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Historians and librarians are interested in watermarks and mould surface patterns in historic papers, because they represent the “fingerprints” of antique papers. However, these features are usually covered or hidden by printing, writing or other media. Different techniques have been developed to extract the watermarks in the paper while avoiding interference from media on the paper. Beta radiography provides good results, but this method cannot be widely used because of radiation safety regulations and the long exposure times required due to weak isotope sources employed. In this work, two promising methods are compared which can be used to extract digital high-resolution images for paper watermarks and these are electron radiography and low energy X-ray radiography. For electron radiography a “sandwich” of a lead sheet, the paper object, and a film in a dark cassette, is formed and it is exposed at higher X-ray potentials (> 300 kV). The photoelectrons escaping from the lead sheet penetrate the paper and expose the film. After development, the film captures the watermark and mould surface pattern Images for the paper being investigated. These images are then digitized using an X-ray film digitizer. The film employed could potentially be replaced by a special type of imaging plate with a very thin protection layer to directly generate digital Images using computed radiography (CR). For the second method, a low energy X-ray source is used with the specimen paper placed on a digital detector array (DDA). This method directly generates a low energy digital radiography (DR) image. Both methods provide high quality images without interference from the printing media, and provide the potential to generate a “fingerprint” database for historical papers. There were nevertheless found to be differences in the images obtained using the two methods. The second method, using a low energy X-ray source, has the potential to be integrated in a portable device with a small footprint incorporating user safety requirements. Differences obtained using the two methods are shown and discussed.

EMG is a medical technique that measures muscle response or electrical activity in response to a nerve’s stimulation of the muscle [10]. In this paper we have classified multiple hand gestures using small number of electrodes. This report aims to review current use of EMG based control system and explain the existing challenges. The stages involved includes data acquisition, feature extraction, classification and controller. Some of the application includes Arm rehabilitation, game controller, wheel chair controllers, etc.

The use of digital tools in algebra education is expected to not only contribute to master skill, but also to acquire conceptual understanding. The question is how digital tools affect students” thinking and understanding. This paper presents an analysis of data of one group of three grade seventh students (12-13 year-old) on the use of a digital tool for algebra, the Cover-up applet for solving equations in particular. This case study was part of a larger teaching experiment on initial algebra enriched with digital technology which aimed to improve students” conceptual understanding and skills in solving equations in one variable. The qualitative analysis of a video observation, digital and written work showed that the use of the applet affects student thinking in terms of strategies used by students while dealing with the equations. We conclude that the effects of the use of the digital tool can be traced from student problem solving strategies on paper-and-pencil environment which are similar to strategies while working with the digital tool. In future research, we recommend to use specific theoretical lenses, such as the theory of instrumental genesis and the onto-semiotic approach, to reveal more explicit relationships between students” conceptual understanding and the use of a digital tool.

The concept of using network centrality measures in the selection process of memetic differential evolution algorithm is proposed. The usual aim for introducing changes in global optimization algorithms is to make it perform better. This short paper does not intend to provide enough experimental details to decide upon the performance of the new method, nevertheless, we definitely obtain interesting insights on how the discovery of local optima were done.

This paper presents a short review on terahertz imaging systems based on several types of technology used in the terahertz detection schemes. Some commercial products from ThruVision Systems Limited Company have utilized GaAs Schottky diode detector at 0.25 THz to produce passive terahertz images for public and homeland security. On the other hand, TeraSense Group Incorporated Company has developed and invented a ground-breaking technology which employs sensor consisting of a matrix of plasmonic semiconductor detectors in their latest products to generate terahertz images in the 0.1 – 1.0 THz frequency range. Recently, the utilization of two-terminal unipolar nanodiodes, known as the self-switching diodes (SSDs), as terahertz detectors has shown promising results. The planar structure of SSD not only enables the device to operate at high frequencies due to low intrinsic parasitic capacitance, but also allows the realization of the device using only a single lithography step. This makes the fabrication process of SSDs faster, more simple, and at lower cost when compared to other electronic devices such as Schottky diodes. The development and recent achievement of SSDs as terahertz detectors are also presented in this paper.

The main goal of this paper to evaluate the performance of the proposed long short-term memory (LSTM)- basis relative humidity (RH) prediction model. Computational physics learning theory is a subfield in artificial intelligence. In this paper, we use the real observed weather data of RH from synoptic station location as an important aspect and effect in weather and climate and using machine learning approach basis on the LSTM neural network, which is a type of recurrent neural network (RNN). We use a machine learning approach to compute the relative humidity basis on the LSTM model. The LSTM is trained by using two years of climate data (from January 2008 to December 2009). LSTM is capable of forecasting complex univariate relative humidity time series with strong no-stationarity. The result shows the usefulness of LSTM and out performs traditional forecasting methods in the challenging relative humidity record problem.

The analytical description of the melt flow within the co-rotating twin screw extruder has been issued in various publications and it is an integral part of calculation models, software solutions for simulating polymer compounding processes such as SIGMA. Nevertheless, the accuracy of an analytical model depends on the defined simplifications. The more simplifications within the analytical description, the more deviation between the technical system and the calculation model. Analytical models for twin screw processes are no exception and are subject to simplifications and adaptations due to the complex geometry and the transient flow field. Therefore, the use of the kinematical inversion principle, the exchange of the original screw channel geometry and the consideration of an evenly distributed pressure gradient are commonly used simplifications for calculations models. In this paper a new analytical approach to calculate the melt flow is presented. The model is based on numerical simulations and with the use of the performance mapping method an analytical calculation method is derived. The advantage of the performance mapping method is that the original channel geometry and kinematical behavior of the twin screws are considered and the transient flow field in the system is used to generate a wide range of performance maps. Within the scope of this work, the performance maps of the melt conveyance and the pressure gradient in the fully filled screw channel are quantitatively examined with the aid of specially defined evaluation routines. Characteristic operating points are identified by the conveying characteristics of the melt which are displayed in the performance maps. The validation of this new analytical approach by using the performance mapping method with numerical data demonstrated that the two-dimensional description of the melt flow within the screw channel flow has a deviation of less than 10 % for varying flow law exponents geometry and process parameters.The analytical description of the melt flow within the co-rotating twin screw extruder has been issued in various publications and it is an integral part of calculation models, software solutions for simulating polymer compounding processes such as SIGMA. Nevertheless, the accuracy of an analytical model depends on the defined simplifications. The more simplifications within the analytical description, the more deviation between the technical system and the calculation model. Analytical models for twin screw processes are no exception and are subject to simplifications and adaptations due to the complex geometry and the transient flow field. Therefore, the use of the kinematical inversion principle, the exchange of the original screw channel geometry and the consideration of an evenly distributed pressure gradient are commonly used simplifications for calculations models. In this paper a new analytical approach to calculate the melt flow is presented. The model is based on numerical simulations and with t...

