Search results for: absolute time

Authors: Okewu E. Jonathan

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There are several techniques of production in the field of ceramics. These different techniques overtime have been categorised under three methods of production which includes; casting, throwing and hand building. Hand building method of production is further broken down into other techniques and they include coiling, slabbing and pinching. Ceramic artists find the different hand building techniques to be very interesting, practicable and rewarding. This has encouraged ceramic artist in their various studios at different levels to experiment for further hand building techniques that could be unique and unusual. The art of “Clay Palm Press” is a development from studio experiment in a quest for uniqueness in conceptual ceramic practise. Clay palm press is a technique that requires no formal tutelage but at the same time, it is not easily comprehensible when viewed. It is a practice of putting semi-solid clay in the palm and inserting a closed fist pressure so as to take the imprint of the human palm. This clay production from the palm when dried, fired and explored into an art, work reveals an absolute awesomeness of what the palm imprint could result in.

Keywords: ceramics, clay palm press, conceptual forms, hand building, technique

Procedia PDF Downloads 245

Authors: H. Yousefnia, A. Aghanejad, A. Mirzaei, R. Enayati, A. R. Jalilian, S. Zolghadri

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Bone metastases occur in many cases at an early stage of the tumour disease; however, their symptoms are recognized rather late. The aim of this study was the preparation and quality control of 111In-BPAMD for diagnostic purposes. 111In was produced at the Agricultural, Medical, and Industrial Research School (AMIRS) by means of 30 MeV cyclotron via natCd(p,x)111In reaction. Complexion of In‐111 with BPAMD was carried out by using acidic solution of 111InCl3 and BPAMD in absolute water. The effect of various parameters such as temperature, ligand concentration, pH, and time on the radiolabeled yield was studied. 111In-BPAMD was prepared successfully with the radiochemical purity of 95% at the optimized condition (100 µg of BPAMD, pH=5, and at 90°C for 1 h) which was measured by ITLC method. The final solution was injected to wild-type mice and biodistribution was determined up to 72 h. SPECT images were acquired after 2 and 24 h post injection. Both the biodistribution studies and SPECT imaging indicated high bone uptake while accumulation in other organs was approximately negligible. The results show that 111In-BPAMD can be used as an excellent tracer for diagnosis of bone metastases by SPECT imaging.

Keywords: biodistribution, BPAMD, 111In, SPECT

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Authors: Tomoko Usui

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In the field of linguistics, it has been said that concepts associated with space and motion systematically contribute structure to the temporal concept. This is the conceptual metaphor theory. conceptual metaphors typically employ a more abstract concept (time) as their target and a more concrete or physical concept as their source (space). This paper will examine two major temporal conceptual metaphors: Ego-centered Moving Time Metaphor and Time-RP Metaphor. Moving time generally receives a front-back orientation, however, Japanese shows a different orientation given to time. By means of Ego perspective, this paper will illustrate the paradox of a metaphorical orientation in time.

Keywords: Ego-centered Moving Time Metaphor, Japanese saki, temporal metaphors, Time RP Metaphor

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Authors: Sunday B. Alabi, Edikan P. Felix, Aniediong M. Umo

