Search results for: candidate selection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2977

Search results for: candidate selection

2497 Free-Standing Pd-Based Metallic Glass Membranes for MEMS Applications

Authors: Wei-Shan Wang, Klaus Vogel, Felix Gabler, Maik Wiemer, Thomas Gessner

Abstract:

Metallic glasses, which are free of grain boundaries, have superior properties including large elastic limits, high strength, and excellent wear and corrosion resistance. Therefore, bulk metallic glasses (BMG) and thin film metallic glasses (TFMG) have been widely developed and investigated. Among various kinds of metallic glasses, Pd-Cu-Si TFMG, which has lower elastic modulus and better resistance of oxidation and corrosions compared to Zr- and Fe-based TFMGs, can be a promising candidate for MEMS applications. However, the study of Pd-TFMG membrane is still limited. This paper presents free-standing Pd-based metallic glass membranes with large area fabricated on wafer level for the first time. Properties of Pd-Cu-Si thin film metallic glass (TFMG) with various deposition parameters are investigated first. When deposited at 25°C, compressive stress occurs in the Pd76Cu6Si18 thin film regardless of Ar pressure. When substrate temperature is increased to 275°C, the stress state changes from compressive to tensile. Thin film stresses are slightly decreased when Ar pressure is higher. To show the influence of temperature on Pd-TFMGs, thin films without and with post annealing below (275°C) and within (370°C) supercooled liquid region are investigated. Results of XRD and TEM analysis indicate that Pd-TFMGs remain amorphous structure with well-controlled parameters. After verification of amorphous structure of the Pd-TFMGs, free-standing Pd-Cu-Si membranes were fabricated by depositing Pd-Cu-Si thin films directly on 200nm-thick silicon nitride membranes, followed by post annealing and dry etching of silicon nitride layer. Post annealing before SiNx removal is used to further release internal stress of Pd-TFMGs. The edge length of the square membrane ranges from 5 to 8mm. The effect of post annealing on Pd-Cu-Si membranes are discussed as well. With annealing at 370°C for 5 min, Pd-MG membranes are fully distortion-free after removal of SiNx layer. Results show that, by introducing annealing process, the stress-relief, distortion-free Pd-TFMG membranes with large area can be a promising candidate for sensing applications such as pressure and gas sensors.

Keywords: amorphous alloy, annealing, metallic glasses, TFMG membrane

Procedia PDF Downloads 346
2496 Coupling Random Demand and Route Selection in the Transportation Network Design Problem

Authors: Shabnam Najafi, Metin Turkay

Abstract:

Network design problem (NDP) is used to determine the set of optimal values for certain pre-specified decision variables such as capacity expansion of nodes and links by optimizing various system performance measures including safety, congestion, and accessibility. The designed transportation network should improve objective functions defined for the system by considering the route choice behaviors of network users at the same time. The NDP studies mostly investigated the random demand and route selection constraints separately due to computational challenges. In this work, we consider both random demand and route selection constraints simultaneously. This work presents a nonlinear stochastic model for land use and road network design problem to address the development of different functional zones in urban areas by considering both cost function and air pollution. This model minimizes cost function and air pollution simultaneously with random demand and stochastic route selection constraint that aims to optimize network performance via road capacity expansion. The Bureau of Public Roads (BPR) link impedance function is used to determine the travel time function in each link. We consider a city with origin and destination nodes which can be residential or employment or both. There are set of existing paths between origin-destination (O-D) pairs. Case of increasing employed population is analyzed to determine amount of roads and origin zones simultaneously. Minimizing travel and expansion cost of routes and origin zones in one side and minimizing CO emission in the other side is considered in this analysis at the same time. In this work demand between O-D pairs is random and also the network flow pattern is subject to stochastic user equilibrium, specifically logit route choice model. Considering both demand and route choice, random is more applicable to design urban network programs. Epsilon-constraint is one of the methods to solve both linear and nonlinear multi-objective problems. In this work epsilon-constraint method is used to solve the problem. The problem was solved by keeping first objective (cost function) as the objective function of the problem and second objective as a constraint that should be less than an epsilon, where epsilon is an upper bound of the emission function. The value of epsilon should change from the worst to the best value of the emission function to generate the family of solutions representing Pareto set. A numerical example with 2 origin zones and 2 destination zones and 7 links is solved by GAMS and the set of Pareto points is obtained. There are 15 efficient solutions. According to these solutions as cost function value increases, emission function value decreases and vice versa.