This paper introduces a procedure to evaluate the wear state of non-return valves based on process and machine data of injection molding machines. In industry, non-return valves of injection molding machines are often replaced following specified maintenance intervals. Due to conservative lifetime estimations, the replacement of non-return valves is often carried out too early, since the current state of wear of the non-return valves is not known without elaborate disassembly and in case of failure other adjacent components can also be damaged. This paper shows an approach for an automated condition monitoring of non-return valves. During production, the corresponding wear state is evaluated without the use of additional sensors. By analyzing the curves of pressure, position signals etc. from process data with injection molding process monitoring tools, specific key figures were defined. These key figures allow wear-specific conclusions about the different signs of wear and thereby allow an estimation of the current wear state of the non-return valve. Based on the current state of wear, it is possible to predict the remaining service life of the non-return valve. The knowledge of the remaining service life leads to increased machine uptime while reducing storage and maintenance costs for plastic processing companies.

Proper description of large deformation of the continuum or the shell requires dealing with curved spaces and application of tensor analysis and distinguishing of covariant and contravariant basis.Thanks to symbolic computations and visualization capabilities of the Mathematica system, this task can be carried out straightfor- ward. It has been already discussed in [1] and [2]. This paper is a further extension of them.First it will be shown that the deformation is indeed changing of curvature of the considered space. Next, there will be shown how Cartesian basis of the flat undeformed space splits to the covariant and contravariant ones and that this basis changes in the space. It makes possible to explain why we have to introduce covariant derivatives and Christoffel symbols, for example. It is important in case of the optical analysis of large deformations of thin wall structures.Moreover it is possible to easily explain that strain tensor is defined with change of metric tensor. It also helps to show the idea of material (Lagrangian) and spatial (Eulerian) description of the deformation and the motion and avoid misunderstandings in this matter.Everything is visualised with 3D graphical capabilities and interactive maniputation of the plots provided within the Mathematica system.This paper can be also usefull inspiration both in teaching and learning of the Continuum Mechanics, the Theory of Shells and Thin-Wall Structures.The work has been presented at the conference Polish Congress of Mechanics, Computer Methods in Mechanics PCM-CMM-2019 in Krakow.

The paper presents considerations regarding the process of determining the fuel consumption from diesel locomotive engines. In order to know the actual fuel consumption for a given engine, depending on the parameters of the drive system operation, it is necessary to carry out activities aimed at determining its operational indicators. This can be achieved by performing tests in real driving conditions or calculating fuel consumption using a calculation method based on the engine operating conditions. The paper presents the fuel consumption of a Stage II approved locomotive engine, which is used to drive various types of off-road machines and rail vehicles. The presented results of fuel consumption include the values determined on the resistor at set operating points and in real operating conditions. Using the assumptions of the vehicle’s operating time density characteristics, a computational method for assessing the fuel consumption of traction locomotives was developed. When comparing the results of bench and real measurements, the influence of the work parameters variability on fuel consumption was determined. In the summary, conclusions regarding the developed method were formulated, and reference was made to the possibility of using this tool to assess the ecological indicators of rail vehicles.

Currently, a significant increase in the interest of the triangle grid stiffened plates and panels can be observed. Isogrid, which is equilateral triangle grid concept, was developed in 1964 by NASA as extremely efficient light-weight structures used in space program. Recently, development of machine tools, made it possible to reduce the costs of manufacturing and allowed for wider application of such structures. Paper presents preliminary experimental and numerical investigations of square isosceles triangle grid stiffened plate under pure shear loading condition. Different ways of FEM modeling of plate were considered and analyzed for simple load cases. Critical and post-critical states of deformation were compared to results of experiment conducted with use of 3D DIC system.Currently, a significant increase in the interest of the triangle grid stiffened plates and panels can be observed. Isogrid, which is equilateral triangle grid concept, was developed in 1964 by NASA as extremely efficient light-weight structures used in space program. Recently, development of machine tools, made it possible to reduce the costs of manufacturing and allowed for wider application of such structures. Paper presents preliminary experimental and numerical investigations of square isosceles triangle grid stiffened plate under pure shear loading condition. Different ways of FEM modeling of plate were considered and analyzed for simple load cases. Critical and post-critical states of deformation were compared to results of experiment conducted with use of 3D DIC system.

One of the innovations which has a major impact on education in the era of industrial revolution 4.0 is virtual laboratory. Virtual lab accommodates practical education with all limitations that exist, like tools and materials of practical equipment in schools which isn’t in line with the current technology. Although virtual laboratories have been realized as a supporting tool in learning process, their applications in vocational education have not been extensively explored yet. With the learning characteristics of the vocational which are a fairly large proportion of practical compared to theoretical activities. This paper reviews the latest developments of virtual labs to gain insight into the various virtual laboratories that may relevant to vocational education. This study used a systematic literature review of selected research papers based on relevant keywords of the virtual lab in vocational education. Insights from the papers reviewed subsequently were developed to elaborate on the use of a virtual lab to be applied in vocational education. Practical learning in vocational education with a virtual lab becomes more flexible without limited space and time. In terms of financing, the development of a virtual lab doesn’t require a large amount of investment if compared with actual laboratory development. For a long period of implementation, there must be added a basic learning process before used, the user has to get experience-based learning first that emphasizes the role of active experience and student involvement. The virtual lab can be applied to practical learning in vocational education, for example in the field of mechanical engineering it can be applied in learning to maintain fuel systems on the engine, with characteristics in the form of procedural steps. The virtual lab can be applied to facilitate students in the learning process so the learning efficiency can increase significantly.

