Search results for: autonomous agricultural machines

Authors: Fahui Jiang, Xinwei Xue, Liyan Zhang, Yanyan Zuo, Hao Zhang, Wei Zheng, Limei Bian, Lingling Hu, Chunlei Hao, Jianghong Du, Yanhua Ci, Ruibao Cheng, Ciren Dawa, Mithun Biswas, Mahbub Ul Islam, Fansheng Meng, Xinhua Peng

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Context: Soil erosion is a global issue that poses a significant threat to agricultural sustainability, particular in northern of China, which experiences the most severe wind erosion worldwide. Conservation tillage is vital in arid regions for preserving soil, enhancing water retention, and sustaining agricultural productivity in the face of limited rainfall. However, the long-term impacts of conservation tillage in semi-arid regions, especially its effects on soil health, wind erosion, and crop productivity, are poorly understood. Objective: Assess the impacts of conservation tillage on soil hydrothermal properties, wind erosion rates, nutrient dynamics, and crop yield, as well as elucidating the underlying mechanisms driving these impacts. Methods: A 9-year in-situ study was conducted in Chifeng, Inner Mongolia Province, comparing conventional rotary tillage (CK) with two conservation tillage methods: no-tillage with straw mulching (CT-1) and no-tillage with standing straw (CT-2). Results: Soil bulk density increased significantly under CT-1 and CT-2 in the topsoil layer (0–20 cm) compared with CK. Soil moisture content exhibited a significant increase pattern under CT-1 and CT-2, while soil temperature decreased under CT-1 but increased under CT-2, relative to CK. These variations in soil hydrothermal properties were more pronounced during the early (critical) crop growth stages and higher temperature conditions (afternoon). Soil loss due to wind erosion, accumulated from a height of 0–50 cm on the land surface, was reduced by 31.3 % and 25.5 % under CT-1 and by 51.5 % and 38.2 % under CT-2 in 2021 and 2022, respectively, compared to CK. Furthermore, the proportion of soil finer particles (clay and silt) increased under CT due to reduced wind erosion. Soil organic carbon significantly increased throughout the soil profile (0–60 cm), particularly in the deeper layers (20–40 cm and 40–60 cm), compared to the surface layer (0–20 cm), with corresponding increases of +57.0 % and +0.18 %, +66.2 % and +80.3 %, and +27.1 % and +14.2 % under CT-1 and CT-2, respectively, relative to CK in 2021. The concentrations of soil nutrients such as total nitrogen, available nitrogen, and available phosphorus and potassium, consistently increased under CT-1 and CT-2 compared to CK, with notable enhancements observed in the topsoil layer (0–20 cm) before seedling time, albeit declining after crop harvest. Generally, CT treatments significantly increased dry matter accumulation (+4.8 % to +30.8 %) and grain yield (+2.22 % to +0.44 %) of maize compared to CK in the semi-arid region over the 9-year study period, particularly notable in dry years and with long-term application. Conclusions and implications: Conservation tillage in semi-arid regions enhanced soil properties, reduced soil erosion, and increased soil nutrient dynamics and crop yield, promising sustainable agricultural practices with environmental benefits. Furthermore, our findings suggest that no-tillage with straw mulching is more suitable for dry and wind erosion sensitive regions.

Keywords: no tillage, conventional tillage, soil water, soil temperature, soil physics

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Authors: Jen-Te Pai, Jao-Heng Liu, Shin-En Pai

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The impact of climate change has intensified in recent years, causing Taiwan to face higher frequency and serious natural disasters. Therefore, it is imperative for industrial parks manufacturers to promote adaptation policies in response to climate change. On the other hand, with the rise of the international anti-terrorism situation, once a terrorist attack occurs, it will attract domestic and international media attention, especially the strategic and economic status of the science park. Thus, it is necessary to formulate adaptation and mitigation strategies under climate change and social economic disasters. After reviewed the literature about climate change, urban disaster prevention, vulnerability assessment, and risk communication, the study selected 62 industrial parks compiled by the Industrial Bureau of the Ministry of Economic Affairs of Taiwan as the research object. This study explored the vulnerability and disaster prevention and disaster relief functional assessment of these industrial parks facing of natural and socio-economic disasters. Furthermore, this study explored planned adaptation of industrial parks management section and autonomous adaptation of corporate institutions in the park. The conclusion of this study is that Taiwan industrial parks with a higher vulnerability to natural and socio-economic disasters should employ positive adaptive behaviours.