Keywords: epsilon-constraint, multi-objective, network design, stochastic

Procedia PDF Downloads 637
2495 Attribute Based Comparison and Selection of Modular Self-Reconfigurable Robot Using Multiple Attribute Decision Making Approach

Authors: Manpreet Singh, V. P. Agrawal, Gurmanjot Singh Bhatti

Abstract:

From the last decades, there is a significant technological advancement in the field of robotics, and a number of modular self-reconfigurable robots were introduced that can help in space exploration, bucket to stuff, search, and rescue operation during earthquake, etc. As there are numbers of self-reconfigurable robots, choosing the optimum one is always a concern for robot user since there is an increase in available features, facilities, complexity, etc. The objective of this research work is to present a multiple attribute decision making based methodology for coding, evaluation, comparison ranking and selection of modular self-reconfigurable robots using a technique for order preferences by similarity to ideal solution approach. However, 86 attributes that affect the structure and performance are identified. A database for modular self-reconfigurable robot on the basis of different pertinent attribute is generated. This database is very useful for the user, for selecting a robot that suits their operational needs. Two visual methods namely linear graph and spider chart are proposed for ranking of modular self-reconfigurable robots. Using five robots (Atron, Smores, Polybot, M-Tran 3, Superbot), an example is illustrated, and raking of the robots is successfully done, which shows that Smores is the best robot for the operational need illustrated, and this methodology is found to be very effective and simple to use.

Keywords: self-reconfigurable robots, MADM, TOPSIS, morphogenesis, scalability

Procedia PDF Downloads 212
2494 A Critical Geography of Reforestation Program in Ghana

Authors: John Narh

Abstract:

There is high rate of deforestation in Ghana due to agricultural expansion, illegal mining and illegal logging. While it is attempting to address the illegalities, Ghana has also initiated a reforestation program known as the Modified Taungya System (MTS). Within the MTS framework, farmers are allocated degraded forestland and provided with tree seedlings to practice agroforestry until the trees form canopy. Yet, the political, ecological and economic models that inform the selection of tree species, the motivations of participating farmers as well as the factors that accounts for differential access to the land and performance of farmers engaged in the program lie underexplored. Using a sequential explanatory mixed methods approach in five forest-fringe communities in the Eastern Region of Ghana, the study reveals that economic factors and Ghana’s commitment to international conventions on the environment underpin the selection of tree species for the MTS program. Social network and access to remittances play critical roles in having access to, and enhances poor farmers’ chances in the program respectively. Farmers are more motivated by the access to degraded forestland to cultivate food crops than having a share in the trees that they plant. As such, in communities where participating farmers are not informed about their benefit in the tree that they plant, the program is largely unsuccessful.

Keywords: translocality, deforestation, forest management, social network

Procedia PDF Downloads 92
2493 Lessons from Vernacular Architecture for Lightweight Construction

Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

Abstract:

With the gravity load reduction in the structural and non-structural components, the lightweight construction will be achieved as well as the improvement of efficiency and functional specifications. The advantages of lightweight construction can be examined in two levels. The first is the mass reduction of load bearing structure which results in increasing internal useful space and the other one is the mass reduction of building which decreases the effects of seismic load as a result. In order to achieve this goal, the essential building materials specifications and also optimum load bearing geometry of structural systems and elements have to be considered, so lightweight materials selection particularly with lightweight aggregate for building components will be the first step of lightweight construction. In the next step, in addition to selecting the prominent samples of Iran's traditional architecture, the process of these works improvement is analyzed through the viewpoints of structural efficiency and lightweighting and also the practical methods of lightweight construction have been extracted. The optimum design of load bearing geometry of structural system has to be considered not only in the structural system elements, but also in their composition and the selection of dimensions, proportions, forms and optimum orientations, can lead to get a maximum materials efficiency for loads and stresses bearing.

Keywords: gravity load, light-weighting structural system, load bearing geometry, seismic behavior

Procedia PDF Downloads 532
2492 An ANOVA-based Sequential Forward Channel Selection Framework for Brain-Computer Interface Application based on EEG Signals Driven by Motor Imagery

Authors: Forouzan Salehi Fergeni

Abstract:

Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

Procedia PDF Downloads 36
2491 An Analysis of Emmanuel Macron's Campaign Discourse

Authors: Robin Turner

Abstract:

