Search results for: uncertainty of processing times

Authors: David Downey

Abstract:

With the introduction of additive manufacturing (3D printing) to produce titanium (Ti6Al4V) components in the medical, aerospace and automotive industries, intricate geometries can be produced with virtually complete design freedom. However, the consideration of microstructural anisotropy resulting from the additive manufacturing process becomes necessary due to this design flexibility and the need to print a geometric shape that can consist of numerous angles, radii, and swept surfaces. A femoral knee implant serves as an example of a 3D-printed near-net-shaped product. The mechanical properties of the printed components, and consequently, their machinability, are affected by microstructural anisotropy. Currently, finish-machining operations performed on titanium printed parts using selective laser melting (SLM) utilize the same cutting tools employed for processing wrought titanium components. Cutting forces for components manufactured through SLM can be up to 70% higher than those for their wrought counterparts made of Ti6Al4V. Moreover, temperatures at the cutting interface of 3D printed material can surpass those of wrought titanium, leading to significant tool wear. Although the criteria for tool wear may be similar for both 3D printed and wrought materials, the rate of wear during the machining process may differ. The impact of these issues on the choice of cutting tool material and tool lifetimes will be discussed.

Keywords: Additive manufacturing, build orientation, microstructural anisotropy, printed titanium Ti6Al4V, tool wear.

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Authors: P. Keerthika, P. Suresh

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Grid is an environment with millions of resources which are dynamic and heterogeneous in nature. A computational grid is one in which the resources are computing nodes and is meant for applications that involves larger computations. A scheduling algorithm is said to be efficient if and only if it performs better resource allocation even in case of resource failure. Resource allocation is a tedious issue since it has to consider several requirements such as system load, processing cost and time, user’s deadline and resource failure. This work attempts in designing a resource allocation algorithm which is cost-effective and also targets at load balancing, fault tolerance and user satisfaction by considering the above requirements. The proposed Budget Constrained Load Balancing Fault Tolerant algorithm with user satisfaction (BLBFT) reduces the schedule makespan, schedule cost and task failure rate and improves resource utilization. Evaluation of the proposed BLBFT algorithm is done using Gridsim toolkit and the results are compared with the algorithms which separately concentrates on all these factors. The comparison results ensure that the proposed algorithm works better than its counterparts.

Keywords: Grid Scheduling, Load Balancing, fault tolerance, makespan, cost, resource utilization.

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Authors: FH. Sarieddeen, R. El Berbari, S. Imad, J. Abdel Baki, M. Hamad, R. Blanc, A. Nakib, Y.Chenoune

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Brain ArterioVenous Malformation (BAVM) is an abnormal tangle of brain blood vessels where arteries shunt directly into veins with no intervening capillary bed which causes high pressure and hemorrhage risk. The success of treatment by embolization in interventional neuroradiology is highly dependent on the accuracy of the vessels visualization. In this paper the performance of clustering techniques on vessel segmentation from 3- D rotational angiography (3DRA) images is investigated and a new technique of segmentation is proposed. This method consists in: preprocessing step of image enhancement, then K-Means (KM), Fuzzy C-Means (FCM) and Expectation Maximization (EM) clustering are used to separate vessel pixels from background and artery pixels from vein pixels when possible. A post processing step of removing false-alarm components is applied before constructing a three-dimensional volume of the vessels. The proposed method was tested on six datasets along with a medical assessment of an expert. Obtained results showed encouraging segmentations.

Keywords: Brain arteriovenous malformation (BAVM), 3-D rotational angiography (3DRA), K-Means (KM) clustering, Fuzzy CMeans (FCM) clustering, Expectation Maximization (EM) clustering, volume rendering.

