Search results for: accuracy improvement

Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

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Authors: Amir Andria Gad Shehata

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Mesfin Getu Woldetensay

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Representatives and commercially viable natural gas liquids (NGLs) recovery processes were studied under various feed conditions that are classified as lean and rich. The conventional turbo- expander process scheme (ISS) was taken as a base case. The performance of this scheme was compared against with the gas sub-cooled process (GSP), cold residue-gas (CRR) and recycle split-vapor (RSV), enhanced NGL recovery process (IPSI-1) and enhanced NGL recovery process with internal refrigeration (IPSI-2). The development made for the GSP, CRR and RSV are at the top section of the demethanizer column whereas the IPSI-1 and IPSI-2 improvement focus in the lower section. HYSYS process flowsheet was initially developed for all the processes including the ISS under a common criteria that could help to demonstrate the performance comparison. Accordingly, a number of simulation runs were made for the selected eight types of feed. Results show that the reboiler duty requirement using rich feeds for GSP, CRR and RSV is quite high compared to IPSI-1 and IPSI-2. The latter shows relatively lower duty due to the presence of self-refrigeration system that allows the inlet feed to be used for achieving cooling without the need to use propane refrigerant. The energy consumption for lean feed is much lower than that of the rich feed in all process schemes.

Keywords: composition, lean, rich, duty

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Authors: H. Alamri

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Natural fiber reinforced composites have attracted researchers for their desirable properties of toughness, high modulus, low density, recyclability, and renewability. In fact, the use of natural fibers in polymer composites has the potential to produce materials with higher specific strength and specific modulus due of their low density. Likewise, polymer-nano-filler composites have been widely investigated for their unique and significant improvement in strength, modulus, impact strength, barrier properties, heat resistance and thermal stability. In this paper, The addition of halloysite nanotubes (HNTs) with three different weight percentages (1%, 3% and 5%) on enhancing barrier and flexural strength and modulus of cellulose-fiber (CF) /epoxy composites after water treatment for six months was studied. Results indicated that water uptake decreased as HNT content increased. The presence of HNT improved flexural strength and flexural modulus of CF/epoxy composites. SEM results showed damages in fiber-matrix interfacial bonding due to water absorption. The addition of HNTs was found to enhance to adhesion between fibers and matrix.

Keywords: mechanical properties, epoxy, nanocomposites, halloysite nanotubes

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Authors: N. Adjlane, N. Haddad

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The American foulbrood is one of the most serious diseases that may affect brood of larvae and pupae stages. The causative organism is a gram positive bacterium Paaenibacillus larvae. American foulbrood infected apiaries suffer from severe economic losses, resulting from significant decreases in honeybee populations and honey production. The aim of this study was to detect Paenibacillus larvae in the remains collected at the bottom of the hive from the suspected hives by direct PCR and culture growth. A total of 56 suspected beehive wax debris samples collected in 40 different apiaries located in the central region of Algeria. MYPGP the culture medium is used during all the identifications of the bacterium. After positive results on samples, biochemical confirmation tests (test of catalase, presence hydrolysis of casein) and microscopic (gram stain) are used in order to verify the accuracy of the initial results. The QIAamp DNA Mini Kit is used to identify the DNA of Paaenibacillus larvae. Paaenibacillus larvae were identified in 14 samples out of 16 by the PCR. A suspected culture-negative sample was found positive through evaluation with PCR. This research is for the bacterium Paaenibacillus larvae in the debris of the colony is an effective method for diagnosis of the pathology of American foulbrood.

Keywords: Paenibacillus larvae, honeybee, PCR, microbiological method

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Kapse Swapnil, K. Shankar

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Aiming at optimizing the weight and deflection of cantilever beam subjected to maximum stress and maximum deflection, Multi-objective Particle Swarm Optimization (MOPSO) with Utopia Point based local search is implemented. Utopia point is used to govern the search towards the Pareto Optimal set. The elite candidates obtained during the iterations are stored in an archive according to non-dominated sorting and also the archive is truncated based on least crowding distance. Local search is also performed on elite candidates and the most diverse particle is selected as the global best. This method is implemented on standard test functions and it is observed that the improved algorithm gives better convergence and diversity as compared to NSGA-II in fewer iterations. Implementation on practical structural problem shows that in 5 to 6 iterations, the improved algorithm converges with better diversity as evident by the improvement of cantilever beam on an average of 0.78% and 9.28% in the weight and deflection respectively compared to NSGA-II.

