conferencing sessions. As a consequence of the program flexibility, students may continue to work full or part time. All of the partner institutions will co-develop four new modules, administer the GTCU and share data, while creating a new stream of the UOIT BA degree. This will increase accessibility for students to bridge from community colleges to university through a fully digital environment. We aim to work collaboratively with Indigenous elders, community members and distance education instructors to increase opportunities for more students to attain a university education.

Keywords: aboriginal, college, competencies, digital, universities

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Authors: Robert Joseph M. Licup

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The deployment of the fifth-generation (5G) mobile system through mmWave frequencies is the new solution in the requirement to provide higher bandwidth readily available for all users. The usage pattern of the mobile users has moved towards either the work from home or online classes set-up because of the pandemic. Previous mobile technologies can no longer meet the high speed, and bandwidth requirement needed, given the drastic shift of transactions to the home. The millimeter-wave (mmWave) underutilized frequency is utilized by the fifth-generation (5G) cellular networks that support multi-gigabit-per-second (Gbps) transmission. However, due to its short wavelengths, high path loss, directivity, blockage sensitivity, and narrow beamwidth are some of the technical challenges that need to be addressed. Different tools, technologies, and scenarios are explored to support network design, accurate channel modeling, implementation, and deployment effectively. However, there is a big challenge on how the consumer will adopt this solution and maximize the benefits offered by the 5G Technology. This research proposes to study the intricacies of technology diffusion, individual attitude, behaviors, and how technology adoption will be attained. The agent based simulation model shaped by the actual applications, technology solution, and related literature was used to arrive at a computational model. The research examines the different attributes, factors, and intricacies that can affect each identified agent towards technology adoption.

Keywords: agent-based model, AnyLogic, 5G O21, 5G mmWave solutions, technology adoption

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Authors: Abdul Mannan Akhtar

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In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: Gabriela V. Angeles Perez, Jose Castillejos Lopez, Araceli L. Reyes Cabello, Emilio Bravo Grajales, Adriana Perez Espinosa, Jose L. Quiroz Fabian

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Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current. However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze. The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS.

Keywords: data mining, k-means, road traffic accidents, Waze, Weka

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Authors: Konrad Rejdak, Agnieszka Korchut, Sebastian Szklener, Urszula Skrobas, Justyna Gerlowska, Katarzyna Grabowska-Aleksandrowicz, Dorota Szczesniak-Stanczyk

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Introduction: Neurodegenerative diseases are frequently accompanied by loss and unwanted change in functional independence, social relationships, and economic circumstances. Currently, the achievements of social robots to date is being projected to improve multidimensional quality of life among people with cognitive impairment and others. Objectives: Identification of particular human needs in context of the changes occurring in course of neurodegenerative diseases. Methods: Based on the 110 surveys performed in Medical University of Lublin from medical staff, patients, and caregivers we made prioritization of the users' needs as: high, medium, and low. The issues included in the surveys concerned four aspects: user acceptance, functional requirements, design of the robotic assistant and preferred types of human-robot interaction. Results: We received completed questionnaires: 50 from medical staff, 30 from caregivers and 30 from potential users. Above 90% of the respondents from each of the three groups, accepted robotic assistant as a potential caregiver. High priority functional capability of assistive technology was to handle emergencies in a private home like recognizing life-threatening situations and reminding about medication intake. With reference to design of the robotic assistant, the majority of the respondent would like to have an anthropomorphic appearance with positive emotionally expressive face. The most important type of human-robot interaction was voice-operated system and by touchscreen. Conclusion: The results from our study might contribute to a better understanding of the system and users’ requirements for the development of a service robot intended to support patients with dementia.

