Search results for: food composition data

Authors: Patrick M. Garvey, Roger P. Pech, Daniel M. Tompkins

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Competition is a widespread interaction and natural selection will encourage the development of mechanisms that recognise and respond to dominant competitors, if this information reduces the risk of a confrontation. As olfaction is the primary sense for most mammals, our research tested whether olfactory ‘eavesdropping’ mediates alien species interactions and whether we could exploit our understanding of this behaviour to create ‘super-lures’. We used a combination of pen and field experiments to evaluate the importance of this behaviour. In pen trials, stoats (Mustela erminea) were exposed to the body odour of three dominant predators (cat / ferret / African wild dog) and these scents were found to be attractive. A subsequent field trial tested whether attraction displayed towards predator odour, particularly ferret (Mustela furo) pheromones, could be replicated with invasive predators in the wild. We found that ferret odour significantly improved detection and activity of stoats and hedgehogs (Erinaceus europaeus), while also improving detections of ship rats (Rattus rattus). Our current research aims to identify the key components of ferret odour, using chemical analysis and behavioural experiments, so that we can produce ‘scent from a can’. A lure based on a competitors’ odour would be beneficial in many circumstances including: (i) where individuals display variability in attraction to food lures, (ii) there are plentiful food resources available, (iii) new immigrants arrive into an area, (iv) long-life lures are required. Pest management can therefore benefit by exploiting behavioural responses to odours to achieve conservation goals.

Keywords: predator interactions, invasive species, eavesdropping, semiochemicals

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Authors: Harminder Singh

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Cold spray is a novel and emerging technology for the fabrication of coating. In this study, coating is successfully developed by this process on superalloy surface. The selected coating composition is already proved as corrosion resistant. The microstructure of the newly developed coating is examined by various characterization techniques, for testing its suitability for high temperature corrosive conditions of waste incinerator. The energy producing waste incinerators are still running at low efficiency, mainly due to their chlorine based highly corrosive conditions. The characterization results show that the developed cold sprayed coating structure is suitable for its further testing in highly aggressive conditions.

Keywords: coating, cold spray, corrosion, microstructure

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Authors: Jung–Min Yang

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In this paper, fault recovery for parallel interconnected asynchronous sequential machines is studied. An adversarial input can infiltrate into one of two submachines comprising parallel composition of the considered asynchronous sequential machine, causing an unauthorized state transition. The control objective is to elucidate the condition for the existence of a corrective controller that makes the closed-loop system immune against any occurrence of adversarial inputs. In particular, an efficient existence condition is presented that does not need the complete modeling of the interconnected asynchronous sequential machine.

Keywords: asynchronous sequential machines, parallel composi-tion, corrective control, fault tolerance

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Authors: Muhammad Shafiq

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In accelerated life testing approaches life time data is obtained under various conditions which are considered more severe than usual condition. Classical techniques are based on obtained precise measurements, and used to model variation among the observations. In fact, there are two types of uncertainty in data: variation among the observations and the fuzziness. Analysis techniques, which do not consider fuzziness and are only based on precise life time observations, lead to pseudo results. This study was aimed to examine the behavior of empirical acceleration functions using fuzzy lifetimes data. The results showed an increased fuzziness in the transformed life times as compare to the input data.

Keywords: acceleration function, accelerated life testing, fuzzy number, non-precise data

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Authors: Joni Asitashvili, Eka Chabashvili, Maya Virsaladze, Alexander Chokhonelidze