In Formula Society of Automotive Engineering (SAE) competition, the design of efficient and powerful combustion engine is required. This paper discussed optimization of gasoline engine using Killer Whale algorithm. The modelling of gasoline engine was built using Multi-Layer Perceptron - Artificial Neural Network (MLP-ANN). A gasoline engine was simulated using Ricardo Wave commercial software to acquire data for training and testing the proposed ANN. The ANN weights were determined by utilizing Levenberg-Marquardt algorithm. The objective function in this paper is to maximize power, minimize the Brake Specific Fuel Consumption (BSFC) and minimize the operational cost. The optimized variables are engine speed (rpm), Air Fuel Ratio (AFR), Mass Fuel Flow (MFF), Intake Pressure (IP), Intake Air Temperature (IAT), Combustion Start (CS) and Throttle Angle (TA). Root Mean Square Error (RMSE) of ANN modelling is 0.021 kW for power and 0.00032 kg/kW.hr for BSFC. The optimization results show that the power increases to 13%, BSFC decreases to 11% and the cost operation decreases to 23% compare with existing design variables

Nanopositioning techniques present an important capability to support the state-of-the-art synchrotron radiation instrumentation research for the Advanced Photon Source (APS) operations and upgrade project. To overcome the performance limitations of precision ball-bearing-based or roller-bearing-based stage systems, compact nanopositioning flexure stages have been designed and developed at the APS for x-ray beamline instrumentation applications. Recent progress of such stages development is discussed in this paper, which includes: rotary flexure stages with degrees travel range and 10-nrad-level resolution for x-ray monochromators and analysers, tip-tilting flexure stages for K-B mirror based nanofocusing hard x-ray optics, and linear vertical and horizontal nanopositioning flexure stages with centimeter-level travel range and microradian-level motion trajectory reproducibility for x-ray optics and sample manipulation. The mechanical design and preliminary test results are described in this paper.

In recent years many of the people are suffering from diabetics which may result damaging the human eye sights by damaging the blood vessels of the retinal by form exudates around the optic disc. In this paper, we intend to build retinal exudates from fundus image to predict the severity of diabetics resulting in blood vessels tissue damages. In order to analysis the blood vessels damage and diabetic severity initially we use appropriate image pre-processing techniques to remove any noise from the retinal funds image, to remove the noise in this paper we use wavelet transform and first order Gaussian derivative and matched filter to segment the fundus image by rotating the original image by certain angle. The filtered data is stored in the matched filter bank, then by applying k-NN clustering technique to identify minimum value in each filter bank and marking such minimum value center of k-nearest neighbor value. Further, Support vector machine a supervised learning algorithm is applied to the identified k-nearest neighbor values thereby predicting the severity of blood vessel tissue damage from the fundus image.

This paper mainly studies the development status and model of power battery. The performance of different battery is analyzed from several aspects. The models are also evaluated and analyzed. The article is presented in a large number of charts which is able to compare or query the performance of different batteries more intuitively. This paper also has reference value to related fields.

The development of spacecraft large-sized reflectors is one of the most urgent issues for the space industry. The reflector structure is to meet such principle criteria as high accuracy in reflective surface configuration and weight. The accuracy in the reflective surface configuration during continuous operation is ensured by the control system. The authors suggest using piezo motors in the control system. The motors of such type of certain small mass-overall characteristics can create high force. This paper presents a new piezo motor design and its operation. A mathematic model of piezo motor operation modes has been worked out which became the basis for setting new designed piezo motor operation modes depending on different loads. The results of the experimental tests of the new designed piezo motor confirmed the results of the theoretical calculations.The development of spacecraft large-sized reflectors is one of the most urgent issues for the space industry. The reflector structure is to meet such principle criteria as high accuracy in reflective surface configuration and weight. The accuracy in the reflective surface configuration during continuous operation is ensured by the control system. The authors suggest using piezo motors in the control system. The motors of such type of certain small mass-overall characteristics can create high force. This paper presents a new piezo motor design and its operation. A mathematic model of piezo motor operation modes has been worked out which became the basis for setting new designed piezo motor operation modes depending on different loads. The results of the experimental tests of the new designed piezo motor confirmed the results of the theoretical calculations.

As various international and government institutions have decreed that electronic devices must adhere to electromagnetic safety standards before they enter the market, electromagnetic shielding has become an important aspect of design considerations. Various materials at different price points have specific characteristics that may cause them to become either optimal or ill-fitting for specific applications, however, testing their shielding capability can be difficult without the expensive equipment in testing facilities. In this paper, a handheld electromagnetic (EM) meter was used in a simplified test set up to assess the shielding effectiveness of 6 shielding materials: silver sleeve, steel mesh, conductive ABS, Al tape, and Al metallised film. Silver sleeve, Al tape, and Al metallised film were chosen to shield a robotic medical device based on their shielding capability, cost-effectiveness, and design flexibility. The CISPR 11 radiated emissions test results of the robotic medical device validated the shielding effectiveness of the materials chosen showing that the handheld EM meter was able to assess the materials’ shielding capability.As various international and government institutions have decreed that electronic devices must adhere to electromagnetic safety standards before they enter the market, electromagnetic shielding has become an important aspect of design considerations. Various materials at different price points have specific characteristics that may cause them to become either optimal or ill-fitting for specific applications, however, testing their shielding capability can be difficult without the expensive equipment in testing facilities. In this paper, a handheld electromagnetic (EM) meter was used in a simplified test set up to assess the shielding effectiveness of 6 shielding materials: silver sleeve, steel mesh, conductive ABS, Al tape, and Al metallised film. Silver sleeve, Al tape, and Al metallised film were chosen to shield a robotic medical device based on their shielding capability, cost-effectiveness, and design flexibility. The CISPR 11 radiated emissions test results of the robotic medical device validated th...