Keywords: Utopia point, multi-objective particle swarm optimization, local search, cantilever beam

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Apurba Kanti Chowdhury, Taslima Zahan

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The inclusion of mungbean in a cropping pattern not only increases the cropping intensity but also enriches soil health as well as ensures nutrition for the fast-growing population of Bangladesh. A study was conducted in the farmers’ field during 2013-14 and 2014-15 to observe the performance of four-crop based improve cropping pattern Potato-Mungbean-Jute -t.aman rice against the existing cropping pattern Potato-Jute -t.aman rice at Domar, Nilphamari followed by randomized complete block design with three replications. Two years study revealed that inclusion of mungbean and better management practices in improved cropping pattern provided higher economic benefit over the existing pattern by 73.1%. Moreover, the average yield of potato increased in the improved pattern by 64.3% compared to the existing pattern; however yield of jute and t.aman rice in improved pattern declined by 5.6% and 10.7% than the existing pattern, respectively. Nevertheless, the additional yield of mungbean in the improved pattern helped to increase rice equivalent yield of the whole pattern by 38.7% over the existing pattern. Thus, the addition of mungbean in the existing pattern Potato-Jute -t.aman rice seems to be profitable for the farmers and also might be sustainable if the market channel of mungbean developed.

Keywords: crop diversity, food nutrition, production efficiency, yield improvement

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Authors: Muhamad Azani Yahya, Vikneswaran Munikanan, Mohammed Alias Yusof

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Lean thinking holds the potential for improving the construction sector, and therefore, it is a concept that should be adopted by construction sector players and academicians in the real industry. Bridging from that, a learning process for construction sector players regarding this matter should be the agenda in gaining the knowledge in preparation for their career. Lean principles offer opportunities for reducing lead times, eliminating non-value adding activities, reducing variability, and are facilitated by methods such as pull scheduling, simplified operations and buffer reduction. Thus, the drive for rapid construction, which is a systematic approach in enhancing efficiency to deliver a project using time reduction, while lean is the continuous process of eliminating waste, meeting or exceeding all customer requirements, focusing on the entire value stream and pursuing perfection in the execution of a constructed project. The methodology presented is shown to be valid through literature, interviews and questionnaire. The results show that the majority of construction sector players unfamiliar with lean thinking and they agreed that it can improve the construction process flow. With this background knowledge established and identified, best practices and recommended action are drawn.

Keywords: construction improvement, rapid construction, time reduction, lean construction

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Authors: Reem Al-Garni

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Malnutrition is a global epidemic, but the under-weight or Failure-To-Thrive risk is increasing in rehabilitation setting and considered one of the contribution factor for developmental delay. Beside the consequences of malnutrition on children growth and development, there are other side-effects that might delay or hold the progress of rehabilitation. The awareness for malnutrition must be raised and discussed by the rehabilitation team, to promote the treatment and to optimize the client care. The solution can start from food supplements intake and / or Enteral Nutrition plan, depending on the malnutrition level and to reach the goal, the medical team should to work together in order to provide comprehensive treatment and to help the family to be able to manage their child condition. We have explore the outcomes of rehabilitation between the children with CP whose diagnosed with malnutrition and children with normal body Wight Over a period of 4 months who received 4-6 weeks of rehabilitation two hours daily by using WeeFIM score to measure rehabilitation outcomes. WeeFIM measures and covers various domains, such as: self-care, mobility, locomotion, communication and other psycho-social aspects. Our findings reported that children with normal body Wight has better outcomes and improvement comparing with children with malnutrition for the entire study sample.

Keywords: Cerebral Palsy (CP), pediatric Functional Independent Measure (WeeFIM), rehabilitation, malnutrition

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Authors: E. Behmanesh, J. Pannek

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Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.

Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method

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Authors: Neda Dekamei, Mostafa Sarabzadeh, Masoumeh Bigdeli

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Backward running is commonly used in different sports conditioning, motor learning, and neurological purposes, and even more commonly in physical rehabilitation. The present study evaluated the effects of six weeks backward and forward running methods on balance promotion adaptation in students. 12 male and female preseniors with the age range of 45-60 years participated and were randomly classified into two groups of backward running (n: 6) and forward running (n: 6) training interventions. During six weeks, 3 sessions per week, all subjects underwent stated different models of backward and forward running training on treadmill (65-80 of HR max). Pre and post-tests were performed by force plate and electromyogram, two times before and after intervention. Data were analyzed using by T test. On the basis of obtained data, significant differences were recorded on balance and plantar flexion force in backward running (BR) and no difference for forward running (FR). It seems the training model of backward running can generate more stimulus to achieve better plantar flexion force and strengthening ankle protectors which leads to balance improvement in pre aging period. It can be recommended as an effective method to promote seniors life quality especially in balance neuromuscular parameters.

