Search results for: agricultural autonomous terrestrial robot

Authors: Jesús M. Martín, Francisco Corona, Dolores Hidalgo

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Landfills present long-term threats to soil, air, groundwater and surface water due to the formation of greenhouse gases (methane gas and carbon dioxide) and leachate from decomposing garbage. The composition of leachate differs from site to site and also within the landfill. The leachates alter with time (from weeks to years) since the landfilled waste is biologically highly active and their composition varies. Mainly, the composition of the leachate depends on factors such as characteristics of the waste, the moisture content, climatic conditions, degree of compaction and the age of the landfill. Therefore, the leachate composition cannot be generalized and the traditional treatment models should be adapted in each case. Although leachate composition is highly variable, what different leachates have in common is hazardous constituents and their potential eco-toxicological effects on human health and on terrestrial ecosystems. Since leachate has distinct compositions, each landfill or dumping site would represent a different type of risk on its environment. Nevertheless, leachates consist always of high organic concentration, conductivity, heavy metals and ammonia nitrogen. Leachate could affect the current and future quality of water bodies due to uncontrolled infiltrations. Therefore, control and treatment of leachate is one of the biggest issues in urban solid waste treatment plants and landfills design and management. This work presents a treatment model that will be carried out "in-situ" using a cost-effective novel technology that combines solar evaporation/condensation plus forward osmosis. The plant is powered by renewable energies (solar energy, biomass and residual heat), which will minimize the carbon footprint of the process. The final effluent quality is very high, allowing reuse (preferred) or discharge into watercourses. In the particular case of this work, the final effluents will be reused for cleaning and gardening purposes. A minority semi-solid residual stream is also generated in the process. Due to its special composition (rich in metals and inorganic elements), this stream will be valorized in ceramic industries to improve the final products characteristics.

Keywords: forward osmosis, landfills, leachate valorization, solar evaporation

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Authors: Seyed Abdolreza Mosavi, Alireza Babakhan, Elham Sadat Hoseinifard

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Knowledge-based firms need to design mechanisms for continuous absorptive and creation of knowledge in order to ensure their survival in the competitive arena and to follow the path of development. Considering the project-oriented nature of product development activities in knowledge-based firms on the one hand and the importance of analyzing the factors affecting knowledge absorptive capacity in these firms on the other, the purpose of this study is to identify and classify the factors affecting project management practices on absorptive knowledge capacity. For this purpose, we have studied and reviewed the theoretical literature in the field of project management and absorptive knowledge capacity so as to clarify its dimensions and indexes. Then, using the ISM method, the relationship between them has been studied. To collect data, 21 questionnaires were distributed in project-oriented knowledge-based companies. The results of the ISM method analysis provide a model for the relationship between project management activities and knowledge absorptive capacity, which includes knowledge acquisition capacity, scope management, time management, cost management, quality management, human resource management, communications management, procurement management, risk management, stakeholders management and integration management. Having conducted the MICMAC analysis, we divided the variables into three groups of independent, relational and dependent variables and came up with no variables to be included in the group of autonomous variables.

Keywords: knowledge absorptive capacity, project management practices, knowledge-based firms, interpretive structural modeling

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Authors: Vangelis Papadimitropoulos

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The paper is part of the research project “Techno-Social Innovation in the Collaborative Economy'', funded by the Hellenic Foundation of Research and Innovation for the years 2022-2024. The research project examines the normative and empirical conditions of grassroots technologically driven innovation, potentially enabling the transition towards a commons-oriented post-capitalist economy. The project carries out a conceptually led and empirically grounded multi-case study of the digital commons, open-source technologies, platform cooperatives, open cooperatives and Distributed Autonomous Organizations (DAOs) on the Blockchain. The methodological scope of research is interdisciplinary inasmuch as it comprises political theory, economics, sustainability science and computer science, among others. The research draws specifically on Michel Bauwens and Vasilis Kostakis' model of open cooperativism between the commons, ethical market entities and a partner state. Bauwens and Kostakis advocate for a commons-based counter-hegemonic post-capitalist transition beyond and against neoliberalism. The research further employs Laclau and Mouffe's discourse theory of hegemony to introduce a post-hegemonic conceptualization of the model of open cooperativism. Thus, the paper aims to outline the theoretical contribution of the research project to contemporary political theory debates on post-capitalism and the collaborative economy.

