Search results for: collaborative problem solving

Authors: Pascal Alberti, Mustapha Mouloua

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In today’s global market economy, various companies are often confronted with the dynamic and complex nature of current competitive markets. The dynamics of these markets are becoming more and more fluid, often requiring companies to provide competitive, definite advantages, and technological responses within increasingly shorte time frames. To meet these demands, companies must rely on the cognitive abilities of actors of creativity to provide tangible answers to the current contextual problems. Thus, it is important to provide a variety of instruments and design tools to support this particular stage of innovation, and to meet their demand expectations. For a number of years now, we have been extensively conducting experiments on the use of mind maps in the context of innovative projects with collaborative research teams from various nationalities. Our research findings reported a significant difference between a “Word” Mind Map and “Photographic” Mind Map, a correlation between the different uses of iconic tools and certain types of innovation, and a relationship between the different cognitive logics. In this paper, we will present our new results related to the effect of symmetrical presentation of a Photographic Mind Map" on the production of design solutions. Finally, we will conclude by highlighting the importance of our experimental method, and discussing both the theoretical and practical implications of our research.

Keywords: creativity, innovation, management, mind mapping, design product

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Authors: Hailu Kebede Bekele

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Construction delays are suitable where project events occur at a certain time expected due to causes related to the client, consultant, and contractor. Delay is the major cause of the cost overrun that leads to the poor efficiency of the project. The cost difference between completion and the originally estimated is known as cost overrun. The common ways of cost overruns are not simple issues that can be neglected, but more attention should be given to prevent the organization from being devastated to be failed, and financial expenses to be extended. The reasons that may raised in different studies show that the problem may arise in construction projects due to errors in budgeting, lack of favorable weather conditions, inefficient machinery, and the availability of extravagance. The study is focused on the pace of mega projects that can have a significant change in the cost overrun calculation.15 mega projects are identified to study the problem of the cost overrun in the site. The contractor, consultant, and client are the principal stakeholders in the mega projects. 20 people from each sector were selected to participate in the investigation of the current mega construction project. The main objective of the study on the construction cost overrun is to prioritize the major causes of the cost overrun problem. The methodology that was employed in the construction cost overrun is the qualitative methodology that mostly rates the causes of construction project cost overrun. Interviews, open-ended and closed-ended questions group discussions, and rating qualitative methods are the best methodologies to study construction projects overrun. The result shows that design mistakes, lack of labor, payment delay, old equipment and scheduling, weather conditions, lack of skilled labor, payment delays, transportation, inflation, and order variations, market price fluctuation, and people's thoughts and philosophies, the prior cause of the cost overrun that fail the project performance. The institute shall follow the scheduled activities to bring a positive forward in the project life.

Keywords: cost overrun, delay, mega projects, design

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Authors: Giuseppe Timperio, Robert de Souza

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Logistics operations in the context of disaster response are characterized by a high degree of complexity due to the combined effect of a large number of stakeholders involved, time pressure, uncertainties at various levels, massive deployment of goods and personnel, and gigantic financial flow to be managed. It also involves several autonomous parties such as government agencies, militaries, NGOs, UN agencies, private sector to name few, to have a highly collaborative approach especially in the critical phase of the immediate response. This is particularly true in the context of L3 emergencies that are the most severe, large-scale humanitarian crises. Decision-making processes in disaster management are thus extremely difficult due to the presence of multiple decision-makers involved, and the complexity of the tasks being tackled. Hence, in this paper, we look at applying ICT based solutions to enable a speedy and effective decision making in the golden window of humanitarian operations. A high-level view of ICT based solutions in the context of logistics operations for humanitarian response in Southeast Asia is presented, and their viability in a real-life case about logistics network design is explored.

Keywords: decision support, disaster preparedness, humanitarian logistics, network design

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Authors: Chunye Gong, Ming Tie, Jie Liu, Weimin Bao, Xinbiao Gan, Shengguo Li, Bo Yang, Xuguang Chen, Tiaojie Xiao, Yang Sun

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Large-scale CFD simulation relies on high-performance parallel computing, and the load balance is the key role which affects the parallel efficiency. This paper focuses on the load-balancing problem of parallel CFD simulation with structured mesh. A mathematical model for this load-balancing problem is presented. The genetic algorithm, fitness computing, two-level code are designed. Optimal selector, robust operator, and local optimization operator are designed. The properties of the presented genetic algorithm are discussed in-depth. The effects of optimal selector, robust operator, and local optimization operator are proved by experiments. The experimental results of different test sets, DLR-F4, and aircraft design applications show the presented load-balancing algorithm is robust, quickly converged, and is useful in real engineering problems.