Keywords: backward running, balance, plantar flexion, pre seniors

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Authors: Sanjaykumar R. Patel, Parth R. Kayastha

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α-lactose monohydrate is widely used in the pharmaceutical industries as an inactive substance that acts as a vehicle or a medium for a drug or other active substance. It is a byproduct of dairy industries, and the recovery of lactose from whey not only boosts the improvement of the economics of whey utilization but also causes a reduction in pollution as lactose recovery can reduce the BOD of whey by more than 80%. In the present study, levels of process parameters were kept as initial lactose concentration (30-50% w/w), sonication amplitude (20-40%), sonication time (2-6 hours), and crystallization temperature (10-20 ^oC) for the recovery of lactose in ultrasound assisted cooling crystallization. In comparison with cooling crystallization, the use of ultrasound enhanced the lactose recovery by 39.17% (w/w). The parameters were optimized for the lactose recovery using Taguchi Method. The optimum conditions found were initial lactose concentration at level 3 (50% w/w), amplitude of sonication at level 2 (40%), the sonication time at level 3 (6 hours), and crystallization temperature at level 1 (10 °C). The maximum recovery was found to be 85.85% at the optimum conditions. Sonication time and the initial lactose concentration were found to be significant parameters for the lactose recovery.

Keywords: crystallization, lactose, Taguchi method, ultrasound

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Authors: Zuoji Huang, Haiming Qian, Chunlin Wang, Jinyan Sun, Nan Xu

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In this paper, the strategy to extract double road edge lines from acquired road stripe image was explored. The workflow is as follows: the road stripes are acquired by probabilistic boosting tree algorithm and morphological algorithm immediately, and road centerlines are detected by thinning algorithm, so the initial road edge lines can be acquired along the road centerlines. Then we refine the results with big variation of local curvature of centerlines. Specifically, the energy function of edge line is constructed by gradient feature and spectral information, and Dijkstra algorithm is used to optimize the initial road edge lines. The Snake model is constructed to solve the fracture problem of intersection, and the discrete dynamic programming algorithm is used to solve the model. After that, we could get the final road network. Experiment results show that the strategy proposed in this paper can be used to extract the continuous and smooth road edge lines from high-resolution remote sensing images with an accuracy of 88% in our study area.

Keywords: road edge lines extraction, energy function, intersection fracture, Snake model

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Authors: Cynthia Oluchi Akagha

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This paper highlights the increase in production cost and the corresponding outcomes in Nigeria using six major manufacturing companies as a case study. During an inflationary period, the cost-of-living increases, which reduces the purchasing power of money. Inflation has become a severe issue in many countries recently. To examine how inflation affects the success of businesses in Nigeria, a quantitative approach and a focus on causality were utilized to examine six (6) functional Nigerian manufacturing enterprises. The correlation between business production cost, cost of items supplied, and gross profit from 2021-2022 was analyzed. The analysis recorded that the cost of production increased in 2022 compared to 2021. The expansion varied between the six companies by 77.1%. Only one company out of six reported a decrease in gross profit in 2022 compared to the previous year. The other five companies' profits increased between 6.5% and 87%. Companies like these have thrived despite the rising cost of living because they have adjusted by increasing their product pricing. Since this change has the most significant influence on consumers, the best long-term reaction for a corporation to inflationary effects is often an improvement in cost efficiency, output, or both.

Keywords: economic meltdown, inflation, organization, performance

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Authors: Shrey Sharma, Gunjan Kumar Verma

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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: inversion, limitations, optimization, resistivity

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: Dalave S. C., S. G. Auti, B. J. Apparao

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Centella asiatica (L) Urban, commonly known as Brahmi and Mandookaparni is a valuable medicinal plant highly valued for its asiaticoside and madecassoside. It is widely used in Ayurveda and Unani systems of medicine. Attempts are made in the present investigation to improve the genotype of Centella plant that can yield higher amount of the therapeutically active compounds viz., asiaticosides and madecassosides, employing techniques of polyploidy breeding. Young developing shoots of Centella were treated with different concentrations of colchicine for varying time intervals. 0.4 % colchicine for 6 hours duration at room temperature was effective in inducing autopolyploidy in this plant. The colchicine treated plants were allowed to reproduce vegetatively for several generations in a polyhouse. The colchicine treated plants showed significant increase in plant size, fresh & dry weights, vigorous growth, broad leaves and double the number of chromosomes. HPTLC analysis of dried leaves of control and polyploid plants, even after 9th generations, revealed that the tetraploids synthesized at two times more asiaticoside and madecassoside, as compared to control, untreated diploid plants.