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Crystal size distribution is of great importance in the sugar factories. It determines the market value of granulated sugar and also influences the cost of production of sugar crystals. Typically, sugar is produced using fed-batch vacuum evaporative crystallizer. The crystallization quality is examined by crystal size distribution at the end of the process which is quantified by two parameters: the average crystal size of the distribution in the mean aperture (MA) and the width of the distribution of the coefficient of variation (CV). Lack of real-time measurement of the sugar crystal size hinders its feedback control and eventual optimisation of the crystallization process. An attractive alternative is to use a soft sensor (model-based method) for online estimation of the sugar crystal size. Unfortunately, the available models for sugar crystallization process are not suitable as they do not contain variables that can be measured easily online. The main contribution of this paper is the development of a regression model for estimating the sugar crystal size as a function of input variables which are easy to measure online. This has the potential to provide real-time estimates of crystal size for its effective feedback control. Using 7 input variables namely: initial crystal size (Lo), temperature (T), vacuum pressure (P), feed flowrate (Ff), steam flowrate (Fs), initial super-saturation (S0) and crystallization time (t), preliminary studies were carried out using Minitab 14 statistical software. Based on the existing sugar crystallizer models, and the typical ranges of these 7 input variables, 128 datasets were obtained from a 2-level factorial experimental design. These datasets were used to obtain a simple but online-implementable 6-input crystal size model. It seems the initial crystal size (Lₒ) does not play a significant role. The goodness of the resulting regression model was evaluated. The coefficient of determination, R² was obtained as 0.994, and the maximum absolute relative error (MARE) was obtained as 4.6%. The high R² (~1.0) and the reasonably low MARE values are an indication that the model is able to predict sugar crystal size accurately as a function of the 6 easy-to-measure online variables. Thus, the model can be used as a soft sensor to provide real-time estimates of sugar crystal size during sugar crystallization process in a fed-batch vacuum evaporative crystallizer.

Keywords: crystal size, regression model, soft sensor, sugar, vacuum evaporative crystallizer

Procedia PDF Downloads 183

Authors: Kiana Zeighami, Morteza Ozlati Moghadam

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Designing a high accuracy and high precision motion controller is one of the important issues in today’s industry. There are effective solutions available in the industry but the real-time performance, smoothness and accuracy of the movement can be further improved. This paper discusses a complete solution to carry out the movement of three stepper motors in three dimensions. The objective is to provide a method to design a fully integrated System-on-Chip (SOC)-based motion controller to reduce the cost and complexity of production by incorporating Field Programmable Gate Array (FPGA) into the design. In the proposed method the FPGA receives its commands from a host computer via wireless internet communication and calculates the motion trajectory for three axes. A profile generator module is designed to realize the interpolation algorithm by translating the position data to the real-time pulses. This paper discusses an approach to implement the linear interpolation algorithm, since it is one of the fundamentals of robots’ movements and it is highly applicable in motion control industries. Along with full profile trajectory, the triangular drive is implemented to eliminate the existence of error at small distances. To integrate the parallelism and real-time performance of FPGA with the power of Central Processing Unit (CPU) in executing complex and sequential algorithms, the NIOS II soft-core processor was added into the design. This paper presents different operating modes such as absolute, relative positioning, reset and velocity modes to fulfill the user requirements. The proposed approach was evaluated by designing a custom-made FPGA board along with a mechanical structure. As a result, a precise and smooth movement of stepper motors was observed which proved the effectiveness of this approach.

Keywords: 3-axis linear interpolation, FPGA, motion controller, micro-stepping

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Authors: J. L. Chukwuneke, C. H. Achebe, S. N. Omenyi

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This research work presents the surface thermodynamics approach to M-TB/HIV-Human sputum interactions. This involved the use of the Hamaker coefficient concept as a surface energetics tool in determining the interaction processes, with the surface interfacial energies explained using van der Waals concept of particle interactions. The Lifshitz derivation for van der Waals forces was applied as an alternative to the contact angle approach which has been widely used in other biological systems. The methodology involved taking sputum samples from twenty infected persons and from twenty uninfected persons for absorbance measurement using a digital Ultraviolet visible Spectrophotometer. The variables required for the computations with the Lifshitz formula were derived from the absorbance data. The Matlab software tools were used in the mathematical analysis of the data produced from the experiments (absorbance values). The Hamaker constants and the combined Hamaker coefficients were obtained using the values of the dielectric constant together with the Lifshitz equation. The absolute combined Hamaker coefficients A132abs and A131abs on both infected and uninfected sputum samples gave the values of A132abs = 0.21631x10-21Joule for M-TB infected sputum and Ã132abs = 0.18825x10-21Joule for M-TB/HIV infected sputum. The significance of this result is the positive value of the absolute combined Hamaker coefficient which suggests the existence of net positive van der waals forces demonstrating an attraction between the bacteria and the macrophage. This however, implies that infection can occur. It was also shown that in the presence of HIV, the interaction energy is reduced by 13% conforming adverse effects observed in HIV patients suffering from tuberculosis.

