Search results for: input processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5666

Search results for: input processing

4826 Assessment of an ICA-Based Method for Detecting the Effect of Attention in the Auditory Late Response

Authors: Siavash Mirahmadizoghi, Steven Bell, David Simpson

Abstract:

In this work a new independent component analysis (ICA) based method for noise reduction in evoked potentials is evaluated on for auditory late responses (ALR) captured with a 63-channel electroencephalogram (EEG) from 10 normal-hearing subjects. The performance of the new method is compared with a single channel alternative in terms of signal to noise ratio (SNR), the number of channels with an SNR above an empirically derived statistical critical value and an estimate of the effect of attention on the major components in the ALR waveform. The results show that the multichannel signal processing method can significantly enhance the quality of the ALR signal and also detect the effect of the attention on the ALR better than the single channel alternative.

Keywords: auditory late response (ALR), attention, EEG, independent component analysis (ICA), multichannel signal processing

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4825 Adaptive Data Approximations Codec (ADAC) for AI/ML-based Cyber-Physical Systems

Authors: Yong-Kyu Jung

Abstract:

The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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4824 Fuzzy Logic Modeling of Evaluation the Urban Skylines by the Entropy Approach

Authors: Murat Oral, Seda Bostancı, Sadık Ata, Kevser Dincer

Abstract:

When evaluating the aesthetics of cities, an analysis of the urban form development depending on design properties with a variety of factors is performed together with a study of the effects of this appearance on human beings. Different methods are used while making an aesthetical evaluation related to a city. Entropy, in its preliminary meaning, is the mathematical representation of thermodynamic results. Measuring the entropy is related to the distribution of positional figures of a message or information from the probabilities standpoint. In this study, analysis of evaluation the urban skylines by the entropy approach was modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Input-output parameters were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between application data and RBMTF is done by using absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of evaluation the urban skylines by the entropy approach. As a result, RBMTF model has shown satisfying relation with experimental results, which suggests an alternative method to evaluation of the urban skylines by the entropy approach.

Keywords: urban skylines, entropy, rule-based Mamdani type, fuzzy logic

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4823 Modeling Aeration of Sharp Crested Weirs by Using Support Vector Machines

Authors: Arun Goel

Abstract:

The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free over-fall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, support vector machine (Polynomial and rbf) models, and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free over-fall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: air entrainment rate, dissolved oxygen, weir, SVM, regression

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4822 Ecological Risk Assessment of Informal E-Waste Processing in Alaba International Market, Lagos, Nigeria

Authors: A. A. Adebayo, O. Osibanjo

Abstract:

Informal electronic waste (e-waste) processing is a crude method of recycling, which is on the increase in Nigeria. The release of hazardous substances such as heavy metals (HMs) into the environment during informal e-waste processing has been a major concern. However, there is insufficient information on environmental contamination from e-waste recycling, associated ecological risk in Alaba International Market, a major electronic market in Lagos, Nigeria. The aims of this study were to determine the levels of HMs in soil, resulting from the e-waste recycling; and also assess associated ecological risks in Alaba international market. Samples of soils (334) were randomly collected seasonally for three years from fourteen selected e-waste activity points and two control sites. The samples were digested using standard methods and HMs analysed by inductive coupled plasma optical emission. Ecological risk was estimated using Ecological Risk index (ER), Potential Ecological Risk index (RI), Index of geoaccumulation (Igeo), Contamination factor (Cf) and degree of contamination factor (Cdeg). The concentrations range of HMs (mg/kg) in soil were: 16.7-11200.0 (Pb); 14.3-22600.0 (Cu); 1.90-6280.0 (Ni), 39.5-4570.0 (Zn); 0.79-12300.0 (Sn); 0.02-138.0 (Cd); 12.7-1710.0 (Ba); 0.18-131.0 (Cr); 0.07-28.0 (V), while As was below detection limit. Concentrations range in control soils were 1.36-9.70 (Pb), 2.06-7.60 (Cu), 1.25-5.11 (Ni), 3.62-15.9 (Zn), BDL-0.56 (Sn), BDL-0.01 (Cd), 14.6-47.6 (Ba), 0.21–12.2 (Cr) and 0.22-22.2 (V). The trend in ecological risk index was in the order Cu > Pb > Ni > Zn > Cr > Cd > Ba > V. The potential ecological risk index with respect to informal e-waste activities were: burning > dismantling > disposal > stockpiling. The index of geo accumulation indices revealed that soils were extremely polluted with Cd, Cu, Pb, Zn and Ni. The contamination factor indicated that 93% of the studied areas have very high contamination status for Pb, Cu, Ba, Sn and Co while Cr and Cd were in the moderately contaminated status. The degree of contamination decreased in the order of Sn > Cu > Pb >> Zn > Ba > Co > Ni > V > Cr > Cd. Heavy metal contamination of Alaba international market environment resulting from informal e-waste processing was established. Proper management of e-waste and remediation of the market environment are recommended to minimize the ecological risks.

