Search results for: incidental information processing

Authors: Rohan Shinde, Shreya Chugh

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Imagine a world where innovation is natural and not unusual. Imagine a world that works on inner wisdom rather than just information. Children live in such a world which is full of possibilities. If they learn to listen to their own intuition, genius would be common. We all are born with a natural intuitive ability to perceive beyond our senses. This is especially visible in children whose minds are still fresh, less obsessive and more in tune with nature. As we grow older, our modern lifestyle overloads with information and stresses our mind which obscures this innate intuitive capacity. The Art of Living Prajñā Yoga (Intuition Process), a 2-day program introduced for kids and teenagers between 5-18 years of age helps to kindle this intuitive ability and build confidence to act on their gut feeling. This program helps them to tap into the intuitive abilities of the mind, which is demonstrated by them seeing colors, reading text and identifying pictures with eyes closed. To make these faculties blossom and get more established, the mind needs proper nurturing and nourishment which is done in the Intuition Process. A research study has been conducted to measure these abilities manifested in students who have this program on different parameters such as confidence level, clarity of mind, problem solving skills, focus, increase in overall performance etc. The results have been plotted on the graph and conclusions are made on effectiveness of intuition process. Experience of few students with special abilities have also been documented.

Keywords: Abilities, Art of Living, Intuition, Mind

Procedia PDF Downloads 221

Authors: Zhenhua Wei, Gabriel Falzone, Bu Wang, Laurent Pilon, Gaurav Sant

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The production of ordinary Portland cement (OPC) is a CO₂ intensive process. Specifically, cement clinkering reactions require not only substantial energy in the form of heat, but also result in the release of CO₂, from limestone decarbonation and the combustion of fuel. To overcome this CO₂ intensive process, clinkering-free cementation is demonstrated by the carbonation of fly ash; i.e., a by-product of coal combustion. It is shown that in moist environments and at sub-boiling temperatures, calcium-rich fly ashes readily react with gas-phase CO₂ to provide cementation. After seven days of CO₂ exposure at 75°C, such formulations achieve a compressive strength on the order of 35 MPa and take-up 9% CO₂ (by mass of the solid). On the other hand, calcium-deficient fly ashes, due to their lack of alkalinity (i.e., abundance of mobile Ca or Mg), show little if any potential for CO₂ uptake and strength gain. The role of the CO₂ concentration and processing temperature are discussed and linked to the progress of reactions, and the development of microstructure. The outcomes demonstrate a means for enabling clinkering-free cementation while enabling beneficial utilization of CO₂ and fly ash; i.e., two abundant but underutilized industrial by-products.

Keywords: fly ash, carbonation, concrete, strength

Procedia PDF Downloads 251

Authors: Yekini Nureni Asafe, Haastrup Victor Adeleye, Ikotun Abiodun Motunrayo, Ojo Olanrewaju

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Web Based Criminal Diary is a web based application whereby data of criminals been convicted by a judge in the court of law in Nigeria are shown to the entire public. Presently, criminal records are kept manually in Nigeria, which means when a person needs to be investigated to know if the person has a criminal record in the country, there is need to pass through different manual processes. With the use of manual record keeping, the criminal records can easily be manipulated by people in charge. The focus of this research work is to design a web-based application system for criminal record in Nigeria, towards elimination of challenges (such as loss of criminal records, in-efficiency in criminal record keeping, data manipulation, and other attendant problems of paper-based record keeping) which surrounds manual processing currently in use. The product of this research work will also help to minimize crime rate in our country since the opportunities and benefits lost as a result of a criminal record create will a lifelong barriers for anyone attempting to overcome a criminal past in our country.

Keywords: court of law, criminal, criminal diary, criminal evidence, Nigeria, web-based

Procedia PDF Downloads 319

Authors: Vineetha Bettaiah, Heggere S. Ranganath

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This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.

Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman

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This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.