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Studying the soundscape is a major challenge in many countries of the civilized world today. The sound environment and music itself are part of the Earth's ecosystem. Therefore, researching its positive or negative impact is important for a clean and healthy environment. The acoustics of nature gave people many musical ideas, and people enriched musical features and performance skills with the ability to imitate the surrounding sound. For example, a population surrounded by mountains invented the technique of antiphonal singing, which mimics the effect of an echo. Canadian composer Raymond Murray Schafer viewed the world as a kind of musical instrument with ever-renewing tuning. He coined the term "Soundscape" as a name of a natural environmental sound, including the sound field of the Earth. It can be said that from which the “music of nature” is constructed. In the 21st century, a new field–Ecomusicology–has emerged in the field of musical art to study the sound ecosystem and various issues related to it. Ecomusicology considers the interconnections between music, culture, and nature–According to the Aaron Allen. Eco-music is a field of ecomusicology concerning with the depiction and realization of practical processes using modern composition techniques. Finding an artificial sound source (instrumental or electronic) for the piece that will blend into the soundscape of Sound Oases. Creating a composition, which sounds in harmony with the vibrations of human, nature, environment, and micro- macrocosm as a whole; Currently, we are exploring the ambient sound of the Georgian urban and suburban environment to discover “Sound Oases" and compose Eco-music works. We called “Sound Oases" an environment with a specific sound of the ecosystem to use in the musical piece as an instrument. The most interesting examples of Eco-music are the round dances, which were already created in the BC era. In round dances people would feel the united energy. This urge to get united revealed itself in our age too, manifesting itself in a variety of social media. The virtual world, however, is not enough for a healthy interaction; we created plan of “contemporary round dance” in sound oasis, found during expedition in Georgian caves, where people interacted with cave's soundscape and eco-music, they feel each other sharing energy and listen to earth sound. This project could be considered a contemporary round dance, a long improvisation, particular type of art therapy, where everyone can participate in an artistic process. We would like to present research result of our eco-music experimental performance.

Keywords: eco-music, environment, sound, oasis

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Authors: Shreyash Hadke, Manendra Singh Parihar, Rajesh Khatirkar

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In the present investigation, the variation in the microstructure with the changes in the heat treatment conditions i.e. temperature and time was observed. Ti-6Al-4V alloy was subject to solution annealing treatments in β (1066C) and α+β phase (930C and 850C) followed by quenching, air cooling and furnace cooling to room temperature respectively. The effect of solution annealing and cooling on the microstructure was studied by using optical microscopy (OM), scanning electron microscopy (SEM), electron backscattered diffraction (EBSD) and x-ray diffraction (XRD). The chemical composition of the β phase for different conditions was determined with the help of energy dispersive spectrometer (EDS) attached to SEM. Furnace cooling resulted in the development of coarser structure (α+β), while air cooling resulted in much finer structure with widmanstatten morphology of α at the grain boundaries. Quenching from solution annealing temperature formed α’ martensite, their proportion being dependent on the temperature in β phase field. It is well known that the transformation of β to α follows Burger orientation relationship (OR). In order to reconstruct the microstructure of parent β phase, a MATLAB code was written using neighbor-to-neighbor, triplet method and Tari’s method. The code was tested on the annealed samples (1066C solution annealing temperature followed by furnace cooling to room temperature). The parent phase data thus generated was then plotted using the TSL-OIM software. The reconstruction results of the above methods were compared and analyzed. The Tari’s approach (clustering approach) gave better results compared to neighbor-to-neighbor and triplet method but the time taken by the triplet method was least compared to the other two methods.

Keywords: Ti-6Al-4V alloy, microstructure, electron backscattered diffraction, parent phase reconstruction

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Authors: A. O Amosu, A. M Hammed, G. W. Maneveldt, D. V. Robertson-Andersson

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In aquaculture, feed utilization is an important factor affecting growth of the target species, and thus the success of the aquaculture operation. Growth of C. gariepinus fingerlings (weight 1.60 ± 0.05 g; length 4.50 ± 0.07cm) was monitored in a closed door hatchery for a period of 21 days in an experiment consisting of 4 treatments stocked at 20 fish/10 litre tanks, fed in triplicate twice daily (08:30, 17:30) at 4% body weight with weight changes recorded every 3 days. Treatments were: 1) FeedX; 2) 35% crude protein diet + non enriched Ulva spp (11.18% crude protein) (CD + NEU); 3) 35% crude protein diet + enriched Ulva spp (11.98% crude protein)(CD +EU) and 4) control diet of 35% crude protein (CD). The production of Ulva spp. biomass was cultivated for a period of 3 months. The result shows that the fish fed macroalgal enriched diet had good growth, though no significant difference (p > 0.05) was recorded amongst the weight gain, %weight gain, specific growth rates and nitrogen metabolism of diets CD + NEU, CD + EU and CD. Significant differences (p < 0.05), were, however, found in the food conversion ratio (FCR) and gross food conversion ratio (gFCR) among the fingerlings across all the different experimental diets. The best FCRs were recorded for control diet (0.79 ± 2.39) and the Ulva enriched (1.75 ± 1.34) diets. The results suggest that the fingerlings were able to utilize Ulva supplemented with control diet better than the FeedX. We have shown that Ulva supplemented diets are good substitutes for formulated and commercial feeds, with potential to be successful fish feed in aquaculture systems.