Keywords: adaptive behaviours, analytic network process, vulnerability, industrial parks

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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: 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: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: Jacqueline Miller, Dongyuan Y. Wang, F. Dan Richard

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Before trying to make an ethical machine that holds a higher ethical standard than humans, a better understanding of human moral standards that could be used as a guide is crucial. How humans make decisions in dangerous driving situations like moral dilemmas can contribute to developing acceptable ethical principles for autonomous vehicles (AVs). This study uses a driving simulator to investigate whether drivers make utilitarian choices (choices that maximize lives saved and minimize harm) in unavoidable automobile accidents (moral dilemmas) with time pressure manipulated. This study also investigates how impulsiveness influences drivers’ behavior in moral dilemmas. Manipulating time pressure results in collisions that occur at varying time intervals (4 s, 5 s, 7s). Manipulating time pressure helps investigate how time pressure may influence drivers’ response behavior. Thirty-one undergraduates participated in this study using a STISM driving simulator to respond to driving moral dilemmas. The results indicated that the percentage of utilitarian choices generally increased when given more time to respond (from 4 s to 7 s). Additionally, participants in vehicle scenarios preferred responding right over responding left. Impulsiveness did not influence utilitarian choices. However, as time pressure decreased, response time increased. Findings have potential implications and applications on the regulation of driver assistance technologies and AVs.

Keywords: time pressure, automobile moral dilemmas, impulsiveness, reaction time

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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: Jia-Shiun Chen, Hsiu-Ying Hwang

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Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control

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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: 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: 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: Paula C. Latorre Arroyo, Andrea C. Latorre Arroyo

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In the present society, children are exposed to and impacted by technology from very early on in various ways. Artificial intelligence (AI), in particular, directly affects them, be it positively or negatively. The concept of artificial intelligence is commonly defined as the technological programming of computers or robotic mechanisms with humanlike capabilities and characteristics. These technologies are often designed as helpful machines or disguised as handy tools that could ultimately steal private information for illicit purposes. Children, being one of the most vulnerable groups due to their lack of experience and knowledge, do not have the ability to recognize or have the malice to distinguish if an apparatus with artificial intelligence is good or bad for them. For this reason, as a society, there must be a sense of responsibility to regulate and monitor different types of uses for artificial intelligence to protect children from potential risks that might arise. This article aims to investigate the many implications that artificial intelligence has in the lives of children, starting from a home setting, within the classroom, and, ultimately, in online spaces. Irrefutably, there are numerous beneficial aspects to the use of artificial intelligence. However, due to its limitless potential and lack of specific and substantial regulations to prevent the illicit use of this technology, safety and privacy concerns surface, specifically regarding the youth. This written work aims to provide an in-depth analysis of how artificial intelligence can both help children and jeopardize their safety. Concluding with resources and data supporting the aforementioned statement.

