Search results for: least absolute shrinkage and selection operator

Authors: Almahd Alshereef, Ahmed Alkilany, Hammad Said, Azuraliza Abu Bakar

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From time to time, electrical power grid is directed by the National Electricity Operator to conduct load shedding, which involves hours' power outages on the area of this study, Southern Electrical Grid of Libya (SEGL). Load shedding is conducted in order to alleviate pressure on the National Electricity Grid at times of peak demand. This approach has chosen a set of categories to study load-shedding problem considering the effect of the demand priorities on the operation of the power system during emergencies. Classification of category region for load shedding problem is solved by a new algorithm (the harmony algorithm) based on the "random generation list of category region", which is a possible solution with a proximity degree to the optimum. The obtained results prove additional enhancements compared to other heuristic approaches. The case studies are carried out on SEGL.

Keywords: optimization, harmony algorithm, load shedding, classification

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Authors: Parvin Malhami

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The purpose of the present study was to investigate the effects of two functional and functional stretching methods of the leg muscles on a selection of kinematical and kinetic indicators among women with ankle instability. Twenty-four persons were targeted and randomly divided into the functional exercise (8 persons), extra-functional exercise (8 persons) and control (8 persons) groups on the basis of inclusion and exclusion criteria. The experimental groups received stretching for eight weeks, 3 sessions each week, and the control group merely performed its daily activities. Then, in order to measure the pre -test and post -test variables, the dorsi flexion, Plantar flexion and ground reaction force were investigated and measured. Data were analyzed using paired T-test and independent T-tests at a significant level of 0.05. All statistical analyses were conducted using SPSS 25 software. The results of the T-test showed the significant effect of eight weeks of functional and Extra functional exercises on dorsi Flexion, Plantar Flexion and ground reaction force. (P≤ 0/001). The results of this study showed that the implementation of the functional and Extra-functional exercise protocol had an impact on the amount of Ankle dorsi Flexion and the Plantar felxion of women with an ankle instability. It was also found that muscle flexibility following the stretch ability of the gastrocnemius muscles facilitates the walking of the wrist installation by affecting the amount of wrist flexion, so these people are recommended to use the functional and extra-functional exercise protocol.

Keywords: functional stretching, extra functional stretching, dorsi flexion, plantar flexion

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Authors: Tahir Majeed, Michael Handschuh, René Meier

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Rheumatoid arthritis patients have swelling and pain at the joints of the hand. The regions where the patient feels pain also show increased body temperature. Thermal cameras can be used to detect the rise in temperature of the affected regions. To monitor the disease progression of rheumatoid arthritis patients, they must visit the clinic regularly for scanning and examination. After scanning and evaluation, the dosage of the medicine is regulated accordingly. To monitor the disease progression over time, the correlation between the images between different visits must be established. It has been observed that by using low-cost thermal cameras, the thermal measurements do not remain the same over time, even within a single scanning. In some situations, temperatures can vary as much as 2°C within the same scanning sequence. In this paper, it has been shown that although the absolute temperature varies over time, the relative difference between the different regions remains similar. Results have been computed over four scanning sequences and are presented.

Keywords: relative thermal difference, rheumatoid arthritis, thermal imaging, thermal sensors

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Authors: Amandeep Singh, Surinder Singh

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A slotted Bow-Tie microstrip patch antenna utilizing input of coplanar waveguide for high frequency wireless applications is proposed and analyzed in this work. RT/Duroid 5880 with its dielectric constant 2.2 is opted for the experimentation to analyze the proposed microstrip slot antenna. This antenna is exclusively designed for the frequency range of 10 GHz to 11 GHz and modelling parameters are obtained from the already existing data and dimensions of antenna are adjusted by employing some corrugated slots in the Bowtie shape to obtain the required bandwidth so that it can radiate within the specified range. The characteristics of proposed antenna are measured by a FEM electromagnetic field solver and it is found that the reflection coefficient, voltage standing wave ratio, radiated gain, feed point impedance, radiation efficiency are in a good agreement. This antenna is also exhibiting an absolute bandwidth of 1000 MHz. The validated results indicate that the proposed bowtie microstrip slot antenna comes under the wideband category and utilized in the wireless application ranges between the 10 GHz – 11 GHz.