Keywords: Centella asiatica, polyploidy, asiaticosides, madecassoside, HPTLC

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Authors: Pooya Niksiar, Ali Ashrafizadeh, Mehrzad Shams, Amir Hossein Madani

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There are many computationally demanding applications in science and engineering which need efficient algorithms implemented on high performance computers. Recently, Graphics Processing Units (GPUs) have drawn much attention as compared to the traditional CPU-based hardware and have opened up new improvement venues in scientific computing. One particular application area is Computational Fluid Dynamics (CFD), in which mature CPU-based codes need to be converted to GPU-based algorithms to take advantage of this new technology. In this paper, numerical solutions of two classes of discrete fluid flow models via both CPU and GPU are discussed and compared. Test problems include an Eulerian model of a two-dimensional incompressible laminar flow case and a Lagrangian model of a two phase flow field. The CUDA programming standard is used to employ an NVIDIA GPU with 480 cores and a C++ serial code is run on a single core Intel quad-core CPU. Up to two orders of magnitude speed up is observed on GPU for a certain range of grid resolution or particle numbers. As expected, Lagrangian formulation is better suited for parallel computations on GPU although Eulerian formulation represents significant speed up too.

Keywords: CFD, Eulerian formulation, graphics processing units, Lagrangian formulation

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Authors: Tigmanshu Bhatnagar, Petra Badke-Schaub

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Facilitating Design Thinking (DT) and Creative Problem Solving (CPS) in engineering education could benefit students by aiding them to think creatively and meaningfully in their education and future profession. A study in the pseudonym of a ‘popup class’ was conducted for a week at the Indian Institute of Technology, Delhi (IITD) to have an indication for the perceived relevance, benefits and challenges of DT and CPS from the perspective of engineering students in India. 30 third year Bachelor of Technology students from various technical fields participated in the study. They were introduced to the notion of DT and CPS via a mix of theoretical lectures, case discussions and practical workshops. Their reactions were identified on the basis of silent observations made during the course and responses were recorded through a questionnaire, which was filled after the course. All the respondents felt that DT and CPS are relevant to their education. It was perceived by them that there is a subtle improvement in the quality, quantity and approach of solutions to open ended problems. 90% responded positively to the induction of such an exercise in their education and reasoned it by stating that it’s important for engineers to know, how to solve open-ended real world problems in a meaningful and innovative way.

Keywords: creative problem solving, design thinking, India, undergraduate engineering education

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Authors: Peng Hao Wang, Ronald Sterkenburg, Garam Kim, Yuwei He

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As composite materials continue to gain popularity in the aerospace industry; large airframe sections made out of composite materials are becoming the standard for aerospace manufacturers. However, the heavy utilization of these composite materials also increases the importance of the recycling of these composite materials. A team of Purdue University School of Aviation and Transportation Technology (SATT) faculty and students have partnered to investigate the characteristics of 3D printed recycled carbon fiber. A prototype of a 3D printed recycled carbon fiber part was provided by an industry partner and different sections of the prototype were used to create specimens. A furnace was utilized in order to remove the polymer from the specimens and the specimen’s fiber content and fiber length was calculated from the remaining fibers. A differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) test was also conducted on the 3D printed recycled carbon fiber prototype in order to determine the prototype’s degree of cure at different locations. The data collected from this study provided valuable information in the process improvement and understanding of 3D printed recycled carbon fiber.

Keywords: 3D printed, carbon fiber, fiber content, recycling

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Authors: Azade Ghorbani-HasanSaraei, Seyed-Ahmad Shahidi, Sakineh Alizadeh, Adeleh Maghsoudlou

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Improvement of color, as a quality attribute of Plum Concentrate, has been made possible by the increase in knowledge of kinetic of color change. Three different heating/evaporation processes were employed for the production of pPlum juice concentrate. The Plum juice was concentrated to a final 55 °Bx from an initial °Bx of 15 by microwave heating, rotary vacuum evaporator and evaporating at atmospheric pressure. The final Plum juice concentration of 55 °Bx was achieved in 17, 24 and 57 min by using the microwave, rotary vacuum and atmospheric heating processes, respectively. The colour change during concentration processes was investigated. Total colour differences, Hunter L, a and b parameters were used to estimate the extent of colour loss. All Hunter colour parameters decreased with time. The zero-order, first-order and a combined kinetics model were applied to the changes in colour parameters. Results indicated that variation in TCD followed both first-order and combined kinetics models, and parameters L, a and b followed only combined model. This model implied that the colour formation and pigment destruction occurred during concentration processes of plum juice.

