Search results for: unplanned change navigation

Authors: Amin Padash, Mehran Khodaparast, Saadat Khodaparast

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Climate change is a significant and lasting change in the statistical distribution of weather patterns over periods ranging from decades to millions of years. Climate change is caused by factors such as biotic processes, variations in solar radiation received by Earth, plate tectonics, and volcanic eruptions. Certain human activities have also been identified as significant causes of recent climate change, often referred to as “Global Warming”. The ultimate goal of this paper is to determine how climate change affects the style of life and all of our activities. The paper focuses on what the effects of humans are on climate change and how communities can achieve sustainable development and use resources in a way that is good for the ecosystem and public. We opine Climate Change is a vital issue that can be called “Wicked Problem”. This paper attempts to address this wicked problem by COMPRAM Methodology as one of the possible solutions.

Keywords: climate change, COMPRAM, human influences, sustainable development, wicked problems

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Authors: Amjad Abdullah, Amjad Yahya, Bushra Aljohani, Amani Alghamdi

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Change point detection is an important part of data analysis. The presence of a change point refers to a significant change in the behavior of a time series. In this article, we examine the detection of multiple change points of parameters of the exponential Lomax distribution, which is broad and flexible compared with other distributions while fitting data. We used the Schwarz information criterion and binary segmentation to detect multiple change points in publicly available data on the average temperature in the ozone layer. The change points were successfully located.

Keywords: binary segmentation, change point, exponentialLomax distribution, information criterion

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Authors: Thomas E. Portegys

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An animal behavior problem is presented in the form of a nest-building task that involves two cooperating virtual birds, a male and female. The female builds a nest into which she lays an egg. The male's job is to forage in a forest for food for both himself and the female. In addition, the male must fetch stones from a nearby desert for the female to use as nesting material. The task is completed when the nest is built, and an egg is laid in it. A goal-seeking neural network and a recurrent neural network were trained and tested with little success. The goal-seeking network was then enhanced with “place cells”, allowing the birds to spatially navigate the world, building the nest while keeping themselves fed. Place cells are neurons in the hippocampus that map space.

Keywords: artificial animal intelligence, artificial life, goal-seeking neural network, nest-building, place cells, spatial navigation

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Authors: Meltem Ucal

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It is obvious that with limited resources and increasing of energy consumption from day to day, increase in amount of greenhouse gases in the atmosphere will increase risk of climate change. The objective of “Raising Awareness in Energy Efficiency of Household Appliances and Climate Change” paper is to make the connection between climate change and energy saving to be understood. First of all, research and evaluation aiming improvement of women’s behaviors of purchasing and using household appliances and also educate next generations who will be faced risks of climate change, with their mothers will be done.

Keywords: energy efficiency, climate change, wareness, household appliences, econometrics model, logit model

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Authors: Mayank Raj, V. G. Narendra

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Ever since the DARPA challenge on autonomous vehicles in 2005, there has been a lot of buzz about ‘Autonomous Vehicles’ amongst the major tech giants such as Google, Uber, and Tesla. Numerous approaches have been adopted to solve this problem, which can have a long-lasting impact on mankind. In this paper, we have used Deep Learning techniques and TensorFlow framework with the goal of building a neural network model to predict (speed, acceleration, steering angle, and brake) features needed for navigation of autonomous vehicles. The Deep Neural Network has been trained on images and sensor data obtained from the comma.ai dataset. A heatmap was used to check for correlation among the features, and finally, four important features were selected. This was a multivariate regression problem. The final model had five convolutional layers, followed by five dense layers. Finally, the calculated values were tested against the labeled data, where the mean squared error was used as a performance metric.

Keywords: autonomous vehicles, deep learning, computer vision, artificial intelligence

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Authors: Lavanya Ratnabala, Robinroy Peter, E. Y. A. Charles

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This research paper addresses the challenges of exploration and navigation in unknown environments from an evolutionary swarm robotics perspective. Path formation plays a crucial role in enabling cooperative swarm robots to accomplish these tasks. The paper presents a method called the sub-goal-based path formation, which establishes a path between two different locations by exploiting visually connected sub-goals. Simulation experiments conducted in the Argos simulator demonstrate the successful formation of paths in the majority of trials. Furthermore, the paper tackles the problem of inter-collision (traffic) among a large number of robots engaged in path formation, which negatively impacts the performance of the sub-goal-based method. To mitigate this issue, a task allocation strategy is proposed, leveraging local communication protocols and light signal-based communication. The strategy evaluates the distance between points and determines the required number of robots for the path formation task, reducing unwanted exploration and traffic congestion. The performance of the sub-goal-based path formation and task allocation strategy is evaluated by comparing path length, time, and resource reduction against the A* algorithm. The simulation experiments demonstrate promising results, showcasing the scalability, robustness, and fault tolerance characteristics of the proposed approach.