Keywords: genetic algorithm, load-balancing algorithm, optimal variation, local optimization

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Authors: D. Dorota

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This paper presents a method to generate and schedule task in the architecture of embedded systems based on the simulated annealing. This method takes into account the attribute of divisibility of tasks. A proposal represents the process in the form of trees. Despite the fact that the architecture of Network-on-Chip (NoC) is an interesting alternative to a bus architecture based on multi-processors systems, it requires a lot of work that ensures the optimization of communication. This paper proposes an effective approach to generate dedicated NoC topology solving communication problems. Network NoC is generated taking into account the energy consumption and resource issues. Ultimately generated is minimal, dedicated NoC topology. The proposed solution is assumed to be a simple router design and the minimum number of lines.

Keywords: Network-on-Chip, NoC-based embedded systems, scheduling task in embedded systems, simulated annealing

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Authors: Luis Rodrigo Valencia Perez, Francisco Flores Aguero, Gibran Aguilar Rangel

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Artificial Intelligence (AI) is rapidly transforming diverse sectors, and higher education in Latin America is no exception. This article explores the impact of AI on higher education institutions in the region, highlighting the imperative need for well-trained teachers in emerging technologies and a cultural shift towards the adoption and efficient use of these tools. AI offers significant opportunities to improve learning personalization, optimize administrative processes, and promote more inclusive and accessible education. However, the effectiveness of its implementation depends largely on the preparation and willingness of teachers to integrate these technologies into their pedagogical practices. Furthermore, it is essential that Latin American countries develop and implement public policies that encourage the adoption of AI in the education sector, thus ensuring that institutions can compete globally. Policies should focus on the continuous training of educators, investment in technological infrastructure, and the creation of regulatory frameworks that promote innovation and the ethical use of AI. Only through a comprehensive and collaborative approach will it be possible to fully harness the potential of AI to transform higher education in Latin America, thereby boosting the region's development and competitiveness on the global stage.

Keywords: artificial intelligence (AI), higher education, teacher training, public policies, latin america, global competitiveness

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Authors: Jason Maffia, Maria D’urso, Robert Crupi, Margaret Cartmell

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The emotional aspects of traumatic events such as workplace violence are often ignored, causing low productivity, disillusionment, and resentment within an organization. As a result, if workplace violence, particularly in healthcare settings, is not adequately addressed, it will become a phenomenon, undermining the peace and stability among the active communities while also posing a risk to the population's health and well-being. This review intends to identify the risk factors and the implications of workplace violence in healthcare settings and highlight the collaborative efforts needed in sustaining control and prevention measures against workplace violence. It is essential that health care organizations are prepared physically and emotionally for traumatic situations. This study explores the theoretical nature of addressing work-related violence in healthcare settings as well as traumatic stress reactivity and the context within which reactions occur and recovery takes place. Cognitive, social, and organizational influences on response are identified and used to tentatively offer explanations for identifying security risks, development, and implementation of de-escalation teams, CISM programs and training staff in violence prevention are among strategies hospitals are employing to keep workers and patients safe. General conclusion regarding the implications for intervention effectiveness and design are discussed.

Keywords: healthcare settings, stress reactions, traumatic events, workplace violence

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Authors: Rizwan Rizwan

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This paper provides an overview of Federated Learning (FL) and its application in enhancing data security, privacy, and efficiency. FL utilizes three distinct architectures to ensure privacy is never compromised. It involves training individual edge devices and aggregating their models on a server without sharing raw data. This approach not only provides secure models without data sharing but also offers a highly efficient privacy--preserving solution with improved security and data access. Also we discusses various frameworks used in FL and its integration with machine learning, deep learning, and data mining. In order to address the challenges of multi--party collaborative modeling scenarios, a brief review FL scheme combined with an adaptive gradient descent strategy and differential privacy mechanism. The adaptive learning rate algorithm adjusts the gradient descent process to avoid issues such as model overfitting and fluctuations, thereby enhancing modeling efficiency and performance in multi-party computation scenarios. Additionally, to cater to ultra-large-scale distributed secure computing, the research introduces a differential privacy mechanism that defends against various background knowledge attacks.