Keywords: open cooperativism, techno-social innovation, post-hegemony, post-capitalism

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Authors: M. Hadavi, Z. Hashemi

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Learning strategies play an important role in the development of language skills. Vocabulary learning strategies as the backbone of these strategies have become a major part of English language teaching. This study is a comparative analysis of Vocabulary Learning Strategies (VLS) use and preference among freshmen and senior EFL medical sciences students with different fields of study. 449 students (236 freshman and 213 seniors) participated in the study. 64.6% were female and 35.4% were male. The instrument utilized in this research was a questionnaire consisting of 41 items related to the students’ approach to vocabulary learning. The items were classified under eight sections as dictionary strategies, guessing strategies, study preferences, memory strategies, autonomy, note- taking strategies, selective attention, and social strategies. The participants were asked to answer each item with a 5-point Likert-style frequency scale as follows:1) I never or almost never do this, 2) I don’t usually do this, 3) I sometimes do this, 4) I usually do this, and 5)I always or almost always do this. The results indicated that freshmen students and particularly surgical technology students used more strategies compared to the seniors. Overall guessing and dictionary strategies were the most frequently used strategies among all the learners (p=0/000). The mean and standard deviation of using VLS in the students who had no previous history of participating in the private English language classes was less than the students who had attended these type of classes (p=0/000). Female students tended to use social and study preference strategies whereas male students used mostly guessing and dictionary strategies. It can be concluded that the senior students under instruction from the university have learned to rely on themselves and choose the autonomous strategies more, while freshmen students use more strategies that are related to the study preferences.

Keywords: vocabulary leaning strategies, medical sciences, students, linguistics

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Authors: Mokhtar Nikgoo

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Definition of dam: A dam is one of the most important and widely used engineering structures, which means stopping or changing the course of water on a river. A lake is formed behind the dam, which is called (reservoir). Water is stored in the tank to be used when needed. The dam building industry is a great service to mankind in the use of water and land resources. If they build the dam in a suitable place, they will prevent floods. The water that collects behind the dam and in the dam's lake and reservoir is a valuable reserve for drinking by people and animals. Dry agricultural lands are also irrigated with this water. In addition, in many dams, the pressure caused by the water fall is directed by turbines, and the turbines move the power generation devices and provide power from electricity

Keywords: dam, shaft, gallery, spillway, power plant

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Authors: S. Schröder, P. Ennen, T. Langer, S. Müller, M. Shehadeh, M. Haberstroh, F. Hees

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Since a bit over a year ago, Festo AG and Co. KG, Festo Didactic SE, robomotion GmbH, the researchers of the Cybernetics-Lab IMA/ZLW and IfU, as well as the Human-Computer Interaction Center at the RWTH Aachen University, have been working together in the focal point of assembly competences to realize different scenarios in the field of human-machine interaction (HMI). In the framework of project ARIZ, questions concerning the future of production within the fourth industrial revolution are dealt with. There are many perspectives of human-robot collaboration that consist Industry 4.0 on an individual, organization and enterprise level, and these will be addressed in ARIZ. The aim of the ARIZ projects is to link AI-Approaches to assembly problems and to implement them as prototypes in demonstrators. To do so, island and flow based production scenarios will be simulated and realized as prototypes. These prototypes will serve as applications of flexible robotics as well as AI-based planning and control of production process. Using the demonstrators, human interaction strategies will be examined with an information system on one hand, and a robotic system on the other. During the tests, prototypes of workspaces that illustrate prospective production work forms will be represented. The human being will remain a central element in future productions and will increasingly be in charge of managerial tasks. Questions thus arise within the overall perspective, primarily concerning the role of humans within these technological revolutions, as well as their ability to act and design respectively to the acceptance of such systems. Roles, such as the 'Trainer' of intelligent systems may become a possibility in such assembly scenarios.