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Authors: Seemaa Diwedi

Abstract:

The study area receives a wide variety of wastes generated by municipalities and the industries like paints and pigments, metal processing industries, thermal power plants electroprocessing industries etc. The Physico-chemical and structural investigation of water from river Pandu indicated high level of chlorides and calcium which made the water unsuitable for human use. Algae like Cyclotella fumida, Asterionella Formosa, Cladophora glomerata, Pediastrum simplex, Scenedesmus bijuga, Cladophora glomerata were the dominant pollution tolerant species recorded under these conditions. The sensitive and less abundant species of algae included Spirogyra sps., Merismopedia sps. The predominance colonies of Zygnema sps, Phormidium sps, Mycrocystis aeruginosa, Merismopedia minima, Pandorina morum, seems to correlate with high organic contents of Pandu river water. This study assumes significance as some algae can be used as bioindicators of water pollution and algal floral of a municipal drain carrying waste effluents from industrial area Kanpur and discharge them into the river Pandu flowing onto southern outskirts of Kanpur city.

Keywords: Kanpur, North India, Physico-chemical, Pollution, River Pandu.

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Authors: Juliana Amaka Ugwu

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Trapping efficiency of methyl eugenol and three locally made food-based lures were evaluated in three locations for trapping of B. dorsalis on mango homestead trees in Ibadan South west Nigeria. The treatments were methyl eugenol, brewery waste, pineapple juice, orange juice, and control (water). The experiment was laid in a Complete Randomized Block Design (CRBD) and replicated three times in each location. Data collected were subjected to analysis of variance and significant means were separated by Turkey’s test. The results showed that B. dorsalis was recorded in all locations of study. Methyl eugenol significantly (P < 0.05) trapped higher population of B. dorsalis in all the study area. The population density of B. dorsalis was highest during the ripening period of mango in all locations. The percentage trapped flies after 7 weeks were 77.85%-82.38% (methyl eugenol), 7.29%-8.64% (pineapple juice), 5.62-7.62% (brewery waste), 4.41%-5.95% (orange juice), and 0.24-0.47% (control). There were no significance differences (p > 0.05) on the population of B. dorsalis trapped in all locations. Similarly, there were no significant differences (p > 0.05) on the population of flies trapped among the food attractants. However, the three food attractants significantly (p < 0.05) trapped higher flies than control. Methyl eugenol trapped only male flies while brewery waste and other food based attractants trapped both male and female flies. The food baits tested were promising attractants for trapping B. dorsalis on mango homestead tress, hence increased dosage could be considered for monitoring and mass trapping as management strategies against fruit fly infestation.

Keywords: Attractants, trapping, mango, Bactrocera dorsalis.

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Authors: Stefan Wagenpfeil, Felix Engel, Paul McKevitt, Matthias Hemmje

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Multimedia Indexing and Retrieval is generally de-signed and implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results but also leads to more complex graph structures. However, graph-traversal-based algorithms for similarity are quite inefficient and computation intensive, espe-cially for large data structures. To deliver fast and effective retrieval, an efficient similarity algorithm, particularly for large graphs, is mandatory. Hence, in this paper, we define a graph-projection into a 2D space (Graph Code) as well as the corresponding algorithms for indexing and retrieval. We show that calculations in this space can be performed more efficiently than graph-traversals due to a simpler processing model and a high level of parallelisation. In consequence, we prove that the effectiveness of retrieval also increases substantially, as Graph Codes facilitate more levels of detail in feature fusion. Thus, Graph Codes provide a significant increase in efficiency and effectiveness (especially for Multimedia indexing and retrieval) and can be applied to images, videos, audio, and text information.

Keywords: indexing, retrieval, multimedia, graph code, graph algorithm

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: Cancer classification, feature selection, deep learning, genetic algorithm.

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: Crime prediction, machine learning, public safety, smart city.