Keywords: CPW, bowtie, FEM, corrugated

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Authors: Ziyad Motala

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It is often proclaimed by leasers in Muslim majority countries that Islamic Law does not permit dissent against a ruler. This paper will evaluate and discuss freedom of speech and dissent as found in concrete prophetic examples during the time of the Prophet Muhammad. It will further look at the examples and practices during the time of the four Noble Caliphs, the immediate successors to the Prophet Muhammad. It will argue that the positivist position of absolute obedience to a ruler is inconsistent with the prophetic tradition. The examples of the Prophet and his immediate four successors (whose lessons Sunni Islam considers to be a source of Islamic Law) demonstrates among the earliest example of freedom of speech and dissent in human history. That tradition frowned upon an inert and uninvolved citizenry. It will conclude with lessons for modern day Muslim majority countries arguing with empirical evidence that freedom of speech, dissent and the right to be governed by consensus versus coercion are fundamental requisites of Islamic law.

Keywords: islamic law, demoracy, freedom of speech, right to dissent

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Authors: Kunya Bowornchockchai

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The objective of this research is to forecast the monthly exchange rate between Thai baht and the US dollar and to compare two forecasting methods. The methods are Box-Jenkins’ method and Holt’s method. Results show that the Box-Jenkins’ method is the most suitable method for the monthly Exchange Rate between Thai Baht and the US Dollar. The suitable forecasting model is ARIMA (1,1,0)  without constant and the forecasting equation is Y_t = Y_t-1 + 0.3691 (Y_t-1 - Y_t-2) When Y_t  is the time series data at time t, respectively.

Keywords: Box–Jenkins method, Holt’s method, mean absolute percentage error (MAPE), exchange rate

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Authors: Ninel Kokanyan, Edvard Kokanyan, Anush Movsesyan, Marc D. Fontana

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Lithium Niobate (LN) is one of the widely used ferroelectrics having a wide number of applications such as phase-conjugation, holographic storage, frequency doubling, SAW sensors. Furthermore, the possibility of doping with rare-earth ions leads to new laser applications. Ho and Tm dopants seem interesting due to laser emission obtained at around 2 µm. Raman spectroscopy is a powerful spectroscopic technique providing a possibility to obtain a number of information about physicochemical and also optical properties of a given material. Polarized Raman measurements were carried out on Ho and Tm doped LN crystals with excitation wavelengths of 532nm and 785nm. In obtained Raman anti-Stokes spectra, we detect expected modes according to Raman selection rules. In contrast, Raman Stokes spectra are significantly different compared to what is expected by selection rules. Additional forbidden lines are detected. These lines have quite high intensity and are well defined. Moreover, the intensity of mentioned additional lines increases with an increase of Ho or Tm concentrations in the crystal. These additional lines are attributed to emission lines reflecting the photoluminescence spectra of these crystals. It means that in our case we were able to detect, within a very good resolution, in the same Stokes spectrum, the transitions between the electronic states, and the vibrational states as well. The analysis of these data is reported as a function of Ho and Tm content, for different polarizations and wavelengths, of the incident laser beam. Results also highlight additional information about π and σ polarizations of crystals under study.

Keywords: lithium niobate, Raman spectroscopy, luminescence, rare-earth ions doped lithium niobate

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Authors: Narumon Piaseu

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This survey research was aimed to describe and compare consumption behavior of health risk food among students in Suan Sunandha Rajabhat University. Sample included 400 undergraduate students enrolled in the first semester of 2008 academic year. Data were collected by using self reported questionnaire developed by the researcher. Data were then analyzed by descriptive statistics including frequency, percentage, mean, standard deviation, and inferential statistics including independent t-test, and Oneway ANOVA. Results revealed that most of the sample were women (67%), enrolled in social related programs (74%). Approximately half of them (45.5%) stayed in dormitory. The mean of monthly income was 5,164 Baht and daily food expenditure was 114.55 Baht. Majority of them (83%) had ready-to-eat food. A major factor influencing their food selection was their parents (61%). A main reason for their food selection was food that looks good (70.75%). Almost half of them (46.25%) had heavy exercise less than 3 times per week. Regarding knowledge on health risk food, 43.5% of the sample had good knowledge. The followings were moderate (41%) and poor (41%). Most of the sample (60.75%) had consumption behavior at low risk. The following was at moderate risk (37.25%). Only 2% were at high risk. Among the sample, consumption behavior of health risk food were significantly different in years of study (F = 3.168, p = .024), daily food expenditure (F = 8.950, p <.001), and knowledge on health risk food (F = 37.856, p <.001), while no significant difference in consumption behavior of health risk food was found in those with a difference in gender, program of study, living place, and monthly income. Results indicate the importance of providing knowledge regarding health risk food for students and their parents in order to promote appropriate food consumption behavior among the students.