Keywords: human-machine interaction, information technology, island based production, assembly competences

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Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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Authors: Masahiro Miyaji

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When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

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The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS

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Authors: Bilge Aydın Er, Yuksel Ardalı

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In Ayvacık village, 80-90% of the population is engaged in agriculture. The pollution was adversely affecting the properties of agricultural origin of the lake. This study is to determine pollution caused by unwanted changes in the Suat Ugurlu Dam Lake has been launched to monitor. Yesilirmak basin is located in the proximal part of the Black Sea. Therefore it was exposed to impact many pollution. In this study, sediment samples from selected points along the lake was made on the analysis. This work was supported by the results of water analyzes. It is clear that urgent measures should be taken to the area of water management

Keywords: eutrophication, Black sea, lake, pollution

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Authors: Md Mizanur Rahman, Lotanna Micah Nneji, Adeola C. Adeniyi, Edem Archibong Eniang, Abiodun B. Onadeko, Felista Kasyoka Kilunda, Babatunde E. Adedeji, Ifeanyi C. Nneji, Adiaha A. A. Ugwumba, Jie-Qiong Jin, Min-Sheng Peng, Caroline Olory, Nsikan Eninekit, Jing Che

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Nigeria contains a number of forest habitats that believed to host highly rich amphibian diversity. However, a dearth of herpetological studies has restricted information on the amphibian diversity in Nigeria. To cover the gap of knowledge, this study focused field surveys on relatively less studied forests–Afi Forest Reserve and Ikpan forest ecosystem. The goal of this study is to make a checklist and to investigate the habitat preferences of amphibians in these two forests. The study areas were surveyed between August 2018 and July 2019 following visual and acoustic methods. Individuals were identified using the morphological and molecular (16S ribosomal RNA) approach. Literature searches were conducted to document additional species that were not encountered during the current field surveys. Using the observational records and arrays of diversity indices, the patterns of species richness and abundance across habitat types were evaluated. Voucher specimens and tissue samples were deposited in the museums of the Department of Zoology, University of Ibadan Nigeria, and the remainder at the Kunming Institute of Zoology (KIZ), Chinese Academy of Sciences, Kunming, China. The result of this study revealed the presence of 30 and 31 amphibian species from the Afi Forest Reserve and the Ikpan Forest Ecosystem, respectively. There were two unidentified species from AFR and one from IFE. In total, 324 individuals of amphibian species were observed from the two study areas. Forest and swamps showed high species diversity and richness than the agricultural field and savannah. Savannah and agricultural fields had the highest similarity in the species composition. Given the increased human disturbances and consequent threats to these forests, this study offers recommendations for the initiation of conservation plans immediately.

Keywords: biodiversity, conservation, cryptic species, ecology, integrated taxonomy, species inventory

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Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

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This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

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Authors: Shreya Srivastava, Sushovan Ghosh, Sagnik Dey

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Aerosols directly affect Earth’s radiation budget by scattering and absorbing incoming solar radiation and outgoing terrestrial radiation. While the uncertainty in aerosol radiative forcing (ARF) has decreased over the years, it is still higher than that of greenhouse gas forcing, particularly in the South Asian region, due to high heterogeneity in their chemical properties. Understanding the Spatio-temporal heterogeneity of aerosol composition is critical in improving climate prediction. Studies using satellite data, in-situ and aircraft measurements, and models have investigated the Spatio-temporal variability of aerosol characteristics. In this study, we have taken aerosol data from Multi-angle Imaging Spectro-Radiometer (MISR) level-2 version 23 aerosol products retrieved at 4.4 km and radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 21 years (2000-2021) over the Indian subcontinent. MISR aerosol product includes size and shapes segregated aerosol optical depth (AOD), Angstrom exponent (AE), and single scattering albedo (SSA). Additionally, 74 aerosol mixtures are included in version 23 data that is used for aerosol speciation. We have seasonally mapped aerosol optical and microphysical properties from MISR for India at quarter degrees resolution. Results show strong Spatio-temporal variability, with a constant higher value of AOD for the Indo-Gangetic Plain (IGP). The contribution of small-size particles is higher throughout the year, spatially during winter months. SSA is found to be overestimated where absorbing particles are present. The climatological map of short wave (SW) ARF at the top of the atmosphere (TOA) shows a strong cooling except in only a few places (values ranging from +2.5o to -22.5o). Cooling due to aerosols is higher in the absence of clouds. Higher negative values of ARF are found over the IGP region, given the high aerosol concentration above the region. Surface ARF values are everywhere negative for our study domain, with higher values in clear conditions. The results strongly correlate with AOD from MISR and ARF from CERES.