Keywords: federated learning, differential privacy, gradient descent strategy, convergence, stability, threats

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Authors: Yawen Wang, Hongchang Chen, Shaomei Li, Chao Gao, Jiangpeng Zhang

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As the main challenge for target tracking is accounting for target scale change and real-time, we combine Mean-Shift and PCA-SIFT algorithm together to solve the problem. We introduce similarity comparison method to determine how the target scale changes, and taking different strategies according to different situation. For target scale getting larger will cause location error, we employ backward tracking to reduce the error. Mean-Shift algorithm has poor performance when tracking scale-changing target due to the fixed bandwidth of its kernel function. In order to overcome this problem, we introduce PCA-SIFT matching. Through key point matching between target and template, that adjusting the scale of tracking window adaptively can be achieved. Because this algorithm is sensitive to wrong match, we introduce RANSAC to reduce mismatch as far as possible. Furthermore target relocating will trigger when number of match is too small. In addition we take comprehensive consideration about target deformation and error accumulation to put forward a new template update method. Experiments on five image sequences and comparison with 6 kinds of other algorithm demonstrate favorable performance of the proposed tracking algorithm.

Keywords: target tracking, PCA-SIFT, mean-shift, scale-adaptive

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Authors: Alexandru Gridan, Georgeta Ionescu, Ovidiu Ionescu, Ramon Jurj, George Sirbu, Mihai Fedorca

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The Brown Bear population size in Romania is approximately 7300-7600 individuals, which is projected to be 3000 individuals over the ecological carrying capacity. The Habitats Directive imposed certain protection rules on European Union (EU) Member States with Brown Bear populations. These however allow countries like Sweden, Croatia, Slovakia, Estonia to hunting as management tool, harvesting up to 10% of the surplus bear population annually. From the point Romania joined the EU to 2016, active conservation management has contributed to maintaining the highest and most genetically diverse Brown Bear population in Europe. Importantly, there has been good coexistence between people and bears and low levels of human-bear conflict. After social pressure and campaigning by some non-governmental organisations citing issues over monitoring, the environment minister decided in September 2016 to stop the use of hunting as a management tool for bears. Against this background, this paper provides a set of recommendations to resolve the current conflict in Romania. These include the need for collaborative decision-making to reduce conflicts between stakeholders and mechanisms to reduce current human-bear conflicts, which have increased by 50 percent in the past year.

Keywords: bear, bear population, bear management, wildlife conflict

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Authors: Vitalis Okwuchukwu Opara

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The task of nation building primarily consist in welding together, diverse cultural groups into a united nation state, which develops a centripetal political culture that makes its people see themselves as members of one nation linked together by more reliable ties than the coercion offered by the state. Comparatively on the contrary, most countries in the world today are comprised of diverse nationalities, each with its unique set of norms and values, which often come into conflict with others. As such, the task of nation building is in uniting these diverse cultural groups into a united nation state and various human elements that make up its geopolitical zone. The most outstanding impediment to achieving this task is unemployment. Unemployment is like a peril against the nation building. Unemployment is an obstacle for growth of a nation. Often it is said that the wise see obstacles as stepping-stones to advance further. The pangs of unemployment impede nation building such that sometimes it takes very long time to do away with the problem. In recent times, there has been a revolutionary wind blowing across the world. This wind is bound to wake up nations leaders to sit up to their responsibility. Unemployment causes youth restiveness, brings leaders to their knees. It breeds problem. This work is intended to expose the pangs of unemployment and its impending peril to nation building.

Keywords: pangs, unemployment, obstacles, nation-building

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Authors: Burcu Akyildiz, Cigdem Kadaifci, Y. Ilker Topcu, Burc Ulengin

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In today’s business environment, companies should make strategic decisions to gain sustainable competitive advantage. Order selection is a crucial issue among these decisions especially for steel production industry. When the companies allocate a high proportion of their design and production capacities to their ongoing projects, determining which customer order should be chosen among the potential orders without exceeding the remaining capacity is the major critical problem. In this study, it is aimed to identify and prioritize the evaluation factors for the customer order selection problem. Conjoint analysis is used to examine the importance level of each factor which is determined as the potential profit rate per unit of time, the compatibility of potential order with available capacity, the level of potential future order with higher profit, customer credit of future business opportunity, and the negotiability level of production schedule for the order.