Keywords: social robot, dementia, requirements, patients needs

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Authors: Irene Carter, Roy Hanes, Judy MacDonald

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Considering that disability is universal and people with disabilities are part of all societies; that there is a connection between the disabled individual and the societal; and that it is society and social arrangements that disable people with impairments, contemporary disability discourse emphasizes the social model of disability to counter medical and rehabilitative models of disability. However, the social model does not go far enough in addressing the issues of oppression and inclusion. The authors indicate that the social model does not specifically or adequately denote the oppression of persons with disabilities, which is a central component of progressive social work practice with people with disabilities. The social model of disability does not go far enough in deconstructing disability and offering social workers, as well as people with disabilities a way of moving forward in terms of practice anchored in individual, familial and societal change. The social model of disability is expanded by incorporating principles of anti-oppression social work practice. Although the contextual analysis of the social model of disability is an important component there remains a need for social workers to provide service to individuals and their families, which will be illustrated through anti-oppressive practice (AOP). By applying an anti-oppressive model of practice to the above definitions, the authors not only deconstruct disability paradigms but illustrate how AOP offers a framework for social workers to engage with people with disabilities at the individual, familial and community levels of practice, promoting an emancipatory focus in working with people with disabilities. An anti- social- oppression social work model of disability connects the day-to-day hardships of people with disabilities to the direct consequence of oppression in the form of ableism. AOP theory finds many of its basic concepts within social-oppression theory and the social model of disability. It is often the case that practitioners, including social workers and psychologists, define people with disabilities’ as having or being a problem with the focus placed upon adjustment and coping. A case example will be used to illustrate how an AOP paradigm offers social work a more comprehensive and critical analysis and practice model for social work practice with and for people with disabilities than the traditional medical model, rehabilitative and social model approaches.

Keywords: anti-oppressive practice, disability, people with disabilities, social model of disability

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Authors: Nazanin Naderi, Milton Smith

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Since worldwide demand for renewable energy is increasing rapidly because of the climate problem and the limitation of fossil fuels, technologies of alternative energy sources have been developed and the electric power network now includes renewable energy resources such as wind energy. Because of the huge advantages that wind energy has, like reduction in natural gas use, price pressure, emissions of greenhouse gases and other atmospheric pollutants, electric sector water consumption and many other contributions to the nation’s economy like job creation it has got too much attention these days from different parts of the world especially in the United States which is trying to provide 20% of the nation’s energy from wind by 2030. This study is trying to evaluate the effect of splitting wind farms on power output. We are trying to find if we can get more output by installing wind turbines in different sites rather than installing all wind turbines in one site. Five potential sites in Texas have been selected as a case study and two years wind data has been gathered for these sites. Wind data are analyzed and effect of correlation between sites on power output has been evaluated. Standard deviation and autocorrelation effect has also been considered for this study. The paper has been organized as follows: After the introduction the second section gives a brief overview of wind analysis. The third section addresses the case study and evaluates correlation between sites, auto correlation of sites and standard deviation of power output. In section four we describe the results.

Keywords: auto correlation, correlation between sites, splitting wind farms, power output, standard deviation

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Authors: Ichiro Takahashi

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One conundrum that macroeconomic theory faces is to explain how an economy can revive from depression, in which the aggregate demand has fallen substantially below its productive capacity. This paper examines an autonomous stabilizing mechanism using an agent-based Wicksell-Keynes macroeconomic model. This paper focuses on the effects of the number of firms and the length of the gestation period for investment that are often assumed to be one in a mainstream macroeconomic model. The simulations found the virtual economy was highly unstable, or more precisely, collapsing when these parameters are fixed at one. This finding may even suggest us to question the legitimacy of these common assumptions. A perpetual decline in capital stock will eventually encourage investment if the capital stock is short-lived because an inactive investment will result in insufficient productive capacity. However, for an economy characterized by a roundabout production method, a gradual decline in productive capacity may not be able to fall below the aggregate demand that is also shrinking. Naturally, one would then ask if our economy cannot rely on an external stimulus such as population growth and technological progress to revive investment, what factors would provide such a buoyancy for stimulating investments? The current paper attempts to answer this question by employing the artificial macroeconomic model mentioned above. The baseline model has the following three features: (1) the multi-period gestation for investment, (2) a large number of heterogeneous firms, (3) demand-constrained firms. The instability is a consequence of the following dynamic interactions. (a) A multiple-period gestation period means that once a firm starts a new investment, it continues to invest over some subsequent periods. During these gestation periods, the excess demand created by the investing firm will spill over to ignite new investment of other firms that are supplying investment goods: the presence of multi-period gestation for investment provides a field for investment interactions. Conversely, the excess demand for investment goods tends to fade away before it develops into a full-fledged boom if the gestation period of investment is short. (b) A strong demand in the goods market tends to raise the price level, thereby lowering real wages. This reduction of real wages creates two opposing effects on the aggregate demand through the following two channels: (1) a reduction in the real labor income, and (2) an increase in the labor demand due to the principle of equality between the marginal labor productivity and real wage (referred as the Walrasian labor demand). If there is only a single firm, a lower real wage will increase its Walrasian labor demand, thereby an actual labor demand tends to be determined by the derived labor demand. Thus, the second positive effect would not work effectively. In contrast, for an economy with a large number of firms, Walrasian firms will increase employment. This interaction among heterogeneous firms is a key for stability. A single firm cannot expect the benefit of such an increased aggregate demand from other firms.