Keywords: artificial intelligence, children, privacy, rights, safety

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Authors: Indu Chandran, Shubham Sharma, Rohan Mehta, Vipin Kizheppatt

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Unmanned aerial vehicles are increasingly being explored as the most promising solution to disaster monitoring, assessment, and recovery. Current relief operations heavily rely on intelligent robot swarms to capture the damage caused, provide timely rescue, and create road maps for the victims. To perform these time-critical missions, efficient path planning that ensures quick coverage of the area is vital. This study aims to develop a technically balanced approach to provide maximum coverage of the affected area in a minimum time using the optimal number of UAVs. A coverage trajectory is designed through area decomposition and task assignment. To perform efficient and autonomous coverage mission, solution to a TSP-based optimization problem using meta-heuristic approaches is designed to allocate waypoints to the UAVs of different flight capacities. The study exploits multi-agent simulations like PX4-SITL and QGroundcontrol through the ROS framework and visualizes the dynamics of UAV deployment to different search paths in a 3D Gazebo environment. Through detailed theoretical analysis and simulation tests, we illustrate the optimality and efficiency of the proposed methodologies.

Keywords: area coverage, coverage path planning, heuristic algorithm, mission monitoring, optimization, task assignment, unmanned aerial vehicles

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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

Procedia PDF Downloads 359

Authors: Wasiu Oyeleke Oyediran

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Maize is a common staple food for human consumption and livestock feeds. It provides employment and means of livelihood for women in both rural areas and urban centres in Nigeria. However, the entrepreneurial skills of women engaged in its processing and value addition has not been fully enhanced. This study was therefore carried out to investigate rural women entrepreneurial skills in maize processing and value addition in Ogun State, Nigeria. Snow ball sampling technique was used in the selection of 70 respondents for this study. Data were analyzed with descriptive statistics and chi-square. Results revealed that majority (50.0%) of the respondents were 31 - 40 years of age and 60% of the respondents had spent 6 – 10 years in maize processing. The respondents have great entrepreneurial skills in popcorn (85.7%), corn cake (80.0%), corn balls (64.3%) and kokoro (52.9%) making. The majority of the respondents accessed information and entrepreneurial skills through fellow processors (88.6%) and friends and neighbours (62.9%). Major constraints to maize processing and value addition were scarcity of raw materials during off season periods (95.7%), ineffective preservation methods (88.6%), lack of modern processing equipment (82.9%), and high cost of processing machines (72.9%). Result of chi-square showed that there is significant association between personal characteristics of the respondents and entrepreneurial skills of the women at p < 0.05. It is hereby recommended that subsidized processing equipment should be made available to the maize processors in the study area by the government and NGOs.

Keywords: women, entreprenuerial skills, maize prcessing, value addition

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Authors: Yongmin You

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Electric machines for office automation device such as printer and scanner have been required the low noise and vibration performance. Many researches about the low noise and vibration of polygon mirror scanner motor have been also progressed. The noise and vibration of polygon mirror scanner motor can be classified by aerodynamic, structural and electromagnetic. Electromagnetic noise and vibration can be occurred by high cogging torque and nonsinusoidal back EMF. To improve the cogging torque and back EMF characteristic, we apply unequal air-gap. To analyze characteristic of a polygon mirror scanner motor, two dimensional finite element method is used. To minimize the cogging torque of a polygon mirror motor, Kriging based on latin hypercube sampling (LHS) is utilized. Compared to the initial model, the torque ripple of the optimized unequal air-gap model was reduced by 23.4 % while maintaining the back EMF and average torque. To verify the optimal design results, the experiment was performed. We measured the vibration in motors at 23,600 rpm which is the rated velocity. The radial and axial gravitational acceleration of the optimal model were declined more than seven times and three times, respectively. From these results, a shape optimized unequal polygon mirror scanner motor has shown the usefulness of an improvement in the torque ripple and electromagnetic vibration characteristic.