Keywords: Alaba international market, ecological risk, electronic waste, heavy metal contamination

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4821 Optimization of the Feedstock Supply of an Oilseeds Conversion Unit for Biofuel Production in West Africa: A Comparative Study of the Supply of Jatropha curcas and Balanites aegyptiaca Seeds

Authors: Linda D. F. Bambara, Marie Sawadogo

Abstract:

Jatropha curcas (jatropha) is the plant that has been the most studied for biofuel production in West Africa. There exist however other plants such as Balanites aegyptiaca (balanites) that have been targeted as a potential feedstock for biofuel production. This biomass could be an alternative feedstock for the production of straight vegetable oil (SVO) at costs lower than jatropha-based SVO production costs. This study aims firstly to determine, through an MILP model, the optimal organization that minimizes the costs of the oilseeds supply of two biomass conversion units (BCU) exploiting respectively jatropha seeds and the balanitès seeds. Secondly, the study aims to carry out a comparative study of these costs obtained for each BCU. The model was then implemented on two theoretical cases studies built on the basis of the common practices in Burkina Faso and two scenarios were carried out for each case study. In Scenario 1, 3 pre-processing locations ("at the harvesting area", "at the gathering points", "at the BCU") are possible. In scenario 2, only one location ("at the BCU") is possible. For each biomass, the system studied is the upstream supply chain (harvesting, transport and pre-processing (drying, dehulling, depulping)), including cultivation (for jatropha). The model optimizes the area of land to be exploited based on the productivity of the studied plants and material losses that may occur during the harvesting and the supply of the BCU. It then defines the configuration of the logistics network allowing an optimal supply of the BCU taking into account the most common means of transport in West African rural areas. For the two scenarios, the results of the implementation showed that the total area exploited for balanites (1807 ha) is 4.7 times greater than the total area exploited for Jatropha (381 ha). In both case studies, the location of pre-processing “at the harvesting area” was always chosen for scenario1. As the balanites trees were not planted and because the first harvest of the jatropha seeds took place 4 years after planting, the cost price of the seeds at the BCU without the pre-processing costs was about 430 XOF/kg. This cost is 3 times higher than the balanites's one, which is 140 XOF/kg. After the first year of harvest, i.e. 5 years after planting, and assuming that the yield remains constant, the same cost price is about 200 XOF/kg for Jatropha. This cost is still 1.4 times greater than the balanites's one. The transport cost of the balanites seeds is about 120 XOF/kg. This cost is similar for the jatropha seeds. However, when the pre-processing is located at the BCU, i.e. for scenario2, the transport costs of the balanites seeds is 1200 XOF/kg. These costs are 6 times greater than the transport costs of jatropha which is 200 XOF/kg. These results show that the cost price of the balanites seeds at the BCU can be competitive compared to the jatropha's one if the pre-processing is located at the harvesting area.

Keywords: Balanites aegyptiaca, biomass conversion, Jatropha curcas, optimization, post-harvest operations

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4820 Development and Verification of the Idom Shielding Optimization Tool

Authors: Omar Bouhassoun, Cristian Garrido, César Hueso

Abstract:

The radiation shielding design is an optimization problem with multiple -constrained- objective functions (radiation dose, weight, price, etc.) that depend on several parameters (material, thickness, position, etc.). The classical approach for shielding design consists of a brute force trial-and-error process subject to previous designer experience. Therefore, the result is an empirical solution but not optimal, which can degrade the overall performance of the shielding. In order to automate the shielding design procedure, the IDOM Shielding Optimization Tool (ISOT) has been developed. This software combines optimization algorithms with the capabilities to read/write input files, run calculations, as well as parse output files for different radiation transport codes. In the first stage, the software was established to adjust the input files for two well-known Monte Carlo codes (MCNP and Serpent) and optimize the result (weight, volume, price, dose rate) using multi-objective genetic algorithms. Nevertheless, its modular implementation easily allows the inclusion of more radiation transport codes and optimization algorithms. The work related to the development of ISOT and its verification on a simple 3D multi-layer shielding problem using both MCNP and Serpent will be presented. ISOT looks very promising for achieving an optimal solution to complex shielding problems.