Despite a fact that using real biological specimens in teaching and learning biodiversity and classification can enhance student’s learning competencies, the biophilia issues emphasizing on student’s attitude to respect the non-human organism should become a challenge to be addressed. Virtual laboratory may provide solutions answering the problems of both, contextuality and biophilia issues in teaching and learning biodiversity and classification. However, appropriate taxonomic concepts and principles are still needed to develop a competence-based virtual laboratory media. This paper aims to analyze challenges and opportunities in developing virtual laboratory in addressing those the two aforementioned issues. Both opportunities and challenges of using virtual laboratory are scrutinized in a context of the important concepts and principles in biodiversity classification and taxonomy. From the perspective of non-anthropocentrism, one of the important affective learning outcomes of teaching and learning biodiversity and classification is building student’s habit to respects to the non-human organism. Therefore, using real biological specimens should be minimized because of its ability in breaking this habit breaking this sensitivity. The problem of contextuality and learning outcome achievement then is challenged. Virtual laboratory may bear opportunities in addressing the problems of contextuality and learning outcome achievement. The virtual laboratory should be systematically designed and structured to assist a ‘step by step’ understanding of the important concepts and principles in biodiversity and classification. A precise 3D taxonomic artificial specimens and model may still be required to complement the virtual laboratory media and altering the contextuality of using the real biological specimens.Despite a fact that using real biological specimens in teaching and learning biodiversity and classification can enhance student’s learning competencies, the biophilia issues emphasizing on student’s attitude to respect the non-human organism should become a challenge to be addressed. Virtual laboratory may provide solutions answering the problems of both, contextuality and biophilia issues in teaching and learning biodiversity and classification. However, appropriate taxonomic concepts and principles are still needed to develop a competence-based virtual laboratory media. This paper aims to analyze challenges and opportunities in developing virtual laboratory in addressing those the two aforementioned issues. Both opportunities and challenges of using virtual laboratory are scrutinized in a context of the important concepts and principles in biodiversity classification and taxonomy. From the perspective of non-anthropocentrism, one of the important affective learning outcomes of teaching and learning bio...

Providing Emergency Power Supply (EPS) by electric vehicles (EVs) is a lower-cost way to provide EPS, and reduces the use of diesel generators effectively, resulting in lower pollution emission. In the places with traditional EPS, the EPS provided by parallel operation of traditional EPS and EVs could reduce the investment and operating cost of traditional EPS system, contributing to the improvement of the economy and reliability of the system. Based on the characteristics of EPS provided by parallel operation of traditional EPS and EVs, this paper proposed a two-layer control strategy to realize EPS provided by parallel operation of traditional EPS and EVs, aiming to take full advantage of battery capacity of EVs and to balance user‘s demand; simulation results show the feasibility of the control strategy proposed.Providing Emergency Power Supply (EPS) by electric vehicles (EVs) is a lower-cost way to provide EPS, and reduces the use of diesel generators effectively, resulting in lower pollution emission. In the places with traditional EPS, the EPS provided by parallel operation of traditional EPS and EVs could reduce the investment and operating cost of traditional EPS system, contributing to the improvement of the economy and reliability of the system. Based on the characteristics of EPS provided by parallel operation of traditional EPS and EVs, this paper proposed a two-layer control strategy to realize EPS provided by parallel operation of traditional EPS and EVs, aiming to take full advantage of battery capacity of EVs and to balance user‘s demand; simulation results show the feasibility of the control strategy proposed.

Every plants need an environment which is in accordance with its adaptability. However, the environment always changes so that it requires regular analysis to maintain plant fertility. Environmental data such as temperature, humidity from soil and air, rainfall, light intensity can be processed using computer algorithms in the form of a sequential (time series) matrix. The paper proposed a sequential Fuzzy Association Rule Mining (FARM) for plants environment classification using Internet of Things (IoT). FARM is used to extract association rule in form of fuzzy memberships from plant environment data that collected from sensors of IoT. Fuzzy is used to facilitate grouping of sensor data and detect changes in the environment when the degree of membership becomes irrelevant. Fuzzy membership degrees are also mapped based on time series to interpret routine environmental changes. The paper showed results of a FARM algorithm for plant environments and prototypes from IoT circuits. FARM algorithm and IoT evaluated using real time data collecting of Aglaonema costatum (Chinese Evergreen). The results shown the FARM capable to extract relevant fuzzy rules with different parameter of tolerance of dependent.Every plants need an environment which is in accordance with its adaptability. However, the environment always changes so that it requires regular analysis to maintain plant fertility. Environmental data such as temperature, humidity from soil and air, rainfall, light intensity can be processed using computer algorithms in the form of a sequential (time series) matrix. The paper proposed a sequential Fuzzy Association Rule Mining (FARM) for plants environment classification using Internet of Things (IoT). FARM is used to extract association rule in form of fuzzy memberships from plant environment data that collected from sensors of IoT. Fuzzy is used to facilitate grouping of sensor data and detect changes in the environment when the degree of membership becomes irrelevant. Fuzzy membership degrees are also mapped based on time series to interpret routine environmental changes. The paper showed results of a FARM algorithm for plant environments and prototypes from IoT circuits. FARM algorithm and IoT eval...

In this paper, we propose a Haar wavelet approach for solving strongly nonlinear oscillators. The proposed method presents an alternative approach to overcome the difficulty of capturing the periodic behavior of the solution, which is characteristic of oscillator equations, and to give a good approximation to the true solution in a very large region. To determine the validation and accuracy of the proposed method, we compare the proposed results with the existed results.In this paper, we propose a Haar wavelet approach for solving strongly nonlinear oscillators. The proposed method presents an alternative approach to overcome the difficulty of capturing the periodic behavior of the solution, which is characteristic of oscillator equations, and to give a good approximation to the true solution in a very large region. To determine the validation and accuracy of the proposed method, we compare the proposed results with the existed results.

Locating and Sizing of Distributed Generation (DG) is an important research topic in the development of microgrids. First, this paper models the uncertainty of its two main Distributed Generation, wind power generation and photovoltaic power generation. Then, considering the economic benefits and technical requirements, three important indicators including investment benefit, network loss improvement and static voltage stability improvement are selected to optimize locating and sizing of DG, and the particle swarm optimization algorithm with inertia weight is used to solve the problem. Finally, the simulation analysis of the IEEE-37 node test feeder shows that the method can effectively improve the voltage level of the system, reduce the active power loss, and improve the static voltage stability of the system. It has certain practical value in the distribution network planning.Locating and Sizing of Distributed Generation (DG) is an important research topic in the development of microgrids. First, this paper models the uncertainty of its two main Distributed Generation, wind power generation and photovoltaic power generation. Then, considering the economic benefits and technical requirements, three important indicators including investment benefit, network loss improvement and static voltage stability improvement are selected to optimize locating and sizing of DG, and the particle swarm optimization algorithm with inertia weight is used to solve the problem. Finally, the simulation analysis of the IEEE-37 node test feeder shows that the method can effectively improve the voltage level of the system, reduce the active power loss, and improve the static voltage stability of the system. It has certain practical value in the distribution network planning.