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Authors: Rakesh Prajapati, Purvik Patel, Avadhoot Rajurkar

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Nowadays, manufacturing industries augment their production lines with modern machining centers backed by CAM software. Several attempts are being made to cut down the programming time for machining complex geometries. Special programs/software have been developed to generate the digital numerical data and to prepare NC programs by using suitable post-processors for different machines. By selecting the tools and manufacturing process then applying tool paths and NC program are generated. More and more complex mechanical parts that earlier were being cast and assembled/manufactured by other processes are now being machined. Majority of these parts require lots of pocketing operations and find their applications in die and mold, turbo machinery, aircraft, nuclear, defense etc. Pocketing operations involve removal of large quantity of material from the metal surface. The modeling of warm cast and clamping a piece of food processing parts which the used of Pro-E and MasterCAM^® software. Pocketing operation has been specifically chosen for toolpath optimization. Then after apply Pocketing toolpath, Multi Tool Selection and Reduce Air Time give the results of software simulation time and experimental machining time.

Keywords: Toolpath, part program, optimization, pocket.

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Authors: Yasin Tadayonrad, Alassane Ballé Ndiaye

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading/unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is the loading/unloading capacity in each source/destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods (FMCG) industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on Python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: Supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming.

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Authors: Martin Klaumünzer, Jakob Hübner, Denis Spitzer

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Within this paper, latest results on processing of energetic nanomaterials by means of the Spray Flash Evaporation technique are presented. This technology constitutes a highly effective and continuous way to prepare fascinating materials on the nano- and micro-scale. Within the process, a solution is set under high pressure and sprayed into an evacuated atomization chamber. Subsequent ultrafast evaporation of the solvent leads to an aerosol stream, which is separated by cyclones or filters. No drying gas is required, so the present technique should not be confused with spray dying. Resulting nanothermites, insensitive explosives or propellants and compositions are foreseen to replace toxic (according to REACH) and very sensitive matter in military and civil applications. Diverse examples are given in detail: nano-RDX (n-Cyclotrimethylentrinitramin) and nano-aluminum based systems, mixtures (n-RDX/n-TNT - trinitrotoluene) or even cocrystalline matter like n-CL-20/HMX (Hexanitrohexaazaisowurtzitane/ Cyclotetra-methylentetranitramin). These nanomaterials show reduced sensitivity by trend without losing effectiveness and performance. An analytical study for material characterization was performed by using Atomic Force Microscopy, X-Ray Diffraction, and combined techniques as well as spectroscopic methods. As a matter of course, sensitivity tests regarding electrostatic discharge, impact, and friction are provided.

Keywords: Continuous synthesis, energetic material, nanoscale, nanothermite, nanoexplosive.

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Authors: K. Parandhama Gowd

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The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: Flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC).

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Authors: Sheam-Chyun Lin, Wei-Kai Chen, Hung-Cheng Yen, Yung-Jen Cheng, Yu-Cheng Chen

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Result from the constant dwindle in natural resources, the alternative way to reduce the costs in our daily life would be urgent to be found in the near future. As the ancient technique based on the theory of solar chimney since roman times, the double-skin façade are simply composed of two large glass panels in purpose of daylighting and also natural ventilation in the daytime. Double-skin façade is generally installed on the exterior side of buildings as function as the window, so there is always a huge amount of passive solar energy the façade would receive to induce the airflow every sunny day. Therefore, this article imposes a domestic double-skin window for residential usage and attempts to improve the volume flow rate inside the cavity between the panels by the frame geometry design, the installation of outlet guide plate and the solar energy collection system. Note that the numerical analyses are applied to investigate the characteristics of flow field, and the boundary conditions in the simulation are totally based on the practical experiment of the original prototype. Then we redesign the prototype from the knowledge of the numerical results and fluid dynamic theory, and later the experiments of modified prototype will be conducted to verify the simulation results. The velocities at the inlet of each case are increase by 5%, 45% and 15% from the experimental data, and also the numerical simulation results reported 20% improvement in volume flow rate both for the frame geometry design and installation of outlet guide plate.