Keywords: sound detection, impulsive signal, background noise, neural network

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Authors: Yu-Ting Wang, Yun-Hsiang Cheng, Chien-Cheng Lin, Kun-Lin Lin

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Using a transient liquid phase method, Al was successfully bonded with Al₂O₃, which deposited Ni, Cu, Ge, and Si at the surface of the Al₂O₃ substrate after annealing at the relatively low melting point of Al. No reaction interlayer existed at the interface of any Al/Al₂O₃ specimens. Al−Fe intermetallic compounds, such as Al₉Fe₂ and Al₃Fe, formed in the Al substrate because of the precipitation of Fe, which was an impurity of the Al foil, and the reaction with Al at the grain boundaries of Al during annealing processing. According to the evaluation results of mechanical and thermal properties, the Al/Al₂O₃ specimen deposited on the Ni film possessed the highest shear strength, thermal conductivity, and bonding area percentage, followed by the Cu, Ge, and Si films. The properties of the Al/Al₂O₃ specimens deposited with Ge and Si were relatively unsatisfactory, which could be because the deposited amorphous layers easily formed oxide, resulting in inferior adhesion between Al and Al₂O₃. Therefore, the optimal choice for use in high-power devices is Al/Al₂O₃, with the deposition of Ni film.

Keywords: direct-bonded aluminum, transient liquid phase, thermal conductivity, microstructures, shear strength

Procedia PDF Downloads 159

Authors: Sakura Ganegama Bogodage, Andrew Yee Tat Leung

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This paper describes experimental, Computational Fluid Dynamics (CFD) and theoretical analysis of a cyclone performance, operated 1.0 g/m3 solid loading rate, at two different inlet velocities (5 m/s and 10 m/s). Comparing experimental results with theoretical and CFD simulation results, it is pronounced that the influence of solid in processing flow is significant than expected. Experimental studies based on gas- solid flows of cyclone separators are complicated as they required advanced sensitive measuring techniques, especially flow characteristics. Thus, CFD modelling and theoretical analysis are economical in analyzing cyclone separator performance but detailed clarifications of the application of these in cyclone separator performance evaluation is not yet discussed. The present study shows the limitations of influencing parameters of CFD and theoretical considerations, comparing experimental results and flow characteristics from CFD modelling.

Keywords: cyclone performance, inlet velocity, pressure drop, solid loading rate

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Authors: Francisco Fernandez de Castro

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The Conditional Cash Transfer (CCT) model gives monetary transfers to beneficiary families on the condition that they take specific education and health actions. According to the economic rationale of CCTs the poor need incentives to invest in their human capital because they are trapped by a lack of information and misleading beliefs. If left to their own decision, the poor will not be able to choose what is in their best interests. The basic assumption of the CCT model is that the poor need incentives to take care of their own education and health-nutrition. Due to the incentives (income cash transfers and conditionalities), beneficiary families are supposed to attend doctor visits and health talks. Children would stay in the school. These incentivized behaviors would produce outcomes such as better health and higher level of education, which in turn will reduce poverty. Based on a grounded theory approach to conduct a two-year period of qualitative data collection in northern Mexico, this study shows that this explanation is incomplete. In addition to the information failure and inadequate beliefs, there are structural barriers in everyday life of households that make health-nutrition and education investments difficult. In-depth interviews and observation work showed that the program takes for granted local conditions in which beneficiary families should fulfill their co-responsibilities. Data challenged the program’s assumptions and unveiled local obstacles not contemplated in the program’s design. These findings have policy and research implications for the CCT agenda. They bring elements for late programming due to the gap between the CCT strategy as envisioned by policy designers, and the program that beneficiary families experience on the ground. As for research consequences, these findings suggest new avenues for scholarly work regarding the causal mechanisms and social processes explaining CCT outcomes.

Keywords: conditional cash transfers, incentives, poverty, structural barriers

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Authors: Polycarpe Feussi

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Globalization, technological and customer increasing changes, amongst other drivers, result in higher levels of uncertainty and unpredictability for organizations. In order for organizations to cope with the uncertain and fast-changing economic and business environment, these organizations need to innovate in order to achieve flexibility. In simple terms, the organizations must develop strategies leading to the ability of these organizations to provide horizontal information connections across the supply chain to create and deliver products that meet customer needs by synchronization of customer demands with product creation. The generated information will create efficiency and effectiveness throughout the whole supply chain regarding production, storage, and distribution, as well as eliminating redundant activities and reduction in response time. In an integrated supply chain, spanning activities include coordination with distributors and suppliers. This paper explains how through postponement strategies, flexibility can be achieved in an organization. In order to achieve the above, a thorough literature review was conducted via the search of online websites that contains material from scientific journal data-bases, articles, and textbooks on the subject of postponement and flexibility. The findings of the research are found in the last part of the paper. The first part introduces the concept of postponement and its importance in supply chain management. The second part of the paper provides the methodology used in the process of writing the paper.