In the context of the strengthening conservative movements such as “Brexit” and the election of US President Donald Trump, the global political stage was shaken up by the election of Emmanuel Macron to the French presidency, defeating the far-right candidate Marine Le Pen. The election itself was a first for the Fifth Republic in which neither final candidate was from the traditional two major political parties: the left Parti Socialiste (PS) and the right Les Républicains (LR). Macron, who served as the Minister of Finance under his predecessor, founded the centrist liberal political party En Marche! in April 2016 before resigning from his post in August to launch his bid for the presidency. Between the time of the party’s creation to the first round of elections a year later, Emmanuel Macron and En Marche! had garnered enough support to make it to the run-off election, finishing far ahead of many seasoned national political figures. Now months into his presidency, the youngest President of the Republic shows no sign of losing fuel anytime soon. His unprecedented success raises a lot of questions with respect to international relations, economics, and the evolving relationship between the French government and its citizens. The effectiveness of Macron’s campaign, of course, relies on many factors, one of which is his manner of communicating his platform to French voters. Using data from oral discourse and primary material from Macron and En Marche! in sources such as party publications and Twitter, the study categorizes linguistic instruments – address, lexicon, tone, register, and syntax – to identify prevailing patterns of speech and communication. The linguistic analysis in this project is two-fold. In addition to these findings’ stand-alone value, these discourse patterns are contextualized by comparable discourse of other 2017 presidential candidates with high emphasis on that of Marine Le Pen. Secondly, to provide an alternative approach, the study contextualizes Macron’s discourse using those of two immediate predecessors representing the traditional stronghold political parties, François Hollande (PS) and Nicolas Sarkozy (LR). These comparative methods produce an analysis that gives insight to not only a contributing factor to Macron’s successful 2017 campaign but also provides insight into how Macron’s platform presents itself differently to previous presidential platforms. Furthermore, this study extends analysis to supply data that contributes to a wider analysis of the defeat of “traditional” French political parties by the “start-up” movement En Marche!.

Keywords: Emmanuel Macron, French, discourse analysis, political discourse

Procedia PDF Downloads 254
2490 Brittle Fracture Tests on Steel Bridge Bearings: Application of the Potential Drop Method

Authors: Natalie Hoyer

Abstract:

Usually, steel structures are designed for the upper region of the steel toughness-temperature curve. To address the reduced toughness properties in the temperature transition range, additional safety assessments based on fracture mechanics are necessary. These assessments enable the appropriate selection of steel materials to prevent brittle fracture. In this context, recommendations were established in 2011 to regulate the appropriate selection of steel grades for bridge bearing components. However, these recommendations are no longer fully aligned with more recent insights: Designing bridge bearings and their components in accordance with DIN EN 1337 and the relevant sections of DIN EN 1993 has led to an increasing trend of using large plate thicknesses, especially for long-span bridges. However, these plate thicknesses surpass the application limits specified in the national appendix of DIN EN 1993-2. Furthermore, compliance with the regulations outlined in DIN EN 1993-1-10 regarding material toughness and through-thickness properties requires some further modifications. Therefore, these standards cannot be directly applied to the material selection for bearings without additional information. In addition, recent findings indicate that certain bridge bearing components are subjected to high fatigue loads, necessitating consideration in structural design, material selection, and calculations. To address this issue, the German Center for Rail Traffic Research initiated a research project aimed at developing a proposal to enhance the existing standards. This proposal seeks to establish guidelines for the selection of steel materials for bridge bearings to prevent brittle fracture, particularly for thick plates and components exposed to specific fatigue loads. The results derived from theoretical analyses, including finite element simulations and analytical calculations, are verified through component testing on a large-scale. During these large-scale tests, where a brittle failure is deliberately induced in a bearing component, an artificially generated defect is introduced into the specimen at the predetermined hotspot. Subsequently, a dynamic load is imposed until the crack initiation process transpires, replicating realistic conditions akin to a sharp notch resembling a fatigue crack. To stop the action of the dynamic load in time, it is important to precisely determine the point at which the crack size transitions from stable crack growth to unstable crack growth. To achieve this, the potential drop measurement method is employed. The proposed paper informs about the choice of measurement method (alternating current potential drop (ACPD) or direct current potential drop (DCPD)), presents results from correlations with created FE models, and may proposes a new approach to introduce beach marks into the fracture surface within the framework of potential drop measurement.

Keywords: beach marking, bridge bearing design, brittle fracture, design for fatigue, potential drop

Procedia PDF Downloads 32
2489 Variable Selection in a Data Envelopment Analysis Model by Multiple Proportions Comparison

Authors: Jirawan Jitthavech, Vichit Lorchirachoonkul

Abstract:

A statistical procedure using multiple comparisons test for proportions is proposed for variable selection in a data envelopment analysis (DEA) model. The test statistic in the multiple comparisons is the proportion of efficient decision making units (DMUs) in a DEA model. Three methods of multiple comparisons test for proportions: multiple Z tests with Bonferroni correction, multiple tests in 2Xc crosstabulation and the Marascuilo procedure, are used in the proposed statistical procedure of iteratively eliminating the variables in a backward manner. Two simulation populations of moderately and lowly correlated variables are used to compare the results of the statistical procedure using three methods of multiple comparisons test for proportions with the hypothesis testing of the efficiency contribution measure. From the simulation results, it can be concluded that the proposed statistical procedure using multiple Z tests for proportions with Bonferroni correction clearly outperforms the proposed statistical procedure using the remaining two methods of multiple comparisons and the hypothesis testing of the efficiency contribution measure.

