59 research outputs found
Pinhkngyan: paths taken to recognizing, doing and developing Indigenous methodologies
No full textIt is agreed that Indigenous scholars should be central in researching Indigenous issues. However, the literature on Indigenous research methodologies remains vague on who should be involved. This study aims to lower the entry barrier to Indigenous methodologies for anyone wholeheartedly committed to contribute to the decolonizing processes of Indigenous communities and beyond. We do so by exploring the main challenges experienced by the first author during her doctoral journey and highlighting how these challenges were dealt with. Four themes identified were as follows: (1) the colonial gaze, (2) battling with the concept of authenticity, (3) recognizing Indigeneity in the ordinary, and (4) reconciliation with the past to pave the way toward a better future. Three lessons learned are discussed. A vision for a more inclusive Indigenous inquiry is offered, suggesting that reconnection, reclaiming and sovereignty are key to establishing an ethical space between Indigenous ways of knowing and the existing dominant knowledge systems.Peer reviewe
Pinhkngyan : Paths Taken to Develop Indigenous Research Methodologies. The Case of the Tayal People, Taiwan
No full textThis case study aims to lower the entry barrier to Indigenous methodologies for anyone wholeheartedly committed to contributing to the decolonizing processes of Indigenous communities and beyond. The case study highlights the main challenges experienced by the first author during her doctoral journey and how she dealt with such challenges. Four themes were identified: (1) the colonial gaze, (2) battling with the concept of authenticity, (3) recognizing Indigeneity in the ordinary, and (4) reconciling with the past to pave the way toward a better future. Moreover, we employ the case study to offer a vision of a more inclusive Indigenous form of inquiry. In our view, it is of vital importance to promote reconnection, reclaiming, and sovereignty as means of establishing an ethical space between Indigenous ways of knowing and the knowledge systems still dominating most academic disciplines.Peer reviewe
Factors Influencing Green Innovation Adoption and Its Impact on the Sustainability Performance of Small- and Medium-Sized Enterprises in Saudi Arabia
No full textDue to the growing worries of communities and governments about the depletion of natural resources and environmental contamination, green innovation (GI) is currently receiving much attention on a global scale. This study intends to investigate how Green Innovation Adoption (GIA) influences Sustainable Performance (SNP) in Saudi Arabia’s small- and medium-sized enterprises (SMEs) based on primary research. A conceptual framework model is developed to better comprehend the relationships of Government Support (GS), External Partnership and Cooperation (EPC), Rules and Regulatory Factors (RR), Market and Customer Factors (MC), Organization and Human Factors (OH), Green Innovation Strategy (GIS), and Technology Factors (TF) with GIA. The evaluation of hypotheses is performed using the Partial Least-Squares Structural Equation Modeling (PLS-SEM) method. The study’s findings are obtained using the SPSS 24.0 and AMOS 24.0 software programs. The results of this study reveal that GS, EPC, RR, MC, OH, and TF all have a positive impact on GIA. Furthermore, it has been noted that GIA has a positive impact on the economic, social, and environmental performance of SMEs in the Kingdom of Saudi Arabia. In accordance with the findings, corporate units that use GI would produce more acceptable eco-friendly and long-term performance
Metode Pengendalian Wideng (Sesarma spp) Hama Bibit Mangrove melalui Kegiatan Budidaya Kepiting Bakau Scylla spp
No full textReboisation is one strategy to anticipate global warming that most easily performed. This re-planting activity is very urgent to be conducted in mangrove areas, since the impact of global warming are very profound at the coastal and lowland areas. Its implementation has been done, but failures are still high. One of the causes often found in the field is pests. Its efficient and effective control are still faces various obstacles. Wideng (Sesarma) is very often perform as pest to the mangrove propagules, therefore could affect the community structure. It is therefore important to establish conceptual study and research on wideng control, especially those that are able to promote participation and benefit the community. One potential control is to empower its natural predators, the mud crab Scylla. The purpose of this research is to analyze the level of Scylla predation, namely of total prey consumed, prey size and prey density presentation. It is also intended to determine weight gain and predation behavior by Scylla. Two units of the test cage were placed in the pond in Tapak Tugurejo Semarang with Complete Randomized Design (3 treatments and 5 replications). Data on predation tests are descriptively and statistically analyzed using JMP software, whereas the study of behavior was analyzed descriptively.