Keywords: Solar energy, Double-skin façades, Thermal buoyancy, Fluid machinery.

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Authors: Stephen Akuma, Isaac Terngu Adom, Evelyn Doofan Akuma

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Generation after generation of humans has experienced conflicts leading to needless deaths. Usually, it begins as a minor argument that occasionally escalates into a full-fledged conflict. There has been a lingering crisis in the Lake Chad Basin (LCB) of Africa for over a decade leading to bloodshed that has claimed thousands of lives. The terrorist group, Boko Haram has claimed responsibility for these deaths. Efforts have been made by the governments in the LCB region to end the crisis through kinetic approaches, but the conflict persists. In this work, we explored non-kinetic methods used by social scientists in resolving conflicts, with a focus on computational approaches due to the increasing processing power of the computer. Firstly, we reviewed the innovative computational methods available for researchers working on conflict, violence, and peace. Secondly, we described how an Agent-Based Model (ABM) can be linked with a Geographic Information System (GIS) to model the LCB. Finally, this research discusses the challenges and opportunities in constructing a Geographic Information System linked Agent-Based Model of the LCB region.

Keywords: Agent-based modelling, conflict, Geographical Information Systems, Lake Chad Basin, simulation.

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Authors: Pearl K. Atuhaire, Sylvia Kaye

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While the need for equal access to civil, political as well as economic, social and cultural rights is clear under the international law, the adoption of the Convention on the Elimination of all forms of Discrimination against women in 1979 made this even clearer. Despite this positive progress, the abuse of refugee women's rights is one of the basic underlying root causes of their marginalisation and violence in their countries of asylum. This paper presents a critical review on the development of refugee women's rights at the international levels and national levels. It provides an array of scholarly literature on this issue and examines the measures taken by the international community to curb the problem of violence against women in their various provisions through the instruments set. It is cognizant of the fact that even if conflict affects both refugee women and men, the effects on women refugees are deep-reaching, due to the cultural strongholds they face. An important aspect of this paper is that it is conceptualised against the fact that refugee women face the problem of sexual and gender based first as refugees and second as women, yet, their rights are stumbled upon. Often times they have been rendered "worthless victims" who are only in need of humanitarian assistance than active participants committed to change their plight through their participation in political, economic and social participation in their societies. Scholars have taken notice of the fact that women's rights in refugee settings have been marginalized and call for a need to incorporate their perspectives in the planning and management of refugee settings in which they live. Underpinning this discussion is feminism theory which gives a clear understanding of the root cause of refugee women's problems. Finally, this paper suggests that these policies should be translated into action at local, national international and regional levels to ensure sustainable peace.

Keywords: Feminism theory, human rights, refugee women, sexual and gender based violence.

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Authors: Satish Kumar, Arun Kumar Gupta, Pankaj Chandna

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In the modern manufacturing systems, the use of thermal cutting techniques using oxyfuel, plasma and laser have become indispensable for the shape forming of high quality complex components; however, the conventional chip removal production techniques still have its widespread space in the manufacturing industry. Both these types of machining operations require the positioning of end effector tool at the edge where the cutting process commences. This repositioning of the cutting tool in every machining operation is repeated several times and is termed as non-productive time or airtime motion. Minimization of this non-productive machining time plays an important role in mass production with high speed machining. As, the tool moves from one region to the other by rapid movement and visits a meticulous region once in the whole operation, hence the non-productive time can be minimized by synchronizing the tool movements. In this work, this problem is being formulated as a general travelling salesman problem (TSP) and a genetic algorithm approach has been applied to solve the same. For improving the efficiency of the algorithm, the GA has been hybridized with a noble special heuristic and simulating annealing (SA). In the present work a novel heuristic in the combination of GA has been developed for synchronization of toolpath movements during repositioning of the tool. A comparative analysis of new Meta heuristic techniques with simple genetic algorithm has been performed. The proposed metaheuristic approach shows better performance than simple genetic algorithm for minimization of nonproductive toolpath length. Also, the results obtained with the help of hybrid simulated annealing genetic algorithm (HSAGA) are also found better than the results using simple genetic algorithm only.