Keywords: postponement strategies, supply chain management, flexibility, logistics

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Authors: O. J. G. Somsen

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One of the tasks of optical surveillance is to detect anomalies in large amounts of image data. However, if the size of the anomaly is very small, limited information is available to distinguish it from the surrounding environment. Spectral detection provides a useful source of additional information and may help to detect anomalies with a size of a few pixels or less. Unfortunately, spectral cameras are expensive because of the difficulty of separating two spatial in addition to one spectral dimension. We investigate the possibility of modifying a simpler spectral line detector for outdoor detection. This may be especially useful if the area of interest forms a line, such as the horizon. We use a monochrome CCD that also enables detection into the near infrared. A simple camera is attached to the setup to determine which part of the environment is spectrally imaged. Our preliminary results indicate that sensitive detection of very small targets is indeed possible. Spectra could be taken from the various targets by averaging columns in the line image. By imaging a set of lines of various width we found narrow lines that could not be seen in the color image but remained visible in the spectral line image. A simultaneous analysis of the entire spectra can produce better results than visual inspection of the line spectral image. We are presently developing calibration targets for spatial and spectral focusing and alignment with the spatial camera. This will present improved results and more use in outdoor application

Keywords: anomaly detection, spectroscopic line imaging, image analysis, outdoor detection

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Authors: Moez ul Hassan, Bushra Noman, Sarmad Hameed, Shahab Mehmood, Asma Bashir

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The importance of Noble prize winning “Patch Clamp Technique” is well documented. However, Patch Clamp Technique is very expensive and hence hinders research in developing countries. In this paper, detection, processing and recording of ultra low current from induced cells by using transimpedence amplifier is described. The sensitivity of the proposed amplifier is in the range of femto amperes (fA). Capacitive-feedback is used with active load to obtain a 20MΩ transimpedance gain. The challenging task in designing includes achieving adequate performance in gain, noise immunity and stability. The circuit designed by the authors was able to measure current in the rangeof 300fA to 100pA. Adequate performance shown by the amplifier with different input current and outcome result was found to be within the acceptable error range. Results were recorded using LabVIEW 8.5®for further research.

Keywords: drug discovery, ionic current, operational amplifier, patch clamp

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Authors: Ariful Islam, Showkat Ahmad Lone

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Statistical distributions have long been employed in the assessment of semiconductor devices and product reliability. The power function-distribution is one of the most important distributions in the modern reliability practice and can be frequently preferred over mathematically more complex distributions, such as the Weibull and the lognormal, because of its simplicity. Moreover, it may exhibit a better fit for failure data and provide more appropriate information about reliability and hazard rates in some circumstances. This study deals with estimating information about failure times of items under step-stress partially accelerated life tests for competing risk based on adoptive type-I progressive hybrid censoring criteria. The life data of the units under test is assumed to follow Mukherjee-Islam distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameters and tampering coefficient. The performances of the resulting estimators of the developed model parameters are evaluated and investigated by using a simulation algorithm.

Keywords: adoptive progressive hybrid censoring, competing risk, mukherjee-islam distribution, partially accelerated life testing, simulation study

Procedia PDF Downloads 347

Authors: K. Malak, A. Nourah, S.Liyakathunisa

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Nowadays, healthcare services are facing many challenges since they are becoming more complex and more needed. Every detail of a patient’s interactions with health care providers is maintained in Electronic Health Records (ECR) and Healthcare information systems (HIS). However, most of the existing systems are often focused on documenting what happens in manual health care process, rather than providing the highest quality patient care. Healthcare business processes and stakeholders can no longer rely on manual processes, to provide better patient care and efficient utilization of resources, Healthcare processes must be automated wherever it is possible. In this research, a detail survey and analysis is performed on the existing health care systems in Saudi Arabia, and an automated smart medical healthcare business process model is proposed. The business process management methods and rules are followed in discovering, collecting information, analysis, redesign, implementation and performance improvement analysis in terms of time and cost. From the simulation results, it is evident that our proposed smart medical records system can improve the quality of the service by reducing the time and cost and increasing efficiency

Keywords: business process management, electronic health records, efficiency, cost, time