Keywords: absorbance, dielectric constant, hamaker coefficient, lifshitz formula, macrophage, mycobacterium tuberculosis, van der waals forces

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Authors: Ajibola Isola, Shattri Mansor, Ojogbane Sani, Olugbemi Tope

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The cadastral map is the rationale behind city management planning and development. For years, cadastral maps have been produced by ground and photogrammetry platforms. Recent evolution in photogrammetry and remote sensing sensors ignites the use of Unmanned Aerial Vehicle systems (UAVs) for cadastral mapping. Despite the time-saving and multi-dimensional cost-effectiveness of the UAV platform, issues related to cadastral map accuracy are a hindrance to the wide applicability of UAVs' cadastral mapping. This study aims to present an approach leading to the generation and assessing the credibility of UAV cadastral mapping. Different sets of Red, Green, and Blue (RGB) photos were obtained from the Tarot 680-hexacopter UAV platform flown over the Universiti Putra Malaysia campus sports complex at an altitude range of 70 m, 100 m, and 250. Before flying the UAV, twenty-eight ground control points were evenly established in the study area with a real-time kinematic differential global positioning system. The second phase of the study utilizes an image-matching algorithm for photos alignment wherein camera calibration parameters and ten of the established ground control points were used for estimating the inner, relative, and absolute orientations of the photos. The resulting orthoimages are exported to ArcGIS software for digitization. Visual, tabular, and graphical assessments of the resulting cadastral maps showed a different level of accuracy. The results of the study show a gradual approach for generating UAV cadastral mapping and that the cadastral map acquired at 70 m altitude produced better results.

Keywords: aerial mapping, orthomosaic, cadastral map, flying altitude, image processing

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

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Authors: Hasrullah Hasrullah

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Since December 2015, the ASEAN Economic Community (AEC) is officially declared in the 27th Summit Conference of ASEAN and Indonesia is one of country are listed in the ASEAN members. Per January 1st, 2016 the ASEAN Economic Community (AEC) came into effect. However, its implementation in Indonesia is still weighing the pros and cons because Indonesia is considered too late to prepare for the ASEAN Economic Community (AEC). In other words, rubber time of Indonesian people has been occurring in the AEC. This paper reviews how Indonesia language influences people’s attitude to be rubber time culture and how time zones of Indonesia influence people’s attitude through media on television to be rubber time culture. The author addresses this research question empirically by collecting data from various sources of data those are relevant and compare among the unification of Indonesia time zones. The result demonstrates that unification of Indonesia time zones to be Standard Indonesia Time is a solution to encourage people to be ready on time for facing ASEAN Economic Community (AEC).

Keywords: unification time zones, Indonesia Language, Rubber Time, AEC

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Authors: Kwok W. Cheung

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A scientific interpretation of creation reconciling the beliefs of six literal days of creation and a 13.7-billion-year-old universe currently perceived by most modern cosmologists is proposed. We hypothesize that the reference timeframe of God’s creation is associated with some cosmic time different from the earth's time. We show that the scale factor of earth time to cosmic time can be determined by the solution of the Friedmann equations. Based on this scale factor and some basic assumptions, we derive a Cosmic Time Dilation model that harmonizes the literal meaning of creation days and scientific discoveries with remarkable accuracy.