Keywords: swarm, path formation, task allocation, Argos, exploration, navigation, sub-goal

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Authors: Kumar Divyendra

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Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.

Keywords: clustering, deep learning, network backbone, parallel computing

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Authors: Muneeb Banday, Anukriti Dixit

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Change in organizations is viewed as a conversion process of the organizational functioning. One of the crucial elements of this conversion process is the employee resistance to organizational change. The existing literature on change resistance has generally treated resistance as a barrier or an opportunity for successful implementation of change. However, there is little empirical research exploring how resistance to change is managed. This may be partially due to difficulty in getting information on resistance to change. The top management does not divulge such information to avoid negative evaluation whereas employees face huge risk in sharing information related to resistance. The focus of the study is to understand how the organization under study dealt with the employee resistance to change. The conversion process is a story of how the organization went from one stage to another. We used narrative approach to change. Data was collected data through company visits and interviews. The interviews were transcribed, coded, and themes were identified. We focused on the strands that left huge scope for alternative interpretations than the dominant narrative of change prevalent in the organization. The study reveals that the top management strategically uses the legitimacy of leadership, roles of key employees, and rationality of change to manage resistance.

Keywords: employee resistance, legitimacy of leadership, narrative analysis, organisational change

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Authors: D. Thawinkarn, S. Wongbutlee

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The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

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Authors: Kelvin Tang

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As the world is approaching global warming of 1.5°C above pre-industrial levels, more atrocious consequences of climate change are projected to occur in the future. Consequently, it is today’s adolescents who will encounter the grand consequences of climate change. Therefore, nurturing adolescents that are well-informed, emotionally engaged, and motivated to take actions for combating climate change may be pivotal. Climate change education has a role in not only raising awareness, but also promoting behaviour change for climate change mitigation and adaptation. However, what kind of climate change education is suitable for whom? Requiring a learner-centred approach, tailoring climate change education requires a comprehensive understanding of the audience and their preconditions. In Japan, where climate change education has yet to be recognised as a field of environmental education, understanding climate change conceptions possessed by early adolescents is critical for a better design and more impactful implementation of climate change education. This exploratory study aims to investigate climate change conceptions among Japanese early adolescents from the perspective of cognition, affective, and conative dimensions. Questionnaire surveys were conducted targeting 423 students aged 12–14 in three public junior high schools located in Kashiwa City and Oita City. Findings suggest that the majority of Japanese early adolescents belong to groups that exhibit lower levels of cognition, affect, and conation in relation to climate change. The relationships among those dimensions were found to be positive and bidirectional. Moreover, several misconceptions about climate change and the effectiveness of its solutions were identified among the sample.

Keywords: climate change conceptions, climate change education, environmental education, adolescents, three learning dimensions, Japan

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Authors: Tabti Lahouaria, Kahlouche Salem, Benadda Belkacem, Beldjilali Bilal

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The European Geostationary Navigation Overlay Service (EGNOS) provides an augmentation signal to GPS (Global Positioning System) single point positioning. Presently EGNOS provides data correction and integrity information using the GPS L1 (1575.42 MHz) frequency band. The main objective of this system is to provide a better real-time positioning precision than using GPS only. They are expected to be used with single-frequency code observations. EGNOS offers navigation performance for an open service (OS), in terms of precision and availability this performance gradually degrades as moving away from the service area. For accurate system performance, the service will become less and less available as the user moves away from the EGNOS service. The improvement in position solution is investigated using the two collocated dual frequency GPS, where no EGNOS Ranging and Integrity Monitoring Station (RIMS) exists. One of the pseudo-range was kept as GPS stand-alone and the other was corrected by EGNOS to estimate the planimetric and altimetric precision for different dates. It is found that precision in position improved significantly in the second due to EGNOS correction. The performance of EGNOS system in the north of Algeria is also investigated in terms of integrity. The results show that the horizontal protection level (HPL) value is below 18.25 meters (95%) and the vertical protection level (VPL) is below 42.22 meters (95 %). These results represent good integrity information transmitted by EGNOS for APV I service. This service is thus compliant with the aviation requirements for Approaches with Vertical Guidance (APV-I), which is characterised by 40 m HAL (horizontal alarm limit) and 50 m VAL (vertical alarm limit).