Procedia PDF Downloads 342

Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

Procedia PDF Downloads 189

Authors: Ahmed Elaksher, Islam Omar

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Accurate geometric relation algorithms are imperative in Earth and planetary satellite and aerial image processing, particularly for high-resolution images that are used for topographic mapping. Most of these satellites carry push-broom sensors. These sensors are optical scanners equipped with linear arrays of CCDs. These sensors have been deployed on most EOSs. In addition, the LROC is equipped with two push NACs that provide 0.5 meter-scale panchromatic images over a 5 km swath of the Moon. The HiRISE carried by the MRO and the HRSC carried by MEX are examples of push-broom sensor that produces images of the surface of Mars. Sensor models developed in photogrammetry relate image space coordinates in two or more images with the 3D coordinates of ground features. Rigorous sensor models use the actual interior orientation parameters and exterior orientation parameters of the camera, unlike approximate models. In this research, we generate a generic push-broom sensor model to process imageries acquired through linear array cameras and investigate its performance, advantages, and disadvantages in generating topographic models for the Earth, Mars, and the Moon. We also compare and contrast the utilization, effectiveness, and applicability of available photogrammetric techniques and softcopies with the developed model. We start by defining an image reference coordinate system to unify image coordinates from all three arrays. The transformation from an image coordinate system to a reference coordinate system involves a translation and three rotations. For any image point within the linear array, its image reference coordinates, the coordinates of the exposure center of the array in the ground coordinate system at the imaging epoch (t), and the corresponding ground point coordinates are related through the collinearity condition that states that all these three points must be on the same line. The rotation angles for each CCD array at the epoch t are defined and included in the transformation model. The exterior orientation parameters of an image line, i.e., coordinates of exposure station and rotation angles, are computed by a polynomial interpolation function in time (t). The parameter (t) is the time at a certain epoch from a certain orbit position. Depending on the types of observations, coordinates, and parameters may be treated as knowns or unknowns differently in various situations. The unknown coefficients are determined in a bundle adjustment. The orientation process starts by extracting the sensor position and, orientation and raw images from the PDS. The parameters of each image line are then estimated and imported into the push-broom sensor model. We also define tie points between image pairs to aid the bundle adjustment model, determine the refined camera parameters, and generate highly accurate topographic maps. The model was tested on different satellite images such as IKONOS, QuickBird, and WorldView-2, HiRISE. It was found that the accuracy of our model is comparable to those of commercial and open-source software, the computational efficiency of the developed model is high, the model could be used in different environments with various sensors, and the implementation process is much more cost-and effort-consuming.

Keywords: photogrammetry, push-broom sensors, IKONOS, HiRISE, collinearity condition

Procedia PDF Downloads 63

Authors: Rana Mohamed, Ahmed E. Gomaa, Gehan Safwat, Ayman Diab

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Background: Bio-fabrication is a multidisciplinary research field that combines several principles, fabrication techniques, and protocols from different fields. The open-source-software movement is a movement that supports the use of open-source licenses for some or all software as part of the broader notion of open collaboration. Additive manufacturing is the concept of 3D printing, where it is a manufacturing method through adding layer-by-layer using computer-aided designs (CAD). There are several types of AM system used, and they can be categorized by the type of process used. One of these AM technologies is Digital light processing (DLP) which is a 3D printing technology used to rapidly cure a photopolymer resin to create hard scaffolds. DLP uses a projected light source to cure (Harden or crosslinking) the entire layer at once. Current applications of DLP are focused on dental and medical applications. Other developments have been made in this field, leading to the revolutionary field 3D bioprinting. The open-source movement was started to spread the concept of open-source software to provide software or hardware that is cheaper, reliable, and has better quality. Objective: Modification of desktop 3D printer into 3D bio-printer and the integration of DLP technology and bio-fabrication to produce an antibacterial dental model. Method: Modification of a desktop 3D printer into a 3D bioprinter. Gelatin hydrogel and sodium alginate hydrogel were prepared with different concentrations. Rhizome of Zingiber officinale, Flower buds of Syzygium aromaticum, and Bulbs of Allium sativum were extracted, and extractions were selected on different levels (Powder, aqueous extracts, total oils, and Essential oils) prepared for antibacterial bioactivity. Agar well diffusion method along with the E. coli have been used to perform the sensitivity test for the antibacterial activity of the extracts acquired by Zingiber officinale, Syzygium aromaticum, and Allium sativum. Lastly, DLP printing was performed to produce several dental models with the natural extracted combined with hydrogel to represent and simulate the Hard and Soft tissues. Result: The desktop 3D printer was modified into 3D bioprinter using open-source software Marline and modified custom-made 3D printed parts. Sodium alginate hydrogel and gelatin hydrogel were prepared at 5% (w/v), 10% (w/v), and 15%(w/v). Resin integration with the natural extracts of Rhizome of Zingiber officinale, Flower buds of Syzygium aromaticum, and Bulbs of Allium sativum was done following the percentage 1- 3% for each extract. Finally, the Antimicrobial dental model was printed; exhibits the antimicrobial activity, followed by merging with sodium alginate hydrogel. Conclusion: The open-source movement was successful in modifying and producing a low-cost Desktop 3D Bioprinter showing the potential of further enhancement in such scope. Additionally, the potential of integrating the DLP technology with bioprinting is a promising step toward the usage of the antimicrobial activity using natural products.