Keywords: cosmological expansion, time dilation, creation, genesis, relativity, Big Bang, biblical hermeneutics

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Authors: Choki, Supatchai Boonpratham, Suwannee Luppanapornlarp

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The objective of this study was to find a correlation between cephalometric measurements and visual perception of facial profile in skeletal type II patients. In this study, 250 lateral cephalograms of female patients from age, 20 to 22 years were analyzed. The profile outlines of all the samples were hand traced and transformed into silhouettes by the principal investigator. Profile ratings were done by 9 orthodontists on Visual Analogue Scale from score one to ten (increasing level of convexity). 37 hard issue and soft tissue cephalometric measurements were analyzed by the principal investigator. All the measurements were repeated after 2 weeks interval for error assessment. At last, the rankings of visual perceptions were correlated with cephalometric measurements using Spearman correlation coefficient (P < 0.05). The results show that the increase in facial convexity was correlated with higher values of ANB (A point, nasion and B point), AF-BF (distance from A point to B point in mm), L1-NB (distance from lower incisor to NB line in mm), anterior maxillary alveolar height, posterior maxillary alveolar height, overjet, H angle hard tissue, H angle soft tissue and lower lip to E plane (absolute correlation values from 0.277 to 0.711). In contrast, the increase in facial convexity was correlated with lower values of Pg. to N perpendicular and Pg. to NB (mm) (absolute correlation value -0.302 and -0.294 respectively). From the soft tissue measurements, H angles had a higher correlation with visual perception than facial contour angle, nasolabial angle, and lower lip to E plane. In conclusion, the findings of this study indicated that the correlation of cephalometric measurements with visual perception was less than expected. Only 29% of cephalometric measurements had a significant correlation with visual perception. Therefore, diagnosis based solely on cephalometric analysis can result in failure to meet the patient’s esthetic expectation.

Keywords: cephalometric measurements, facial profile, skeletal type II, visual perception

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Authors: Wiwat Kittinaraporn, Napat Harnpornchai, Sutja Boonyachut

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This paper deals with the application of a novel neural network technique, so-called Support Vector Machine (SVM). The objective of this study is to explore the variable and parameter of forecasting factors in the construction industry to build up forecasting model for construction quantity in Thailand. The scope of the research is to study the non-residential construction quantity in Thailand. There are 44 sets of yearly data available, ranging from 1965 to 2009. The correlation between economic indicators and construction demand with the lag of one year was developed by Apichat Buakla. The selected variables are used to develop SVM models to forecast the non-residential construction quantity in Thailand. The parameters are selected by using ten-fold cross-validation method. The results are indicated in term of Mean Absolute Percentage Error (MAPE). The MAPE value for the non-residential construction quantity predicted by Epsilon-SVR in corporation with Radial Basis Function (RBF) of kernel function type is 5.90. Analysis of the experimental results show that the support vector machine modelling technique can be applied to forecast construction quantity time series which is useful for decision planning and management purpose.

Keywords: forecasting, non-residential, construction, support vector machines

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Authors: U. Sabura Banu, S. K. Lakshmanaprabu

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The improvement of meta-heuristic algorithm encourages control engineer to design an optimal controller for industrial process. Most real-world industrial processes are non-linear multivariable process with high interaction. Even in sub-process unit, thousands of loops are available mostly interacting in nature. Optimal controller design for such process are still challenging task. Closed loop controller design by multiloop PID involves a tedious procedure by performing interaction study and then PID auto-tuning the loop with higher interaction. Finally, detuning the controller to accommodate the effects of the other process variables. Fractional order PID controllers are replacing integer order PID controllers recently. Design of Multiloop Fractional Order (MFO) PID controller is still more complicated. Cuckoo algorithm, a swarm intelligence technique is used to optimally tune the MFO PID controller with easiness minimizing Integral Time Absolute Error. The closed loop performance is tested under servo, regulatory and servo-regulatory conditions.