Keywords: aquaculture, clarias gariepinus, growth, macroalgae, nutrient, ulva

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Authors: Feras Hanandeh, Izzat Alsmadi, Muhammad M. Kwafha

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Prefix trees or tries are data structures that are used to store data or index of data. The goal is to be able to store and retrieve data by executing queries in quick and reliable manners. In principle, the structure of the trie depends on having letters in nodes at the different levels to point to the actual words in the leafs. However, the exact structure of the trie may vary based on several aspects. In this paper, we evaluated different structures for building tries. Using datasets of words of different sizes, we evaluated the different forms of trie structures. Results showed that some characteristics may impact significantly, positively or negatively, the size and the performance of the trie. We investigated different forms and structures for the trie. Results showed that using an array of pointers in each level to represent the different alphabet letters is the best choice.

Keywords: data structures, indexing, tree structure, trie, information retrieval

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Authors: Elizaveta Petelina, Anton Sizo

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Environmental remediation projects deal with a wide spectrum of data, including data collected during site assessment, execution of remediation activities, and environmental monitoring. Therefore, an appropriate data management is required as a key factor for well-grounded decision making. The Environmental Data Management System (EDMS) was developed to address all necessary data management aspects, including efficient data handling and data interoperability, access to historical and current data, spatial and temporal analysis, 2D and 3D data visualization, mapping, and data sharing. The system focuses on support of well-grounded decision making in relation to required mitigation measures and assessment of remediation success. The EDMS is a combination of enterprise and desktop level data management and Geographic Information System (GIS) tools assembled to assist to environmental remediation, project planning, and evaluation, and environmental monitoring of mine sites. EDMS consists of seven main components: a Geodatabase that contains spatial database to store and query spatially distributed data; a GIS and Web GIS component that combines desktop and server-based GIS solutions; a Field Data Collection component that contains tools for field work; a Quality Assurance (QA)/Quality Control (QC) component that combines operational procedures for QA and measures for QC; Data Import and Export component that includes tools and templates to support project data flow; a Lab Data component that provides connection between EDMS and laboratory information management systems; and a Reporting component that includes server-based services for real-time report generation. The EDMS has been successfully implemented for the Project CLEANS (Clean-up of Abandoned Northern Mines). Project CLEANS is a multi-year, multimillion-dollar project aimed at assessing and reclaiming 37 uranium mine sites in northern Saskatchewan, Canada. The EDMS has effectively facilitated integrated decision-making for CLEANS project managers and transparency amongst stakeholders.

Keywords: data management, environmental remediation, geographic information system, GIS, decision making

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Authors: Kamila Weissova, Jitka Skrabalova, Katerina Skalova, Jana Koprivova, Zdenka Bendova