Keywords: optimization, shielding, nuclear, genetic algorithm

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4819 Tank Barrel Surface Damage Detection Algorithm

Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

Abstract:

The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

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4818 Examining Predictive Coding in the Hierarchy of Visual Perception in the Autism Spectrum Using Fast Periodic Visual Stimulation

Authors: Min L. Stewart, Patrick Johnston

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Predictive coding has been proposed as a general explanatory framework for understanding the neural mechanisms of perception. As such, an underweighting of perceptual priors has been hypothesised to underpin a range of differences in inferential and sensory processing in autism spectrum disorders. However, empirical evidence to support this has not been well established. The present study uses an electroencephalography paradigm involving changes of facial identity and person category (actors etc.) to explore how levels of autistic traits (AT) affect predictive coding at multiple stages in the visual processing hierarchy. The study uses a rapid serial presentation of faces, with hierarchically structured sequences involving both periodic and aperiodic repetitions of different stimulus attributes (i.e., person identity and person category) in order to induce contextual expectations relating to these attributes. It investigates two main predictions: (1) significantly larger and late neural responses to change of expected visual sequences in high-relative to low-AT, and (2) significantly reduced neural responses to violations of contextually induced expectation in high- relative to low-AT. Preliminary frequency analysis data comparing high and low-AT show greater and later event-related-potentials (ERPs) in occipitotemporal areas and prefrontal areas in high-AT than in low-AT for periodic changes of facial identity and person category but smaller ERPs over the same areas in response to aperiodic changes of identity and category. The research advances our understanding of how abnormalities in predictive coding might underpin aberrant perceptual experience in autism spectrum. This is the first stage of a research project that will inform clinical practitioners in developing better diagnostic tests and interventions for people with autism.

Keywords: hierarchical visual processing, face processing, perceptual hierarchy, prediction error, predictive coding

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4817 Dynamic Behavior of Brain Tissue under Transient Loading

Authors: Y. J. Zhou, G. Lu

Abstract:

In this paper, an analytical study is made for the dynamic behavior of human brain tissue under transient loading. In this analytical model the Mooney-Rivlin constitutive law is coupled with visco-elastic constitutive equations to take into account both the nonlinear and time-dependent mechanical behavior of brain tissue. Five ordinary differential equations representing the relationships of five main parameters (radial stress, circumferential stress, radial strain, circumferential strain, and particle velocity) are obtained by using the characteristic method to transform five partial differential equations (two continuity equations, one motion equation, and two constitutive equations). Analytical expressions of the attenuation properties for spherical wave in brain tissue are analytically derived. Numerical results are obtained based on the five ordinary differential equations. The mechanical responses (particle velocity and stress) of brain are compared at different radii including 5, 6, 10, 15 and 25 mm under four different input conditions. The results illustrate that loading curves types of the particle velocity significantly influences the stress in brain tissue. The understanding of the influence by the input loading cures can be used to reduce the potentially injury to brain under head impact by designing protective structures to control the loading curves types.

Keywords: analytical method, mechanical responses, spherical wave propagation, traumatic brain injury

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4816 Geophysical Methods and Machine Learning Algorithms for Stuck Pipe Prediction and Avoidance

Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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4815 Resource Framework Descriptors for Interestingness in Data

Authors: C. B. Abhilash, Kavi Mahesh

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Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.

Keywords: RDF, interestingness, knowledge base, semantic data

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4814 Comparison of Computer Software for Swept Path Analysis on Example of Special Paved Areas

Authors: Ivana Cestar, Ivica Stančerić, Saša Ahac, Vesna Dragčević, Tamara Džambas

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On special paved areas, such as road intersections, vehicles are usually moving through horizontal curves with smaller radii and occupy considerably greater area compared to open road segments. Planning procedure of these areas is mainly an iterative process that consists of designing project elements, assembling those elements to a design project, and analyzing swept paths for the design vehicle. If applied elements do not fulfill the swept path requirements for the design vehicle, the process must be carried out again. Application of specialized computer software for swept path analysis significantly facilitates planning procedure of special paved areas. There are various software of this kind available on the global market, and each of them has different specifications. In this paper, comparison of two software commonly used in Croatia (Auto TURN and Vehicle Tracking) is presented, their advantages and disadvantages are described, and their applicability on a particular paved area is discussed. In order to reveal which one of the analyszed software is more favorable in terms of swept paths widths, which one includes input parameters that are more relevant for this kind of analysis, and which one is more suitable for the application on a certain special paved area, the analysis shown in this paper was conducted on a number of different intersection types.