Keywords: 3D printing, 3D bio-printing, DLP, hydrogel, antibacterial activity, zingiber officinale, syzygium aromaticum, allium sativum, panax ginseng, dental applications

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Authors: Mohammad S. Rouhi, Magdalena Juntikka

Abstract:

Processing of polymer fiber composites has a remarkable influence on their mechanical performance. These mechanical properties are even more influenced when using recycled reinforcement. Therefore, we place particular attention on the evaluation of micromechanical models to estimate the mechanical properties and compare them against the experimental results of the manufactured composites. For the manufacturing process, an epoxy matrix and carbon fiber production cut-offs as reinforcing material are incorporated using a vacuum infusion process. In addition, continuous textile reinforcement in combination with the epoxy matrix is used as reference material to evaluate the kick-down in mechanical performance of the recycled composite. The experimental results show less degradation of the composite stiffness compared to the strength properties. Observations from the modeling also show the same trend as the error between the theoretical and experimental results is lower for stiffness comparisons than the strength calculations. Yet still, good mechanical performance for specific applications can be expected from these materials.

Keywords: composite recycling, carbon fibers, mechanical properties, micromechanics

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Authors: Diana G. Ramirez-Wong, Marius Ramirez, Regina Sanchez-Leija, Adriana Rugerio, R. Araceli Mauricio-Sanchez, Martin A. Hernandez-Landaverde, Arturo Carranza, John A. Pojman, Josue D. Mota-Morales, Gabriel Luna-Barcenas

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Chitin films were prepared using alpha-chitin from shrimp shells as raw material and a simple method of precipitation-evaporation. Choline chloride: urea Deep Eutectic Solvent (DES) was used to disperse chitin and compared against hexafluoroisopropanol (HFIP). A careful analysis of the chemical and crystalline structure was followed along the synthesis of the films, revealing crystalline-phase transitions. The full conversion of alpha- to beta-, or alpha- to gamma-chitin structure were detected by XRD and NMR on the films. The synthesis of highly crystalline monophasic gamma-chitin films was achieved using a DES; whereas HFIP helps to promote the beta-phase. These results are encouraging to continue in the study of DES as good processing media to control the final properties of chitin based materials.

Keywords: chitin, deep eutectic solvent, polymorph, phase transformation

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Authors: Jeonghwan Jeon, Mintak Han, Youngjun Kim

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Due to the rapid development of information and communication technology (ICT), a substantial transformation is currently happening in the society. As the range of intelligent technologies and services is continuously expanding, ‘things’ are becoming capable of communicating one another and even with people. However, such “Internet of Things” has the technical weakness so that a great amount of such information transferred in real-time may be widely exposed to the threat of security. User’s personal data are a typical example which is faced with a serious security threat. The threats of security will be diversified and arose more frequently because next generation of unfamiliar technology develops. Moreover, as the society is becoming increasingly complex, security vulnerability will be increased as well. In the existing literature, a considerable number of private and public reports that forecast future society have been published as a precedent step of the selection of future technology and the establishment of strategies for competitiveness. Although there are previous studies that forecast security technology, they have focused only on technical issues and overlooked the interrelationships between security technology and social factors are. Therefore, investigations of security threats in the future and security technology that is able to protect people from various threats are required. In response, this study aims to derive potential security threats associated with the development of technology and to explore the security technology that can protect against them. To do this, first of all, private and public reports that forecast future and online documents from technology-related communities are collected. By analyzing the data, future issues are extracted and categorized in terms of STEEP (Society, Technology, Economy, Environment, and Politics), as well as security. Second, the components of potential security threats are developed based on classified future issues. Then, points that the security threats may occur –for example, mobile payment system based on a finger scan technology– are identified. Lastly, alternatives that prevent potential security threats are proposed by matching security threats with points and investigating related security technologies from patent data. Proposed approach can identify the ICT-related latent security menaces and provide the guidelines in the ‘problem – alternative’ form by linking the threat point with security technologies.