Keywords: Cuckoo algorithm, mutliloop fractional order PID controller, two Interacting conical tank process

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Authors: Jasmina Pluncevic Gligoroska, Sanja Manchevska, Vaska Antevska, Lidija Todorovska, Beti Dejanova, Sunchica Petrovska, Ivanka Karagjozova, Elizabeta Sivevska

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Introduction: Anthropometric measurements are integral part of regular medical examinations of athletes. In addition to the quantification of the size of the body, these measurements indicate the quality of the physical status, because of its association with sports performance. The purpose of this study was to examine whether there are differences in anthropometric parameters and body mass components in female athletes who participate in two different types of sports. Methods: A total of 27 athletes, 15 handball players and 12 basketball players, at the average age of 22.7 years (age span from 17 to 30 years) entered the study. Anthropometric method by Matiegka was used for determination of body components. Sixteen anthropometric measures were taken: height, weight, four diameters of joints, four circumferences of limbs and six skin folds. Results: Handball players were 169.6±6.7 cm tall and 63,75±7.5 kg heavy. Their average relative muscle mass (absolute mass in kg) was 51% (32.5kg), while bone component was 16.8% (10.7kg) and fat component was 14.3% (7.74kg). The basketball players were 177.4±8.2cm tall and 70.37±12.1kg heavy. Their average relative muscle mass (absolute mass in kg) was 51.9 % (36.6kg), bone component was 16.37% (11.5kg) and fat component was 15.36% (9.4kg). The comparison of anthropometric values showed that basketball players were statistically significantly higher and heavier than handball players (p<0.05). Statistically significant difference (p<0.05) was observed in the range of upper leg circumference (higher in basketball players) and the forearm skin fold (higher in the basketball players). Conclusion: Handball players and basketball players significantly differed in basic anthropometric measures (height and weight), but the body components had almost identical values. The anthropometric measurements that have been taken did not show significant difference between handball and basketball female players despite the different physical demands of the games.

Keywords: anthropometry, body components, basketball, handball female players

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Authors: Imran Badshah

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Pedestrian service time reflects the performance of the facility, and it’s a key parameter to analyze the capability of facilities provided to serve pedestrians. The level of service of pedestrians (LOS) mainly depends on pedestrian time and safety. The pedestrian time utilized by taking a service is mainly influenced by the number of available services and the time utilized by each pedestrian in receiving a service; that is called a delay time. In this paper, we analyzed the simulated pedestrian service time with different delay times. A simulation is performed in AnyLogic by developing a model that reflects the real scenario of pedestrian services such as ticket machine gates at rail stations, airports, shopping malls, and cinema halls. The simulated pedestrian time is determined for various delay values. The simulated result shows how pedestrian time changes with the delay pattern. The histogram and time plot graph of a model gives the mean, maximum and minimum values of the pedestrian time. This study helps us to check the behavior of pedestrian time at various services such as subway stations, airports, shopping malls, and cinema halls.

Keywords: agent-based simulation, anylogic model, pedestrian behavior, time delay

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Meesun Sun, Yongmin Kim

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Estimating maintenance cost is crucial in defense management because it affects military budgets and availability of equipment. When it comes to estimating maintenance cost of the deployed equipment, time series forecasting can be applied with the actual historical cost data. It is more difficult issue to estimate maintenance cost of new equipment for which the actual costs are not provided. In this underlying context, this study proposes an analytical method for maintenance cost estimating relationships (CERs) development of helicopters using linear programming. The CERs can be applied to a new helicopter because they use non-cost independent variables such as the number of engines, the empty weight and so on. In the Republic of Korea, the maintenance cost of new equipment has been usually estimated by reflecting maintenance cost to unit price ratio of the legacy equipment. This study confirms that the CERs perform well for the 10 types of airmobile helicopters in terms of mean absolute percentage error by applying leave-one-out cross-validation. The suggested method is very useful to estimate the maintenance cost of new equipment and can help in the affordability assessment of acquisition program portfolios for total life cycle systems management.

Keywords: affordability analysis, cost estimating relationship, helicopter, linear programming, maintenance cost

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Authors: Hexiong Liu

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Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.

Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy

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Authors: Poonam Malik, Ravi Bhushan

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This work describes a very efficient approach for synthesis of activated ester of (S)-naproxen which was characterized by UV, IR, ¹HNMR, elemental analysis and polarimetric studies. It was used as a C-N bond forming chiral derivatizing reagent for further synthesis of diastereomeric amides of (RS)-salbutamol (a β₂ agonist that belongs to the group β-adrenolytic and is marketed as racamate) under microwave irradiation. The diastereomeric pair was separated by achiral phase HPLC, using mobile phase in gradient mode containing methanol and aqueous triethylaminephosphate (TEAP); separation conditions were optimized with respect to pH, flow rate, and buffer concentration and the method of separation was validated as per International Council for Harmonisation (ICH) guidelines. The reagent proved to be very effective for on-line sensitive detection of the diastereomers with very low limit of detection (LOD) values of 0.69 and 0.57 ng mL⁻¹ for diastereomeric derivatives of (S)- and (R)-salbutamol, respectively. The retention times were greatly reduced (2.7 min) with less consumption of organic solvents and large (α) as compared to literature reports. Besides, the diastereomeric derivatives were separated and isolated by preparative HPLC; these were characterized and were used as standard reference samples for recording ¹HNMR and IR spectra for determining absolute configuration and elution order; it ensured the success of diastereomeric synthesis and established the reliability of enantioseparation and eliminated the requirement of pure enantiomer of the analyte which is generally not available. The newly developed reagent can suitably be applied to several other amino group containing compounds either from organic syntheses or pharmaceutical industries because the presence of (S)-Npx as a strong chromophore would allow sensitive detection.This work is significant not only in the area of enantioseparation and determination of absolute configuration of diastereomeric derivatives but also in the area of developing new chiral derivatizing reagents (CDRs).

Keywords: chiral derivatizing reagent, naproxen, salbutamol, synthesis

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Authors: Yutae Lee

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This paper considers a discrete-time bulk-arrival bulkservice queueing system, where service capacity varies depending on the previous service time. By using the generating function technique and the supplementary variable method, we compute the distributions of the queue length at an arbitrary slot boundary and a departure time.

Keywords: discrete-time queue, bulk queue, variable service capacity, queue length distribution

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Authors: Majid Yazdandoust

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This study, tries to suggest a design method based on displacement using finite difference numerical modeling in reinforcing soil retaining wall with steel strip. In this case, dynamic loading characteristics such as duration, frequency, peak ground acceleration, geometrical characteristics of reinforced soil structure and type of the site are considered to correct the pseudo static method and finally introduce the pseudo static coefficient as a function of seismic performance level and peak ground acceleration. For this purpose, the influence of dynamic loading characteristics, reinforcement length, height of reinforced system and type of the site are investigated on seismic behavior of reinforcing soil retaining wall with steel strip. Numerical results illustrate that the seismic response of this type of wall is highly dependent to cumulative absolute velocity, maximum acceleration, and height and reinforcement length so that the reinforcement length can be introduced as the main factor in shape of failure. Considering the loading parameters, mechanically stabilized earth wall parameters and type of the site showed that the used method in this study leads to most efficient designs in comparison with other methods which are generally suggested in cods that are usually based on limit-equilibrium concept. The outputs show the over-estimation of equilibrium design methods in comparison with proposed displacement based methods here.

Keywords: pseudo static coefficient, seismic performance design, numerical modeling, steel strip reinforcement, retaining walls, cumulative absolute velocity, failure shape

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Salman Hussam

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As a monitoring system to manage employees' time and employers' business, this system (logger) will monitor the employees at work and will announce them if they spend too much time on social media (even if they are using proxy it will catch them). In this way, people will spend less time at work and more time with family.

Keywords: clients, employees, employers, family, monitoring, systems, social media, time

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Authors: Anand Kishore Kola, G. Uday Bhaskar Babu, Kotturi Ajay Kumar

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The modern dynamic systems used in industries are complex in nature and hence the fractional order controllers have been contemplated as a fresh approach to control system design that takes the complexity into account. Traditional integer order controllers use integer derivatives and integrals to control systems, whereas fractional order controllers use fractional derivatives and integrals to regulate memory and non-local behavior. This study provides a method based on the maximumsensitivity (Ms) methodology to discover all resilient fractional filter Internal Model Control - proportional integral derivative (IMC-PID) controllers that stabilize the closed-loop system and deliver the highest performance for a time delay system with a Smith predictor configuration. Additionally, it helps to enhance the range of PID controllers that are used to stabilize the system. This study also evaluates the effectiveness of the suggested controller approach for minimum phase system in comparison to those currently in use which are based on Integral of Absolute Error (IAE) and Total Variation (TV).