Keywords: software comparison, special paved areas, swept path analysis, swept path input parameters

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4813 An Experimental Study of Scalar Implicature Processing in Chinese

Authors: Liu Si, Wang Chunmei, Liu Huangmei

Abstract:

A prominent component of the semantic versus pragmatic debate, scalar implicature (SI) has been gaining great attention ever since it was proposed by Horn. The constant debate is between the structural and pragmatic approach. The former claims that generation of SI is costless, automatic, and dependent mostly on the structural properties of sentences, whereas the latter advocates both that such generation is largely dependent upon context, and that the process is costly. Many experiments, among which Katsos’s text comprehension experiments are influential, have been designed and conducted in order to verify their views, but the results are not conclusive. Besides, most of the experiments were conducted in English language materials. Katsos conducted one off-line and three on-line text comprehension experiments, in which the previous shortcomings were addressed on a certain extent and the conclusion was in favor of the pragmatic approach. We intend to test the results of Katsos’s experiment in Chinese scalar implicature. Four experiments in both off-line and on-line conditions to examine the generation and response time of SI in Chinese "yixie" (some) and "quanbu (dou)" (all) will be conducted in order to find out whether the structural or the pragmatic approach could be sustained. The study mainly aims to answer the following questions: (1) Can SI be generated in the upper- and lower-bound contexts as Katsos confirmed when Chinese language materials are used in the experiment? (2) Can SI be first generated, then cancelled as default view claimed or can it not be generated in a neutral context when Chinese language materials are used in the experiment? (3) Is SI generation costless or costly in terms of processing resources? (4) In line with the SI generation process, what conclusion can be made about the cognitive processing model of language meaning? Is it a parallel model or a linear model? Or is it a dynamic and hierarchical model? According to previous theoretical debates and experimental conflicts, presumptions could be made that SI, in Chinese language, might be generated in the upper-bound contexts. Besides, the response time might be faster in upper-bound than that found in lower-bound context. SI generation in neutral context might be the slowest. At last, a conclusion would be made that the processing model of SI could not be verified by either absolute structural or pragmatic approaches. It is, rather, a dynamic and complex processing mechanism, in which the interaction of language forms, ad hoc context, mental context, background knowledge, speakers’ interaction, etc. are involved.

Keywords: cognitive linguistics, pragmatics, scalar implicture, experimental study, Chinese language

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4812 Influence of Thermal Processing Methods on Antinutrient of Artocarpus heterophyllus Seeds

Authors: Marina Zulkifli, Mohd Faizal Mashhod, Noriham Abdullah

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The aim of this study was to determine the antinutrient compounds of jackfruit (Artocarpus heterophyllus) seeds as affected by thermal processes. Two types of heat treatments were applied namely boiling and microwave cooking. Results of this study showed that boiling caused a significant decrease in phytate content (30.01%), oxalate content (33.22%), saponin content (35.69%) and tannin content (44.58%) as compared to microwave cooking and raw seed. The percentage loss of antinutrient compounds in microwaved seed was: phytate 24.58%, oxalate 27.28%, saponin 16.50% and tannin 32.21%. Hence, these findings suggested that boiling is an effective treatment to reduce the level of toxic compounds in foods.

Keywords: jackfruit, heat treatments, antinutrient compounds, thermal processing

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4811 A Fuzzy Mathematical Model for Order Acceptance and Scheduling Problem

Authors: E. Koyuncu

Abstract:

The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling

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4810 Estimation of the Road Traffic Emissions and Dispersion in the Developing Countries Conditions

Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal

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We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.

Keywords: air pollution, dispersion, emissions, line sources, road traffic, urban transport

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4809 Impact of Varying Malting and Fermentation Durations on Specific Chemical, Functional Properties, and Microstructural Behaviour of Pearl Millet and Sorghum Flour Using Response Surface Methodology