Keywords: food consumption, risky behavior, Suan Sunandha Rajabhat University, health risk

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Authors: Nadia Chagtmi, Nejla Rejab, Noureddine Boulejfen

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This paper presents a calibration approach based on artificial neural networks (ANN) to determine the envelop signal (I+jQ) of a six-port based receiver (SPR). The memory effects called also dynamic behavior and the nonlinearity brought by diode based power detector have been taken into consideration by the ANN. Experimental set-up has been performed to validate the efficiency of this method. The efficiency of this approach has been confirmed by the obtained results in terms of waveforms. Moreover, the obtained error vector magnitude (EVM) and the mean absolute error (MAE) have been calculated in order to confirm and to test the ANN’s performance to achieve I/Q recovery using the output voltage detected by the power based detector. The baseband signal has been recovered using ANN with EVMs no higher than 1 % and an MAE no higher than 17, 26 for the SPR excited different type of signals such QAM (quadrature amplitude modulation) and LTE (Long Term Evolution).

Keywords: six-port based receiver; calibration, nonlinearity, memory effect, artificial neural network

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Authors: Whitehead-Clarke T., Beynon V., Banks J., Karanjia R., Mudera V., Windsor A., Kureshi A.

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Introduction: Mesh implants are regularly used to help repair both hiatus hernias (HH) and diaphragmatic hernias (DH). In vivo studies are used to test not only mesh safety but increasingly comparative efficacy. Our work examines the field of in vivo mesh testing for HH and DH models to establish current practices and standards. Method: This systematic review was registered with PROSPERO. Medline and Embase databases were searched for relevant in vivo studies. 44 articles were identified and underwent abstract review, where 22 were excluded. 4 further studies were excluded after full text review – leaving 18 to undergo data extraction. Results: Of 18 studies identified, 9 used an in vivo HH model and 9 a DH model. 5 studies undertook mechanical testing on tissue samples – all uniaxial in nature. Testing strip widths ranged from 1-20mm (median 3mm). Testing speeds varied from 1.5-60mm/minute. Upon histology, the most commonly assessed structural and cellular factors were neovascularization and macrophages, respectively (n=9 each). Structural analysis was mostly qualitative, where cellular analysis was equally likely to be quantitative. 11 studies assessed adhesion formation, of which 8 used one of four scoring systems. 8 studies measured mesh shrinkage. Discussion: In vivo studies assessing mesh for HH and DH repair are uncommon. Within this relatively young field, we encourage surgical and materials testing institutions to discuss its standardisation.

Keywords: hiatus, diaphragmatic, hernia, mesh, materials testing, in vivo

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Authors: J. BalaRaju, M. Govinda Raj, C. S. N. Murthy

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Every organization in the competitive world tends to improve its economy by increasing their production and productivity rates. Unequivocally, the production in Indian underground mines over the years is not satisfactory, due to a variety of reasons. There are manifold of avenues for the betterment of production, and one such approach is through enhanced utilization of mechanized equipment such as Load Haul Dumper (LHD). This is used as loading and hauling purpose in underground mines. In view of the aforementioned facts, this paper delves into identification of the key influencing factors such as LHDs maintenance effectiveness, vehicle condition, operator skill and utilization of the machines on performance of LHDs. An attempt has been made for improvement of performance of the equipment through evaluation of Overall Equipment Effectiveness (OEE). Two different approaches for evaluation of OEE have been adopted and compared under various operating conditions. The use of OEE calculation in terms of percentage availability, performance and quality and the hitherto existing situation of the underground mine production is evaluated. Necessary recommendations are suggested to mining industry on the basis of OEE.