Keywords: aerosol Radiative forcing (ARF), aerosol composition, single scattering albedo (SSA), CERES

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Authors: Wonder Ngezimana, Benjamin Alex Madzivire

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As new public universities are being applauded for being promulgated in Zimbabwe, there is need for comprehensive plan for ensuring sustainable competitive advantages in their niche mandated areas. Unhealthy competition between university faculties for enrolment hinders growth of the newly established universities faculties, especially in the agricultural sciences related disciplines. Blue ocean metaphor is based on creation of competitor-free market unlike 'red oceans', which are well explored and crowded with competitors. This study seeks to explore the potential contribution of blue oceans strategy (BOS) for growth of universities with bias towards faculties of agriculture in public universities in Zimbabwe. Case studies with agricultural sciences related disciplines were selected across three universities for interviewing. Data was collected through 10 open ended questions on academics in different management positions within university faculties of agriculture. Summative analysis was thereafter used during coding and interpretation of the data. Study findings show that there are several important elements for making offerings more comprehendible towards fostering faculty growth and performance with bias towards student enrolment. The results points towards BOS form of value innovations with various elements to consider in faculty offerings. To create valued innovation beyond the red oceans, the cases in this study have to be modelled to foster changes in enrolment, modes of delivery, certification, being research oriented with excellence in teaching, ethics, service to the community and entrepreneurship. There is, therefore, need to rethink strategy towards reshaping inclusive enrolment, industry relevance, affiliations, lifelong learning, sustainable student welfare, ubuntu, exchange programmes, research excellence, alumni support and entrepreneurship. Innovative strategic collaborations and partnerships, anchored on technology boost the strategic offerings henceforth leveraging on various offerings in this study. Areas of further study include the amplitude of blue oceans shown in the university faculty offerings and implementation strategies of BOS.

Keywords: blue oceans strategy, collaborations, faculty offerings, value innovations

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Authors: P. M. Naushad Ali

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India’s strength in basic research is recognized internationally. Science and Technology research in India has been performed by six distinct bodies or organizations such as Cooperative Research Associations, Autonomous Research Council, Institute under Ministries, Industrial R&D Establishment, Universities, Private Institutions. All most all these institutions are having a well-established library/information center to cater the information needs of their users like scientists and technologists. Information Management (IM) comprises disciplines concerned with the study and the effective and efficient management of information and resources, products and services as well as the understanding of the involved technologies and the people engaged in this activity. It is also observed that the libraries and information centers in India are also using modern technologies for the management of various activities and services to serve their users in a better way. Science and Technology libraries in the country are usually better equipped because the investment in Science and Technology in the country are much larger than those in other fields. Thus, most of the Science and Technology libraries are equipped with modern IT-based tools for handling and management of library services. In spite of these facts Science and Technology libraries are having all the characteristics of a model organization where computer application is found most successful, however, the adoption of this IT based management tool is not uniform in these libraries. The present study will help to know about the level use of IT-based management tools for the information management of Science and Technology libraries in India. The questionnaire, interview, observation and document review techniques have been used in data collection. Finally, the author discusses findings of the study and put forward some suggestions to improve the quality of Science and Technology institute library services in India.