Keywords: conjoint analysis, order prioritization, profit management, structural steel firm

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Authors: Mahmoud Samkan

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In this paper, the design and assessment of new coordination between Power System Stabilizers (PSSs) and Static Var Compensator (SVC) in a multimachine power system via statistical method are proposed. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is handled as an optimization problem. The Bacterial Swarming Optimization (BSO), which synergistically couples the Bacterial Foraging (BF) with the Particle Swarm Optimization (PSO), is employed to seek for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is enhanced. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is executed to validate the robustness of coordinated controller versus uncoordinated one.

Keywords: SVC, PSSs, multimachine power system, coordinated design, bacteria swarm optimization, statistical assessment

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Authors: Girish Choudhary

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Education is in a state of flux. Not only one need to acquire skills in order to cope with a fast changing global world, an explosive growth in technology, on the other hand is providing a new wave of teaching tools - computer aided video instruction, hypermedia, multimedia, CD-ROMs, Internet connections, and collaborative software environments. The emerging technology incorporates the group qualities of interactive, classroom-based learning while providing individual students the flexibility to participate in an educational programme at their own time and place. The technology facilitating self learning also seems to provide a cost effective solution to the dilemma of delivering education to masses. Online education is a unique learning domain that provides for many to many communications as well. The computer conferencing software defines the boundaries of the virtual classroom. The changing paradigm provides access of instruction to a large proportion of society, promises a qualitative change in the quality of learning and echoes a new way of thinking in educational theory that promotes active learning and open new learning approaches. Putting it to practice is challenging and may fundamentally alter the nature of educational institutions. The subsequent part of paper addresses such questions viz. 'Do we need to radically re-engineer the curriculum and foster an alternate set of skills in students?' in the onward journey.

Keywords: on-line education, self learning, energy and power engineering, future education

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Authors: Mohammad Reza Esmaili

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After the occurrence of blackouts, the most important subject is how fast the electric service is restored. Power system restoration is an immensely complex issue and there should be a plan to be executed within the shortest time period. This plan has three main stages of black start, network reconfiguration and load restoration. In the black start stage, operators and experts may face several problems, for instance, the unsuccessful connection of the long high-voltage transmission line connected to the electrical source. In this situation, the generator may be tripped because of the unsuitable setting of its line charging mode or high absorbed reactive power. In order to solve this problem, the line charging process is defined as a nonlinear programming problem, and it is optimized by using GAMS software in this paper. The optimized process is performed on a grid that includes a 250 MW hydroelectric unit and a 400 KV transmission system. Simulations and field test results show the effectiveness of optimal planning.

Keywords: power system restoration, black start, line charging mode, nonlinear programming

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Authors: Alaa A. Osman, Amgad M. Bayoumy Aly, Ismail El baialy, Osama E. Abdellatif, Essam E. Khallil

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In this paper, a numerical simulation of a finned store separating from a wing-pylon configuration has been studied and validated. A dynamic unstructured tetrahedral mesh approach is accomplished by using three grid sizes to numerically solving the discretized three dimensional, inviscid and compressible Navier-stokes equations. The method used for computations of separation of an external store assuming quasi-steady flow condition. Computations of quasi-steady flow have been directly coupled to a six degree-of-freedom (6DOF) rigid-body motion code to generate store trajectories. The pressure coefficients at four different angular cuts and time histories of various trajectory parameters during the store separation are compared for every grid size with published experimental data.

Keywords: CFD modelling, transonic store separation, quasi-steady flow, moving-body trajectories

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Authors: Niloufar Ghoreishi, Ali Nekouzadeh

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The stability of the flight during maneuvering and in response to probable perturbations is one of the most essential features of an aircraft that should be analyzed and designed for. In this study, we derived the non-linear governing equations of aircraft dynamics during the climb/descend phase and simulated a model aircraft. The corresponding force and moment dimensionless coefficients of the model and their variations with elevator angle and other relevant aerodynamic parameters were measured experimentally. The short-period mode and phugoid mode response were simulated by solving the governing equations numerically and then compared with the desired stability parameters for the particular level, category, and class of the aircraft model. To meet the target stability, a controller was designed and used. This resulted in significant improvement in the stability parameters of the flight.