Keywords: agent-based macroeconomic model, business cycle, demand constraint, gestation period, representative agent model, stability

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Authors: Akanksha Bhatnagar, Sandhya Kortegare, Felice Elefant

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Context: Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by progressive cognitive decline and memory loss. The cause of AD is not fully understood, but it is thought to be caused by a combination of genetic, environmental, and lifestyle factors. One of the hallmarks of AD is the loss of neurons in the hippocampus, a brain region that is important for memory and learning. This loss of neurons is thought to be caused by a decrease in histone acetylation, which is a process that regulates gene expression. Research Aim: The research aim of the study was to develop mall molecule compounds that can enhance the activity of Tip60, a histone acetyltransferase that is important for memory and learning. Methodology/Analysis: The researchers used in silico structural modeling and a pharmacophore-based virtual screening approach to design and synthesize small molecule compounds strongly predicted to target and enhance Tip60’s HAT activity. The compounds were then tested in vitro and in vivo to assess their ability to enhance Tip60 activity and rescue cognitive deficits in AD models. Findings: The researchers found that several of the compounds were able to enhance Tip60 activity and rescue cognitive deficits in AD models. The compounds were also developed to cross the blood-brain barrier, which is an important factor for the development of potential AD therapeutics. Theoretical Importance: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Data Collection: The study collected data from a variety of sources, including in vitro assays and animal models. The in vitro assays assessed the ability of compounds to enhance Tip60 activity using histone acetyltransferase (HAT) enzyme assays and chromatin immunoprecipitation assays. Animal models were used to assess the ability of the compounds to rescue cognitive deficits in AD models using a variety of behavioral tests, including locomotor ability, sensory learning, and recognition tasks. The human clinical trials will be used to assess the safety and efficacy of the compounds in humans. Questions: The question addressed by this study was whether Tip60 HAT activators could be developed as therapeutic agents for AD. Conclusions: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Further research is needed to confirm the safety and efficacy of these compounds in humans.

Keywords: Alzheimer's disease, cognition, neuroepigenetics, drug discovery

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Authors: Ronel Solis, Leonardo Collado

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Migration law in the Republic of Panama has been regulated mainly by the executive branch. This has created a crisis not only institutional but also social because the evolution of these norms has rested greatly from the discretion of the government in office. This has created instability in immigration regulation and more now, with the migration crisis of which Panama is also part. Different migration policies have been established. The most recent is that of the controlled migration flow, in which, for humanitarian reasons, migrants move from the border with Colombia to the border with Costa Rica. Unfortunately, such control is not enough, and in some cases, unprotected migrants have been confined for months, their passports have been withheld, and no recognition of their rights is offered. The Inter-American Court of Human Rights has condemned Panama for the unfair detention of an irregular migrant, who was detained for two years in Panamanian prisons, without having committed a crime and without accessing a just defense. This is the case Vélez Loor vs. the Republic of Panama. Uncontrollable migration has been putting pressure on Panamanian public health services. The recent denunciation of HIV-related NGOs that warns that there are hundreds of foreigners who receive expensive antiretroviral therapy in Panama is serious, and several of them are irregular migrants. On the other hand, there are no border control posts with the Republic of Colombia, because it is a jungle area and migrants are exposed to arms and drug trafficking, and unfortunately, also to prostitution. Government entities such as the border police service have provided humanitarian support to migrants on the border with Colombia, although it is not their administrative function, and various entities discuss who should address this crisis. However, few economic resources are allocated by the government to solve this problem, especially with the recent mass migration of Venezuelans who have fled their country. The establishment of a migratory normative code is necessary to establish uniformity in the recognition and application of migratory rights. In this way, dependence on the changing migration policies of the different Panamanian governments would be eliminated, and the rights of migrants and nationals would be guaranteed.