Keywords: information management, science and technology libraries, India, IT-based tools

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Authors: Savannah Rugg, Carlo Moreno, Pushpa Soti, Alexis Racelis

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Situated in deep South Texas, the Lower Rio Grande Valley (LRGV) is considered one the most productive agricultural regions in the southern US. With the highest concentration of organic farms in the state (Hidalgo county), the LRGV has a strong potential to be leaders in sustainable agriculture. Finding management practices that comply with organic certification and increase the health of the agroecosytem and the farmers working the land is increasingly pertinent. Cover cropping, or the intentional planting of non-cash crop vegetation, can serve multiple functions in an agroecosystem by decreasing environmental pollutants that originate from the agroecosystem, reducing inputs needed for crop production, and potentially decreasing on-farm costs for farmers—overall increasing the sustainability of the farm. Use of cover crops on otherwise fallow lands have shown to enhance ecosystem services such as: attracting native beneficial insects (pollinators), increase nutrient availability in topsoil, prevent nutrient leaching, increase soil organic matter, and reduces soil erosion. In this study, four cover crops (Lablab, Sudan Grass, Sunn Hemp, and Pearl Millet) were analyzed in the subtropical region of south Texas to see how their multiple functions enhance ecosystem services. The four cover crops were assessed to see their potential to harbor native insects, their potential to increase soil nitrogen, to increase soil organic matter, and to suppress weeds. The preliminary results suggest that these subtropical varieties of cover crops have potential to enhance ecosystem services on agricultural land in the RGV by increasing soil organic matter (in all varieties), increasing nitrogen in topsoil (Lablab, Sunn Hemp), and reducing weeds (Sudan Grass).

Keywords: cover crops, ecosystem services, subtropical agriculture, sustainable agriculture

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Authors: Ayhan Varol, Aysenur Ugurlu

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Due to the depletion of fossil fuels and climate change, there is a rising interest in renewable energy sources. In this concept, a wide range of biomass (energy crops, animal manure, solid wastes, etc.) are used for energy production. There has been a growing interest in biomethane production from biomass. Biomethane production from organic wastes is a promising alternative for waste management by providing organic matter stabilization. Anaerobic digestion of organic material produces biogas, and organic substrate is degraded into a more stable material. Therefore, anaerobic digestion technology helps reduction of carbon emissions and produces renewable energy. The hydraulic retention time (HRT) and organic loading rate (OLR), as well as TS (VS) loadings, influences the anaerobic digestion of organic wastes significantly. The optimum range for HRT varies between 15 days to 30 days, whereas OLR differs between 0.5 to 5 g/L.d depending on the substrate type and its lipid, protein and carbohydrate contents. The organic wastes have biogas production potential through anaerobic digestion. In this study, biomethane production potential of wastes like sugar beet bagasse, agricultural residues, food wastes, olive mill pulp, and dairy manure having different characteristics was investigated in mesophilic CSTR reactor, and their performances were compared. The reactor was mixed in order to provide homogenized content at a rate of 80 rpm. The organic matter content of these wastes was between 85 to 94 % with 61% (olive pulp) to 22 % (food waste) dry matter content. The hydraulic retention time changed between 20-30 days. High biogas productions, 13.45 to 5.70 mL/day, were achieved from the wastes studied when operated at 9 to 10.5% TS loadings where OLR varied between 2.92 and 3.95 gVS/L.day. The results showed that food wastes have higher specific methane production rate and volumetric methane production potential than the other wastes studied, under the similar OLR values. The SBP was 680, 585, 540, 390 and 295 mL/g VS for food waste, agricultural residues, sugar beet bagasse, olive pulp and dairy manure respectively. The methane content of the biogas varied between 72 and 60 %. The volatile solids conversion rate for food waste was 62%.