Keywords: utilization, maintenance, availability, performance and quality

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Authors: Syed Talib Abbas Raza, Tahseen Ahmed Jilani, Saleem Abdullah

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This paper presents interval-valued intuitionistic fuzzy soft sets based TOPSIS method for group decision making. The interval-valued intuitionistic fuzzy soft set is a mutation of an interval-valued intuitionistic fuzzy set and soft set. In group decision making problems IVIFSS makes the process much more algebraically elegant. We have used weighted arithmetic averaging operator for aggregating the information and define a new Hybrid Score Function as metric tool for comparison between interval-valued intuitionistic fuzzy values. In an illustrative example we have applied the developed method to a criminological problem. We have developed a group decision making model for integrating the imprecise and hesitant evaluations of multiple law enforcement agencies working on target killing cases in the country.

Keywords: group decision making, interval-valued intuitionistic fuzzy soft set, TOPSIS, score function, criminology

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Andrew Fife, Jean-Francois Esculier, Codi Ramsey, Kim Hebert-Losier

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Objectives: We aimed to identify how an evidence-based educational video influences how runners select shoes, and perceive shoe comfort, satisfaction, and performance over three months in comparison with a control video. Design: Double-blind randomised controlled trial. Method: Fifty-six runners were randomly assigned to view one of two video presentations prior to purchasing new shoes for road running in speciality stores. Runners completed a survey with regards to their own shoes and one in reference to the new shoes purchased at three timepoints: before first use, one-month post-purchase, and three-months post-purchase. Perceived shoe comfort, satisfaction, and performance were assessed using 100 mm visual analogue scales. Factors that influenced their shoe purchase were ranked in order of importance. Results: Comfort and satisfaction were not significantly different between groups and timepoints. The perceived performance of new shoes (75.6 mm) was significantly greater than own shoes (mean: 67.6 mm) before first use, but ratings returned to own-shoe levels one month later in both groups. The group receiving the evidence-based presentation reported their purchased shoes as being influenced more by the video (55.4 mm) than the control group (21.8 mm), although both chose the same brand and model as previously worn over half of the time. Runners in both groups prioritised fit, comfort, and choosing similar shoes to the ones they previously used. Conclusions: In contrast to expectations, the evidence-based educational video did not appear to influence running shoe selection, or overall perceived shoe comfort, satisfaction, or performance.

Keywords: comfort, consumer behaviour, consciousness, education, running, shoes

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Authors: Ali Safaeianpour, Nima Shamandi

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As air traffic expands, many airports have evolved into transit centers for people, information, and commerce, and technology implementation is an absolute part of airport development. Several challenges are in the way of implementing technology in an airport. Airport 4.0 proposes the "Smart Airport" concept, which focuses on using modern technologies such as Big Data, the Internet of Things (IoT), advanced biometric systems, blockchain, and cloud computing to alter and enhance passengers' journeys. Several common IoT concrete topics as partial keys to smart airports are discussed and introduced, ranging from automated check-in systems to exterior tracking processes, with the goal of enlightening more and more insightful ideas and proposals about smart airport solutions. IoT will dramatically alter people's lives by infusing intelligence, boosting the quality of life, and assembling it smarter. This paper reviews the approaches to transforming an airport into a smart airport and describes several enabling components of IoT and challenges that can hinder the implementation of a smart airport's function, which require to be addressed.

Keywords: airport 4.0, digital airport, smart airport, IoT

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Authors: Maia Kukhaleishvili, Ekaterine Bulauri, Iveta Megrelishvili, Tamar Shamatava, Tamar Chipashvili

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Plant viruses can cause loss of yield and quality in a lot of important crops. Symptoms of pathogens are variable depending on the cultivars and virus strain. Selection of resistant potato varieties would reduce the risk of virus transmission and significant economic impact. Other way to avoid reduced harvest yields is regular potato seed production sampling and testing for viral infection. The aim of this study was to determine the occurrence and distribution of viral diseases according potato cultivars for further selection of virus-free material in Georgia. During the summer 2015- 2016, 5 potato cultivars (Sante, Laura, Jelly, Red Sonia, Anushka) at 5 different farms located in Akhalkalaki were tested for 6 different potato viruses: Potato virus A (PVA), Potato virus M (PVM), Potato virus S (PVS), Potato virus X (PVX), Potato virus Y (PVY) and potato leaf roll virus (PLRV). A serological method, Double Antibody Sandwich-Enzyme linked Immunosorbent Assay (DASELISA) was used at the laboratory to analyze the results. The result showed that PVY (21.4%) and PLRV (19.7%) virus presence in collected samples was relatively high compared to others. Researched potato cultivars except Jelly and Laura were infected by PVY with different concentrations. PLRV was found only in three potato cultivars (Sante, Jelly, Red Sonia) and PVM virus (3.12%) was characterized with low prevalence. PVX, PVA and PVS virus infection was not reported. It would be noted that 7.9% of samples were containing PVY/PLRV mix infection. Based on the results it can be concluded that PVY and PLRV infections are dominant in all research cultivars. Therefore significant yield losses are expected. Systematic, long-term control of potato viral infection, especially seed-potatoes, must be regarded as the most important factor to increase seed productivity.