Keywords: future society, information and communication technology, security technology, technology forecasting

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Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

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The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.

Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing

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Authors: Chaudhary Itisha, Shankar Manu

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Patient satisfaction represents a crucial aspect in the evaluation of health care services. Preoperative teaching provides the patient with pertinent information concerning the surgical process and the intended surgical procedure as well as anticipated patient behavior (anxiety, fear), expected sensation, and the probable outcomes. Although patient education is part of Accreditation protocols, it is not uniform at most places. The aim of this study was to try to assess the benefit of preoperative patient education on selected post-operative outcome parameters; mainly, post-operative pain scores, requirement of additional analgesia, return to activity of daily living and overall patient satisfaction, and try to standardize few education protocols. Dependent variables were measured before and after the treatment on a study population of 302 volunteers. Educational intervention was provided by the Investigator in the preoperative period to the study group through personal counseling. An information booklet contained detailed information was also provided. Statistical Analysis was done using Chi square test, Mann Whitney u test and Fischer Exact Test on a total of 302 subjects. P value <0.05 was considered as level of statistical significance and p<0.01 was considered as highly significant. This study suggested that patients who are given a structured, individualized and elaborate preoperative education and counseling have a better ability to cope up with postoperative pain in the immediate post-operative period. However, there was not much difference when the patients have had almost complete recovery. There was no difference in the requirement of additional analgesia among the two groups. There is a positive effect of preoperative counseling on expected return to the activities of daily living and normal work schedule. However, no effect was observed on the activities in the immediate post-operative period. There is no difference in the overall satisfaction score among the two groups of patients. Thus this study concludes that there is a positive benefit as suggested by the results for pre-operative patient education. Although the difference in various parameters studied might not be significant over a long term basis, they definitely point towards the benefits of preoperative patient education. 

Keywords: patient education, post-operative pain, postoperative outcomes, patient satisfaction

Procedia PDF Downloads 339

Authors: Melissa C. Monney

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Psychological testing has been of interest to researchers for many years as useful tools in assessing and diagnosing various disorders as well as to assist in understanding human behavior. However, for over 20 years now, researchers and laypersons alike have been interested in using them for other purposes, such as determining factors in employee selection, promotion, and even termination. In recent years, psychological assessments have been useful in facilitating workplace decision processing, regarding employee circulation within organizations. This literature review explores four of the most commonly used psychological tests in workplace environments, namely cognitive ability, emotional intelligence, integrity, and personality tests, as organizations have used these tests to assess different factors of human behavior as predictive measures of future employee behaviors. The findings suggest that while there is much controversy and debate regarding the validity and reliability of these tests in workplace settings as they were not originally designed for these purposes, the use of such assessments in the workplace has been useful in decreasing costs and employee turnover as well as increase job satisfaction by ensuring the right employees are selected for their roles.

Keywords: cognitive ability, personality testing, predictive validity, workplace behavior

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Authors: Cesar Maximo Oliva González, Javier Acevedo Cortez, Boris Kharisov, Thelma Serrano Quezada

Abstract:

The importance of the crude oil refining process is due to the demand for petroleum products such as gasoline, kerosene, asphalt, etc., which are used in daily activities and have a high impact on the global economy. In the processes of oil obtaining and refining, it is common to find problems such as spills on seabed and high energy consumption in processing. In order to quickly and efficiently attack these problems, the use of adsorbents has taken on great importance due to its ease of implementation, as well as the possibility of their regeneration to be reused. In this work, the use of two types of adsorbents is proposed: the first is a natural adsorbent such as aloe vera or nopal, which were lyophilized and hydrophobized to achieve a selectivity in oil adsorption in oil / water mixtures. The second is a mixed iron/nickel oxide, which is specially designed to adsorb the asphaltenes in the heavy fractions of the oil; in addition, this type of adsorbents presents catalytic properties that manage to decompose the heavier fractions of the petroleum in light hydrocarbons, descending thus the energy required for the oil refining process.