Keywords: EGNOS, GPS, positioning, integrity, protection level

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Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

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In a rapidly growing developing country cities are becoming more urbanized leading to modifications in urban climate. Rapid urbanization, especially unplanned urban land expansion, together with climate change has a profound impact on the urban settlement and urban thermal environment. Cities, particularly Pakistan are facing remarkably environmental issues and uneven development, and thus it is important to strengthen the investigation of urban environmental pressure brought by land-use changes and urbanization. The present study investigated the long term modification of the urban environment by urbanization utilizing Spatio-temporal dynamics of land-use change, urban population data, urban heat islands, monthly maximum, and minimum temperature of thirty years, multi remote sensing imageries, and spectral indices such as Normalized Difference Built-up Index and Normalized Difference Vegetation Index. The results indicate rapid growth in an urban built-up area and a reduction in vegetation cover in the last three decades (1990-2020). A positive correlation between urban heat islands and Normalized Difference Built-up Index, whereas a negative correlation between urban heat islands and the Normalized Difference Vegetation Index clearly shows how urbanization is affecting the local environment. The increase in air and land surface temperature temperatures is dangerous to human comfort. Practical approaches, such as increasing the urban green spaces and proper planning of the cities, have been suggested to help prevent further modification of the urban thermal environment by urbanization. The findings of this work are thus important for multi-sectorial use in the cities of Pakistan. By taking into consideration these results, the urban planners, decision-makers, and local government can make different policies to mitigate the urban land use impacts on the urban thermal environment in Pakistan.

Keywords: land use, urban environment, local climate, Lahore

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Authors: Mihai Duguleana, Florin Girbacia, Cristian Postelnicu, Raffaello Brodi, Marcello Carrozzino

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Augmented Reality (AR) has taken a big leap with the introduction of mobile applications which co-locate bi-dimensional (e.g. photo, video, text) and tridimensional information with the location of the user enriching his/her experience. This study presents the advantages of using Mobile Augmented Reality (MAR) technologies in traveling applications, improving cultural heritage exploration. We propose a location-based AR application which combines co-location with the augmented visual information about Pisa monuments to establish a friendly navigation in this historic city. AR was used to render contextual visual information in the outdoor environment. The developed Android-based application offers two different options: it provides the ability to identify the monuments positioned close to the user’s position and it offers location information for getting near the key touristic objectives. We present the process of creating the monuments’ 3D map database and the navigation algorithm.

Keywords: augmented reality, electronic compass, GPS, location-based service

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Authors: Gareth Baxter

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We use a mathematical model of language change to examine two recently observed patterns of language change: one in which most speakers change gradually, following the mean of the community change, and one in which most individuals use predominantly one variant or another, and change rapidly if they change at all. The model is based on Croft’s Utterance Selection account of language change, which views language change as an evolutionary process, in which different variants (different ‘ways of saying the same thing’) compete for usage in a population of speakers. Language change occurs when a new variant replaces an older one as the convention within a given population. The present model extends a previous simpler model to include effects related to speaker aging and interspeaker variation in behaviour. The two patterns of individual change (one more centralized and the other more polarized) were recently observed in historical language changes, and it was further observed that slower changes were more associated with the centralized pattern, while quicker changes were more polarized. Our model suggests that the two patterns of change can be explained by different balances between the preference of speakers to use one variant over another and the degree of accommodation to (propensity to adapt towards) other speakers. The correlation with the rate of change appears naturally in our model, and results from the fact that both differential weighting of variants and the degree of accommodation affect the time for change to occur, while also determining the patterns of change. This work represents part of an ongoing effort to examine phenomena in language change through the use of mathematical models. This offers another way to evaluate qualitative explanations that cannot be practically tested (or cannot be tested at all) in a real-world, large-scale speech community.