The pulsed plasma thruster (PPT) is a potential electric thruster for microsatellites. One important content of PPT performance research is the measurement of micro-thrust and micro-impulse. This paper summarizes the 4 typical dynamic measuring systems at home and abroad, which include the single pendulum type, the torsion pendulum type, the cantilever type and the balance type. In the paper, the structure principle, measurement performance, advantages and disadvantages of various configurations are compared and analyzed. The development process of each micro-thrust and micro-impulse measurement technology is summarized, and its developing trend is prospected.

Newly developed 3D reconstruction technology has many uses ranging from facial recognition, self-driving vehicles, and producing accurate models of samples. To utilize 3D reconstruction, a depth map of the sample must be generated from a series of images. This can be done using stereoscopic 3D, or in the case of a fixed camera (such as the 10ID On-Axis Microscope at NSLS-II used for this paper) through focus stacking. This paper will explain how focus stacking can be used to generate in-focus images at very shallow depth of fields, and merge these images to create depth maps and 3D models.

One of the vital components for the pebble reactor is the fuel handling system which was employed to load, recirculate and discharge the depleted fuel during the operation of reactor. The previous fuel handling design and experience of the High Temperature Reaktor 10 MWth (HTR-10) and HTR-PM were beneficial for the development of High Temperature Gas-cooled Reaktor (HTGR) in Indonesia such as for the Reaktor Daya Eksperiment (RDE) 10 MWth and PELUIT 150 MWth. One of the focus for the development especially for the control is an important factor to ensure that the reliability and the safety during operation were guarantee. Therefore, aims of this paper is to understand and develop the automatic control system of the fuel handling. The development was done by applying the logic flowchart of the fuel handling HTGR with the HTR-10 as the reference. Some modification was made considering the future application in Indonesia It was demonstrated that the automation systems with Programmable Logic Controller (PLC) can control handling systems easily because each valve can be drive to open and close immediately as requested from the sensor. It was also demostrated that the timing chart monitoring confirms the control of flowchart process description for the new fresh fuel loading.One of the vital components for the pebble reactor is the fuel handling system which was employed to load, recirculate and discharge the depleted fuel during the operation of reactor. The previous fuel handling design and experience of the High Temperature Reaktor 10 MWth (HTR-10) and HTR-PM were beneficial for the development of High Temperature Gas-cooled Reaktor (HTGR) in Indonesia such as for the Reaktor Daya Eksperiment (RDE) 10 MWth and PELUIT 150 MWth. One of the focus for the development especially for the control is an important factor to ensure that the reliability and the safety during operation were guarantee. Therefore, aims of this paper is to understand and develop the automatic control system of the fuel handling. The development was done by applying the logic flowchart of the fuel handling HTGR with the HTR-10 as the reference. Some modification was made considering the future application in Indonesia It was demonstrated that the automation systems with Programmable Logic Controller (PLC)...

The advent of Automated Fiber Placement (AFP) systems have aided the rapid manufacturing of composite aerospace structures. One of the challenges that AFP systems bring is the variability of the deposited prepreg tape layers, which are prone to gaps, overlaps and twists. The current detection method used in industry involves halting fabrication and performing a time consuming visual inspection of each tape layer. Typical AFP systems use a quartz lamp to heat the base layer to make the surface tacky as it deposits another tape layer. The innovation discussed in this paper is to use the preheated base layer as a through transmission heat source and inspect the newly added tape layer in situ using a thermographic camera mounted onto the AFP structure. Such a system would not only increase manufacturing throughput by reducing inspection times, but would also aid in process development for new structural designs or material systems. To this end, a small thermal camera was mounted onto an AFP robotic research platform at NASA, and thermal data was collected during typical and experimental layup operations. The data was post processed to reveal defects such as tow overlap/gap, wrinkling, and peel-up. Defects that would have been impossible to detect visually were also revealed in the data, such as poor/loss of adhesion between plies and the effects of vacuum debulking. This paper will cover the results of our experiments, and the recent progress on the data reduction algorithms in preparation for machine learning development.

Computational Thinking is introduced as a problem-solving ability that is important for future generations to master. The mastery of computational thinking skills from an early age prepares children to anticipate competition and pursue success in the future. Robotics devices are widely advocated as interactive learning media to facilitate Computational Thinking development. Educational robotics have grown from ideas that represent critical stages of Computational Thinking. The application of robotics in teaching computational thinking skills is increasingly used and is evident in the literature. The paper reviews the development of an innovative robotics device in facilitating understanding of computational thinking in young children in terms of several aspects of computational thinking indicators. A review was also conducted to see the advantages and disadvantages of commercially available robotics devices. This paper was prepared by applying critical analysis methods to the literature published from 1952 to 2017 in international journals and proceedings. As a recommendation for future research, this paper proposes for an educational robotic development that facilitates the of computational thinking skills, especially for early childhood education.

Electrohydrodynamic inkjet printing (e-jet printing) is one type of micro/nano scale 3D printing techniques that automatically deposit functional materials to form 3D structures on the substrate. Unlike traditional thermal or acoustic inkjet printing, e-jet printing utilizes high electrical forces for the ink to overcome surface tension at the tip of micro needles. The droplets and filaments coming out from the needle have dimensions much smaller than the dimension of the needle, thus to print geometries in micro and nano scale. E-jet printing process parameters can affect the final quality attributes of fabricated constructs. Currently, assessment of these critical geometries and attributes information must be performed offline using optical microscopy or scanning electron microscopy. This drawback affected the efficiency of micro/nano printing from translation to industrial practice. The research in this paper focused on fundamental research to enable in-situ monitoring of e-jet printing using a real-time images characterization technique. In conclusion, the study in this paper investigated using machine vision for real-time monitoring of micro/nano scale 3D printing. The method worked well for micro-filament detection in e-jet printing, and may be further implemented into feedback control system of complicated e-jet printing. However, the optical machine vision was limited to micro scale detection. One of the future research topic is to develop nano scale in-situ detection mechanism for e-jet printing.