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Any Arctic visitor has to deal with extreme conditions, including constant light during the summer season or constant darkness during winter time. Light/dark cycle is the most powerful synchronizing signal for biological clock and the absence of daily dark period during the polar day can significantly alter the functional state of the internal clock. However, the inner clock can be synchronized by other zeitgebers such as physical activity, food intake or social interactions. Here, we investigated the effect of polar day on circadian clock of 10 researchers attending the polar base station in the Svalbard region during July. The data obtained on Svalbard were compared with the data obtained before the researchers left for the expedition (in the Czech Republic). To determine the state of circadian clock we used wrist actigraphy followed by sleep diaries, saliva, and buccal mucosa samples, both collected every 4 hours during 24h-interval to detect melatonin by radioimmunoassay and clock gene (PER1, BMAL1, NR1D1, DBP) mRNA levels by RT-qPCR. The clock gene expression was analyzed using cosinor analysis. From our results, it is apparent that the constant sunlight delayed melatonin onset and postponed the physical activity in the same order. Nevertheless, the clock gene expression displayed higher amplitude on Svalbard compared to the amplitude detected in the Czech Republic. These results have suggested that the common daily schedule at the Svalbard expedition can strengthen circadian rhythm in the environment that is lacking light/dark cycle. In conclusion, the constant sunlight delays melatonin onset, but it still maintains its rhythmic secretion. The effect of constant sunlight on circadian clock can be minimalized by common daily scheduled activity.

Keywords: actighraph, clock genes, human, melatonin, polar day

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Authors: Y. Hajjam, I. T. Alami, S. M. Udupa, S. Cherkaoui

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Faba bean (Vicia faba L.) is an important food legume crop in Morocco. It is mainly used as human food and feed for animals. Faba bean also plays an important role in cereal-based cropping systems, when rotated with cereals it improves soil fertility by fixing N2 in root nodules mediated by Rhizobium. Both faba bean and its biological nitrogen fixation symbiotic bacterium Rhizobium are affected by different stresses such as: salinity, drought, pH, heavy metal, and the uptake of inorganic phosphate compounds. Therefore, the aim of the present study was to evaluate the phenotypic diversity among the faba bean rhizobial isolates and to select the tolerant strains that can fix N2 under environmental constraints for inoculation particularly for affected soils, in order to enhance the productivity of faba bean and to improve soil fertility. Result have shown that 62% of isolates were fast growing with the ability of producing acids compounds , while 38% of isolates are slow growing with production of alkalins. Moreover, 42.5% of these isolates were able to solubilize inorganic phosphate Ca3(PO4)2 and the index of solubilization was ranged from 2.1 to 3.0. The resistance to extreme pH, temperature, water stress heavy metals and antibiotics lead us to classify rhizobial isolates into different clusters. Finally, the authentication test under greenhouse conditions showed that 55% of the rhizobial isolates could induce nodule formation on faba bean (Vicia faba L.) under greenhouse experiment. This phenotypic characterization may contribute to improve legumes and non legumes crops especially in affected soils and also to increase agronomic yield in the dry areas.

Keywords: rhizobia, vicia faba, phenotypic characterization, nodule formation, environmental constraints

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Authors: Bharat Singh Om Prakash Vyas

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Now a day’s applications deal with High Dimensional Data have tremendously used in the popular areas. To tackle with such kind of data various approached has been developed by researchers in the last few decades. To tackle with such kind of data various approached has been developed by researchers in the last few decades. One of the problems with the NMF approaches, its randomized valued could not provide absolute optimization in limited iteration, but having local optimization. Due to this, we have proposed a new approach that considers the initial values of the decomposition to tackle the issues of computationally expensive. We have devised an algorithm for initializing the values of the decomposed matrix based on the PSO (Particle Swarm Optimization). Through the experimental result, we will show the proposed method converse very fast in comparison to other row rank approximation like simple NMF multiplicative, and ACLS techniques.

Keywords: ALS, NMF, high dimensional data, RMSE

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Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

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Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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Authors: Christina Killian, Katie Wall, Séamus Fanning, Guerrino Macori