Keywords: flight stability, phugoid mode, short period mode, climb phase, damping coefficient

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Authors: Rabia Korkmaz Tan, Şebnem Bora

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The major problem encountered when modeling complex systems with agent-based modeling and simulation techniques is the existence of large parameter spaces. A complex system model cannot be expected to reflect the whole of the real system, but by specifying the most appropriate parameters, the actual system can be represented by the model under certain conditions. When the studies conducted in recent years were reviewed, it has been observed that there are few studies for parameter tuning problem in agent based simulations, and these studies have focused on tuning parameters of a single model. In this study, an approach of parameter tuning is proposed by using metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Firefly (FA) algorithms. With this hybrid structured study, the parameter tuning problems of the models in the different fields were solved. The new approach offered was tested in two different models, and its achievements in different problems were compared. The simulations and the results reveal that this proposed study is better than the existing parameter tuning studies.

Keywords: parameter tuning, agent based modeling and simulation, metaheuristic algorithms, complex systems

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Authors: Wid Kattan, Rahaf Albarraq

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Background: Tokophobia is a pathological fear of pregnancy that can lead to the avoidance of childbirth. It is classified as primary or secondary. This report describes a patient with tokophobia, as well as her presentation, risk factors, comorbidities, and treatment. Case Presentation: A 43-year-old Saudi woman experienced tokophobia upon becoming pregnant for the fifth time. She was assessed in two clinical interviews by a consultant psychiatrist specializing in women’s mental health. In addition, she completed several questionnaires for assessment of different aspects of her mental health: overall depression, perinatal depression, generalized anxiety, maternal functioning, and fear of childbirth (FOC). Several risk factors and comorbidities that may have contributed to the development of tokophobia in this patient were discussed, including traumatic experiences in previous deliveries, the unplanned nature of the pregnancy, perinatal depression, and pronounced symptoms of anxiety. A collaborative decision to perform a C-section was made, in line with obstetric guidelines and good mental health practice. Full symptomatic recovery was achieved immediately after delivery. Conclusions: We hope to increase clinical awareness of the assessment and management of tokophobia, which is a relatively new concept and, as yet, understudied.

Keywords: tokophobia, fear of childbirth, mental health, anxiety, case report, depression, fear of delivery, psychiatry, cesarean section, perinatal depression

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Authors: Lauren B. Birney

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This project focuses upon the expansion of the existing "Curriculum and Community Enterprise for the Restoration of New York Harbor in New York City Public Schools" NSF EHR DRL 1440869, NSF EHR DRL 1839656 and NSF EHR DRL 1759006. This project is recognized locally as “Curriculum and Community Enterprise for Restoration Science,” or CCERS. CCERS is a comprehensive model of ecological restoration-based STEM education for urban public-school students. Following an accelerated rollout, CCERS is now being implemented in 120+ Title 1 funded NYC Department of Education middle schools, led by two cohorts of 250 teachers, serving more than 11,000 students in total. Initial results and baseline data suggest that the CCERS model, with the Billion Oyster Project (BOP) as its local restoration ecology-based STEM curriculum, is having profound impacts on students, teachers, school leaders, and the broader community of CCERS participants and stakeholders. Students and teachers report being receptive to the CCERS model and deeply engaged in the initial phase of curriculum development, citizen science data collection, and student-centered, problem-based STEM learning. The BOP CCERS Digital Platform will serve as the central technology hub for all research, data, data analysis, resources, materials and student data to promote global interactions between communities, Research conducted included qualitative and quantitative data analysis. We continue to work internally on making edits and changes to accommodate a dynamic society. The STEM Collaboratory NYC® at Pace University New York City continues to act as the prime institution for the BOP CCERS project since the project’s inception in 2014. The project continues to strive to provide opportunities in STEM for underrepresented and underserved populations in New York City. The replicable model serves as an opportunity for other entities to create this type of collaboration within their own communities and ignite a community to come together and address the notable issue. Providing opportunities for young students to engage in community initiatives allows for a more cohesive set of stakeholders, ability for young people to network and provide additional resources for those students in need of additional support, resources and structure. The project has planted more than 47 million oysters across 12 acres and 15 reef sites, with the help of more than 8,000 students and 10,000 volunteers. Additional enhancements and features on the BOP CCERS Digital Platform will continue over the next three years through funding provided by the National Science Foundation, NSF DRL EHR 1759006/1839656 Principal Investigator Dr. Lauren Birney, Professor Pace University. Early results from the data indicate that the new version of the Platform is creating traction both nationally and internationally among community stakeholders and constituents. This project continues to focus on new collaborative partners that will support underrepresented students in STEM Education. The advanced Digital Platform will allow for us connect with other countries and networks on a larger Global scale.