Keywords: virus, potato, infection, diseases

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Authors: Md. Moniruzzaman, Thirayoot Limanond

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Being the most visible indicator, the transport system of a city points out how developed the city is. Dhaka megacity holds a mixed composition of motorized and non-motorized modes of transport and the number of vehicle figure is escalating over times. And this obviously poses associated environmental costs like air pollution, noise etc. which is degrading the quality of life in the city. Eventually sustainable transport or more importantly green transport from environmental point of view has become a prime choice to the transport professionals in order to cope up the crisis. Currently the city authority is planning to execute such sustainable transport systems that could serve the pressing demand of the present and meet the future needs effectively. This study focuses on the selection and evaluation of green transportation systems among potential alternatives on a priority basis. In this paper, Fuzzy TOPSIS - a multi-criteria decision method is presented to find out the most prioritized alternative. In the first step, Twenty-one individual specific criteria for sustainability assessment are selected. In the following step, experts provide linguistic ratings to the potential alternatives with respect to the selected criteria. The approach is used to generate aggregate scores for sustainability assessment and selection of the best alternative. In the third step, a sensitivity analysis is performed to understand the influence of criteria weights on the decision making process. The key strength of fuzzy TOPSIS approach is its practical applicability having a generation of good quality solution even under uncertainty.

Keywords: green transport, multi-criteria decision approach, urban transportation system, sustainability assessment, fuzzy theory, uncertainty

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Authors: Mahmoud M. Othman, Almoataz Y. Abdelaziz, Yasser G. Hegazy

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This paper presents a load control strategy based on modification of the Big Bang Big Crunch optimization method. The proposed strategy aims to determine the optimal load to be controlled and the corresponding time of control in order to minimize the energy purchased from substation. The presented strategy helps the distribution network operator to rely on the renewable energy sources in supplying the system demand. The renewable energy sources used in the presented study are modeled using the diagonal band Copula method and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithm.

Keywords: big bang big crunch, distributed generation, load control, optimization, planning

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Authors: W. A. M. Abdel Kawy, Kh. M. Darwish

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Adequate land use selection is an essential step towards achieving sustainable development. The main object of this study is to develop a new scale for land suitability system, which can be compatible with the local conditions. Furthermore, it aims to adapt the conventional land suitability systems to match the actual environmental status in term of soil types, climate and other conditions to evaluate land suitability for newly reclaimed areas. The new system suggests calculation of land suitability considering 20 factors affecting crop selection grouping into five categories; crop-agronomic, land management, development, environmental conditions and socio – economic status. Each factor is summed by each other to calculate the total points. The highest rating for each factor indicates the highest preference for the evaluated crop. The highest rated crops for each group are those with the highest points for the actual suitability. This study was conducted to assess the application efficiency of the new land suitability scale in recently reclaimed sites in Egypt. Moreover, 35 representative soil profiles were examined, and soil samples were subjected to some physical and chemical analysis. Actual and potential suitabilities were calculated by using the new land suitability scale. Finally, the obtained results confirmed the applicability of a new land suitability system to recommend the most promising crop rotation that can be applied in the study areas. The outputs of this research revealed that the integration of different aspects for modeling and adapting a proposed model provides an effective and flexible technique, which contribute to improve land suitability assessment for several crops to be more accurate and reliable.