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Deep-level metagenomics offers a useful technical approach to explore the three dynamic One Health axes: healthcare, domiciliary and veterinary. There is currently limited understanding of the composition of complex biofilms, natural abundance of AMR genes and gene transfer occurrence in these ecological niches. By using a newly established small-scale complex biofilm model, COMBAT has the potential to provide new information on microbial diversity, antimicrobial resistance (AMR)-encoding gene abundance, and their transfer in complex biofilms of importance to these three One Health axes. Shotgun metagenomics has been used to sample the genomes of all microbes comprising the complex communities found in each biofilm source. A comparative analysis between untreated and biocide-treated biofilms is described. The basic steps include the purification of genomic DNA, followed by library preparation, sequencing, and finally, data analysis. The use of long-read sequencing facilitates the completion of metagenome-assembled genomes (MAG). Samples were sequenced using a PromethION platform, and following quality checks, binning methods, and bespoke bioinformatics pipelines, we describe the recovery of individual MAGs to identify mobile gene elements (MGE) and the corresponding AMR genotypes that map to these structures. High-throughput sequencing strategies have been deployed to characterize these communities. Accurately defining the profiles of these niches is an essential step towards elucidating the impact of the microbiota on each niche biofilm environment and their evolution.

Keywords: COMBAT, biofilm, metagenomics, high-throughput sequencing

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Authors: Mingmei Zhang, Xinyong Li

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AgInS₂/SnS₂ (AIS) nanocomposites were synthesized by a simple hydrothermal method. The morphology and composition of the fabricated AIS nanocomposites were investigated by field-emission scanning electron microscopy (SEM), X-ray diffraction (XRD), high resolution transmission electron microscopy (HRTEM) and X-ray photoelectron spectroscopy (XPS). Moreover, the as-prepared AIS photocatalysts exhibited excellent photocatalytic activities for the degradation of Norfloxacin (NOR), mainly due to its high optical absorption and separation efficiency of photogenerated electron-hole pairs, as evidenced by UV–vis diffusion reflection spectra (DRS) and Surface photovoltage (SPV) spectra. Furthermore, the interfacial charges transfer mechanism was also discussed by DFT calculations.

Keywords: AIS nanocomposites, electron-hole pairs, charges transfer, DFTcaculations

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Authors: Ritesh Watharkar, Sourabh Chakraborty, Brijesh Srivastava

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Reduction of water from the fruits and vegetables using different drying techniques is widely employed to prolong the shelf life of these food commodities. Heat transfer occurs inside the sample by conduction and mass transfer takes place by diffusion in accordance with temperature and moisture concentration gradient respectively during drying. This study was undertaken to study and model the thin layer drying behavior of Bhimkol pulp. The drying was conducted in a tray drier at 500c temperature with 5, 10 and 15 % concentrations of added maltodextrin. The drying experiments were performed at 5mm thickness of the thin layer and the constant air velocity of 0.5 m/s.Drying data were fitted to different thin layer drying models found in the literature. Comparison of fitted models was based on highest R2(0.9917), lowest RMSE (0.03201), and lowest SSE (0.01537) revealed Middle equation as the best-fitted model for thin layer drying with 10% concentration of maltodextrin. The effective diffusivity was estimated based on the solution of Fick’s law of diffusion which is found in the range of 3.0396 x10-09 to 5.0661 x 10-09. There was a reduction in drying time with the addition of maltodextrin as compare to the raw pulp.

Keywords: Bhimkol, diffusivity, maltodextrine, Midilli model

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Authors: Muna Khushaim

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Aluminum-based alloys play a key role in modern engineering, especially in the aerospace industry. Introduction of solute atoms such as Li and Cu is the main approach to improve the strength in age-hardenable Al alloys via the precipitation hardening phenomenon. Knowledge of the decomposition process of the microstructure during the precipitation reaction is particularly important for future technical developments. The objective of this study is to investigate the nano-scale chemical composition in the Al-Cu, Al-Li and Al-Li-Cu during the early stage of the precipitation sequence and to describe whether this compositional difference correlates with variations in the observed precipitation kinetics. Comparing the random binomial frequency distribution and the experimental frequency distribution of concentrations in atom probe tomography data was used to investigate the early stage of decomposition in the different binary and ternary alloys which were experienced different heat treatments. The results show that an Al-1.7 at.% Cu alloy requires a long ageing time of approximately 8 h at 160 °C to allow the diffusion of Cu atoms into Al matrix. For the Al-8.2 at.% Li alloy, a combination of both the natural ageing condition (48 h at room temperature) and a short artificial ageing condition (5 min at 160 °C) induces increasing on the number density of the Li clusters and hence increase number of precipitated δ' particles. Applying this combination of natural ageing and short artificial ageing conditions onto the ternary Al-4 at.% Li-1.7 at.% Cu alloy induces the formation of a Cu-rich phase. Increasing the Li content in the ternary alloy up to 8 at.% and increasing the ageing time to 30 min resulted in the precipitation processes ending with δ' particles. Thus, the results contribute to the understanding of Al-alloy design.