In this paper, using fuzzy logic technique an intelligent traffic signal control is introduced. The existing traffic light controllers would not give a best solution to this problem as it changes traffic lights based on constant cycle time. Fuzzy logic controllers can be used to deal with linguistic and unpredictable traffic data to control the signal timings. This paper aims at developing an intelligent traffic light controller using fuzzy logic technique and illustrated a control procedure using if – then rules.

Operator support systems are extensively studied and developed to support human operators for their activities in especially an abnormal condition of a nuclear power plant. By the advancement of computer technology and artificial intelligence, an operator support system can provide detailed support information based on detailed models and utilizing detailed simulation of plant dynamics and/or complicated inference algorithms. However, human operators may not understand the detailed support information under high mental pressure in an abnormal plant condition. In such a case, it is important how to provide essential and understandable support information. This paper deals with a technique to simplify functional models in order to display operator support information that is generated based on detailed functional models. This paper defines eight cognitive states of human operators from the viewpoint of cognitive abilities of human. In addition, three ways to simplify functional models are identified.

The paper presents new and original thin-walled structures designed using the application version of the method of statically admissible discontinuous stress fields (SADSF) assuming the condition of equalized equivalent stress in the limit state. The said structures are based on a C-shaped profile, are built of plane elements and designed for carrying torsional moment load. As a result of designing, spatial layout and connection systems of their component elements, as well as their shape and dimensions, were obtained. The paper shows thin structures being designed have good elastic carrying properties, though the method is approximate. These properties can be several or even a dozen or so times better than properties of the systems designed with use of traditional or intuitive methods.The paper presents new and original thin-walled structures designed using the application version of the method of statically admissible discontinuous stress fields (SADSF) assuming the condition of equalized equivalent stress in the limit state. The said structures are based on a C-shaped profile, are built of plane elements and designed for carrying torsional moment load. As a result of designing, spatial layout and connection systems of their component elements, as well as their shape and dimensions, were obtained. The paper shows thin structures being designed have good elastic carrying properties, though the method is approximate. These properties can be several or even a dozen or so times better than properties of the systems designed with use of traditional or intuitive methods.

This paper presents straightforward sensitivity assessment of a telecommunication tower. The analysis is set to identify the elements of the tower which may be reinforced with the greatest structural advantage. As current expert opinions on structural redesign of similar structures due to a planned addition of extra loads are mainly based on deterministic computations or engineering intuition, the probabilistic-based approach is proposed to verify and supplement the reinforcement design projects, in contrary to the existing action course. In the paper, the analysis is performed on an example of a standard, spatial telecommunication truss tower subjected to a standard set of loads, special attention is paid to wind and icing load. The cross-sectional areas of curbs and braces of each tower segment are adopted as random variables of the problem, in the form of sets of percentage increments of the initial cross-sectional area values. Joint impact is observed of individual variable change and the change imposed by groups of key variables with a similar impact on the structural load capacity. Finally, engineering-oriented conclusions are presented, of probabilistic origin. A beneficial solution of the reinforcement is proposed, maintaining the reliability of the initial tower.

The paper outlines energy management concepts using PV panels for a grid. The necessity of considering energy management as a crucial innovation in load supplying to permit a more powerful penetration of renewable energy usage with the help of solar energy at a building and metropolis level. It also significantly points out the energy savings by the consumer and helps in reduction of CO2 emissions in the process [1-2] The driving factors to enhance the current power distribution are presented, and the benefits concerning grids are underlined. In the paper, energy management analysis is assessed by taking into account all the electrical value and the demand-side management. [3] In the paper, the evaluations of ecological benefits are reported, and a cost benefit analysis of the energy management system is performed. The need of energy management in distribution systems is necessary because it helps us determine the exact energy consumed by the load as well as different sectors of the load. It also gives us perspective on how much energy is needed and the sources it can be obtained from. The study being done in this paper is at a residential society in Chennai, Tamil Nadu comprising 2 buildings of 40 flats each equipped with standard lights, fans, air conditioners and heaters.

The paper aims to numerically reflect mineral-asphalt mixture structure by a standard FEM software. Laboratory test results are presented due to bending tests of circular notched elements. The result scatter is relatively high. An attempt was made to form a random aggregate distribution in order to obtain various results corresponding to laboratory tests. The material structure calibration, its homogenization and finite element dimensioning are the issues decisive for the objective mixture description. The representative volume element (RVE) is investigated here, while it does not precisely reflect the material structure it displays relevant global material parameters. The simulation procedure applied here makes it possible to introduce the name of Monte Carlo simulation-based constitutive model.The paper aims to numerically reflect mineral-asphalt mixture structure by a standard FEM software. Laboratory test results are presented due to bending tests of circular notched elements. The result scatter is relatively high. An attempt was made to form a random aggregate distribution in order to obtain various results corresponding to laboratory tests. The material structure calibration, its homogenization and finite element dimensioning are the issues decisive for the objective mixture description. The representative volume element (RVE) is investigated here, while it does not precisely reflect the material structure it displays relevant global material parameters. The simulation procedure applied here makes it possible to introduce the name of Monte Carlo simulation-based constitutive model.