Keywords: Bonferroni correction, efficient DMUs, Marascuilo procedure, Pastor et al. method, 2xc crosstabulation

Procedia PDF Downloads 307
2488 Applied Methods for Lightweighting Structural Systems

Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

Abstract:

With gravity load reduction in the structural and non-structural components, the lightweight construction will be achieved as well as the improvement of efficiency and functional specifications. The advantages of lightweight construction can be examined in two levels. The first is the mass reduction of load bearing structure which results in increasing internal useful space and the other one is the mass reduction of building which decreases the effects of seismic load as a result. In order to achieve this goal, the essential building materials specifications and also optimum load bearing geometry of structural systems and elements have to be considered, so lightweight materials selection particularly with lightweight aggregate for building components will be the first step of lightweight construction. In the next step, in addition to selecting the prominent samples of Iran's traditional architecture, the process of these works improvement is analyzed through the viewpoints of structural efficiency and lightweighting and also the practical methods of lightweight construction have been extracted. The optimum design of load bearing geometry of structural system has to be considered not only in the structural system elements, but also in their composition and the selection of dimensions, proportions, forms and optimum orientations, can lead to get a maximum materials efficiency for loads and stresses bearing.

Keywords: gravity load, lightweighting structural system, load bearing geometry, seismic behavior

Procedia PDF Downloads 512
2487 Economical and Technical Analysis of Urban Transit System Selection Using TOPSIS Method According to Constructional and Operational Aspects

Authors: Ali Abdi Kordani, Meysam Rooyintan, Sid Mohammad Boroomandrad

Abstract:

Nowadays, one the most important problems in megacities is public transportation and satisfying citizens from this system in order to decrease the traffic congestions and air pollution. Accordingly, to improve the transit passengers and increase the travel safety, new transportation systems such as Bus Rapid Transit (BRT), tram, and monorail have expanded that each one has different merits and demerits. That is why comparing different systems for a systematic selection of public transportation systems in a big city like Tehran, which has numerous problems in terms of traffic and pollution, is essential. In this paper, it is tried to investigate the advantages and feasibility of using monorail, tram and BRT systems, which are widely used in most of megacities in all over the world. In Tehran, by using SPSS statistical analysis software and TOPSIS method, these three modes are compared to each other and their results will be assessed. Experts, who are experienced in the transportation field, answer the prepared matrix questionnaire to select each public transportation mode (tram, monorail, and BRT). The results according to experts’ judgments represent that monorail has the first priority, Tram has the second one, and BRT has the third one according to the considered indices like execution costs, wasting time, depreciation, pollution, operation costs, travel time, passenger satisfaction, benefit to cost ratio and traffic congestion.

Keywords: BRT, costs, monorail, pollution, tram

Procedia PDF Downloads 172
2486 A Selection Approach: Discriminative Model for Nominal Attributes-Based Distance Measures

Authors: Fang Gong

Abstract:

Distance measures are an indispensable part of many instance-based learning (IBL) and machine learning (ML) algorithms. The value difference metrics (VDM) and inverted specific-class distance measure (ISCDM) are among the top-performing distance measures that address nominal attributes. VDM performs well in some domains owing to its simplicity and poorly in others that exist missing value and non-class attribute noise. ISCDM, however, typically works better than VDM on such domains. To maximize their advantages and avoid disadvantages, in this paper, a selection approach: a discriminative model for nominal attributes-based distance measures is proposed. More concretely, VDM and ISCDM are built independently on a training dataset at the training stage, and the most credible one is recorded for each training instance. At the test stage, its nearest neighbor for each test instance is primarily found by any of VDM and ISCDM and then chooses the most reliable model of its nearest neighbor to predict its class label. It is simply denoted as a discriminative distance measure (DDM). Experiments are conducted on the 34 University of California at Irvine (UCI) machine learning repository datasets, and it shows DDM retains the interpretability and simplicity of VDM and ISCDM but significantly outperforms the original VDM and ISCDM and other state-of-the-art competitors in terms of accuracy.

Keywords: distance measure, discriminative model, nominal attributes, nearest neighbor

Procedia PDF Downloads 108
2485 Practical Evaluation of High-Efficiency Si-based Tandem Solar Cells

Authors: Sue-Yi Chen, Wei-Chun Hsu, Jon-Yiew Gan

Abstract:

Si-based double-junction tandem solar cells have become a popular research topic because of the advantages of low manufacturing cost and high energy conversion efficiency. However, there is no set of calculations to select the appropriate top cell materials. Therefore, this paper will propose a simple but practical selection method. First of all, we calculate the S-Q limit and explain the reasons for developing tandem solar cells. Secondly, we calculate the theoretical energy conversion efficiency of the double-junction tandem solar cells while combining the commercial monocrystalline Si and materials' practical efficiency to consider the actual situation. Finally, we conservatively conclude that if considering 75% performance of the theoretical energy conversion efficiency of the top cell, the suitable bandgap energy range will fall between 1.38eV to 2.5eV. Besides, we also briefly describe some improvements of several proper materials, CZTS, CdSe, Cu2O, ZnTe, and CdS, hoping that future research can select and manufacture high-efficiency Si-based tandem solar cells based on this paper successfully. Most importantly, our calculation method is not limited to silicon solely. If other materials’ performances match or surpass silicon's ability in the future, researchers can also apply this set of deduction processes.