Keywords: agent based modeling, cultural evolution, language change, social behavior modeling, social influence

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Authors: Tagore Sai Priya Nunna, Ankhi Banerjee

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The rapid growth of the tourism industry in India in the last few years after the economic crisis in 2009 has been one of the significant causes that led to the Land Use Land Cover change (LULC) of most tourism destinations. The tourist regions are subjected to significant increase in built-up due to increased construction activities for developing accommodation facilities further boosting tourism demand. This research attempts to analyse the changing LULC and the growth pattern of the built-up area within tourist destinations. Four popular tourist destinations, which promises various types of tourism activity and which are significantly dependent on tourism for economic growth, are selected for the study. The study uses remotely sensed data for analysis of land use change through supervised segmentation into five broad classes. Further, the landuse map is reclassified into binary classes to extract the built-up area. The growth patterns of the built-up are analysed in terms of size, shape, direction and form of growth, through a set of spatial metrics. Additionally, a detailed analysis of the existing development pattern corresponding to planned development zones was performed to identify unplanned growth spots in the study regions. The findings of the study provide insights into how tourism has contributed to significant changes in LULC around tourist sites. Also, the study highlights the growth pattern of built-up areas with respect to the type of tourism activity and geographical characteristics. The research attempts to address the need of integrating spatial metrics for the development of sustainable tourism plans as part of the goals of sustainable development.

Keywords: built-up, growth, patterns, tourism, sustainable

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Authors: Andrey Kupriyanov

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In recent years, much attention has been paid to the problems of ionospheric disturbances and their influence on the signals of global navigation satellite systems (GNSS) around the world. This is due to the increase in solar activity, the expansion of the scope of GNSS, the emergence of new satellite systems, the introduction of new frequencies and many others. The influence of the Earth's ionosphere on the propagation of radio signals is an important factor in many applied fields of science and technology. The paper considers the application of the method of transionospheric sounding using measurements from signals from Global Navigation Satellite Systems to determine the TEC distribution and scintillations of the ionospheric layers. To calculate these parameters, the International Reference Ionosphere (IRI) model of the ionosphere, refined in the local area, is used. The organization of operational monitoring of ionospheric parameters is analyzed using several NovAtel GPStation6 base stations. It allows performing primary processing of GNSS measurement data, calculating TEC and fixing scintillation moments, modeling the ionosphere using the obtained data, storing data and performing ionospheric correction in measurements. As a result of the study, it was proved that the use of the transionospheric sounding method for reconstructing the altitude distribution of electron concentration in different altitude range and would provide operational information about the ionosphere, which is necessary for solving a number of practical problems in the field of many applications. Also, the use of multi-frequency multisystem GNSS equipment and special software will allow achieving the specified accuracy and volume of measurements.

Keywords: global navigation satellite systems (GNSS), GPstation6, international reference ionosphere (IRI), ionosphere, scintillations, total electron content (TEC)

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Authors: Yahya N. Alfraidi, Abdel Halim Boussabaine

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Climate change risk impacts are one of the most challenging aspects that faces the built environment now and the near future. The impacts of climate change on buildings are considered in four different dimensions: physical, economic, social, and management. For each of these, the risks are discussed as they arise from various effects linked to climate change, including windstorms, precipitation, temperature change, flooding, and sea-level rise. For example, building assets in cities will be exposed to extreme hot summer days and nights due to the urban heat island effect and pollution. Buildings also could be vulnerable to water, electricity, gas, etc., scarcity. Building materials, fabric and systems could also be stressed by the emerging climate risks. More impotently the building users might experience extreme internal and extern comfort conditions leading to lower productivity, wellbeing and health problems. Thus, the main aim of this paper to document the emerging risks from climate change on building assets. An in-depth discussion on the consequences of these climate change risk is provided. It is expected that the outcome of this research will be a set of risk design indicators for developing and procuring resilient building assets.

Keywords: climate change, risks of climate change, risks on building from climate change, buildings