Keywords: STEM education, environmental restoration science, technology, citizen science

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Authors: Rui de Abrantes, André Luiz Silva Forcetto

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Air pollution is a big problem in many cities around the world. Brazilian big cities also have this problem, where millions of people are exposed daily to pollutants levels above the recommended by WHO. Brazil has taken several actions to reduce air pollution, among others, controlling the atmospheric emissions from vehicles, non-road mobile machinery, and motorcycles, but on the other side, there are no emissions controls for locomotives, which are exposing the population to tons of pollutants annually. The rail network is not homogeneously distributed in the national territory; it is denser near the big cities, and this way, the population is more exposed to pollutants; apart from that, the government intends to increase the rail network as one of the strategies for greenhouse gas mitigation, complying with the international agreements against the climate changes. This paper initially presents the estimated emissions from locomotive fleets with no emission control and with emission control equivalent to US Tier 3 from 2028 and for the next 20 years. However, we realized that a program equivalent to phase Tier 3 would not be effective, so we proposed a program in two steps that will avoid the release of more than 2.4 million tons of CO and 531,000 tons of hydrocarbons, 3.7 million tons of nitrogen oxides, and 102,000 tons of particulate matter in 20 years.

Keywords: locomotives, emission control, air pollution, pollutants emission

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Authors: Erinetta P. Anjani, Karina Mariz, Rifqi K. Fathianto

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While Islam teaches its’ followers to be mindful of God’s creation, including the environment, Indonesia as one of the world’s largest Muslim country, is now also world’s second-largest plastic waste contributor. The problem of waste is a complicated matter in Indonesia and is worsening because many landfills are now on verge of overcapacity. The causes of this problem are at least due to two things. First is Indonesia’s bad waste management. Second, people’s low of eco-literacy, as can be seen in massive use of non-degradable materials, low rate of waste separation, low rate of recycling and up cycling, whereas households are the largest source of waste in Indonesia. Mostly dealing with patriarchal culture, women in Indonesia play big and important role in their households, from family matter to household management (including waste management), to economic matter. Uniquely, the majority of Muslim women in Indonesia are engaged in -arisan- women social gathering or in -majelis ta’lim- women community in Islamic prayer, which serves as a social mechanism. As many NGOs are working on tackling environmental issues by raising awareness in order for the people to adapt a more environmentally-friendly household management practices, the problem of waste in Indonesia is meeting a bright light. Using qualitative data and descriptive analysis, the following is a proposal for a program intended to spread eco-literacy for waste management to women in Indonesia through their social gathering in order for them to gain awareness and start implementing eco-actions in their households. We attempt Waste4Change, a social company which provides environmentally-friendly waste management services, to reach women with modules that consist of environmental education, trainings, and workshops. We will then monitor and counsel the women to make sure if the lesson is going to be fully applied in their houses. The program will take place nearby University of Indonesia, Depok, West Java.

Keywords: eco-literacy, environmental education, household waste management, Muslim women social gathering, Waste4Change

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Authors: Guenther Schuh, Sebastian Woelk

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Companies face increasing challenges in research due to higher costs and risks. The intensifying technology complexity and interdisciplinarity require unique know-how. Therefore, companies need to decide whether research shall be conducted internally or externally with partners. On the other hand, research institutes meet increasing efforts to achieve good financing and to maintain high research reputation. Therefore, relevant research topics need to be identified and specialization of competency is necessary. However, additional competences for solving interdisciplinary research projects are also often required. Secured financing can be achieved by bonding industry partners as well as public fundings. The realization of faster and better research drives companies and research institutes to cooperate in organized research networks, which are managed by an administrative organization. For an effective and efficient cooperation, necessary processes, roles, tools and a set of rules need to be determined. The goal of this paper is to show the state-of-art research and to propose a governance framework for organized research networks.