The multispectral imaging technique has been used for skin analysis, especially for distant mapping of in-vivo two major skin chromophores: melanin and blood. Previously, we have developed a new LED-based MSI system. Our MSI system captures only 11 monoband images of human skin which is too little for providing an accurate diagnostic information. We implemented artificial neural network (ANN) algorithm to retrieve a hyperspectral reflectance cube between 380 and 880 nm with a 5 nm resolution. In this paper, we present the validation results our MSI’s performance in order to estimate melanin and blood content in human skin. Validation is done by comparing the estimation results captured by the MSI system and the spectrometer with diffuse reflectance spectroscopy (DRS) technique. For validation, we used agar-based phantom as object. In addition, we also present the results of in vivo testing in uper human palm skin with 5 samples. The estimation results of melanin content by using MSI system and the spectrometer follows the equation y = 0.9565x with the coefficient of determination (R2) of 0.9934. On the other hand, the estimation result of the blood content follows the equation y = 1.1881x with the coefficient of determination (R2) of 0.9226. The average melanin content estimate results with the MSI system was 1.29% greater than the spectrometer, while the average blood content was 1.06% higher for the same in vivo skin data test. According the results, the LED-based MSI can be used for the direct and noninvasive skin assessment accurately. For example, measurement of melanin content in the skin is the most essential in the skin diagnosis process, especially in cases of hypo-pigmentation and hyper-pigmentation. In other cases, some cancers such as melanoma, basal cell carcinoma (BCC), and the tumor can also be differentiated by measurement of melanin and blood content.The multispectral imaging technique has been used for skin analysis, especially for distant mapping of in-vivo two major skin chromophores: melanin and blood. Previously, we have developed a new LED-based MSI system. Our MSI system captures only 11 monoband images of human skin which is too little for providing an accurate diagnostic information. We implemented artificial neural network (ANN) algorithm to retrieve a hyperspectral reflectance cube between 380 and 880 nm with a 5 nm resolution. In this paper, we present the validation results our MSI’s performance in order to estimate melanin and blood content in human skin. Validation is done by comparing the estimation results captured by the MSI system and the spectrometer with diffuse reflectance spectroscopy (DRS) technique. For validation, we used agar-based phantom as object. In addition, we also present the results of in vivo testing in uper human palm skin with 5 samples. The estimation results of melanin content by using MSI system and the spectro...

Pattern analysis has been shown to have higher reliability for melanoma and nevus classification. The ABCD method, which is common to be used as a melanoma diagnosis method, has been shown to have inappropriate weighting for each parameter. In addition, pattern analysis has been shown to have a higher success for diagnosing melanoma. In this paper, we choose the Grey Level Co-occurrence Matrix (GLCM) as a texture parameter to represent the pattern of melanoma. We also choose Deep Neural Network (DNN) to retrieve information from the data set. DNN has the capability of analyzing data with a high level of abstraction. Therefore, we choose DNN as a method to classify melanoma and nevus. We use the International Skin Imaging Collaboration (ISIC) archive database as our training and validation data. We use 773 nevi with 870 melanoma images as training data and separate 200 Nevus and 200 Melanoma images as validation data. We achieve 81.75% diagnostic accuracy, 75.5% sensitivity, and 88% specificityPattern analysis has been shown to have higher reliability for melanoma and nevus classification. The ABCD method, which is common to be used as a melanoma diagnosis method, has been shown to have inappropriate weighting for each parameter. In addition, pattern analysis has been shown to have a higher success for diagnosing melanoma. In this paper, we choose the Grey Level Co-occurrence Matrix (GLCM) as a texture parameter to represent the pattern of melanoma. We also choose Deep Neural Network (DNN) to retrieve information from the data set. DNN has the capability of analyzing data with a high level of abstraction. Therefore, we choose DNN as a method to classify melanoma and nevus. We use the International Skin Imaging Collaboration (ISIC) archive database as our training and validation data. We use 773 nevi with 870 melanoma images as training data and separate 200 Nevus and 200 Melanoma images as validation data. We achieve 81.75% diagnostic accuracy, 75.5% sensitivity, and 88% specificity

The paper deals with the kinetic (that is, impact-driven penetration) effect of aircraft (aerial vehicles, AV) colliding with thin metal barriers at high velocities. Investigating this impact-driven penetration effect of AV involves studying the processes of perforation (perforation means that the aircraft emerges fully on the other side of the barrier), which requires not only computational simulations, but also actual experiments, due to how complex these processes are. The objective of our investigation is twofold: first, we want to develop an analytical method for computing the parameters of the impact-driven AV penetration effect, said method correctly taking into account the perforation process specifics; then, we want to verify the computation results obtained. The paper uses a quasi-dynamic approach to computing impact-driven penetration effect of poorly deformable AVs that makes it possible to account for strength and inertial resistance of a thin metal barrier. We present and state an analytical computational method making it possible to estimate the impact-driven penetration effect of AVs that may interact with thin metal barriers either as an emergency situation or as part of their regular functionality (h/d < 0.5). We compared analytical computation results to experimental data (that is, validated our model) for various AVs at velocities of 79.3 to 315 m/s. We used our analytical method to compute impact-driven penetration AV effect on spatially separated thin metal barriers (screens). The results obtained may be used for preliminary estimation when developing requirements for AV components during its regular operation or an emergency. More accurate estimates will involve small-scale physical modelling methods and numerical simulations.

The paper describes the research stand and presents analysis of selected vibrations results of artillery and rocket missiles equipped with a radio proximity sensor.The paper describes the research stand and presents analysis of selected vibrations results of artillery and rocket missiles equipped with a radio proximity sensor.

This paper considers dual channel closed loop supply chain with one manufacture and two retailers. A manufacturer combined the offline channel with a direct online channel in product sales. In this research, we inspected the dual channel closed loop supply chain model by notice delivery lead time for the online channel and price discount contracts. We constructed mathematical models with the profit maximization motive which is determined by three decision variables. Furthermore, we determine the optimal solution of the model. We analyze the effects of delivery lead time and price discount contract on the optimal operation. The results of the study show that delivery lead time strongly influences on the optimal profit system and price discount contract perform better than non-contract scenarios.This paper considers dual channel closed loop supply chain with one manufacture and two retailers. A manufacturer combined the offline channel with a direct online channel in product sales. In this research, we inspected the dual channel closed loop supply chain model by notice delivery lead time for the online channel and price discount contracts. We constructed mathematical models with the profit maximization motive which is determined by three decision variables. Furthermore, we determine the optimal solution of the model. We analyze the effects of delivery lead time and price discount contract on the optimal operation. The results of the study show that delivery lead time strongly influences on the optimal profit system and price discount contract perform better than non-contract scenarios.

A method to create mammography phantoms with radiopaque ink and an inkjet printer was developed. A mammography image was printed on several sheets of bond paper, modulated by a calibration function, creating a phantom image that can emulate the original object in a clinical image. The radiopaque ink on paper was stable, at least, over a month. The representation of the mammography image was visually equivalent, and the limitations of the method come from noise, alignment difficulties, and dynamic range compression.

