Improving Calibration Strategy for LIBS Heavy Metals Analysis in Agriculture Applications

A new calibration procedure, known as mapping conditional-calibration laser-induced breakdown spectroscopy (LIBS), has been suggested to improve analysis results for heterogeneous samples. The procedure is based on LIBS elemental mapping, followed by signal conditioning in every sampling spot to skip signal outliers, then by finalizing the calibration curve construction. The suggested mapping conditional calibration procedure was verified for zinc analysis in soybean grist samples. The laser parameters correspond to those of the hand-held LIBS instrument in order to estimate the influence of sample surface heterogeneity under on-site analysis conditions. The laser spot (60 μm) was equal to or smaller than the typical size of grist particles (40–500 μm) but laser crater dimensions were significantly greater and varied widely (150–450 μm). The LIBS mapping of different spectral signals (atomic and ionic lines for major and minor components) was achieved. Elemental maps were normalized to achieve signal maps that were conditionally spotted to skip signal outliers. It was demonstrated that the suggested mapping conditional-calibration LIBS provided 15 ppm RMSECV for zinc determination in heterogeneous samples, which is typical for agricultural products.

Investigation of Valvetrain Dynamics Using Transient Dynamic Simulation in ANSYS

Engine valvetrain is one of the complex mechanisms in internal combustion engine as it involves many components namely, cam, pushrod, rocker lever, crosshead, intake and exhaust valves etc. Due to many components, their interactions with each other and presence of valve lash makes the system complicated to simulate. Typically, engine system level valvetrain dynamic simulation is performed in 1D software. Aim of this study is to understand the physics governing interactions and motion of the components in the valvetrain. This is done by simulating an inline 6-cylinder engine valvetrain mechanism through transient dynamic analysis in Ansys. This paper describes an approach used to simulate the valvetrain mechanism in Ansys and associated learnings. Finite Element Analysis model considers actual stiffnesses of all components. Appropriate joints/contacts are used to model the interactions. The comparative assessment of the valvetrain forces between Ansys results and 1D simulation results shows a good match. Further, 3D simulation in Ansys captures the key characteristics of valvetrain like crosshead tilting, uneven valve actuations and closing. It is also able to predict uneven contact and polishing observed on valve tip face. Overall, this study helped to ascertain the validity of 3D FEA method. This method also enhances the understanding of the valvetrain dynamics which can be helpful in further design improvements. This paper also includes a discussion on further steps to improve analysis model to make it more realistic e.g. including hot valve lash, valve seat wear etc. These improvements will help to understand effects of valve lash on valve velocities, sudden impact loads on valves, valve stresses/fatigue, pushrod buckling etc.

Binary Priority Outlier Classifier Based Outlier Elimination

Outliers are records that deviate from normal behavioral pattern. This causes a serious issue when it comes to analysing data. In the recent years there has been great research to identify these outliers. Identifying them not only helps improve analysis of data but also provides many applications. The paper presents a way of indenting these outliers based on priority assigned to the attributes. The priorities are then added for each record in the dataset and the pattern is analysed. A concept based on interquartile range is used to eliminate the outliers. Hence the classifier divides the dataset into two classes: outliers and normal data.

Study on Effect of Productivity on Applying Ergonomic Principle

This study was to investigate the effect of productivity in the construction industry due to the un-ergonomic working atmosphere. The construction industry is a large number of workers concerning industry it leads to productivity loss or due risk factors in the working site. In the review, to improve analysis a drawback, we took ergonomic awareness questionnaire survey among the Engineers in Karur district. Based on the survey results, the awareness of term ergonomics is only 20% and Engineers accept to adopt the ergonomics principles. We extended our work to apply ergonomic principles in the site. The ergonomic deficiency was identified, and gradually new ergonomic principles were applied in plastering and brickwork. 1% increase in productivity measured at 7 days of implementation.