Keywords: high-efficiency solar cells, material selection, Si-based double-junction solar cells, Tandem solar cells, photovoltaics.

Procedia PDF Downloads 109
2484 Screening for Hit Identification against Mycobacterium abscessus

Authors: Jichan Jang

Abstract:

Mycobacterium abscessus is a rapidly growing life-threatening mycobacterium with multiple drug-resistance mechanisms. In this study, we screened the library to identify active molecules targeting Mycobacterium abscessus using resazurin live/dead assays. In this screening assay, the Z-factor was 0.7, as an indication of the statistical confidence of the assay. A cut-off of 80% growth inhibition in the screening resulted in the identification of four different compounds at a single concentration (20 μM). Dose-response curves identified three different hit candidates, which generated good inhibitory curves. All hit candidates were expected to have different molecular targets. Thus, we found that compound X, identified, may be a promising candidate in the M. abscessus drug discovery pipeline.

Keywords: Mycobacterium abscessus, antibiotics, drug discovery, emerging Pathogen

Procedia PDF Downloads 202
2483 Timescape-Based Panoramic View for Historic Landmarks

Authors: H. Ali, A. Whitehead

Abstract:

Providing a panoramic view of famous landmarks around the world offers artistic and historic value for historians, tourists, and researchers. Exploring the history of famous landmarks by presenting a comprehensive view of a temporal panorama merged with geographical and historical information presents a unique challenge of dealing with images that span a long period, from the 1800’s up to the present. This work presents the concept of temporal panorama through a timeline display of aligned historic and modern images for many famous landmarks. Utilization of this panorama requires a collection of hundreds of thousands of landmark images from the Internet comprised of historic images and modern images of the digital age. These images have to be classified for subset selection to keep the more suitable images that chronologically document a landmark’s history. Processing of historic images captured using older analog technology under various different capturing conditions represents a big challenge when they have to be used with modern digital images. Successful processing of historic images to prepare them for next steps of temporal panorama creation represents an active contribution in cultural heritage preservation through the fulfillment of one of UNESCO goals in preservation and displaying famous worldwide landmarks.

Keywords: cultural heritage, image registration, image subset selection, registered image similarity, temporal panorama, timescapes

Procedia PDF Downloads 159
2482 The Hotel Logging Behavior and Factors of Tourists in Bankontee District, Samut Songkhram Province, Thailand

Authors: Aticha Kwaengsopha

Abstract:

The purpose of this research was to study the behaviour and related factors that tourists utilized for making decisions to choose their accommodations at a tourist destination, Bangkontee district, Samut Songkhran Province, Thailand. The independent variables included gender, age, income, occupation, and region, while the three important dependent variables included selection behaviour, factors related selection process, and satisfaction of the accommodation service. A total of 400 Thai and international tourists were interviewed at tourist destination of Bangkontee. A questionnaire was used as the tool for collecting data. Descriptive statistics in this research included percentage, mean, and standard deviation. The findings revealed that the majority of respondents were single, female, and with the age between 23-30 years old. Most of the international tourists were from Asia and planned to stay in Thailand about 1-6 days. In addition, the majority of tourists preferred to travel in small groups of 3 persons. The majority of respondents used internet and word of mouth as the main tool to search for information. The majority of respondents spent most of their budget on food & drink, accommodation, and travelling. Even though the majority of tourists were satisfied with the quality of accommodation, the price range of accommodation, and the image of accommodation and the facilities of the accommodation, they indicated that they were not likely to re-visit Thailand in the near future.