Keywords: modern dynamic systems, fractional order controllers, maximum-sensitivity, IMC-PID controllers, Smith predictor, IAE and TV

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Authors: Sunny Ewankhiwimen Aigbomian

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Time, is a scarce resource and in everything we do, time is required to accomplish any given task. The need for this presentation is predicated on the way majority of Nigerian especially in the public sector operators see “Time Management”. Time as resources cannot be regained if lost or managed badly. As a significant aspect of human life it should be handled with diligence and utmost seriousness if the public sector is to function as a coordinated entity. In our homes, private life and offices, we schedule different things to ensure that some things do not go the unexpected. When it comes to service delivery on the part of government, it ought to be more serious because government is all about effect and efficient service delivery and “Time” is a significant variable necessary to successful accomplishment. The need for Nigerian government to re-examine time management in her public sector with a view of repositioning the sector to be able to compete well with other public sectors in the world. The peculiarity of Time management in Public Sector in Nigerian context as examined and some useful recommendations of immerse assistance proffered.

Keywords: Nigeria, public sector, time management, task

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Siddharth Rana

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As we know so far, there are 3 dimensions that we are capable of interpreting and perceiving, and there is a 4th dimension, called time, about which we don’t know much yet. We, as humans, live in the 4th dimension, not the 3rd. We travel 3 dimensionally but cannot yet travel 4 dimensionally; perhaps if we could, then visiting the past and the future would be like climbing a mountain or going down a road. So far, we humans are not even capable of imagining any higher dimensions than the three dimensions in which we can travel. We are the beings of the 4th dimension; we are the beings of time; that is why we can travel 3 dimensionally; however, if, say, there were beings of the 5th dimension, then they would easily be able to travel 4 dimensionally, i.e., they could travel in the 4th dimension as well. Beings of the 5th dimension can easily time travel. However, beings of the 4th dimension, like us, cannot time travel because we live in a 4-D world, traveling 3 dimensionally. That means to ever do time travel, we just need to go to a higher dimension and not only perceive it but also be able to travel in it. However, traveling to the past is not very possible, unlike traveling to the future. Even if traveling to the past were possible, it would be very unlikely that an event in the past would be changed. In this paper, some approaches are provided to define time, our movement in time to the future, some aspects of time travel using dimensions, and how we can perceive a higher dimension.

Keywords: time, dimensions, String theory, relativity

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Authors: Ani Thomas

Abstract:

Every narrative is a temporal construct. Every narrative creates a qualitative experience of time for the viewer. The paper argues for the concept of a qualified time that emerges from the interaction between the narrative and the audience. The paper also challenges the conventional understanding of narrative time as either story time, real time or discourse time. Looking at narratives through the medium of Cinema, the study examines how narratives create and manipulate duration or durée, the qualitative experience of time as theorized by Henri Bergson. The paper further analyzes how Cinema and, by extension, narratives are nothing but Durée and the filmmaker, the artist of durée, who shape and manipulate the perception and emotions of the viewer through the manipulation and construction of durée. The paper draws on cinematic works to look at the techniques to demonstrate how filmmakers use, for example, editing, sound, compositional and production narratives etc., to create various modes of durée that challenge, amplify or unsettle the viewer’s sense of time. Bringing together the Viewer’s durée and exploring its interaction with the narrative construct, the paper explores the emergence of the new qualitative time, the narrative durée, that defines the audience experience.