Visual Maps for Process Research: Displaying the Invisible

In this article, we present visual maps as a way of visually representing qualitative data to improve rigor and analysis in process research. Visual representation of data is an essential element of scientific discourse, and historically scholars have put a great deal of effort into finding creative and efficient ways of visually representing quantitative data. Nevertheless, despite endeavors to integrate visual methods into organizational and management research, qualitative research still lacks a conceptual grounding of the ontological status of visual representation as well as effective tools to visually display data. We contribute to filling these gaps and start a discussion on qualitative data visualization by proposing Latour’s concept of inscription as a conceptual framework and the use of visual maps as a methodological tool for qualitative process research. We provide an analytical example of how visual mapping could become a methodological tool that enables recognizing patterns, condensing data, and comparing and examining relationships over time that are not necessarily visible independently of their representations. This also enables researchers to make sense of data, improve analysis, and theorize, thus fostering reflexive thinking and facilitating communication.

FORMS OF REHABILITATION OF A CHILD WITH AUTISM DESCRIBED IN MODERN MEDICAL LITERATURE

Introduction Autism is a complex neurodevelopmental disorder with unknown etiopathogenesis. The clinical picture of every child with autism is different. The spectrum of symptoms includes a number of characteristic features that the patient manifests. Patients often have the problem of coexisting disorders. Difficulties in communication often make it difficult to diagnose. Hence the strictly individualized rehabilitation program, which should be tailored to the needs and preferences of the patient. Effective therapy should be carried out, taking into account the patient’s motivation and pleasure. Aim A systematic review of publications for the most commonly used therapies in the rehabilitation of patients with autism and their effectiveness confirmed scientifically. Material and methods A review of the literature on the PubMed search engine has been made since 2000. Search terms used: ‘autism’, ‘ASD’, ‘therapy’, ‘physiotherapy’, ‘rehabilitation’. Results Among the articles found in the PubMed search after entering keywords, it can be stated that the majority of publications concerned alternative medicine, especially animal therapy. Others have also appeared, e.g. manual therapy, martial arts, acupuncture, choreotherapy or music therapy. Conclusions Children with autism spectrum disorders require constant rehabilitation. The form it takes depends individually on the patient’s current state. The chosen therapy may affect one deficit aspect of the child, but not improve another, for which the next treatment is required to improve. Analysis of the publication, however, indicates the positive impact of rehabilitation in children with autism.

CIM-Powered Multi-Hazard Simulation Framework Covering both Individual Buildings and Urban Areas

To improve the ability to prepare for and adapt to potential hazards in a city, efforts are being invested in evaluating the performance of the built environment under multiple hazard conditions. An integrated physics-based multi-hazard simulation framework covering both individual buildings and urban areas can help improve analysis efficiency and is significant for urban planning and emergency management activities. Therefore, a city information model-powered multi-hazard simulation framework is proposed considering three types of hazards (i.e., earthquake, fire, and wind hazards). The proposed framework consists of three modules: (1) data transformation, (2) physics-based hazard analysis, and (3) high-fidelity visualization. Three advantages are highlighted: (1) the database with multi-scale models is capable of meeting the various demands of stakeholders, (2) hazard analyses are all based on physics-based models, leading to rational and scientific simulations, and (3) high-fidelity visualization can help non-professional users better understand the disaster scenario. A case study of the Tsinghua University campus is performed. The results indicate the proposed framework is a practical method for multi-hazard simulations of both individual buildings and urban areas and has great potential in helping stakeholders to assess and recognize the risks faced by important buildings or the whole city.

Towards Extract-Transform-Load Operations in a Big Data context

Big Data emerged after a big explosion of data from the Web 2.0, digital sensors, and social media applications such as Facebook, Twitter, etc. In this constant growth of data, many domains are influenced, especially the decisional support system domain, where the integration of processes should be adapted to support this huge amount of data to improve analysis goals. The basic purpose of this research article is to adapt extract-transform-load processes with Big Data technologies, in order to support not only this evolution of data but also the knowledge discovery. In this article, a new approach called Big Dimensional ETL (BigDimETL) is suggested to deal with ETL basic operations and take into account the multidimensional structure. In order to accelerate data handling, the MapReduce paradigm is used to enhance data warehousing capabilities and HBase as a distributed storage mechanism. Experimental results confirm that the ETL operation performs well especially with adapted operations.