Keywords: executive branch, irregular migration, migration code, Republic of Panama

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Authors: Demur Bakuradze, Mzia Beruashvili

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It is known that bioactive compounds that are secreted by allelopathic plants sown with the main culture and are natural phytotoxic substances can be used as natural pesticides that, unlike synthetic agrochemicals, are less likely to disrupt the global ecosystem. Alternative plant protection approaches to date include components of integrated pest management programs and natural plant protection tools. Every year, more and more evidence is given on the successful use of these means, including allelopathic compounds in plant protection against pests. Proper use of these interactions between plants and other organisms can become a serious alternative to synthetic pesticides. Due to the relevance of the issue, the purpose of the study was to study the impact of some companion allelopathic plants on the Tomato culture (variety ‘Kharisgula’) on the test plot of the Tsilkani Base Bioagricultural Service of the Agricultural Research Center (East Georgia) and the village of Kharagauli. The study was conducted in 2023-2024 with methods adopted in organic agriculture and plant protection. Various companion plants were studied: Basil (Ocimum basilicum L.), Imeretian saffron or marigold (Tagetes patula L.) and beans (Phaseolus vulgaris L.) (variety ‘Tsanava’) affects tomato culture in mixed crops. It was established that when sowing basil in rows and on the perimeter, the yield in the Tsilkani increased by 39.7%, and in Sagandzile - 42.8%. In the case of Imeretian saffron, economic efficiency in Tsilkani reached 29.5%, in Sagandzile - 28.5%, while the difference in the bean variant with the control was 31.7% in Tsilkani, and in Sagandzile - 23.8%. The study also found that when sowing aromatic plants (basil, marigold) with tomato, the number and spread of pests is quite decreasing compared to the control. In particular, the number of green vegetable bugs (Nezara viridula L.) decreased by 59.4% compared to control.

Keywords: allelopathy, companion planting, tomato, bioproduction

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Authors: Zahra Khodaee

Abstract:

Environmental Justice (EJ) concept consists of multifaceted movements, community struggles, and discourses in contemporary societies that seek to reduce environmental risks, increase environmental protections, and generally reduce environmental inequalities suffered by minority and poor communities; a term that incorporates ‘environmental racism’ and ‘environmental classism,’ captures the idea that different racial and socioeconomic groups experience differential access to environmental quality. This article explores environmental justice as an urban phenomenon in urban planning and applies it in peri-urban environment of a metropolis. Tehran peri-urban environments which are the result of meeting the city- village- nature systems or «city-village junction» have gradually faced effects such as accelerated environmental decline, changes without land-use plan, and severe service deficiencies. These problems are instances of environmental injustice which make the planners to adjust the problems and use and apply the appropriate strategies and policies by looking for solutions and resorting to theories, techniques and methods related to environmental justice. In order to access to this goal, try to define environmental justice through justice and determining environmental justice indices to analysis environmental injustice in case study. Then, make an effort to introduce some criteria to select case study in two micro and micro levels. Qiyamdasht town as the peri-urban environment of Tehran metropolis is chosen and examined to show the existence of environmental injustice by questionnaire analysis and SPSS software. Finally, use AIDA technique to design a strategic plan and reduce environmental injustice in case study by introducing the better scenario to be used in policy and decision making areas.

Keywords: environmental justice, metropolis of Tehran, Qiyam, Dasht peri, urban settlement, analysis of interconnected decision area (AIDA)

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Authors: Jangje Park, So Young Kim

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The market demand for audio quality in mobile devices continues to increase, and audible buzz noise generated in time division communication is a chronic problem that goes against the market demand. In the case of time division type communication, the RF Power Amplifier (RF PA) is driven at the audio frequency cycle, and it makes various influences on the audio signal. In this paper, we measured the ground bounce noise generated by the peak current flowing through the ground network in the RF PA with the audio frequency; it was confirmed that the noise is the cause of the audible buzz noise during a call. In addition, a grounding method of the microphone device that can improve the buzzing noise was proposed. Considering that the level of the audio signal generated by the microphone device is -38dBV based on 94dB Sound Pressure Level (SPL), even ground bounce noise of several hundred uV will fall within the range of audible noise if it is induced by the audio amplifier. Through the grounding method of the microphone device proposed in this paper, it was confirmed that the audible buzz noise power density at the RF PA driving frequency was improved by more than 5dB under the conditions of the Printed Circuit Board (PCB) used in the experiment. A fundamental improvement method was presented regarding the buzzing noise during a mobile phone call.