Keywords: behaviour, decision factors, tourists, media engineering

Procedia PDF Downloads 270
2481 Characterization of Complex Gold Ores for Preliminary Process Selection: The Case of Kapanda, Ibindi, Mawemeru, and Itumbi in Tanzania

Authors: Sospeter P. Maganga, Alphonce Wikedzi, Mussa D. Budeba, Samwel V. Manyele

Abstract:

This study characterizes complex gold ores (elemental and mineralogical composition, gold distribution, ore grindability, and mineral liberation) for preliminary process selection. About 200 kg of ore samples were collected from each location using systematic sampling by mass interval. Ores were dried, crushed, milled, and split into representative sub-samples (about 1 kg) for elemental and mineralogical composition analyses using X-ray fluorescence (XRF), fire assay finished with Atomic Absorption Spectrometer (AAS), and X-ray Diffraction (XRD) methods, respectively. The gold distribution was studied on size-by-size fractions, while ore grindability was determined using the standard Bond test. The mineral liberation analysis was conducted using ThermoFisher Scientific Mineral Liberation Analyzer (MLA) 650, where unsieved polished grain mounts (80% passing 700 µm) were used as MLA feed. Two MLA measurement modes, X-ray modal analysis (XMOD) and sparse phase liberation-grain X-ray mapping analysis (SPL-GXMAP), were employed. At least two cyanide consumers (Cu, Fe, Pb, and Zn) and kinetics impeders (Mn, S, As, and Bi) were present in all locations investigated. Copper content at Kapanda (0.77% Cu) and Ibindi (7.48% Cu) exceeded the recommended threshold of 0.5% Cu for direct cyanidation. The gold ore at Ibindi indicated a higher rate of grinding compared to other locations. This could be explained by the highest grindability (2.119 g/rev.) and lowest Bond work index (10.213 kWh/t) values. The pyrite-marcasite, chalcopyrite, galena, and siderite were identified as major gold, copper, lead, and iron-bearing minerals, respectively, with potential for economic extraction. However, only gold and copper can be recovered under conventional milling because of grain size issues (galena is exposed by 10%) and process complexity (difficult to concentrate and smelt iron from siderite). Therefore, the preliminary process selection is copper flotation followed by gold cyanidation for Kapanda and Ibindi ores, whereas gold cyanidation with additives such as glycine or ammonia is selected for Mawemeru and Itumbi ores because of low concentrations of Cu, Pb, Fe, and Zn minerals.

Keywords: complex gold ores, mineral liberation, ore characterization, ore grindability

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2480 Different in Factors of the Distributor Selection for Food and Non-Food OTOP Entrepreneur in Thailand

Authors: Phutthiwat Waiyawuththanapoom

Abstract:

This study has only one objective which is to identify the different in factors of choosing the distributor for food and non-food OTOP entrepreneur in Thailand. In this research, the types of OTOP product will be divided into two groups which are food and non-food. The sample for the food type OTOP product was the processed fruit and vegetable from Nakorn Pathom province and the sample for the non-food type OTOP product was the court doll from Ang Thong province. The research was divided into 3 parts which were a study of the distribution pattern and how to choose the distributor of the food type OTOP product, a study of the distribution pattern and how to choose the distributor of the non-food type OTOP product and a comparison between 2 types of products to find the differentiation in the factor of choosing distributor. The data and information was collected by using the interview. The populations in the research were 5 producers of the processed fruit and vegetable from Nakorn Pathom province and 5 producers of the court doll from Ang Thong province. The significant factor in choosing the distributor of the food type OTOP product is the material handling efficiency and on-time delivery but for the non-food type OTOP product is focused on the channel of distribution and cost of the distributor.

Keywords: distributor, OTOP, food and non-food, selection

Procedia PDF Downloads 351
2479 River Stage-Discharge Forecasting Based on Multiple-Gauge Strategy Using EEMD-DWT-LSSVM Approach

Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

Abstract:

This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

Procedia PDF Downloads 171
2478 Fuzzy Decision Making to the Construction Project Management: Glass Facade Selection

Authors: Katarina Rogulj, Ivana Racetin, Jelena Kilic

Abstract:

In this study, the fuzzy logic approach (FLA) was developed for construction project management (CPM) under uncertainty and duality. The focus was on decision making in selecting the type of the glass facade for a residential-commercial building in the main design. The adoption of fuzzy sets was capable of reflecting construction managers’ reliability level over subjective judgments, and thus the robustness of the system can be achieved. An α-cuts method was utilized for discretizing the fuzzy sets in FLA. This method can communicate all uncertain information in the optimization process, taking into account the values of this information. Furthermore, FLA provides in-depth analyses of diverse policy scenarios that are related to various levels of economic aspects when it comes to the construction projects' valid decision making. The developed approach is applied to CPM to demonstrate its applicability. Analyzing the materials of glass facades, variants were defined. The development of the FLA for the CPM included relevant construction projec'ts stakeholders that were involved in the criteria definition to evaluate each variant. Using fuzzy Decision-Making Trial and Evaluation Laboratory Method (DEMATEL) comparison of the glass facade was conducted. This way, a rank, according to the priorities for inclusion into the main design, of variants is obtained. The concept was tested on a residential-commercial building in the city of Rijeka, Croatia. The newly developed methodology was then compared with the existing one. The aim of the research was to define an approach that will improve current judgments and decisions when it comes to the material selection of buildings facade as one of the most important architectural and engineering tasks in the main design. The advantage of the new methodology compared to the old one is that it includes the subjective side of the managers’ decisions, as an inevitable factor in each decision making. The proposed approach can help construction projects managers to identify the desired type of glass facade according to their preference and practical conditions, as well as facilitate in-depth analyses of tradeoffs between economic efficiency and architectural design.