Keywords: biogas production, organic wastes, biomethane, anaerobic digestion

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Authors: Jiri Beranovsky, Jaroslav Knapek, Tomas Kralik, Kamila Vavrova

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The paper deals with the results of research focused on the complex aspects of the use of intentionally grown biomass on agricultural land for the production of solid biofuels as an alternative for individual household heating. . The study primarily deals with the analysis of CO2 emissions of the logistics cycle of biomass for the production of energy pellets. Growing, harvesting, transport and storage are evaluated in the pellet production cycle. The aim is also to take into account the consumption profile during the year in terms of heating of common family houses, which are typical end-market segment for these fuels. It is assumed that in family houses, bio-pellets are able to substitute typical fossil fuels, such as brown coal and old wood burning heating devices and also electric boilers. One of the competing technology with the pellets are heat pumps. The results show the CO2 emissions related with considered fuels and technologies for their utilization. Comparative analysis is aimed biopellets from intentionally grown biomass, brown coal, natural gas and electricity used in electric boilers and heat pumps. Analysis combines CO2 emissions related with individual fuels utilization with costs of these fuels utilization. Cost of biopellets from intentionally grown biomass is derived from the economic models of individual energy crop plantations. At the same time, the restrictions imposed by EU legislation on Ecodesign's fuel and combustion equipment requirements and NOx emissions are discussed. Preliminary results of analyzes show that to achieve the competitiveness of pellets produced from specifically grown biomass, it would be necessary to either significantly ecological tax on coal (from about 0.3 to 3-3.5 EUR/GJ), or to multiply the agricultural subsidy per area. In addition to the Czech Republic, the results are also relevant for other countries, such as Bulgaria and Poland, which also have a high proportion of solid fuels for household heating.

Keywords: CO2 emissions, heating costs, energy crop, pellets, brown coal, heat pumps, economical evaluation

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Authors: Gadisa Demie, Mesele Negash, Zerihun Asrat, Lojka Bohdan

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Deforestation and forest degradation in the tropics have led to significant carbon (C) emissions. Agroforestry (AF) is a suitable land-use option for tackling such declines in ecosystem services, including climate change mitigation. However, it is unclear how biomass models, AF practices, and socio-ecological factors determine these roles, which hinders the implementation of climate change mitigation initiatives. This study aimed to estimate the ecosystem C stocks of the studied AF practices in relation to socio-ecological variables in central Ethiopia. Out of 243 AF farms inventoried, 108 were chosen at random from three AF practices to estimate their biomass and soil organic carbon. A total of 432 soil samples were collected from 0–30 and 30–60 cm soil depths; 216 samples were taken for each soil organic carbon fraction (%C) and bulk density computation. The study found that the currently developed allometric equations were the most accurate to estimate biomass C for trees growing in the landscape when compared to previous models. The study found higher overall biomass C in woodlots (165.62 Mg ha-¹) than in homegardens (134.07 Mg ha-¹) and parklands (19.98 Mg ha-¹). Conversely, overall, SOC was higher for homegardens (143.88 Mg ha-¹), but lower for parklands (53.42 Mg ha-¹). The ecosystem C stock was comparable between homegardens (277.95 Mg ha-¹) and woodlots (275.44 Mg ha-¹). The study found that elevation, wealthy levels, AF farm age, and size have a positive and significant (P < 0.05) effect on overall biomass and ecosystem C stocks but non-significant with slope (P > 0.05). Similarly, SOC increased with increasing elevation, AF farm age, and wealthy status but decreased with slope and non-significant with AF farm size. The study also showed that species diversity had a positive (P <0.05) effect on overall biomass C stocks in homegardens. The overall study highlights that AF practices have a great potential to lock up more carbon in biomass and soils; however, these potentials were determined by socioecological variables. Thus, these factors should be considered in management strategies that preserve trees in agricultural landscapes in order to mitigate climate change and support the livelihoods of farmers.

Keywords: agricultural landscape, biomass, climate change, soil organic carbon

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Authors: Sankhanil Das, Arunava Dasgupta, Keya Mitra