The results demonstrated that Scylla is able to prey and consume wideng namely the life ones. Scylla perform no respecter of prey body size, since wideng of small body size (2-3 cm), preferably the same to the moderate size (4-5cm) and large size (> 5 cm). The level of consumption gives a high weight gain for Scylla, between 182 - 197% in just 6 days. In term of presentation of the treatment, showed that wideng really liked the presentation of the feed lot at once rather than presenting a slightly but gradually. Finally, feeding on Scylla with wideng through cultivation, particularly in fattening purposes, using wideng is reasonable and flexible to be applied for fishermen. This concept, together with other control components (components of a dissertation study of the author), is very supportive on the wideng control whiles provide economic benefits to the society aton
Robust Underwater Direction-of-Arrival Estimation Method Using Acoustic Sensor Array under Unknown Swing Deviation Elements
No full textThis paper presents a strategy called the alternating iterative minimization method (AIMM), aimed at enhancing the precision of direction of arrival (DOA) estimation when utilizing an acoustic vector sensor array (AVSA) with unknown swing deviation elements (SDEs). The AVSA model with unknown SDEs is formulated by incorporating the swing deviation parameter. Later, to estimate the swing deviation matrix (SDM) and the sparse signal power by using the alternating iteration method, the auxiliary cost functions with respect to SDM and the sparse signal power are formulated based on the regularized weighted least squares (RWLS) and regularized covariance matrix fitting (RCMF) criteria. Furthermore, their analytical expressions have also been quantified. In order to mitigate the effect of unknown SDEs on the accuracy of DOA estimation, any sub-time segment (STS) in the dataset is selected as the reference to convert the received data of different STS into the reference STS using the estimated SDM. The simulation and experimental outcomes conclusively represent the effectiveness of the suggested TSIM approach using AVSA in handling unknown SDEs
An intelligent fault detection method for PWR-type nuclear power plants using neuro-encoder binary cells
No full textIn this study, a comprehensive model has been presented which is capable of fault detection and classification in the feed water heaters system of a pressurized water reactor nuclear power plant. Along with the known faults detection, this model is also capable of detecting and segregating unknown faults. In addition to this, it also has the potential for accurate classification of those fault extents which are not part of its training. This model has been developed through the combined use of auto-encoders and neural networks, called neuro-encoder binary cells, by arranging them in a cascaded manner. In total, ten different fault types have been used for its training, while ten unknown fault extents as well as five unknown fault types have been utilized for its independent testing. Additionally, this model has also been evaluated against the noisy data in order to verify its robustness. A comparison has also been presented between the performance of proposed model and other commonly used classification and anomaly detection methods
Phosphate fertilizer premixing with farmyard manure enhances phosphorus availability in calcareous soil for higher wheat productivity
No full textInternational audienceFixation reactions reduce the concentration of soluble phosphorus (P) and affect crop growth in alkaline calcareous soils. In lab and greenhouse studies, phosphoric acid (PA) or diammonium phosphate (DAP) were evaluated at various P rates (0, 18, 36 and 54 mg kg−1 soil), either as non-mix (designated as NM-PA and NM-DAP, respectively) or after premixing with farmyard manure (FYM) at 400 mg kg−1 soil (designated as PM-PA and PM-DAP, respectively). The amended soil was incubated at 25 °C and 70% water holding capacity for 7 weeks; thereafter, 32P dynamics were measured using the Freundlich kinetic model. A greenhouse study was also conducted using the same thirteen treatments (as used in incubation experiment) and wheat cultivar (Galaxy 2013) was grown following standard agronomic practices. The results showed that application of PM-PA at the highest rate, which caused maximum change in Pr (ΔPr = 59%) in laboratory condition, also produced maximum P uptake by grain (190.3 mg pot−1) and grain yield (44.1 g pot−1) of wheat in greenhouse experiment. Similarly, regression analysis showed that an increase in Pr values caused a corresponding increase in crop parameters. The results suggested that pre-mixing P fertilizer with FYM could be a viable technique to increase P supply and enhance productivity of wheat in alkaline calcareous soils
Passive Sonar Multiple-Target Tracking with Nonlinear Doppler and Bearing Measurements Using Multiple Sensors
No full textThe major advantage of the passive multiple-target tracking is that the sonars do not emit signals and thus they can remain covert, which will reduce the risk of being attacked. However, the nonlinearity of the passive Doppler and bearing measurements, the range unobservability problem, and the measurement to target data association uncertainty make the passive multiple-target tracking problem challenging. To deal with the target to measurement data association uncertainty problem from multiple sensors, this paper proposed a batch recursive extended Rauch-Tung-Striebel smoother- (RTSS-) based probabilistic multiple hypothesis tracker (PMHT) algorithm, which can effectively handle a large number of passive measurements including clutters. The recursive extended RTSS which consists of a forward filter and a backward smoothing is used to deal with the nonlinear Doppler and bearing measurements. The target range unobservability problem is avoided due to using multiple passive sensors. The simulation results show that the proposed algorithm works well in a passive multiple-target tracking system under dense clutter environment, and its computing cost is low
Passive Tracking of Multiple Underwater Targets in Incomplete Detection and Clutter Environment
No full textA major advantage of the use of passive sonar in the tracking multiple underwater targets is that they can be kept covert, which reduces the risk of being attacked. However, the nonlinearity of the passive Doppler and bearing measurements, the range unobservability problem, and the complexity of data association between measurements and targets make the problem of underwater passive multiple target tracking challenging. To deal with these problems, the cardinalized probability hypothesis density (CPHD) recursion, which is based on Bayesian information theory, is developed to handle the data association uncertainty, and to acquire existing targets’ numbers and states (e.g., position and velocity). The key idea of the CPHD recursion is to simultaneously estimate the targets’ intensity and the probability distribution of the number of targets. The CPHD recursion is the first moment approximation of the Bayesian multiple targets filter, which avoids the data association procedure between the targets and measurements including clutter. The Bayesian-filter-based extended Kalman filter (EKF) is applied to deal with the nonlinear bearing and Doppler measurements. The experimental results show that the EKF-based CPHD recursion works well in the underwater passive multiple target tracking system in cluttered and noisy environments
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