Keywords: audio frequency, buzz noise, ground bounce, microphone grounding

Procedia PDF Downloads 139

Authors: Suteera Pradubwong, Darawan Augsornwan, Pornpen Pathumwiwathana, Benjamas Prathanee, Bowornsilp Chowchuen

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Background: Cleft lip and palate (CLP) congenital anomalies have a high prevalence in the Northeast of Thailand. A care team’s understand of treatment plan would help to guide the family of patients with CLP to achieve the treatment. Objectives: To examine the impact of the empowering volunteer project, established in the northeast Thailand. Materials and Methods: The Empowering Volunteer project was conducted in 2008 under the Tawanchai Royal Granted project. The patients and family’s general information, treatment, the group brainstorming, and satisfaction with the project were analyzed. Results: Participants were 12 children with CLP, their families and five volunteers with CLP; the participating patients were predominantly females and the mean, age was 12.2 years. The treatment comprised of speech training, dental hygiene care, bone graft and orthodontic treatment. Four issues were addressed including: problems in taking care of breast feeding; instructions’ needs for care at birth; difficulty in access information and society impact; and needs in having a network of volunteers. Conclusions: Empowering volunteer is important for holistic care of patients with CLP which provides easy access and multiple channels for patients and their families. It should be developed as part of the self-help and family support group, the development of community based team and comprehensive CLP care program.

Keywords: self-help and family support group, community based model, volunteer, cleft lip-cleft palate

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Authors: Abdulkarim Yusuf

Abstract:

Motivation: The Nigerian economy has seen significant macroeconomic instability, fuelled mostly by an overreliance on fluctuating oil revenues. The rising disparity between tax receipts and government spending in Nigeria necessitates government borrowing to fund the anticipated pace of economic growth. Rising public debt and fiscal sustainability are limiting the government's ability to invest in key infrastructure that promotes private investment and growth in Nigeria. Objective: This paper fills an empirical research vacuum by examining the impact of public debt on fiscal sustainability in Nigeria, given the significance of fiscal stability in decreasing poverty and the constraints that an unsustainable debt burden imposes on it. Data and method: Annual time series data covering the period 1980 to 2022 exposed to conventional and structural breaks stationarity tests and the Autoregressive Distributed Lag estimation approach were adopted for this study. Results: The results reveal that domestic debt stock, debt service payment, foreign reserve stock, exchange rate, and private investment all had a major adverse effect on fiscal stability in the long and short run, corroborating the debt overhang and crowding-out hypothesis. External debt stock, prime lending rate, and degree of trade openness, which boosted fiscal stability in the long run, had a major detrimental effect on fiscal stability in the short run, whereas foreign direct investment inflows had an important beneficial impact on fiscal stability in both the long and short run. Implications: The results indicate that fiscal measures that inspire domestic resource mobilization, sustainable debt management techniques, and dependence on external debt to boost deficit financing will improve fiscal stability and drive growth.

Keywords: ARDL co-integration, debt overhang, debt servicing, fiscal stability, public debt

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Authors: Nahla H. Alaswadko, Rayya A. Hassan, Bayar N. Mohammed

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Empirical deterministic models have been developed to predict roughness progression of heavy duty spray sealed pavements for a dataset representing rural arterial roads. The dataset provides a good representation of the relevant network and covers a wide range of operating and environmental conditions. A sample with a large size of historical time series data for many pavement sections has been collected and prepared for use in multilevel regression analysis. The modelling parameters include road roughness as performance parameter and traffic loading, time, initial pavement strength, reactivity level of subgrade soil, climate condition, and condition of drainage system as predictor parameters. The purpose of this paper is to report the approaches adopted for models development and validation. The study presents multilevel models that can account for the correlation among time series data of the same section and to capture the effect of unobserved variables. Study results show that the models fit the data very well. The contribution and significance of relevant influencing factors in predicting roughness progression are presented and explained. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data.