Keywords: Non-productive time, Airtime, 2.5 D milling, Laser cutting, Metaheuristic, Genetic Algorithm, Simulated Annealing.

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Mann Rattana-Areeyagon, Wutichai Namjaiprasert

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G-code is the main factor in computer numerical control (CNC) machine for controlling the toolpaths and generating the profile of the object’s features. For obtaining high surface accuracy of the surface finish, non-stop operation is required for CNC machine. Recently, to design a new product, the strategy that concerns about a change that has low impact on business and does not consume lot of resources has been introduced. Cost and time for designing minor changes can be reduced since the traditional geometric details of the existing models are applied. In order to support this strategy as the alternative channel for machining operation, this research proposes the automatic generating codes for CNC milling operation. Using this technique can assist the manufacturer to easily change the size and the geometric shape of the product during the operation where the time spent for setting up or processing the machine are reduced. The algorithm implemented on MATLAB platform is developed by analyzing and evaluating the geometric information of the part. Codes are created rapidly to control the operations of the machine. Comparing to the codes obtained from CAM, this developed algorithm can shortly generate and simulate the cutting profile of the part.

Keywords: Geometric shapes, Milling operation, Minor changes, CNC Machine, G-code, and Cutting parameters.

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Authors: Ladda Leungratanamart, Seree Chadcham

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Fluid intelligence declines along with age, but it can be developed. For this reason, increasing fluid intelligence in young adults can be possible. This study examined the effects of a two-month treadmill exercise program on fluid intelligence. The researcher designed a treadmill exercise program to promote cardiorespiratory fitness. Thirty-eight healthy voluntary students from the Boromarajonani College of Nursing, Chon Buri were assigned randomly to an exercise group (n=18) and a control group (n=20). The experiment consisted of three sessions: The baseline session consisted of measuring the VO₂max, electroencephalogram and behavioral response during performed the Raven Progressive Matrices (RPM) test, a measure of fluid intelligence. For the exercise session, an experimental group exercises using treadmill training at 60 % to 80 % maximum heart rate for 30 mins, three times per week, whereas the control group did not exercise. For the following two sessions, each participant was measured the same as baseline testing. The data were analyzed using the t-test to examine whether there is significant difference between the means of the two groups. The results showed that the mean VO₂ max in the experimental group were significantly more than the control group (p<.05), suggesting a two-month treadmill exercise program can improve fluid intelligence. When comparing the behavioral data, it was found that experimental group performed RPM test more accurately and faster than the control group. Neuroelectric data indicated a significant increase in percentages of alpha band ERD (%ERD) at P3 and Pz compared to the pre-exercise condition and the control group. These data suggest that a two-month treadmill exercise program can contribute to the development of cardiorespiratory fitness which influences an increase fluid intelligence. Exercise involved in cortical activation in difference brain areas.

Keywords: Treadmill exercise, fluid intelligence, raven progressive matrices test, %ERD of upper Alpha band.

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Authors: Omar A. Saraereh, M. A. Smadi, A. K. S. Al-Bayati, Jasim A. Ghaeb, Qais H. Alsafasfeh

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A low profile planar antenna for twelve-band operation in the mobile phone is presented. The proposed antenna radiating elements occupy an area equals 17 × 50 mm² are mounted on the compact no-ground portion of the system circuit board to achieve a simple low profile structure. In order to overcome the shortcoming of narrow bandwidth for conventional planar printed antenna, a novel bandwidth enhancement approach for multiband handset antennas is proposed here. The technique used in this study shows that by using a coupled-fed mechanism and a slotted ground structure, a multiband operation with wideband characteristic can be achieved. The influences of the modifications introduced into the ground plane improved significantly the bandwidths of the designed antenna. The slotted ground plane structure with the coupled-fed elements contributes their lowest, middle and higher-order resonant modes to form four operating modes. The generated modes are able to cover LTE 700/2300/2500, GSM 850/900/1800/1900, UMTS, WiMAX 3500, WLAN 2400/5200/5800 operations. Parametric studies via simulation are provided and discussed. Proposed antenna’s gain, efficiency and radiation pattern characteristics over the desired operating bands are obtained and discussed. The reasonable results observed can meet the requirements of practical mobile phones.