In this paper, the isolated DC-DC converters fly back, forward converter, and hybrid converter topologies are considered for analysis. However, each topology has definite boundaries that are hard to resolve that can be overcome by the hybrid topology. This paper presents a hybrid type of forward, and fly back converter, allocation of the transformer utilization factor a better manner, has exceptionally high voltage gain and high efficiency. Achieving soft switching with control and design is easy. The forward fly back converters are simulated using MATLAB Simulink employing the results are analyzed and compared the efficiencies with theoretical and simulated values. The theoretical analysis of flyback-forward converter using DSPIC30F4011 is verified by comparing the theoretical and simulation results with a prototype of 100W and 2 kHz switching frequency.

High speed vehicle as a vibration system, resonance generated in flight may be harmful to high speed vehicles. It is possible to solve the resonance problem by acquiring the natural frequency of the high-speed aircraft and then taking some measures to avoid the natural frequency of the high speed vehicle. Therefore, In this paper, the modal test of the high speed vehicle was carried out by using the running hammer method and the PolyMAX modal parameter identification method. Firstly, the total frequency response function, coherence function of the high speed vehicle are obtained by the running hammer stimulation test, and through the modal assurance criterion (MAC) to determine the accuracy of the estimated parameters. Secondly, the first three order frequencies, the pole steady state diagram of the high speed vehicles is obtained by the PolyMAX modal parameter identification method. At last, the natural frequency of the vibration system was accurately obtained by the running hammer method.High speed vehicle as a vibration system, resonance generated in flight may be harmful to high speed vehicles. It is possible to solve the resonance problem by acquiring the natural frequency of the high-speed aircraft and then taking some measures to avoid the natural frequency of the high speed vehicle. Therefore, In this paper, the modal test of the high speed vehicle was carried out by using the running hammer method and the PolyMAX modal parameter identification method. Firstly, the total frequency response function, coherence function of the high speed vehicle are obtained by the running hammer stimulation test, and through the modal assurance criterion (MAC) to determine the accuracy of the estimated parameters. Secondly, the first three order frequencies, the pole steady state diagram of the high speed vehicles is obtained by the PolyMAX modal parameter identification method. At last, the natural frequency of the vibration system was accurately obtained by the running hammer method.

Most of the engineering fields, including mechatronics, require reliable operation of structures. Because of that, structural health monitoring (SHM) is rapidly becoming an integral part of critical structures. There are many different SHM techniques and each of them has its own advantages and disadvantages related to techniques sensitivity to defects and operational costs. A lot of study is done in vibration based SHM, especially in modal analysis and operational modal analysis (OMA) fields. This paper proposes signal processing algorithm called Modal Field Comparison Method (MFCM) for OMA based SHM system. The method considers processing of vibration responses, such as acceleration or deformation signals, received from multiple vibration sensors installed on the structure. MFCM gives a single value estimation of how the condition of a structure has changed in relation to reference condition. Theoretical basis of the method is presented, as well as results of experimental study on a cantilever beam with 12 deformation sensors (piezo films). Sensitivity to condition modification was also studied by installing test masses on the beam. The paper discusses good and promising results of the study, but further work is necessary to establish foundation for a potential automatic SHM system.

Operating room is one of sectors in a hospital which exerts a great impact on the hospital. This kind of facility may both cost a lot and earn a lot, therefore the hospital management should have an excellent operating room scheduling. This paper aimed to establish efficiency of operating room scheduling by minimizing patient waiting time, considering that it belongs to one of indicators for operating room efficiency. Cluster analysis applied to categorize all of the surgery activities according to data of surgical durations and types of surgery. All of the resulting clusters were plotted in order to determine the scheduling priority. The priority was determined by referring to the lowest scores of standard deviation of surgical activity duration. The results indicate that the determination of scheduling priority using cluster analysis enhanced operating room performance by decreasing the patient waiting time of 39.34%.Operating room is one of sectors in a hospital which exerts a great impact on the hospital. This kind of facility may both cost a lot and earn a lot, therefore the hospital management should have an excellent operating room scheduling. This paper aimed to establish efficiency of operating room scheduling by minimizing patient waiting time, considering that it belongs to one of indicators for operating room efficiency. Cluster analysis applied to categorize all of the surgery activities according to data of surgical durations and types of surgery. All of the resulting clusters were plotted in order to determine the scheduling priority. The priority was determined by referring to the lowest scores of standard deviation of surgical activity duration. The results indicate that the determination of scheduling priority using cluster analysis enhanced operating room performance by decreasing the patient waiting time of 39.34%.

In this paper, a grey prediction model is used to predict the carbon emission in Hebei province, and the impact analysis model based on TermCo2 is established. At the same time, we read a lot about CGE and study on how to build the scene, the selection of key parameters, and sensitivity analysis of application scenarios do industry for reference.In this paper, a grey prediction model is used to predict the carbon emission in Hebei province, and the impact analysis model based on TermCo2 is established. At the same time, we read a lot about CGE and study on how to build the scene, the selection of key parameters, and sensitivity analysis of application scenarios do industry for reference.

The deterministic prediction of wind power, the probability prediction and the prediction of wind power ramp events are introduced in this paper. Deterministic prediction includes the prediction of statistical learning based on histor ical data and the prediction of physical models based on NWP data. Due to the great impact of wind power ramp events on the power system, this paper also introduces the prediction of wind power ramp events. At last, the evaluation indicators of all kinds of prediction are given. The prediction of wind power can be a good solution to the adverse effects of wind power on the power system due to the abrupt, intermittent and undulation of wind power.

This study presents a simulation based optimization study of a multi-tube trapezoidal cavity receiver of a Linear Fresnel Collector plant in Pretoria, South Africa. A comprehensive optimization study - an optical, thermal and economic optimization study - based on realistic simulations of these objective goals on an annual basis for such a plant is presented in this paper. This paper could be used as an applicable guideline for future researchers who work on the optimization of Concentrated Solar Power Plants.

This paper presents an approach for lifelong learning in the field of Bulgarian cultural and historical heritage supported by an intelligent software assistant known as Tourist Guide. The Tourist Guide operates in the e-learning environment called Virtual Education Space that is implemented as an Internet of Things ecosystem. The guide provides various possibilities of students to involve in lifelong learning education especially in informal education. Furthermore, the paper presents the architecture of the Tourist guide and its components in detail.