Keywords: roughness progression, empirical model, pavement performance, heavy duty pavement

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Authors: Arezoo Fallahi

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Background and purpose: Non-alcoholic fatty liver is one of the most common liver disorders, which, as the most important cause of death from liver disease, has unpleasant consequences and complications. The aim of this study was to investigate the effect of an educational intervention based on a health belief model to prevent non-alcoholic fatty liver among women. Materials and Methods: This experimental study was performed among 110 women referring to comprehensive health service centers in Malayer City, west of Iran, in 2023. Using the available sampling method, 110 Participants were divided into experimental and control groups. The data collection tool included demographic characteristics and a questionnaire based on the health belief model. In The experimental group, three one-hour training sessions were conducted in the form of pamphlets, lectures and group discussions. Data were analyzed using SPSS software version 21, by correlation tests, paired t-tests independent t-tests. Results: The mean age of participants was 38.07±6.28 years, and Most of the participants were middle-aged, married, housewives with academic education, middle-income and overweight. After the educational intervention, the mean scores of the constructs include perceived sensitivity (p=0.01), perceived severity (p=0.01), perceived benefits (p=0.01), guidance for internal (p=0.01) and external action (p=0.01), and perceived self-efficacy (p=0.01) in the experimental group were significantly higher than the control group. The score of perceived barriers in the experimental group decreased after training. The perceived obstacles score in the test group decreased after the training (15.2 ± 3.9 v.s 11.2 ± 3.3, (p<0.01). Conclusion: The findings of the study showed that the design and implementation of educational programs based on the constructs of the health belief model can be effective in preventing women from developing higher levels of non-alcoholic fatty liver.

Keywords: health, education, believe, behaviour

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Natália Bruno Chaves, Richardes Caúla, Roosevelt do Vale, Daniela Toneti, Rafaela Carvalho, Renata Silva Lopes, Antônio Carlos Júnior, Adner Nobre, Viviane Santiago, Yara Alana Caldato, Estefania Rodriguez Urrego, André Buarque Lemos, Catarina Nucci Stetner, Marcos Mauro Barreto, Stefany Moreira Lima, Mara Cavalcante, Ticiane Ribeiro

Abstract:

The Well Born (Nascer Bem – in Portuguese) Program was created in the Hapvida health network with the aim of improving access to safe and quality prenatal care for users. In addition to offering a line of prenatal care, the inclusion of obstetric nursing and the decentralization of childbirth, bring security that professionals did not indicate the route of delivery for professional convenience. The introduction of the nursing consultation came to reinforce the care to our users, strengthening their bond and reception. In 2021, the program maintained an average of 40% of normal births in the north, northeast and central-west regions of Brazil, an average above that observed in the rest of the country's private health systems, around 20%. In addition, the neonatal hospitalization rate of this population remained around 5.1%, a figure below the national average. With these data, the “Nascer Bem” program is affirmed as a safe and effective strategy for the promotion of safe normal birth.

Keywords: quality, safe, prenatal, obstetric nursing

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Authors: Juliza Hidayati, Sukardi, Ani Suryani, Sugiharto, Anas M. Fauzi

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The idea of making North Sumatera as a barometer of national oil palm industry requires efforts commodities and agro-industry development of oil palm. One effort that can be done is by successful execution plantation revitalization. The plantation Revitalization is an effort to accelerate the development of smallholder plantations, through expansion and replanting by help of palm Estate Company as business partner and bank financed plantation revitalization fund. Business partner agreement obliged and bound to make at least the same smallholder plantation productivity with business partners, so that the refund rate to banks become larger and prosperous people as a plantation owner. Generally low productivity of smallholder plantations under normal potential caused a lot of old and damaged plants with plant material at random. The purpose of revitalizing oil palm plantations is which are to increase their competitiveness through increased farm productivity. The research aims to identify potential criteria in influencing plantation productivity improvement priorities to be observed and followed up in order to improve the competitiveness of destinations and make North Sumatera barometer of national palm oil can be achieved. Research conducted with Analytical Network Process (ANP), to find the effect of dependency relationships between factors or criteria with the knowledge of the experts in order to produce an objective opinion and relevant depict the actual situation.

Keywords: palm barometer, acceleration of plantation development, productivity, revitalization

Procedia PDF Downloads 682