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This paper investigates the relationship between natural ecological systems and modern urban morphology. Over years, ecological conditions represented by natural resources such as natural landforms, systems of water, urban geography and land covers have been a significant driving factor of how settlements have formed, expanded and functioned. These have played a pivotal role in formation of the community character and the cultural identity of the urban spaces, and have steered cultural behavior within these settings. Such cultural behaviors have been instrumental in transforming mere spaces to places with meaning and symbolism. The natural process of city formation is principally founded upon the idea of balance and harmony, mostly in a subconscious manner. Reimaging such processes of natural evolution, this paper systematically builds a development model that generates a balance between environment and development, with specific focus on the Urban-Rural fringe areas in the Temple Town of Puri, in Eastern India. Puri represents a unique cross section of ecological landscape, cultural practices and religious symbolism with a very rich history and a vibrant heritage. While the city centre gets more and more crowded by tourists and pilgrims to accommodate related businesses, the original residents of Puri relocate to move towards the urban peripheral areas for better living conditions, gradually converting agricultural lands into non agricultural uses. This rapid spread into the rural hinterland is devoid of any connection with the rich cultural identity of Puri. These past four decades of ‘development’ has been at the cost of 810 Hectares of ecological Lake systems in the region. Invaluable ecological resources at urban rural edges are often viewed as hindrances to development and conceptualized as taking away from the image of the city. This paper attempts to understand the language of development over years on existing natural resources through topo-analysis and proposes a sustainable approach of development using different planning tools, with ecological resources as the pivotal factor of development.

Keywords: livability, sustainable development, urbanization, urban-rural edge

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Authors: Yu-Chen Chien, Sheng-Jung Ou, Shang-Ling Hsu

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Many aboriginal tribes in the early modern began to actively promote tribal tourism. The tribe uses rich ecological environment and unique folk culture successfully attract crowds. In addition to the tribe in the construction level to consider the cultural heritage and living needs, in order to improve tribal tourism for the tribe to bring the benefits of all levels, as well as to avoid the tourism industry is too prosperous brought negative tourism impact. How to successfully create the conditions of mutual benefit of residents and tourists is an important issue common to many tribes. Hualien Turuku Hongye Tribe in Taiwan around the tourist resources are very rich. It is famous for its Hongye hot springs and Ruisui hot springs. Hongye tribe to develop tribal tourism is bound to use its own has three advantages: Truku culture, in the agricultural products experience and marketing, and the surrounding hot springs industry tourism benefits. Tribal Development Association in the past to promote these three advantages for tribal tourism. But due to the impact of many levels led to the tribes in the promotion of tourism on the ineffective. At present, in addition to the Hongye Tribal Development Association in promoting tribal tourism, local residents to promote cultural heritage workshop also gradually rise. Its purpose is to link local cultural resources, agricultural specialty resources, spa tourism industry, the revitalization of the internal development of the tribes at all levels. Each tribe to promote tribal tourism due to geographical environment, resource types have a different set of practices and patterns. This study explores the tourist opportunities and resource points of Hongye tribes, and tribal tourism has been to promote the operation practices and benefits. To understand the difficulties encountered in the implementation of tribal tourism and the impact of all levels. Reference successful development of domestic and foreign tourism tribal tribe case. Develop a questionnaire and using the questionnaire survey to understand tribal residents for the tribal tribes to promote tribal tourism views. Finally, it puts forward some suggestions and strategies to promote the tribal tourism in Hongye tribe.

Keywords: cultural tourism, tourism impact, aboriginal tribe, Hongye Tribe

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Authors: Ryuji Yamazaki, Masahiro Kochi, Weiran Zhu, Hiroko Kase

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In care for older adults, behavioral and psychological symptoms of dementia (BPSD) like agitation and aggression are distressing for patients and their caretakers, often resulting in premature institutionalization with increased costs of care. To improve mood and mitigate symptoms, as a non-pharmaceutical approach, emotion-oriented therapy like reminiscence work is adopted in face-to-face communication. Telecommunication support is expected to be provided by robotic media as a bridge for digital divide for those with dementia and facilitate social interaction both verbally and nonverbally. The purpose of this case study is to explore the conditions in which robotic media can effectively attract attention from older adults with dementia and promote their well-being. As a pilot study, we introduced the pillow-phone Hugvie^®, a huggable humanly shaped communication medium to five residents with dementia at a care facility, to investigate how the following conditions work for the elderly when they use the medium; 1) no sound, 2) radio, non-interactive, 3) daily conversation, and 4) reminiscence work. As a result, under condition 4, reminiscence work, the five participants kept concentration in interacting with the medium for a longer duration than other conditions. In condition 4, they also showed larger amount of utterances than under other conditions. These results indicate that providing topics related to personal histories through robotic media could affect communication positively and should, therefore, be further investigated. In addition, the issue of ethical implications by using persuasive technology that affects emotions and behaviors of older adults is also discussed.

