3,680 research outputs found
Evaluation of sensor technologies for on-line raw material characterization in “Reiche Zeche” underground mine - outcomes of RTM implementation
No full textThe increasing advances in sensor technology have resulted in greater availability of sensor data for a wide range of applications. One such application is raw material characterization in mining operations. Sensor technologies operate over certain range of the electromagnetic spectrum and provide information on several aspects of material properties. The sensitivity and the material properties the instrument detects and measures varies from sensor to sensor. The purpose of this study was to synthesize and evaluate the use of sensor technologies for characterization of a polymetallic sulphide deposit in “Reiche Zeche” underground mine. This paper discusses the material characterization methodology using sensor technologies, demonstrates how it fits within the Real-Time Mining (RTM) framework, identifies the interface for both software and hardware requirements and defines the gaps and limitations of application of sensors. It provides a brief overview of the use of sensor and data fusion for material characterization to convey a high-level context in raw material characterization. The sensor technologies considered in this study include RGB imaging, visible–near infrared (VNIR), short wave infrared (SWIR), mid-wave infrared (MWIR), long-wave infrared (LWIR) and Raman spectroscopy.The required information from sensor data in mining operations is not limited to grade control applications. Information on co-occurring minerals or elements are also important for definition of requirements in mineral processing, to identify indirect proxies of elements/minerals of interest, to understand the formation of minerals, to define requirements for blasting parameters, to improve safety and to define requirements for environmental monitoring of toxic material. In view of these points, there is a need for combinations of sensors to achieve a near complete description of material composition and properties. The methodological approaches developed for information extraction from each sensor data and fused data are presented. This includes both direct mineral fingerprinting and indirect proxies using spectral data. The efficient sensor data processing methods and the acquired results from the use of individual sensor and the fused data are summarized. Overall, the acquired results from the use of each sensor technology and the data fusion approach significantly contributed to an improvement of data quality and illustrate the efficiency of use of sensors in the mining industry. However, some of the observed limitations include lack of system robustness, a need for test case specific mineral libraries, the need for development of an integrated principled tool for efficient data collection, processing and knowledge generation. Going forward, automated material characterization is possible with robust system design (exemplified by portable and ruggedized system) and efficient software (test case specific mineral libraries) that can be developed using a combined sensor signal.Resource Engineerin
Consumer Perception of Bread Quality
No full textBread contains a wide range of important nutritional components which provide a positive effect on human health. However, the consumption of bread in Belgium is declining during the last decades. This is due to factors such as changing eating patterns and a increasing choice of substitutes like breakfast cereals and fast foods. The aim of this study is to investigate consumer’s quality perception of bread towards sensory, health and nutrition attributes. Consumer’s quality perception of bread seams to be determined by sensory and health attributes. Three clusters of consumers are identified based on these attributes. In the first cluster, consumers’ quality perception of bread is not dependent on the health attributes it embraces, but to some extent on sensory attributes. For the second cluster, both health and sensory attributes appear to influence quality perception. In the third cluster only sensory attributes appear to be important in determining quality perception, though in a negative direction. The results of this study will possibly help health professionals and policy makers to systematically inform the consumers about the positive effects of bread and its components. Furthermore, firms can use the result to build up a tailor-made marketing strategy.Consumer, Quality perception, Bread, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety,
Raw Materials Business Continuity Plan: A Case Study at SABIC in Europe
No full textThe high level complexity of today’s supply chains, their strive for ever increasing efficiency, and their global structure have rendered supply risk management more important than ever, forcing companies to start taking measures against supply chain vulnerabilities, especially on the inbound side. A great deal of the risks on the inbound side of a firm is caused by the inability of a supplier to provide the purchasing company with the raw materials demanded. Given these conditions, SABIC in Europe is interested in adopting a risk management approach on its entire supply base. To provide a solution to this problem, this research has been conducted in the form of a single case study facilitated by the European Procurement Department of SABIC in Europe, backed up by an extensive literature review. The outcome of the project is a 3-step raw materials business continuity plan: identification of critical raw materials, identification and assessment of supplier risk sources, and identification of suitable risk reduction methods.Management of TechnologyIntegrated Operations and Supply Chain ManagementTechnology, Policy and Managemen
Raw Data: The mnemonic tuning for contamination
No full textRaw data of the experiments reported in Fernandes and collaborators, exploring the mnemonic tuning for contamination:
[1] Fernandes, N.L., Pandeirada, J., Soares, S.C., & Nairne, J. (2017). Adaptive Memory: The Mnemonic Value of Contamination. Evolution and Human Behavior, 38, 451–460. https://doi.org/10.1016/j.evolhumbehav.2017.04.003
[2] Fernandes, N.L., Pandeirada, J.N.S., & Nairne, J. (2021). The mnemonic tuning for contamination: A replication and extension study using more ecologically-valid stimuli. Evolutionary Psychology, 19, 1-13. https://doi.org/10.1177/147470492094623
The use of RGB Imaging and FTIR Sensors for Mineral mapping in the Reiche Zeche underground test mine, Freiberg