Keywords: cinema, time, bergson, duree

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Authors: John O. Akindoyo, M. D. H. Beg, Suriati Binti Ghazali, Nitthiyah Jeyaratnam

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Regeneration of bone due to the many health challenges arising from traumatic effects of bone loss, bone tumours and other bone infections is fast becoming indispensable. Over the period of time, some approaches have been undertaken to mitigate this challenge. This includes but not limited to xenografts, allografts, autografts as well as artificial substitutions like bioceramics, synthetic cements and metals. However, most of these techniques often come along with peculiar limitation and problems such as morbidity, availability, disease transmission, collateral site damage or absolute rejection by the body as the case may be. Hydroxyapatite (HA) is very compatible and suitable for this application. However, most of the common methods for HA synthesis are expensive and environmentally unfriendly. Extraction of HA from bio-wastes have been perceived not only to be cost effective, but also environment-friendly. In this research, HA was produced from bio-waste: namely bovine bones through a combination of hydrothermal chemical processes and ordinary calcination techniques. Structure and property of the HA was carried out through different characterization techniques (such as TGA, FTIR, DSC, XRD and BET). The synthesized HA was found to possess similar properties to stoichiometric HA with highly desirable thermal, degradation, structural and porous properties. This material is unique for its potential minimal cost, environmental friendliness and property controllability. It is also perceived to be suitable for tissue and bone engineering applications.

Keywords: biomaterial, biopolymer, bone, hydroxyapatite

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Authors: Andreas Rudisch, Ralf Lampert, Andreas Kolbitsch

Abstract:

It is a well-known fact among the engineering community that earthquakes with comparatively low magnitudes can cause serious damage to nonstructural components (NSCs) of buildings, even when the supporting structure performs relatively well. Past research works focused mainly on NSCs of nuclear power plants and industrial plants. Particular attention should also be given to architectural façade elements of old masonry buildings (e.g. ornamental figures, balustrades, vases), which are very vulnerable under seismic excitation. Large numbers of these historical nonstructural components (HiNSCs) can be found in highly frequented historical city centers and in the event of failure, they pose a significant danger to persons. In order to estimate the vulnerability of acceleration sensitive HiNSCs, the peak horizontal floor acceleration (PHFA) is used. The PHFA depends on the dynamic characteristics of the building, the ground excitation, and induced nonlinearities. Consequently, the PHFA can not be generalized as a simple function of height. In the present research work, an extensive case study was conducted to investigate the influence of induced nonlinearity on the PHFA for old masonry buildings. Probabilistic nonlinear FE time-history analyses considering three different hazard levels were performed. A set of eighteen synthetically generated ground motions was used as input to the structure models. An elastoplastic macro-model (multiPlas) for nonlinear homogenized continuum FE-calculation was calibrated to multiple scales and applied, taking specific failure mechanisms of masonry into account. The macro-model was calibrated according to the results of specific laboratory and cyclic in situ shear tests. The nonlinear macro-model is based on the concept of multi-surface rate-independent plasticity. Material damage or crack formation are detected by reducing the initial strength after failure due to shear or tensile stress. As a result, shear forces can only be transmitted to a limited extent by friction when the cracking begins. The tensile strength is reduced to zero. The first goal of the calibration was the consistency of the load-displacement curves between experiment and simulation. The calibrated macro-model matches well with regard to the initial stiffness and the maximum horizontal load. Another goal was the correct reproduction of the observed crack image and the plastic strain activities. Again the macro-model proved to work well in this case and shows very good correlation. The results of the case study show that there is significant scatter in the absolute distribution of the PHFA between the applied ground excitations. An absolute distribution along the normalized building height was determined in the framework of probability theory. It can be observed that the extent of nonlinear behavior varies for the three hazard levels. Due to the detailed scope of the present research work, a robust comparison with code-recommendations and simplified PHFA distributions are possible. The chosen methodology offers a chance to determine the distribution of PHFA along the building height of old masonry structures. This permits a proper hazard assessment of HiNSCs under seismic loads.

Keywords: nonlinear macro-model, nonstructural components, time-history analysis, unreinforced masonry

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