Keywords: BPSD, reminiscence, tactile telecommunication, utterances

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Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

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Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

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Authors: Bourhim Mohammad Redouane, Cheto Said, Qaddoury Ahmed, Hirich Abdelaziz, Ghoulam Cherki

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Several abiotic stresses cause disruptions in the properties of agricultural soils and hence their loss worldwide. Among these abiotic stresses, Salinity to which most crops were exposed caused an important reduction in their productivity. Therefore, in order to deal with this challenging problem, we rely on cultivating alternative plants that can tolerate the adverse salinity stress, such as quinoa (Chenopodium quinoa). Although even it was qualified as tolerant to Salinity, the quinoa’s performance could be negatively affected under high salinity levels. Thus, our study aims to assess the effects of the application of soil amendments to improve quinoa tolerance levels under high Salinity. Thus, three quinoa varieties (Puno, ICBA-Q5, and Titicaca) were grown on agricultural soil under a greenhouse with five amendments; Biochar “Bc,” compost “Cp,” black soldier insect frass “If,” cow manure “Fb” and phosphogypsum “Pg.” Two controls without amendment were adopted consisting of the salinized negative one “T(-)” and the non-salinized positive one “T(+).” After 20 days from sowing, the plants were irrigated with a saline solution of 16 dS/m prepared with NaCl for a period of 60 days. Then plant tolerance was assessed based on agrophysiological parameters. The results showed that salinity stress negatively affected the quinoa plants for all the analyzed agrophysiological parameters in the three varieties compared to their corresponding controls “T(+).” However, most of these parameters were significantly enhanced by the application of soil amendments compared to their negative controls “T(-).” For instance, the biomass was improved by 91.8% and 69.4%, respectively, for Puno and Titicaca varieties amended with “Bc.” The total nitrogen amount was increased by 220% for Titicaca and ICBA-Q5 plants cultivated in the soil amended with “If.” One of the most important improvements was noted for potassium content in Titicaca amended with “Pg,” which was six times higher compared to the negative control. Besides, the plants of Puno amended with “Cp” showed an improvement of 75.9% for the stomatal conductance and 58.5% for nitrate reductase activity. Nevertheless, the pronounced varietal difference was registered between Puno and Titicaca, presenting the highest performances mainly for the soil amended with “If,” “Bc,” and “Pg.”

Keywords: chenopodium quinoa, salinity, soil amendments, growth, nutrients, nitrate reductase

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Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

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Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

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Authors: Yiping Meng, Yiming Sun

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The traditional construction industry is unable to meet the requirements for novel fabrication and construction. Automated construction and digital design have emerged as industry development trends that compensate for this shortcoming under the backdrop of Industrial Revolution 4.0. Benefitting from more flexible working space and more various end-effector tools compared to CNC methods, robot fabrication and construction techniques have been used in irregular architectural design. However, there is a lack of a systematic and comprehensive design and optimisation workflow considering geometric form, material, and fabrication methods. This paper aims to propose a design optimisation workflow for improving the rationality of a free-form timber structure fabricated by the robotic arm. Firstly, the free-form surface is described by NURBS, while its structure is calculated using the finite element analysis method. Then, by considering the characteristics and limiting factors of robotic timber fabrication, strain energy and robustness are set as optimisation objectives to optimise structural morphology by gradient descent method. As a result, an optimised structure with axial force as the main force and uniform stress distribution is generated after the structure morphology optimisation process. With the decreased strain energy and the improved robustness, the generated structure's bearing capacity and mechanical properties have been enhanced. The results prove the feasibility and effectiveness of the proposed optimisation workflow for free-form timber structure morphology design.

Keywords: robotic fabrication, free-form timber structure, Multi-objective optimisation, Structural morphology, rational design

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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