Keywords: Antenna, handset, LTE, Mobile, Multiband, Slotted ground, specific absorption rate (SAR).

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Authors: Ingy A. El-Khouly, Khaled S. El-Kilany, Aziz E. El-Sayed

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The process of wafer fabrication is arguably the most technologically complex and capital intensive stage in semiconductor manufacturing. This large-scale discrete-event process is highly reentrant, and involves hundreds of machines, restrictions, and processing steps. Therefore, production control of wafer fabrication facilities (fab), specifically scheduling, is one of the most challenging problems that this industry faces. Dispatching rules have been extensively applied to the scheduling problems in semiconductor manufacturing. Moreover, lot release policies are commonly used in this manufacturing setting to further improve the performance of such systems and reduce its inherent variability. In this work, simulation is used in the scheduling of re-entrant flow shop manufacturing systems with an application in semiconductor wafer fabrication; where, a simulation model has been developed for the Intel Five-Machine Six Step Mini-Fab using the ExtendTM simulation environment. The Mini-Fab has been selected as it captures the challenges involved in scheduling the highly re-entrant semiconductor manufacturing lines. A number of scenarios have been developed and have been used to evaluate the effect of different dispatching rules and lot release policies on the selected performance measures. Results of simulation showed that the performance of the Mini-Fab can be drastically improved using a combination of dispatching rules and lot release policy.

Keywords: Dispatching rules, lot release policy, re-entrant flowshop, semiconductor manufacturing.

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Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

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In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: Fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange.

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Authors: Abhijit Mitra, C. Ardil

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We investigate sonic cues for binaural sound localization within classrooms and present a structural model for the same. Two of the primary cues for localization, interaural time difference (ITD) and interaural level difference (ILD) created between the two ears by sounds from a particular point in space, are used. Although these cues do not lend any information about the elevation of a sound source, the torso, head, and outer ear carry out elevation dependent spectral filtering of sounds before they reach the inner ear. This effect is commonly captured in head related transfer function (HRTF) which aids in resolving the ambiguity from the ITDs and ILDs alone and helps localize sounds in free space. The proposed structural model of HRTF produces well controlled horizontal as well as vertical effects. The implemented HRTF is a signal processing model which tries to mimic the physical effects of the sounds interacting with different parts of the body. The effectiveness of the method is tested by synthesizing spatial audio, in MATLAB, for use in listening tests with human subjects and is found to yield satisfactory results in comparison with existing models.

Keywords: Auditory localization, Binaural sound, Head related impulse response, Head related transfer function, Interaural level difference, Interaural time difference, Localization cues.

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Authors: Mehrdad N. Khajavi , Golamhassan Paygane, Ali Hakima