Keywords: aluminum alloy, atom probe tomography, early stage, decomposition

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Authors: Wang Lin, Li Zhiqiang

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The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: behavior pattern, cooperative learning, data analyze, k-means clustering algorithm

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Authors: G. Martino, F. Silva, E. Marchal

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The control over delivered iron ore blend characteristics is one of the most important aspects of the mining business. The iron ore price is a function of its composition, which is the outcome of the beneficiation process. So, end-to-end integrated planning of mine operations can reduce risks of penalties on the iron ore price. In a standard iron mining company, the production chain is composed of mining, ore beneficiation, and client supply. When mine planning and client supply decisions are made uncoordinated, the beneficiation plant struggles to deliver the best blend possible. Technological improvements in several fields allowed bridging the gap between departments and boosting integrated decision-making processes. Clusterization and classification algorithms over historical production data generate reasonable previsions for quality and volume of iron ore produced for each pile of run-of-mine (ROM) processed. Mathematical modeling can use those deterministic relations to propose iron ore blends that better-fit specifications within a delivery schedule. Additionally, a model capable of representing the whole production chain can clearly compare the overall impact of different decisions in the process. This study shows how flexibilization combined with a planning optimization model between the mine and the ore beneficiation processes can reduce risks of out of specification deliveries. The model capabilities are illustrated on a hypothetical iron ore mine with magnetic separation process. Finally, this study shows ways of cost reduction or profit increase by optimizing process indicators across the production chain and integrating the different plannings with the sales decisions.

Keywords: clusterization and classification algorithms, integrated planning, mathematical modeling, optimization, penalty minimization

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: Ming Lun Wang, Yan Wang, Ning Ruo Sun

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With the development of cloud computing, more and more users start to utilize the cloud storage service. However, there exist some issues: 1) cloud server steals the shared data, 2) sharers collude with the cloud server to steal the shared data, 3) cloud server tampers the shared data, 4) sharers and key generation center (KGC) conspire to steal the shared data. In this paper, we use advanced encryption standard (AES), hash algorithms, and accountable key-policy attribute-based encryption without key escrow (WOKE-AKP-ABE) to build a security cloud storage scheme. Moreover, the data are encrypted to protect the privacy. We use hash algorithms to prevent the cloud server from tampering the data uploaded to the cloud. Analysis results show that this scheme can resist conspired attacks.

Keywords: cloud storage security, sharing storage, attributes, Hash algorithm

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Authors: M. Bučas, A. Skersonas, E. Ivanauskas, J. Lesutienė, N. Nika, G. Srėbalienė, E. Tiškus, J. Gintauskas, A.Šaškov, G. Martin