Keywords: polygon mirror scanner motor, optimal design, finite element method, vibration

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Authors: Ahmad Shanei, Milad Baradaran-Ghahfarokhi

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This study aimed to investigate testicular dose (TD) and the associated risk of heritable disease from common pelvis radiotherapy of male patients in Iran. In this work, the relation between TD and changes in beam energy, pelvis size, source to skin distance (SSD) and beam directions (anterior or posterior) were also evaluated. The values of TDs were measured on 67 randomly selected male patients during common pelvis radiotherapy using 1.17 and 1.33 MeV, Theratron Cobalt-60 unit at SSD of 80 cm and 9 MV, Neptun 10 PC and 18 MV, GE Saturne 20 at SSD of 100 cm at Seyed-Al Shohada Hospital, Isfahan, Iran. Results showed that the maximum TD was up to 12% of the tumor dose. Considering the risk factor for radiation-induced heritable disorders of 0.1% per Sv, an excess risk of hereditary disorders of 72 per 10000 births was conservatively calculated. There was a significant difference in the measured TD using different treatment machines and energies (P < 0.001). The TD at 100 cm SSD were much less than that for 80 cm SSD (P <0.001). The Pearson Correlation test showed that, as expected, there was a strong correlation between TD and patient’s pelvis size (r = 0.275, P <0.001). Using the student’s t-tests, it was found that, there was not a significant difference between TD and beam direction (P = 0.231). Iranian male patients undergoing pelvic radiotherapy have the potential of receiving a TD of more than 1 Gy which might result in temporary azoospermia. The risk for induction of hereditary disorders in future generations should be considered as low but not negligible in comparison with the correspondent nominal risk.

Keywords: pelvis radiotherapy, testicular dose, infertility, hereditary effects

Procedia PDF Downloads 547

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

Procedia PDF Downloads 193

Authors: Victoria L. Chester, Usha Kuruganti

Abstract:

The forest industry is a major economic sector of Canada and also one of the most dangerous industries for workers. The use of mechanized mobile forestry harvesting machines has successfully reduced the incidence of injuries in forest workers related to manual labor. However, these machines have also created additional concerns, including a high machine operation learning curve, increased the length of the workday, repetitive strain injury, cognitive load, physical and mental fatigue, and increased postural loads due to sitting in a confined space. It is critical to obtain objective performance data for employers to develop appropriate work practices for this industry, however ergonomic field studies of this industry are lacking mainly due to the difficulties in obtaining comprehensive data while operators are cutting trees in the woods. The purpose of this study was to establish a measurement and experimental protocol to examine the effects of worker skill level and movement training speed (joystick crane speed) on harvesting performance using a forestry simulator. A custom wrist angle measurement device was developed as part of the study to monitor Euler angles during operation of the simulator. The device of the system consisted of two accelerometers, a Bluetooth module, three 3V coin cells, a microcontroller, a voltage regulator and an application software. Harvesting performance and crane data was provided by the simulator software and included tree to frame collisions, crane to tree collisions, boom tip distance, number of trees cut, etc. A pilot study of 3 operators with various skill levels was tested to identify factors that distinguish highly skilled operators from novice or intermediate operators. Dependent variables such as reaction time, math skill, past work experience, training movement speed (e.g. joystick control speeds), harvesting experience level, muscle activity, and wrist biomechanics were measured and analyzed. A 10-channel wireless surface EMG system was used to monitor the amplitude and mean frequency of 10 upper extremity muscles during pre and postperformance on the forestry harvest stimulator. The results of the pilot study showed inconsistent changes in median frequency pre-and postoperation, but there was the increase in the activity of the flexor carpi radialis, anterior deltoid and upper trapezius of both arms. The wrist sensor results indicated that wrist supination and pronation occurred more than flexion and extension with radial-ulnar rotation demonstrating the least movement. Overall, wrist angular motion increased as the crane speed increased from slow to fast. Further data collection is needed and will help industry partners determine those factors that separate skill levels of operators, identify optimal training speeds, and determine the length of training required to bring new operators to an efficient skill level effectively. In addition to effective and employment training programs, results of this work will be used for selective employee recruitment strategies to improve employee retention after training. Further, improved training procedures and knowledge of the physical and mental demands on workers will lead to highly trained and efficient personnel, reduced risk of injury, and optimal work protocols.

Keywords: EMG, forestry, human factors, wrist biomechanics

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

Procedia PDF Downloads 359

Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

Abstract:

Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

Procedia PDF Downloads 139