Keywords: colour, kinetics, concentration, plum juice

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Authors: Yong Ho Jeon, Youn Mi Lee, Yong Yoon Lee

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Effects of cold plasma treatment on various plant seed germination were studied. The seeds of hot pepper, cucumber, tomato and arabidopsis were exposed to plasma and the plasma was generated in various devices. The germination speed was evaluated compared to an unexposed control. A positive effect on germination speed was observed in all tested seeds but the effects strongly depended on the type of the used plasma device (Argon-DBD, surface-DBD or MARX generator), time of exposure (6s~10min or 1~10shots) and kind of seeds. The SEM images showed that arrays of gold particles along the cell wall were observed on the surface of cucumber seeds showed a germination-accelerating effect by plasma treatment, which was the same as untreated. However, when treated with the high dose plasma, gold particles were not arrayed at the seed surface, it seems that due to the surface etching. This may suggest that the germination is not promoted by etching or damage of surface caused by the plasma treatment. Seedling growth improvement was also observed by indirect plasma treatment. These lead to an important conclusion that the effect of charged particles on plasma play the essential role in plant germination and indirect plasma treatment offers new perspectives for large scale application.

Keywords: cold plasma, cucumber, germination, SEM

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Authors: Dudul Das, Pankaj Kalita, Sangeeta Borah

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Freshwater availability in the world is as low as 1% of total water available and in many geographical locations dissolved fluoride and arsenic are serious problem. In India availability of freshwater will be stressed by 2025, so the availability saline water from sea is a hope for the people of Indian sub-continent, but saline water is not drinkable it need to be processed, which again require a huge amount of energy. So the most easy and handy option in such situation for all those problems is solar still, this investigation presents various scopes for improvement of its efficiency. Experiments showed that by increasing the absorber plate area through better design can increase the distillate output by two fold and by using jute wicks in the modified absorber plate increases the output up to three times that of conventional solar still available in the Department of Energy, Tezpur University. The experiment is carried out at constant water depth of 8.5 cm and glass cover inclination of 27o facing South. The exergy analysis carried out clearly resulted that with the use of jute wick and baffle plated basin the efficiency achieved more than the simple baffle plated basin. The Instantaneous exergy without jute wick ranges from 2.5% to 4.5% while using jute it ranges from 1.5% to 5.15%.

Keywords: fluoride, absorber plate, jute wick, instantaneous exergy

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Authors: Chia-Chen Wei, Pack Hsieh, Jeffrey Chen

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Surface Mount Technology (SMT) is widely used in the area of the electronic assembly in which the electronic components are mounted to the surface of the printed circuit board (PCB). Most of the defects in the SMT process are mainly related to the quality of solder paste printing. These defects lead to considerable manufacturing costs in the electronics assembly industry. Therefore, the solder paste inspection (SPI) machine for controlling and monitoring the amount of solder paste printing has become an important part of the production process. So far, the setting of the SPI threshold is based on statistical analysis and experts’ experiences to determine the appropriate threshold settings. Because the production data are not normal distribution and there are various variations in the production processes, defects related to solder paste printing still occur. In order to solve this problem, this paper proposes an online machine learning algorithm, called the automatic threshold adjustment (ATA) algorithm, and closed-loop architecture in the SMT process to determine the best threshold settings. Simulation experiments prove that our proposed threshold settings improve the accuracy from 99.85% to 100%.