Keywords: construction projects management, DEMATEL, fuzzy logic approach, glass façade selection

Procedia PDF Downloads 131
2477 A Hybrid Genetic Algorithm for Assembly Line Balancing In Automotive Sector

Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

Abstract:

This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

Procedia PDF Downloads 129
2476 Georgia Case: Tourism Expenses of International Visitors on the Basis of Growing Attractiveness

Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

Abstract:

At present actual tourism indicators cannot be calculated in Georgia, making it impossible to perform their quantitative analysis. Therefore, the study conducted by us is highly important from a theoretical as well as practical standpoint. The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors and to calculate statistical attractiveness indices of the tourism potential of Georgia. During the research, the method involving random and proportional selection has been applied. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from major Georgian airports, and a representative population of foreign visitors and a rule of selection of respondents were determined. The results show a trend of growth in tourist numbers and the share of tourists from post-soviet countries are constantly increasing. The level of satisfaction with tourist facilities and quality of service has improved, but still we have a problem of disparity between the service quality and the prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher. Attractiveness of popular cities of Georgia has increased by 43%.

Keywords: tourist, expenses, indexes, statistics, analysis

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2475 Optimization of a Convolutional Neural Network for the Automated Diagnosis of Melanoma

Authors: Kemka C. Ihemelandu, Chukwuemeka U. Ihemelandu

Abstract:

The incidence of melanoma has been increasing rapidly over the past two decades, making melanoma a current public health crisis. Unfortunately, even as screening efforts continue to expand in an effort to ameliorate the death rate from melanoma, there is a need to improve diagnostic accuracy to decrease misdiagnosis. Artificial intelligence (AI) a new frontier in patient care has the ability to improve the accuracy of melanoma diagnosis. Convolutional neural network (CNN) a form of deep neural network, most commonly applied to analyze visual imagery, has been shown to outperform the human brain in pattern recognition. However, there are noted limitations with the accuracy of the CNN models. Our aim in this study was the optimization of convolutional neural network algorithms for the automated diagnosis of melanoma. We hypothesized that Optimal selection of the momentum and batch hyperparameter increases model accuracy. Our most successful model developed during this study, showed that optimal selection of momentum of 0.25, batch size of 2, led to a superior performance and a faster model training time, with an accuracy of ~ 83% after nine hours of training. We did notice a lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone. Training set image transformations did not result in a superior model performance in our study.

Keywords: melanoma, convolutional neural network, momentum, batch hyperparameter

Procedia PDF Downloads 98
2474 An Energy Holes Avoidance Routing Protocol for Underwater Wireless Sensor Networks

Authors: A. Khan, H. Mahmood

Abstract:

In Underwater Wireless Sensor Networks (UWSNs), sensor nodes close to water surface (final destination) are often preferred for selection as forwarders. However, their frequent selection makes them depleted of their limited battery power. In consequence, these nodes die during early stage of network operation and create energy holes where forwarders are not available for packets forwarding. These holes severely affect network throughput. As a result, system performance significantly degrades. In this paper, a routing protocol is proposed to avoid energy holes during packets forwarding. The proposed protocol does not require the conventional position information (localization) of holes to avoid them. Localization is cumbersome; energy is inefficient and difficult to achieve in underwater environment where sensor nodes change their positions with water currents. Forwarders with the lowest water pressure level and the maximum number of neighbors are preferred to forward packets. These two parameters together minimize packet drop by following the paths where maximum forwarders are available. To avoid interference along the paths with the maximum forwarders, a packet holding time is defined for each forwarder. Simulation results reveal superior performance of the proposed scheme than the counterpart technique.

Keywords: energy holes, interference, routing, underwater

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2473 Theoretical Investigation on Electronic and Magnetic Properties of Cubic PrMnO3 Perovskite

Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Abbad, T. Lantri, A. Zitouni

Abstract:

The purpose of this study was to investigate the structural,electronic and magnetic properties of the cubic praseodymium oxides perovskites PrMnO3. It includes our calculations based on the use of the density functional theory (DFT) with both generalized gradient approximation (GGA) and GGA+U approaches, The spin polarized electronic band structures and densities of states as well as the integer value of the magnetic moment of the unit cell (6 μB) illustrate that PrMnO3 is half-metallic ferromagnetic. The study prove that the compound is half-metallic ferromagnetic however the results obtained, make the cubic PrMnO3 a promising candidate for application in spintronics.