No full textThe application of sensor technologies for raw material characterization is rapidly growing, and innovative advancement of the technologies is observed. Sensors are being used as laboratory and in-situ techniques for characterization and definition of raw material proper-ties. However, application of sensor technologies for underground mining resource extrac-tion is very limited and highly dependent on the geological and operational environment. In this study the potential of RGB imaging and FTIR spectroscopy for the characterization of polymetallic sulphide minerals in a test case of Freiberg mine was investigated. A defined imaging procedure was used to acquire RGB images. The images were georeferenced, mosaicked and a mineral map was produced using a supervised image classification tech-nique. Five mineral types have been identified and the overall classification accuracy shows the potential of the technique for the delineation of sulphide ores in an underground mine. FTIR data in combination with chemometric techniques were evaluated for discrimi-nation of the test case materials. Experimental design was implemented in order to identify optimal pre-processing strategies. Using the processed data, PLS-DA classification mo-dels were developed to assess the capability of the model to discriminate the three materi-al types. The acquired calibration and prediction statistics show the approach is efficient and provides acceptable classification success. In addition, important variables (wavel-ength location) responsible for the discrimination of the three materials type were identifi-ed.Resource Engineerin
Venous Resection During Pancreatoduodenectomy for Pancreatic Ductal Adenocarcinoma—A Multicentre Propensity Score Matching Analysis of the Recurrence After Whipple’s (RAW) Study
No full textBackground: Pancreatoduodenectomy with venous resection (PDVR) may be performed to achieve tumour clearance in patients with a pancreatic ductal adenocarcinoma (PDAC) with venous involvement. This study aimed to evaluate the impact of PDVR on PDAC outcomes. Methods: In total, 435 PDAC patients with either R0 status (n = 322) or R1 status within the superior mesenteric vein groove (n = 113) were extracted from the Recurrence After Whipple’s (RAW) study dataset. PDVR patients were matched in a 1:2 ratio with standard PD patients. Comparisons were then made between the two groups (surgical radicality and survival). Results: A total of 81 PDVRs were matched with 162 PDs. Neoadjuvant chemotherapy (5.7% vs. 13.6%, p = 0.032) and R1 resection rates (17.9% vs. 42%, p < 0.001) were higher in the PDVR group. Risk factors for R1 resection included venous resection (p < 0.001 for sleeve and p = 0.034 for segmental resection), pT3 (p = 0.007), and pN1 stage (p = 0.045). PDVR patients had lower median overall survival (OS, 21 vs. 30 months (m), p = 0.023) and disease-free survival (DFS, 17 m vs. 24 m, p = 0.043). Among PDVR patients, R status did not impact on OS (R0: 23 m, R1: 21 m, p = 0.928) or DFS (R0: 18 m, R1: 17 m, p = 0.558). Irrespective of R status, systemic recurrence was higher in the PDVR group (p = 0.034). Conclusions: Independent of R status, the PDVR group had lower overall survival and higher systemic recurrence rates
Raw Data from the Study of the Room-Temperature Superconductivity and Its Advanced Solid State
No full textThis is the raw dataset of the research article entitled "Room-temperature superconductivity in an artificial 2D metallic phononic crystal: Fabrication, properties, and application" written by Nobuyuki Zen.
Not only the raw data in the main article but also those in the Supplementary Material are included here.
"***.ogwu" can be opened with a data analysis and graphing software, Origin (OriginLab Corporation).
"***.xlsx" can be opened with Excel (Microsoft).
"PnC-Nb_i-line-Layout.GDS" is the GDSII file of the PnC pattern used in this study.
The author assumes no responsibility for any problem that may result from dealing with this data. In particular, the addition of the author as a responsible author and/or an inventor in any publication, including electronic publications, is prohibited
The Study of Process of Alternative Fuel Production from Renewable Raw Materials
No full textAbstractThe objective of the research was to study the process of biofuels production from raw materials of plant origin such as wastes of food and agricultural industry. The process includes a stage of enzymatic degradation of plant polysaccharides. The proposed method allows to produce ecologically friendly renewable biofuels and to provide partial utilization of carbohydrate-containing industrial wastes or by-products. The economic efficacy of alcohol production is increased due to the yield growth as a result of the optimization of the microbiological synthesis process.The disadvantages of existing methods of biofuel production are usage of food crops as raw materials, high labour and financial costs incurred during planting, harvesting, handling and storage of such crops and a small yield of the final product. The proposed method of biofuel production is based on the usage of non-edible raw materials of plant origin such as wastes and by-products of isolation of protein preparations from lupin seeds. The bioconversion of polysaccharide complex of feedstock to soluble carbohydrates is carried out using a composition of hydrolytic enzymes with cellulase activity of at least 3500 units gram 1 and xylanase activity of at least 2500 units gram-1. The liquid biobutanol is produced by fermentation of carbohydrate substrate obtained as a waste or a by-product after processing of raw materials with bacteria Clostridium beijerinckii
Factors Affecting Raw Material Write Off: A Case Study of the Sri Lankan Apparel Industry
No full textThe Sri Lankan apparel industry is considered as the most significant and dynamic contributor to the country’s economy. Though the industry creates profits in significant still it has many losses in financial aspects such as the cost of raw material. Therefore this research was carried out as a case study in the Sri Lankan apparel industry to identify factors affecting raw material write off. The main raw material considered in the study was fabric being the single largest cost factor in the apparel industry. This research randomly selected 85 schedules as the sample. Both primary and secondary data were used and collected through author observations, interviews and secondary data sources. The data were quantitatively analyzed with regression analysis. The results showed that both excess ordered raw material quantity and yield per yardage saving were the significant factors that affected on raw material write off in the Sri Lankan apparel industry. Further descriptive analysis revealed that pattern changes and marker improvement mainly contributed to this yield per yardage saving. The regression analysis further identified a significant relationship among the raw material write off quantity, excess ordered raw material quantity and yield per yardage saving. Also this study suggested to create a Lean manufacturing culture to minimize raw material write off in the apparel industry
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