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Submerged vegetation enhances heterogeneity of sublittoral habitats; therefore, macrophyte stands are essential elements of aquatic ecosystems to maintain a diverse fish fauna. Fish-habitat relations have been extensively studied in streams and coastal waters, but in lakes and estuaries are still underestimated. The aim of this study is to assess temporal (diurnal and seasonal) patterns of fish juvenile assemblages associated with common submerged macrophyte habitats, which have significantly spread during the recent decade in the upper littoral part of the Curonian Lagoon. The assessment was performed by means of an upgraded pop-up net approach resulting in much precise sampling versus other techniques. The optimal number of samples (i.e., pop-up nets) required to cover>80% of the total number of fish species depended on the time of the day in both study sites: at least 7and 9 nets in the evening (18-24 pm) in the Southern and Northern study sites, respectively. In total, 14 fish species were recorded, where perch and roach dominated (respectively 48% and 24%). From multivariate analysis, water salinity and seasonality (temperature or sampling month) were primary factors determining fish assemblage composition. The southern littoral area, less affected by brackish water conditions, hosted a higher number of species (13) than in the Northern site (8). In the latter site, brackish water tolerant species (three-spined and nine-spined sticklebacks, spiny loach, roach, and round goby) were more abundant than in the Southern site. Perch and ruffe dominated in the Southern site. Spiny loach and nine-spined stickleback were more frequent in September, while ruffe, perch, and roach occurred more in July. The diel dynamics of the common species such as perch, roach, and ruffe followed the general pattern, but it was species specific and depended on the study site, habitat, and month. The species composition between macrophyte habitats did not significantly differ; however, it differed from the results obtained in 2005 at both study sites indicating the importance of expanded charophyte stands during the last decade in the littoral zone.

Keywords: diel dynamics, charophytes, pondweeds, herbivorous and benthivorous fishes, littoral, nursery habitat, shelter

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Authors: Binjuan Xu, Qian Zhao, Ping Jiang, Bo Guo, Zhijun Cheng, Xiaoyue Wu

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Astronautical valves are key units in engine systems of astronautical products; their reliability will influence results of rocket or missile launching, even lead to damage to staff and devices on the ground. Besides failure in engine system may influence the hitting accuracy and flight shot of missiles. Therefore high reliability is quite essential to astronautical products. There are quite a few literature doing research based on few failure test data to estimate valves’ reliability, thus this paper proposed a new method to estimate valves’ reliability, according to the corresponding tests of different failure modes, this paper takes advantage of tests data which acquired from temperature, vibration, and action tests to estimate reliability in every failure modes, then this paper has regarded these three kinds of tests as three stages in products’ process to integrate these results to acquire valves’ reliability. Through the comparison of results achieving from tests data and simulated data, the results have illustrated how to obtain valves’ reliability based on the few failure data with failure modes and prove that the results are effective and rational.

Keywords: censored data, temperature tests, valves, vibration tests

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Authors: Zh. M. Blednova, P. O. Rusinov

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Results of research on the formation of the surface layers of a material with shape memory effect (SME) based on TiNi diffusion metallization in molten Pb-Bi under isothermal conditions in an argon atmosphere are presented. It is shown that this method allows obtaining of uniform surface layers in nanostructured state of internal surfaces on the articles of complex shapes with stress concentrators. Structure, chemical and phase composition of the surface layers provide a manifestation of TiNi shape memory. The average grain size of TiNi coatings ranges between 60 ÷ 160 nm.

Keywords: diffusion metallization, nikelid titanium surface layers, shape memory effect, nanostructures

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Authors: C. Xavier Mendieta, J. J McArthur

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Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: building archetypes, data analysis, energy benchmarks, GHG emissions

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Authors: Nadia Nisha Musa, Nur Atirah Hasmi, Hasnun Nita Ismail, Zulfadli Mahfodz

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In Malaysian Education System, subject related to biodiversity has started in the curriculum from Foundation Study until tertiary education. Biodiversity become the focus of attention due to awareness on global warming which potentially leads to a loss of biodiversity. A loss in biodiversity means a loss in medicinal discoveries and reduces food supply. It is of great important to ensure that young generations become aware of biodiversity conservation. The more interactive approaches are needed to build society with a high awareness for biodiversity conservation. To address this challenge, the goal of this study is to enhance intrinsic motivation of biological students via ARCS model of instruction. Self-access learning materials such as tutorial, module and fieldwork were designed with ARCS elements to a sample size of 70 university students from the beginning of the semester. Both paper and online surveys were used to collect data from the respondents. The results showed that elements of attention, relevance, confidence and satisfaction have a positive impact on intrinsic motivation of students and their academic performance.