Keywords: big data analytics, Industry 4.0, SPI threshold setting, surface mount technology

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Authors: Yong Zhao, Jian He, Cheng Zhang

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Cardiovascular diseases caused by hypertension are extremely threatening to human health, and early diagnosis of hypertension can save a large number of lives. Traditional hypertension detection methods require special equipment and are difficult to detect continuous blood pressure changes. In this regard, this paper first analyzes the principle of heart rate variability (HRV) and introduces sliding window and power spectral density (PSD) to analyze the time domain features and frequency domain features of HRV, and secondly, designs an HRV-based hypertension prediction network by combining Resnet, attention mechanism, and multilayer perceptron, which extracts the frequency domain through the improved ResNet18 features through a modified ResNet18, its fusion with time-domain features through an attention mechanism, and the auxiliary prediction of hypertension through a multilayer perceptron. Finally, the network was trained and tested using the publicly available SHAREE dataset on PhysioNet, and the test results showed that this network achieved 92.06% prediction accuracy for hypertension and outperformed K Near Neighbor(KNN), Bayes, Logistic, and traditional Convolutional Neural Network(CNN) models in prediction performance.

Keywords: feature extraction, heart rate variability, hypertension, residual networks

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Authors: Derick Shi-Chen Ou, Liang-Yu Chen

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Background: Acupuncture, a potential alternative, and complementary therapy revealed insufficient evidence in depression treatment. The efficacy of acupuncture treatment was still uncertainty. To evaluate the effect of acupuncture in treating depression, the randomized controlled trials (RCTs) were examined. Methods: RCTs of the acupuncture therapy in treating major depression were searched from MEDLINE from 2007 to 2017. Keywords used for searching strategy included acupuncture, acupoint, and major depressive disorder. Results: Among the nine RCTs, four studies demonstrated great improvement in acupuncture treatment and five studies revealed the effectiveness of acupuncture intervention in medication. General trends suggest that acupuncture treatment is as effective as antidepressants with minimal side effects. Conclusion: Despite the promising results from the RCTs, there are still a variety of limitations, including small sample size, imprecise enrollment criteria, difficulties with blinding, randomization, short duration of study and lack of longitudinal follow-up. Therefore, the evidence that acupuncture as an alternative therapy for depression is inconclusive. More rigorously designed RCTs should be conducted in the future.

Keywords: acupuncture, major depressive disorders, randomized clinical trials, antidepressants

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Authors: Alireza Yavar, Sukiman Sarmani, Khoo Kok Siong

Abstract:

The residents of villages in Kandal province of Cambodia, because of dietary habits, lifestyle and ecological conditions, are exposed to toxic elements like arsenic (As) and mercury (Hg). For comparison purpose, scalp hair samples of 12-17 school children from three villages of Anglong Romiot (AR), Svay Romiot (SR) and Kampong Kong (KK) in Kandal province of Cambodia were considered using k0- instrumental neutron activation method (k0-INAA). The samples irradiated 6 hours with 750 kW power in Malaysian nuclear agency (MNA) research reactor and subsequently found gamma peaks of radionuclides in samples using HPGe detector. The average values of arsenic and mercury were 0.0 and 3.52 (mg/kg) in AR; 1.88 and 4.26 (mg/kg) in SR; 2.81 and 3.37 (mg/kg) in KK, respectively. The results indicate KK, SR, and AR villages were in high, medium and control level of arsenic pollution, respectively. However, Hg concentration were highest in SR, then KK and AR villages, respectively. The accuracy of the method was assessed by analyzing ERM-DB001-human hair as certified reference materials (CRMs), which experimental result of ERM-DB001 was consistent with certified values. In addition, correlation between As and Hg levels was found by Pearson’s correlation test.

Keywords: Kandal province of Cambodia, k0- instrumental neutron activation method., scalp human hair, arsenic and mercury

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Authors: Shahnaz Safitri, Rose Mini Agoes Salim, Pratiwi Widyasari

Abstract:

Intellectual disability is characterized by significant limitations in intellectual functioning and adaptive behavior that appears before the age of 18 years old. The prominent impacts of intellectual disability in adolescents are failure to establish interpersonal relationships as socially expected and lower academic achievement. Meanwhile, it is known that emotion regulation skills have a role in supporting the functioning of individual, either by nourishing the development of social skills as well as by facilitating the process of learning and adaptation in school. This study aims to look for the effectiveness of Dialectical Behavior Therapy (DBT) in developing emotion regulation skills for adolescents with intellectual disability. DBT's special consideration toward clients’ social environment and their biological condition is foreseen to be the key for developing emotion regulation capacity for subjects with intellectual disability. Through observations on client's behavior, conducted before and after the completion of DBT intervention program, it was found that there is an improvement in client's knowledge and attitudes related to the mastery of emotion regulation skills. In addition, client's consistency to actually practice emotion regulation techniques over time is largely influenced by the support received from the client's social circles.

Keywords: adolescent, dialectical behavior therapy, emotion regulation, intellectual disability

Procedia PDF Downloads 311