Keywords: interorganizational cooperation, design of network governance, research network

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Authors: Khawar Ali

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We present the numerical study of unsteady hydromagnetic (MHD) flow and heat transfer characteristics of a viscous incompressible electrically conducting water-based hybrid metallic nanofluid (containing Cu-Au/ H₂O nanoparticles) between two orthogonally moving porous coaxial disks with suction. Different from the classical shooting methodology, we employ a combination of a direct and an iterative method (SOR with optimal relaxation parameter) for solving the sparse systems of linear algebraic equations arising from the FD discretization of the linearized self similar nonlinear ODEs. Effects of the governing parameters on the flow and heat transfer are discussed and presented through tables and graphs. The findings of the present investigation may be beneficial for the electronic industry in maintaining the electronic components under effectiveand safe operational conditions.

Keywords: heat transfer enhancement, hybrid metallic nanofluid, viscous dissipation and joule heating effect , Two dimensional flow

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Authors: Junling Li, Fang Meng, Yichun Zhang

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Image saliency detection has been long studied, while several challenging problems are still unsolved, such as detecting saliency inaccurately in complex scenes or suppressing salient objects in the image borders. In this paper, we propose a new saliency detection algorithm in order to solving these problems. We represent the image as a graph with superixels as nodes. By considering appearance similarity between the boundary and the background, the proposed method chooses non-saliency boundary nodes as background priors to construct the background probability model. The probability that each node belongs to the model is computed, which measures its similarity with backgrounds. Thus we can calculate saliency by the transformed probability as a metric. We compare our algorithm with ten-state-of-the-art salient detection methods on the public database. Experimental results show that our simple and effective approach can attack those challenging problems that had been baffling in image saliency detection.

Keywords: visual saliency, background probability, boundary knowledge, background priors

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Authors: Jingya Liu, Yue Wu, Jiabin Luo

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This work investigates an intermodal transportation system for delivering goods from a Regional Distribution Centre to supermarkets on the Isle of Wight (IOW) via the port of Southampton or Portsmouth in the UK. We consider this integrated logistics chain as a 3-echelon transportation system. In such a system, there are two types of transport methods used to deliver goods across the Solent Channel: one is accompanied transport, which is used by most supermarkets on the IOW, such as Spar, Lidl and Co-operative food; the other is unaccompanied transport, which is used by Aldi. Five transport scenarios are studied based on different transport modes and ferry routes. The aim is to determine an optimal delivery plan for supermarkets of different business scales on IOW, in order to minimise the total running cost, fuel consumptions and carbon emissions. The problem is modelled as a vehicle routing problem with time windows and solved by genetic algorithm. The computing results suggested that accompanied transport is more cost efficient for small and medium business-scale supermarket chains on IOW, while unaccompanied transport has the potential to improve the efficiency and effectiveness of large business scale supermarket chains.

Keywords: genetic algorithm, intermodal transport system, Isle of Wight, optimization, supermarket

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: R. Rama Kishore, Sunesh

Abstract:

Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.

Keywords: digital watermarking, visual cryptography, histogram, butter worth filter

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Authors: Araba A. Z. Osei-Tutu, Ebenezer Odame, Joseph Bawa, Samuel Amponsah

Abstract:

Education is recognized as a fundamental human right and a catalyst for development. Despite progress in the provision of higher education on the African continent, there persist challenges with the tripartite areas of access, equity and quality. Therefore, this systematic review aimed at providing a comprehensive overview of conversations and voices of scholars on these three concepts in HE in Africa. The systematic review employed a thematic analysis approach, synthesizing findings from 38 selected sources. After a critical analysis of the sources included in the systematic review, deficits in access, quality, and equity were outlined, focusing on infrastructure, regional disparities, and privatization challenges. The review also revealed the weak enforcement of quality assurance measures. Strategies for improvement, proffered by the study, include expanding public sector HE, deregulating the educational sector, promoting open and distance learning, implementing preferential admission policies, and enhancing financial aid. This research contributes valuable insights for policymakers, educators, and stakeholders, fostering a collaborative approach to address challenges and promote holistic development in African higher education.

Keywords: access, equity, quality, higher education, Africa, systematic review, strategies

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Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

Abstract:

The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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