Keywords: intrinsic motivation, ARCS model of instruction, biodiversity, self-access learning

Procedia PDF Downloads 222

Authors: M. L. Gaol, I. W. Mudita

Abstract:

Indonesia is well known as a country covered by lush tropical rain forests, but in fact, the northeastern part of the country, within the areas geologically known as Lesser Sunda, the dominant vegetation is tropical savanna. Lesser Sunda is a chain of islands located closer to Australia than to islands in the other parts of the country. Among those of islands in the chain which is closes to Australia, and thereby most strongly affected by the hot and dry Australian climate, is the island of Timor, the western part of which belongs to Indonesia and the eastern part is a sovereign state East Timor. Regardless of being the most dominant vegetation cover, tropical savanna in West Timor, especially its understory, is rarely investigated. This research was therefore carried out to investigate the structure, composition and diversity of the understory of this tropical savanna as the basis for looking at the possibility of introducing other spesieis for various purposes. For this research, 14 terrestrial communities representing major types of the existing savannas in West Timor was selected with aid of the most recently available satellite imagery. At each community, one stand of the size of 50 m x 50 m most likely representing the community was as the site of observation for the type of savanna under investigation. At each of the 14 communities, 20 plots of 1 m x 1 m in size was placed at random to identify understory species and to count the total number of individuals and to estimate the cover of each species. Based on such counts and estimation, the important value of each species was later calculated. The results of this research indicated that the understory of savanna in West Timor consisted of 73 understory species. Of this number of species, 18 species are grasses and 55 are non-grasses. Although lower than non-grass species, grass species indeed dominated the savanna as indicated by their number of individuals (65.33 vs 34.67%), species cover (57.80 vs 42.20%), and important value (123.15 vs 76.85). Of the 14 communities, the lowest density of grass was 13.50/m2 and the highest was 417.50/m2. Of 18 grass species found, all were commonly found as agricultural weeds, whereas of 55 non-grass, 10 species were commonly found as agricultural weeds, environmental weeds, or invasive species. In terms of better managing the savanna in the region, these findings provided the basis for planning a more integrated approach in managing such agricultural and environmental weeds as well as invasive species by considering the structure, composition, and species diversity of the understory species existing in each site. These findings also provided the basis for better understanding the flora of the region as a whole and for developing a flora database of West Timor in future.

Keywords: tropical savanna, understory species, integrated management, weedy and invasive species

Procedia PDF Downloads 136

Authors: Zhen Peng, Baifeng Wu

Abstract:

Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.

Keywords: data parallelism, collision detection, single instruction multiple data, building information modeling, continuous scalability

Procedia PDF Downloads 289

Authors: Hiesik Kim, Yong-Beom Kim, Jaheon Gu

Abstract:

Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to rate up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group (SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with a different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as open source hardware, gas sensor, and Bluetooth module and algorithm controlling transmission rate is demonstrated. Experiment controlling transmission rate also is progressed by developing Android application receiving measured data, and controlling this rate is available at the experiment result. It is important that in the future, improvement for communication algorithm be needed because a few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, IoT, transmission

Procedia PDF Downloads 278

Authors: Adewole A. Ayoade, Marshall R. Sweatt, John P. H. Steele, Qi Han, Khaled Al-Wahedi, Hamad Karki, William A. Yearsley

Abstract:

Understanding the behavioral characteristics of sensors is a crucial step in fusing data from several sensors of different types. This paper introduces a practical, real-time approach to integrate heterogeneous sensor data to achieve higher accuracy than would be possible from any one individual sensor in localizing a mobile robot. We use this approach in both indoor and outdoor environments and it is especially appropriate for those environments like oil and gas refineries due to their sparse and featureless nature. We have studied the individual contribution of each sensor data to the overall combined accuracy achieved from the fusion process. A Sequential Update Extended Kalman Filter(EKF) using validation gates was used to integrate GPS data, Compass data, WiFi data, Inertial Measurement Unit(IMU) data, Vehicle Velocity, and pose estimates from Fiducial marker system. Results show that the approach can enable a mobile robot to navigate autonomously in any environment using a priori information.

Keywords: inspection mobile robot, navigation, sensor fusion, sequential update extended Kalman filter

Procedia PDF Downloads 472