Keywords: cubic, DFT, electronic properties, magnetic moment, spintronics

Procedia PDF Downloads 458
2472 Automatic Detection of Defects in Ornamental Limestone Using Wavelets

Authors: Maria C. Proença, Marco Aniceto, Pedro N. Santos, José C. Freitas

Abstract:

A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Keywords: automatic detection, defects, fracture lines, wavelets

Procedia PDF Downloads 244
2471 Feature Selection Approach for the Classification of Hydraulic Leakages in Hydraulic Final Inspection using Machine Learning

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

Procedia PDF Downloads 157
2470 MicroRNA Drivers of Resistance to Androgen Deprivation Therapy in Prostate Cancer

Authors: Philippa Saunders, Claire Fletcher

Abstract:

INTRODUCTION: Prostate cancer is the most prevalent malignancy affecting Western males. It is initially an androgen-dependent disease: androgens bind to the androgen receptor and drive the expression of genes that promote proliferation and evasion of apoptosis. Despite reduced androgen dependence in advanced prostate cancer, androgen receptor signaling remains a key driver of growth. Androgen deprivation therapy (ADT) is, therefore, a first-line treatment approach and works well initially, but resistance inevitably develops. Abiraterone and Enzalutamide are drugs widely used in ADT and are androgen synthesis and androgen receptor signaling inhibitors, respectively. The shortage of other treatment options means acquired resistance to these drugs is a major clinical problem. MicroRNAs (miRs) are important mediators of post-transcriptional gene regulation and show altered expression in cancer. Several have been linked to the development of resistance to ADT. Manipulation of such miRs may be a pathway to breakthrough treatments for advanced prostate cancer. This study aimed to validate ADT resistance-implicated miRs and their clinically relevant targets. MATERIAL AND METHOD: Small RNA-sequencing of Abiraterone- and Enzalutamide-resistant C42 prostate cancer cells identified subsets of miRs dysregulated as compared to parental cells. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) was used to validate altered expression of candidate ADT resistance-implicated miRs 195-5p, 497-5p and 29a-5p in ADT-resistant and -responsive prostate cancer cell lines, patient-derived xenografts (PDXs) and primary prostate cancer explants. RESULTS AND DISCUSSION: This study suggests a possible role for miR-497-5p in the development of ADT resistance in prostate cancer. MiR-497-5p expression was increased in ADT-resistant versus ADT-responsive prostate cancer cells. Importantly, miR-497-5p expression was also increased in Enzalutamide-treated, castrated (ADT-mimicking) PDXs versus intact PDXs. MiR-195-5p was also elevated in ADT-resistant versus -responsive prostate cancer cells, while there was a drop in miR-29a-5p expression. Candidate clinically relevant targets of miR-497-5p in prostate cancer were identified by mining AGO-PAR-CLIP-seq data sets and may include AVL9 and FZD6. CONCLUSION: In summary, this study identified microRNAs that are implicated in prostate cancer resistance to androgen deprivation therapy and could represent novel therapeutic targets for advanced disease.

Keywords: microRNA, androgen deprivation therapy, Enzalutamide, abiraterone, patient-derived xenograft

Procedia PDF Downloads 133
2469 Robust Half-Metallicity and Magnetic Properties of Cubic PrMnO3 Perovskite

Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Abbad, T. Lantri, A. Zitouni

Abstract:

The purpose of this study was to investigate the structural,electronic and magnetic properties of the cubic praseodymium oxides perovskites PrMnO3. It includes our calculations based on the use of the density functional theory (DFT) with both generalized gradient approximation (GGA) and GGA+U approaches, The spin polarized electronic band structures and densities of states aswellas the integer value of the magnetic moment of the unit cell (6 μB) illustrate that PrMnO3 is half-metallic ferromagnetic. The study shows that the robust half-metallicity makes the cubic PrMnO3 a promising candidate for application in spintronics.

Keywords: Perovskite, DFT, electronic properties, Magnetic moment, half-metallic

Procedia PDF Downloads 451
2468 Structural, Electronic and Magnetic Properties of Co and Mn Doped CDTE

Authors: A. Zitouni, S. Bentata, B. Bouadjemi, T. Lantri, W. Benstaali, A. Zoubir, S. Cherid, A. Sefir

Abstract:

The structural, electronic, and magnetic properties of transition metal Co and Mn doped zinc-blende semiconductor CdTe were calculated using the density functional theory (DFT) with both generalized gradient approximation (GGA). We have analyzed the structural parameters, charge and spin densities, total and partial densities of states. We find that the Co and Mn doped zinc blende CdTe show half-metallic behavior with a total magnetic moment of 6.0 and 10.0 µB, respectively.The results obtained, make the Co and Mn doped CdTe a promising candidate for application in spintronics.

Keywords: first-principles, half-metallic, diluted magnetic semiconductor, magnetic moment

Procedia PDF Downloads 453