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Authors: Raman Kumar Singh

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Urbanization and economic growth are considered to be the most striking features of the past century. There is currently a radical demographic shift in progress worldwide, wherein people are moving from rural to urban areas at an increasing rate. The UN-Habitat report 2005 indicates that in 2025, 61 per cent of the 5 billion world population will reside in the urban areas with about 85 per cent of the development process taking place in the urban hinterlands widely referred to as ‘peri-urban’, ‘suburbs’, ‘urban fringe’, ‘city edge’, ‘metropolitan shadow’, or ‘urban sprawl’. In this context the study is broadly concerned with understanding the development of the industrial hub in the Gurgaon and its impact on the immediate neighbourhood. However studies have revealed that with the increase of industrial development the growth pattern changes rapidly, not only the growth of the urban area but the overall economy shifts from more agrarian to non-agrarian, with the change in the occupational pattern of the people. The process is mainly known as tertiarization, where a number of tertiary activities increase in comparison to primary or secondary. The change in the occupational pattern creates a pull factor on its immediate neighbourhood, which triggers the in- migrations from the rural areas as people come in the core urban area in search of the better job opportunities and increased standards of living. But this gives way to the unplanned growth of the urban fringe and the villages which tend to accommodate the migrants and in turn the pressure on the socio-economic infrastructure increases. Therefore, it becomes increasing necessary for the government institution and policy level intervention to provide an overall socio-economic growth along with rapid industrial growth.

Keywords: policy intervention, urban morphology, urban industrial hub, livelihood transformation

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Authors: Dewan Ali Ahsan

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Hilsa (Tenualosa ilisha) is one of the most important anadromous fish species of the trans-boundary ecosystem of Bangladesh, India and Myanmar. Hilsa is not only an economically important species specially for Bangladesh and India, but also for the integral part of the culture of the Bangladesh and India. This flag-ship species in Bangladesh contributed alone of 10.82% of the total fish production of the country and about 75% of world’s total catch of hilsa comes from Bangladesh alone. As hilsa is an anadromous fish, it migrates from the Bay of Bengal to rivers for spawning, nursing and growing and for all of these purposes hilsa needs freshwaters. Ripe broods prefer turbid, fast flowing freshwater for spawning but young prefer clear and slow flowing freshwater. Climate change (salinity intrusion, sea level rise, temperature rise, impact of fresh water flow), unplanned developmental activities and other anthropogenic activities all together are severely damaging the hilsa stock and its habitats. So, climate change and human interferences are predicted to have a range of direct and indirect impacts on marine and freshwater hilsa fishery, with implications for fisheries-dependent economies, coastal communities and fisherfolk. The present study identified that salinity intrusion, siltation in river bed, decrease water flow from upstream, fragmentation of river in dry season, over exploitation, use of small mesh nets are the major reasons to affect the upstream migration of hilsa and its sustainable management. It has been also noticed that Bangladesh government has taken some actions for hilsa management. Government is trying to increase hilsa production not only by conserving jatka (juvenile hilsa) but also protecting the brood hilsa during the breeding seasons by imposing seasonal ban on fishing, restricted mesh size etc. Unfortunately, no such management plans are available for Indian and Myanmar territory. As hilsa is a highly migratory trans-boundary fish in the Bay of Bengal (and all of these countries share the same stock), it is essential to adopt a joint management policy (by Bangladesh-India-Myanmar) for the sustainable management for the hilsa stock.

Keywords: hilsa, climate change, south-east Asia, fishery management

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Authors: Resul Fikir

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Unmanned Aircraft Systems (UAS) become indispensable parts of modern airpower as force multiplier .One of the main advantages of UAS is long endurance. UAS have to take extra payloads to accomplish different missions but these payloads decrease endurance of aircraft because of increasing drug. There are continuing researches to increase the capability of UAS. There are some vertical thermal air currents, which can cause climb and increase endurance, in nature. Birds and gliders use thermals to gain altitude with no effort. UAS have wide wing which can use of thermals like birds and gliders. Thermal regions, which is area of 2-3 NM, exist all around the world. It is free and clean source. This study analyses if thermal regions can be adopted and implemented as an assistant tool for UAS route planning. First and second part of study will contain information about the thermal regions and current applications about UAS in aviation and climbing performance with a real example. Continuing parts will analyze the contribution of thermal regions to UAS endurance. Contribution is important because planning declaration of UAS navigation rules will be in 2015.

Keywords: unmanned aircraft systems, Air4All, thermals, gliders

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Authors: Ehsan Eshtehardian, Saeed Khodaverdi

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This paper surveys the studies on construction change and reveals some of the potential future works. A full-scale investigation of change literature, including change definitions, types, causes and effects, and change management systems, is accomplished to explore some of the coming change trends. It is tried to pick up the critical works in each section to deduct a true timeline of construction changes. The findings show that leaping from best practice guides in late 1990s and generic process models in the early 2000s to very advanced modeling environments in the mid-2000s and the early 2010s have made gaps along with opportunities for change researchers in order to develop some more easy and applicable models. Another finding is that there is a compelling similarity between the change and risk prediction models. Therefore, integrating these two concepts, specifically from proactive management point of view, may lead to a synergy and help project teams avoid rework. Also, the findings show that exploitation of cause-effect relationship models, in order to facilitate the dispute resolutions, seems to be an interesting field for future works.