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Vehicle which are turning or maneuvering at high speeds are susceptible to sliding and subsequently deviate from desired path. In this paper the dynamics governing the Yaw/Roll behavior of a vehicle has been simulated. Two different simulations have been used one for the real vehicle, for which a fuzzy controller is designed to increase its directional stability property. The other simulation is for a hypothetical vehicle with much higher tire cornering stiffness which is capable of developing the required lateral forces at the tire-ground patch contact to attain the desired lateral acceleration for the vehicle to follow the desired path without slippage. This simulation model is our reference model. The logic for keeping the vehicle on the desired track in the cornering or maneuvering state is to have some braking forces on the inner or outer tires based on the direction of vehicle deviation from the desired path. The inputs to our vehicle simulation model is steer angle δ and vehicle velocity V , and the outputs can be any kinematical parameters like yaw rate, yaw acceleration, side slip angle, rate of side slip angle and so on. The proposed fuzzy controller is a feed forward controller. This controller has two inputs which are steer angle δ and vehicle velocity V, and the output of the controller is the correcting moment M, which guides the vehicle back to the desired track. To develop the membership functions for the controller inputs and output and the fuzzy rules, the vehicle simulation has been run for 1000 times and the correcting moment have been determined by trial and error. Results of the vehicle simulation with fuzzy controller are very promising and show the vehicle performance is enhanced greatly over the vehicle without the controller. In fact the vehicle performance with the controller is very near the performance of the reference ideal model.

Keywords: Vehicle, Directional Stability, Fuzzy Logic Controller, ANFIS..

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Authors: Chanon Aphirukmatakun, Natasha Dejdumrong

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In image processing and visualization, comparing two bitmapped images needs to be compared from their pixels by matching pixel-by-pixel. Consequently, it takes a lot of computational time while the comparison of two vector-based images is significantly faster. Sometimes these raster graphics images can be approximately converted into the vector-based images by various techniques. After conversion, the problem of comparing two raster graphics images can be reduced to the problem of comparing vector graphics images. Hence, the problem of comparing pixel-by-pixel can be reduced to the problem of polynomial comparisons. In computer aided geometric design (CAGD), the vector graphics images are the composition of curves and surfaces. Curves are defined by a sequence of control points and their polynomials. In this paper, the control points will be considerably used to compare curves. The same curves after relocated or rotated are treated to be equivalent while two curves after different scaled are considered to be similar curves. This paper proposed an algorithm for comparing the polynomial curves by using the control points for equivalence and similarity. In addition, the geometric object-oriented database used to keep the curve information has also been defined in XML format for further used in curve comparisons.

Keywords: Bezier curve, Said-Ball curve, Wang-Ball curve, DP curve, CAGD, comparison, geometric object database.

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Authors: André C. Silva, Mariana R. Barros, Elenice M. S. Silva, Douglas. Y. Marinho, Diego F. Lopes, Débora N. Sousa, Raphael S. Tomáz

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Modern agriculture requires productivity, efficiency and quality. Therefore, there is need for agricultural limestone implementation that provides adequate amounts of calcium and magnesium carbonates in order to correct soil acidity. During the limestone process, fine particles (with average size under 400#) are generated. These particles do not have economic value in agricultural and metallurgical sectors due their size. When limestone is used for agriculture purposes, these fine particles can be easily transported by wind generated air pollution. Therefore, briquetting, a mineral processing technique, was used to mitigate this problem resulting in an agglomerated product suitable for agriculture use. Briquetting uses compressive pressure to agglomerate fine particles. It can be aided by agglutination agents, allowing adjustments in shape, size and mechanical parameters of the mass. Briquettes can generate extra profits for mineral industry, presenting as a distinct product for agriculture, and can reduce the environmental liabilities of the fine particles storage or disposition. The produced limestone briquettes were subjected to shatter and water action resistance tests. The results show that after six minutes completely submerged in water, the briquettes where fully diluted, a highly favorable result considering its use for soil acidity correction.

Keywords: Agglomeration, briquetting, limestone, agriculture.