Keywords: analytic hierarchy process, land suitability, multi-criteria analysis, new reclaimed areas, soil parameters

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Authors: Mahesh Gupta

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The main goal in the design of a die for extrusion of a complex profile is to obtain a uniform velocity at the die exit. If the velocity at the exit of an extrusion die is not uniform, the shape of the extrudate profile can change significantly after the polymer exits the die. To rectify the extrudate distortion caused by non-uniform exit velocity, calibrators and sizers are often installed along the extrudate cooling system. Furthermore, the profile shape in calibrators and sizers is sometimes gradually changed to intentionally deform the extrudate to the required final product shape. This is exploited to simplify extrusion die design, because a relatively simple profile at the die exit can be modified to obtain a more complex profile by deforming it in calibrators or sizers. The gradual change in the shape of calibrator or sizer profiles can also be used to extrude slightly different profiles from the same die. In the present work, a combined flow, thermal and structural analysis is used to accurately predict distortion of extrudate profile after the polymer leaves a die. Simulations of the flow and extrudate deformation in two different bilayer coextrusion dies with gradually changing profile shape in successive calibrators and sizers will be presented. The effect of non-uniform exit velocity, cooling shrinkage and shape of sizer profiles on extrudate deformation is included in the simulation. The predicted extrudate shape and layer structure is found to match accurately with those in a coextruded product.

Keywords: coextrusion, extrusion die design, finite element method, polymers

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Authors: Matthew Heidman, Susan Dallabrida, Analice Costa

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For infant caregivers, choosing an infant formula for their child can be a difficult task in an already stressful environment of caring for a newborn. There exist several channels that influence purchasing decision of infant formula such as, friends and family and their experiences, health care professionals, social media influencers, as well as standard media marketing. This study sought to identify the key channels by which caregivers obtain information regarding infant formula and help them make their purchasing decision. A digital survey was issued for 90 days in the US (n=121) and 30 days in Mexico (n=88) targeting respondents with children ≤4 years of age. Respondents were asked two key questions regarding the influences on their purchasing decisions: 1) “When choosing a formula brand, what do you do to help you make your decision?”, and 2) “When choosing a formula brand, what is most important to you?”. A list of potential answers was provided for each question and respondents were asked to select all that apply to them. Lastly, respondents were provided a 5-point Likert scale and asked to respond to the statement 3) “I am more likely to buy a particular formula brand if my pediatrician recommends it to me”. For question 1, in the US and Mexico, 76% and 95% of respondents respectively, selected “I ask my pediatrician” which represented the top selection. For question 2, 52% and 45% of respondents respectively, selected “On package “Pediatrician Recommended” claim…” which also represented the top selection. For statement 3, 82% and 89% of respondents respectively, stated that they either “somewhat agree” or “strongly agree” with the statement. For infant caregivers, the pediatrician is a very important channel of influence when it comes to purchasing decision of infant formula. Caregivers clearly see the pediatrician as the arbiter of their child’s nutrition and seek their recommendations for infant formula use. For infant formula manufacturers, it is important that they see the pediatrician as the gatekeeper to this market, and they put resources into medical marketing communication to this health care professional group to ensure success.

Keywords: infant formula, pediatrician, purchasing driver, caregiver

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Authors: Jai Heui Kim, Sotheara Veng

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This paper studies the portfolio optimization problem for a pension fund under a hybrid model of stochastic volatility and constant elasticity of variance (CEV) using asymptotic analysis method. When the volatility component is fast mean-reverting, it is able to derive asymptotic approximations for the value function and the optimal strategy for general utility functions. Explicit solutions are given for the exponential and hyperbolic absolute risk aversion (HARA) utility functions. The study also shows that using the leading order optimal strategy results in the value function, not only up to the leading order, but also up to first order correction term. A practical strategy that does not depend on the unobservable volatility level is suggested. The result is an extension of the Merton's solution when stochastic volatility and elasticity of variance are considered simultaneously.

Keywords: asymptotic analysis, constant elasticity of variance, portfolio optimization, stochastic optimal control, stochastic volatility

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: P. Meethum, C. Suvanjumrat

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Many aluminum motorcycle parts produced by a high pressure die casting. Some parts such as fuel caps were a thin and complex shape. This part risked for porosities and blisters on surface if it only depended on an experience of mold makers for mold design. This research attempted to use CAST-DESIGNER software simulated the high pressure die casting process with the same process parameters of a motorcycle fuel cap production. The simulated results were compared with fuel cap products and expressed the same porosity and blister locations on cap surface. An average of absolute difference of simulated results was obtained 0.094 mm when compared the simulated porosity and blister defect sizes on the fuel cap surfaces with the experimental micro photography. This comparison confirmed an accuracy of software and will use the setting parameters to improve fuel cap molds in the further work.