Keywords: construction change, change management systems, dispute resolutions, change literature

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Zhan Fengmei Yao, Hui Li, Jiahua Zhang

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The Northeast China (NEC) was the most important agriculture areas and known as the Golden-Maize-Belt. Based on observed crop data and crop model, we design four simulating experiments and separate relative impacts and contribution under climate change, planting date shift, and varieties change as well change of varieties and planting date. Without planting date and varieties change, maize yields had no significant change trend at Hailun station located in the north of NEC, and presented significant decrease by 0.2-0.4 t/10a at two stations, which located in the middle and the south of NEC. With planting date change, yields showed a significant increase by 0.09 - 0.47 t/10a. With varieties change, maize yields had significant increase by 1.8~ 1.9 t/10a at Hailun and Huadian stations, but a non-significant and low increase by 0.2t /10a at Benxi located in the south of NEC. With change of varieties and planting date, yields presented a significant increasing by 0.53-2.0 t/10a. Their contribution to yields was -25% ~ -55% for climate change, 15% ~ 35% for planting date change, and 20% ~110% for varieties change as well 30% ~135% for varieties with planting date shift. It found that change in varieties and planting date were highest yields and were responsible for significant increases in maize yields, varieties was secondly, and planting date was thirdly. It found that adaptation in varieties and planting date greatly improved maize yields, and increased yields annual variability. The increase of contribution with planting date and varieties change in 2000s was lower than in 1990s. Yields with the varieties change and yields with planting date and varieties change all showed a decreasing trend at Huadian and Benxi since 2002 or so. It indicated that maize yields increasing trend stagnated in the middle and south of NEC, and continued in the north of NEC.

Keywords: climate change, maize yields, varieties, planting date, impacts

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Authors: Thomas Lauer

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The paper aims to give an overview of change management research by using bibliometric methodology. Based on research papers of the last decade, which are listed on Research Gate, a multidimensional categorization is done. Considering categories like topic (e.g., success factors), industry, or research methodology, the development of the discipline is traced and, in a second step, confronted with external developments of the business environment, such as climate change, gen Z or COVID, to name a few. Based on these findings, a final evaluation concerning the thematical fit of previous research topics is also made, as well as a preview of likely future trends in change management sciences.

Keywords: change management, bibliometrics, scientific trends, research topics

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Authors: Tony Mann

Abstract:

This paper sets out the case for involving and engaging employees/workers/stakeholders/staff in any significant change that is being considered by the senior executives of the organization. It establishes the rationale, the approach, the methodology of engagement and the benefits of a participative approach. It challenges the new norm of imposing change for fear of resistance and instead suggests that involving people has better outcomes and a longer-lasting impact. Various strategic models are introduced and illustrated to explain how the process can be most effective. The paper highlights one model in particular (the Process Iceberg® Organizational Change model) that has proven to be instrumental in developing effective change. Its use is demonstrated in its various forms and explains why so much change fails to address the key elements and how we can be more productive in managing change. ‘Participation’ in change is too often seen as negative, expensive and unwieldy. The paper aims to show that another model: UIA=O+E, can offset the difficulties and, in fact, produce much more positive and effective change.

Keywords: facilitation, stakeholders, buy-in, digital workshops

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Authors: Peter Sauer, Thomas Hinze, Petra Hofstedt

Abstract:

To avoid obstacles in the surrounding environment and to navigate to a given target belong to the most important tasks for mobile robots. According to these tasks different data structures are suitable. To avoid near obstacles, occupancy grid maps are an ideal representation of the surroundings. For less fine grained tasks, such as navigating from one room to another in an apartment, pure grid maps are inappropriate. Grid maps are very detailed, calculating paths to navigate between rooms based on grid maps would take too long. Instead, graph-based data structures, so-called topologies, turn out to be a proper choice for such tasks. In this paper we present two methods to dynamically create topologies from grid maps. Both methods are based on non-uniform grid maps. The topologies are generated on-the-fly and can easily be modified to represent changes in the environment. This allows a hybrid approach to control mobile robots, where, depending on the situation and the current task, either the grid map or the generated topology may be used.