Keywords: nanomaterials, oil spills, remediation, natural adsorbents, mixed oxides

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Authors: Mazharuddin Syed Ahmed

Abstract:

This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

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Authors: Chattrarat Hotrawaisaya

Abstract:

This research aims to formulate the logistics collaborative model which is the management tool for orchid flower exporter. The researchers study logistics activities in orchid supply chain that stakeholders can collaborate and develop, including demand forecasting, inventory management, warehouse and storage, order-processing, and transportation management. The research also explores logistics collaboration implementation into orchid’s stakeholders. The researcher collected data before implementation and after model implementation. Consequently, the costs and efficiency were calculated and compared between pre and post period of implementation. The research found that the results of applying the logistics collaborative model to orchid exporter reduces inventory cost and transport cost. The model also improves forecasting accuracy, and synchronizes supply chain of exporter. This research paper contributes the uniqueness logistics collaborative model which value to orchid industry in Thailand. The orchid exporters may use this model as their management tool which aims in competitive advantage.

Keywords: logistics, orchid, supply chain, collaboration

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Authors: Yan Zhang

Abstract:

Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Qingsheng Qi, Cuijuan Gao, Carol Sze Ki Lin

Abstract:

Food waste can be defined as a by-product of food processing by industries and consumers, which has not been recycled or used for other purposes. Stringent waste regulations worldwide are pushing local companies and sectors towards higher sustainability standards. The development of novel strategies for food waste re-use is economically and environmentally sound, as it solves a waste management issue and represents an inexpensive nutrient source for biotechnological processes. For example, Yarrowia lipolytica is a yeast which can utilize hydrophobic substrates, such as fatty acids, lipids, and alkanes and simple carbon sources, such as glucose and glycerol, which can all be found in food waste. This broad substrate range makes Y. lipolytica a promising candidate for the degradation and valorisation of food waste, and for the production of organic acids, such as citric and α-ketoglutaric acids. Current research conducted in our group demonstrated that Y. lipolytica was shown to be able to produce succinic acid. In this talk, we will focus on the application of genetically modified yeast Y. lipolytica for fermentative succinic acid production with an aim to increase productivity and yield.

Keywords: food waste, succinic acid, Yarrowia lipolytica, bioplastic

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Authors: Milena Nanova, Radul Shishkov, Martin Georgiev, Damyan Damov

Abstract:

This research paper presents an in-depth exploration of the use of generative design in urban residential architecture, with a dual focus on aligning aesthetic values with legal and environmental constraints. The study aims to demonstrate how generative design methodologies can innovate residential building designs that are not only legally compliant and environmentally conscious but also aesthetically compelling. At the core of our research is a specially developed generative design framework tailored for urban residential settings. This framework employs computational algorithms to produce diverse design solutions, meticulously balancing aesthetic appeal with practical considerations. By integrating site-specific features, urban legal restrictions, and environmental factors, our approach generates designs that resonate with the unique character of urban landscapes while adhering to regulatory frameworks. The paper explores how modern digital tools, particularly computational design, and algorithmic modelling, can optimize the early stages of residential building design. By creating a basic parametric model of a residential district, the paper investigates how automated design tools can explore multiple design variants based on predefined parameters (e.g., building cost, dimensions, orientation) and constraints. The paper aims to demonstrate how these tools can rapidly generate and refine architectural solutions that meet the required criteria for quality of life, cost efficiency, and functionality. The study utilizes computational design for database processing and algorithmic modelling within the fields of applied geodesy and architecture. It focuses on optimizing the forms of residential development by adjusting specific parameters and constraints. The results of multiple iterations are analysed, refined, and selected based on their alignment with predefined quality and cost criteria. The findings of this research will contribute to a modern, complex approach to residential area design. The paper demonstrates the potential for integrating BIM models into the design process and their application in virtual 3D Geographic Information Systems (GIS) environments. The study also examines the transformation of BIM models into suitable 3D GIS file formats, such as CityGML, to facilitate the visualization and evaluation of urban planning solutions. In conclusion, our research demonstrates that a generative parametric approach based on real geodesic data and collaborative decision-making could be introduced in the early phases of the design process. This gives the designers powerful tools to explore diverse design possibilities, significantly improving the qualities of the investment during its entire lifecycle.

Keywords: architectural design, residential buildings, urban development, geodesic data, generative design, parametric models, workflow optimization

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Authors: Elizaveta Petelina, Anton Sizo

Abstract:

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

Procedia PDF Downloads 161