Keywords: aluminum, die casting, fuel cap, motorcycle

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Authors: Avi Harel

Abstract:

Most accidents are commonly attributed in hindsight to human errors, yet most methodologies for safety focus on technical issues. According to the Black Swan theory, this paradox is due to insufficient data about the ways systems fail. The article presents a study of the sources of errors, and proposes a methodology for utility-oriented design, comprising methods for coping with each of the sources identified. Accident analysis indicates that errors typically result from difficulties of operating in exceptional conditions. Therefore, following STAMP, the focus should be on preventing exceptions. Exception analysis indicates that typically they involve an improper account of the operational scenario, due to deficiencies in the system integration. The methodology proposes a model, which is a formal definition of the system operation, as well as principles and guidelines for safety-oriented system integration. The article calls to develop and integrate tools for recording and analysis of the system activity during the operation, required to implement validate the model.

Keywords: accidents, complexity, errors, exceptions, interaction, modeling, resilience, risks

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Authors: Debjit Dutta, P. Roy, O. Panella

Abstract:

In recent years, non Hermitian interaction in non relativistic as well as relativistic quantum mechanics have been examined from various aspect. We can observe interesting fact that for such systems a class of potentials, namely the PT symmetric and η-pseudo Hermitian admit real eigenvalues despite being non Hermitian and analogues of those system have been experimentally verified. Point to be noted that relativistic non Hermitian (PT symmetric) interactions can be realized in optical structures and also there exists photonic realization of the (1 + 1) dimensional Dirac oscillator. We have thoroughly studied generalized Dirac oscillators with non Hermitian interactions in (1 + 1) dimensions. To be more specific, we have examined η pseudo Hermitian interactions within the framework of generalized Dirac oscillator in (1 + 1) dimensions. In particular, we have obtained a class of interactions which are η-pseudo Hermitian and the metric operator η could have been also found explicitly. It is possible to have exact solutions of the generalized Dirac oscillator for some choices of the interactions. Subsequently we have employed the mapping between the generalized Dirac oscillator and the Jaynes Cummings (JC) model by spin flip to obtain a class of exactly solvable non Hermitian JC as well as anti Jaynes Cummings (AJC) type models.

Keywords: Dirac oscillator, non-Hermitian quantum system, Hermitian, relativistic

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Authors: Hefzollah Mohammadian, Ensieh Hajeb, Mohamad Baqer Heidari

Abstract:

In this paper, for the protection and safety of tanks gases (flammable materials) and also due to the considerable economic value of the reservoir, the new system for the protection, the conservation and fire fighting has been cloned. The system consists of several parts: the Sensors to detect heat and fire with Nanotechnology (nano sensor), Barrier for isolation and protection from a range of two electronic zones, analyzer for detection and locating point of fire accurately, Main electronic board to announce fire, Fault diagnosis in different locations, such as relevant alarms and activate different devices for fire distinguish and announcement. An important feature of this system, high speed and capability of fire detection system in a way that is able to detect the value of the ambient temperature that can be adjusted. Another advantage of this system is autonomous and does not require human operator in place. Using nanotechnology, in addition to speeding up the work, reduces the cost of construction of the sensor and also the notification system and fire extinguish.

Keywords: analyser, barrier, heat resistance, general fault, general alarm, nano sensor

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Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

Abstract:

Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

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Authors: Mei-Hsiu Chi, Jyh-Yang Wu, Sheng-Gwo Chen

Abstract:

The diffusion-reaction equations are important Partial Differential Equations in mathematical biology, material science, physics, and so on. However, finding efficient numerical methods for diffusion-reaction systems on curved surfaces is still an important and difficult problem. The purpose of this paper is to present a convergent geometric method for solving the reaction-diffusion equations on closed surfaces by an O(r)-LTL configuration method. The O(r)-LTL configuration method combining the local tangential lifting technique and configuration equations is an effective method to estimate differential quantities on curved surfaces. Since estimating the Laplace-Beltrami operator is an important task for solving the reaction-diffusion equations on surfaces, we use the local tangential lifting method and a generalized finite difference method to approximate the Laplace-Beltrami operators and we solve this reaction-diffusion system on closed surfaces. Our method is not only conceptually simple, but also easy to implement.

Keywords: closed surfaces, high-order approachs, numerical solutions, reaction-diffusion systems

Procedia PDF Downloads 353