Keywords: robot navigation, occupancy grids, topological maps, dynamic map creation

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Authors: Krishna Prasad Regmi, Jun-Bo Tu, Cheng-Qun Hou, Li-Feng Li

Abstract:

Maxillofacial trauma in a pediatric group of patients is particularly challenging, as these patients have significant differences from adults as far as the facial skeleton is concerned. Mandibular condylar fractures are common presentations to hospitals across the globe and remain the most important cause of temporomandibular joint (TMJ) ankylosis. The etiology and epidemiology of pediatric trauma involving the diacapitular condylar fractures (DFs) have been reported in a large series of patients. Nevertheless, little is known about treatment protocols for DFs in children. Accordingly, the treatment modalities for the management of pediatric fractures also differ. We suggest following the PDA and intracapsular ABC classification of condylar fracture to increase the overall postoperative satisfaction level that bypasses the change of subjective feelings of patients’ from preoperative to the postoperative condition. At the same time, use of 3-D technology and surgical navigation may also increase treatment accuracy.

Keywords: maxillofacial trauma, diacapitular fracture, condylar fracture, PDA classification

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Authors: Benjamin Anabaraonye

Abstract:

Our environment is our entitlement, and it is our duty to guard it for the safety of our society. It is, therefore, in our best interest to explore the necessary tools required to tackle the issues of environmental pollution which are major causes of climate change. Poetry has been discovered through our study as a valuable tool for tackling climate change and environmental pollution. This study explores the science of poetry and how important it is for scientists and engineers to develop their creativity to obtain relevant skills needed to tackle these global challenges. Poetry has been discovered as a great tool for climate change education which in turn brings about climate change adaptation and mitigation. This paper is, therefore, a clarion and urgent call for us to rise to our responsibility for a sustainable future.

Keywords: climate change, education, environment, poetry

Procedia PDF Downloads 176

Authors: Osman Yildiz

Abstract:

As it is predicted 2559 years before there is nothing permanent except change. In our turbulent World, Organizations will always be faced with the challenge of determining the path that will always keep them on balance en route that will bring success. That means from top to bottom, every organisation is exposed to fight to stay afloat and compete while they face the continuous prospect of change in an increasingly competitive and globalized World. Otherwise, they would fail to realize their goals and targets, and ultimately would disappear. But the organizations that will celebrate success five or ten years from now will be the winners of the fight by having recognizing that planning the change was only the first step in the journey and put sufficient efforts into the task of leading change. Increasingly unpredictable and competitive organizational environments have put pressure on leaders across all industries to better manage the change. The key of establishing effective change and transformation in organisations lies on the steps taken before the change happens depending to the quality of the human sources; readiness for change, acknowledgement by management, prepared leaders, motivated employees, overcoming the resistance to change and ultimately adapting change into the organization. Due to these factors, leaders managing the organisational development can ensure organizations and employees to meet new performance targets, motivation and skills rapidly and effectively. Finally, this article will provide some tools for leaders, and discuss how to catch organisational development and manage the innovations in effective ways.

Keywords: managing the change, organizational change, human factor, leaders, globalization, organisational development

Procedia PDF Downloads 250

Authors: Mbadiwe S. Benyeogor, Oladayo O. Olakanmi, Kosisochukwu P. Nnoli, Olusegun I. Lawal, Eric JJ. Gratton

Abstract:

For a robot or any vehicular system to navigate in off-road terrain, its driving mechanisms and the electro-software system must be capable of generating, controlling, and moderating sufficient mechanical power with precision. This paper proposes an autonomous robot with a gyro-stabilized active suspension system in form of a hybrid quadrupedal wheel drive mechanism. This system is to serve as a miniature model for demonstrating how off-road vehicles can be robotized into efficient terramechanical mobile platforms that are capable of self-balanced autonomous navigation and maneuvering on rough and uneven topographies. Results from tests and analysis show that the developed system performs as expected. Therefore, our model and control devices can be adapted to computerizing, automating, and upgrading the operation of unmanned ground vehicles for off-road navigation.

Keywords: active suspension, autonomous robots, edge computing, navigational sensors, terramechanics

Procedia PDF Downloads 122