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Authors: Ezinne M. Igwe

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Statements of facts have been made about Nollywood, a segment of the Nigerian film industry that has in recent times become phenomenal due largely to its quantity of production and specific production style. In the face of recent transformations reshaping the industry, matters have been arising which have not been given due academic attention from an industry player perspective. While re-addressing such issues like structure, policy and informality, this study benefits from a new perspective – that of a community member adopting participant observation to research into a familiar culture. With data drawn from an extensive ethnographic study of the industry, this paper examines these matters with an emphasis on structure and the industry’s overall political economy. Drawing from discourses on the new and old Nollywood labels and other current matters arising within the industry such as the MOPICON bill redraft, corporate financing and possibilities of regeneration, this paper examines structure and power struggle within Nollywood. These are championing regenerative processes that bring about formalization, professionalism and the quest for a transnational presence, which have only been superficially evaluated. Focused essentially on Nollywood’s political economy, this study critically analyses the transforming face of an informal industry, the consistent quest for structure, quality and standard, and issues of corporate sponsorship as possible trends of regeneration. It evaluates them as indicators of regeneration, questioning the possibilities of their sustenance in an industry experiencing increased interactions with the formal economy and an influx of young professionals. With findings that make sustained regeneration both certain (due to increased formal economy interaction) and uncertain (due to the dysfunctionality of the society and its political system), it concludes that the transforming face of the industry suggests impending gentrification of the industry.

Keywords: Formalization, MOPICON, Nollywood, Structure.

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Authors: Jacqueline R. T. Alipo-on, Francesca I. F. Escobar, Myles J. T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

Abstract:

Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis on the ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heart beat types. The dataset used in this work is the synthetic MIT-Beth Israel Hospital (MIT-BIH) Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: Heartbeat classification, convolutional neural network, electrocardiogram signals, ECG signals, generative adversarial networks, long short-term memory, LSTM, ResNet-50.

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Authors: Hyun-Gwang Cho, Wan-Seok Yang, Su-Jin Kim, Jeong-Seok Oh, Chun-Hong Park

Abstract:

Machine tools are improved capacity remarkably during the 20th century. Improving the precision of machine tools are related with precision of products and accurate processing is always associated with the subject of interest. There are a lot of the elements that determine the precision of the machine, as guides, motors, structure, control, etc. In this paper we focused on the phenomenon that vertical movement system has worse precision than horizontal movement system even they were made up with same components. The vertical movement system needs to be studied differently from the horizontal movement system to develop its precision. The vertical movement system has load on its transfer direction and it makes the movement system weak in precision than the horizontal one. Some machines have mechanical counter balance, hydraulic or pneumatic counter balance to compensate the weight of the machine head. And there is several type of compensating the weight. It can push the machine head and also can use chain or wire lope to transfer the compensating force from counter balance to machine head. According to the type of compensating, there could be error from friction, pressure error of hydraulic or pressure control error. Also according to what to use for transferring the compensating force, transfer error of compensating force could be occur.

Keywords: Chain chordal action, counter balance, setup error, vertical positioning system.

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Authors: Masaumi Nakahara, Sou Watanabe, Hiromichi Ogi, Atsuhiro Shibata, Kazunori Nomura

Abstract:

In the Japan Atomic Energy Agency, three types of experimental research, advanced reactor fuel reprocessing, radioactive waste disposal, and nuclear fuel cycle technology, have been carried out at the Chemical Processing Facility. The facility has generated high level radioactive liquid and solid wastes in hot cells. The high level radioactive solid waste is divided into three main categories, a flammable waste, a non-flammable waste, and a solid reagent waste. A plastic product is categorized into the flammable waste and molten with a heating mantle. The non-flammable waste is cut with a band saw machine for reducing the volume. Among the solid reagent waste, a used adsorbent after the experiments is heated, and an extractant is decomposed for its stabilization. All high level radioactive solid wastes in the hot cells are packed in a high level radioactive solid waste can. The high level radioactive solid waste can is transported to the 2nd High Active Solid Waste Storage in the Tokai Reprocessing Plant in the Japan Atomic Energy Agency.

Keywords: High level radioactive solid waste, advanced reactor fuel reprocessing, radioactive waste disposal, nuclear fuel cycle technology.

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Authors: Carol Anne Hargreaves

Abstract:

A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: Machine learning, stock market trading, logistic principal component analysis, automated stock investment system.

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