Authors: G. Olamiti; TK. Takalani; D. Beswa, AIO Jideani

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The study investigated the effects of malting and fermentation times on some chemical, functional properties and microstructural behaviour of Agrigreen, Babala pearl millet cultivars and sorghum flours using response surface methodology (RSM). Central Composite Rotatable Design (CCRD) was performed on two independent variables: malting and fermentation times (h), at intervals of 24, 48, and 72, respectively. The results of dependent parameters such as pH, titratable acidity (TTA), Water absorption capacity (WAC), Oil absorption capacity (OAC), bulk density (BD), dispersibility and microstructural behaviour of the flours studied showed a significant difference in p < 0.05 upon malting and fermentation time. Babala flour exhibited a higher pH value at 4.78 at 48 h malted and 81.9 fermentation times. Agrigreen flour showed a higher TTA value at 0.159% at 81.94 h malted and 48 h fermentation times. WAC content was also higher in malted and fermented Babala flour at 2.37 ml g-1 for 81.94 h malted and 48 h fermentation time. Sorghum flour exhibited the least OAC content at 1.67 ml g-1 at 14 h malted and 48 h fermentation times. Agrigreen flour recorded the least bulk density, at 0.53 g ml-1 for 72 h malted and 24 h fermentation time. Sorghum flour exhibited a higher content of dispersibility, at 56.34%, after 24 h malted and 72 h fermented time. The response surface plots showed that increased malting and fermentation time influenced the dependent parameters. The microstructure behaviour of malting and fermentation times of pearl millet varieties and sorghum flours showed isolated, oval, spherical, or polygonal to smooth surfaces. The optimal processing conditions, such as malting and fermentation time for Agrigreen, were 32.24 h and 63.32 h; 35.18 h and 34.58 h for Babala; and 36.75 h and 47.88 h for sorghum with high desirability of 1.00. The validation of the optimum processing malting and fermentation times (h) on the dependent improved the experimented values. Food processing companies can use the study's findings to improve food processing and quality.

Keywords: Pearl millet, malting, fermentation, microstructural behaviour

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4808 An Evaluation of Medical Waste in Health Facilities through Data Envelopment Analysis (DEA) Method: Turkey-Amasya Public Hospitals Union Model

Authors: Murat Iskender Aktaş, Sadi Ergin, Rasime Acar Aktaş

Abstract:

In the light of fast-paced changes and developments in the health sector, the Ministry of Health started a new structuring with decree law numbered 663 within the scope of the Project of Transformation in Health. Accordingly, hospitals should ensure patient satisfaction through more efficient, more effective use of resources and sustainable finance by placing patients in the centre and should operate to increase efficiency to its maximum level while doing these. Within this study, in order to find out how efficient the hospitals were in terms of medical waste management between the years 2011-2014, the data from six hospitals of Amasya Public Hospitals Union were evaluated separately through Data Envelopment Analysis (DEA) method. First of all, input variables were determined. Input variables were the number of patients admitted to polyclinics, the number of inpatients in clinics, the number of patients who were operated and the number of patients who applied to the laboratory. Output variable was the cost of medical wastes in Turkish liras. Each hospital’s total medical waste level before and after public hospitals union; the amounts of average medical waste per patient admitted to polyclinics, per inpatient in clinics, per patient admitted to laboratory and per operated patient were compared within each group. In addition, average medical waste levels and costs were compared for Turkey in general and Europe in general. Paired samples t-test was used to find out whether the changes (increase-decrease) after public hospitals union were statistically significant. The health facilities that were unsuccessful in terms of medical waste management before and after public hospital union and the factors that caused this failure were determined. Based on the results, for each health facility that was ineffective in terms of medical waste management, the level of improvement required for each input was determined. The results of the study showed that there was an improvement in medical waste management applications after the health facilities became a member of public hospitals union; their medical waste levels were lower than the average of Turkey and Europe while the averages of cost of disposal were the highest.

Keywords: medical waste management, cost of medical waste, public hospitals, data envelopment analysis

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4807 Pale, Soft, Exudative (PSE) Turkey Meat in a Brazilian Commercial Processing Plant

Authors: Danielle C. B. Honorato, Rafael H. Carvalho, Adriana L. Soares, Ana Paula F. R. L. Bracarense, Paulo D. Guarnieri, Massami Shimokomaki, Elza I. Ida

Abstract:

Over the past decade, the Brazilian production of turkey meat increased by more than 50%, indicating that the turkey meat is considered a great potential for the Brazilian economy contributing to the growth of agribusiness at the marketing international scenario. However, significant color changes may occur during its processing leading to the pale, soft and exudative (PSE) appearance on the surface of breast meat due to the low water holding capacity (WHC). Changes in PSE meat functional properties occur due to the myofibrils proteins denaturation caused by a rapid postmortem glycolysis resulting in a rapid pH decline while the carcass temperature is still warm. The aim of this study was to analyze the physical, chemical and histological characteristics of PSE turkey meat obtained from a Brazilian commercial processing plant. The turkey breasts samples were collected (n=64) at the processing line and classified as PSE at L* ≥ 53 value. The pH was also analyzed after L* measurement. In sequence, PSE meat samples were evaluated for WHC, cooking loss (CL), shear force (SF), myofibril fragmentation index (MFI), protein denaturation (PD) and histological evaluation. The abnormal color samples presented lower pH values, 16% lower fiber diameter, 11% lower SF and 2% lower WHC than those classified as normal. The CL, PD and MFI were, respectively, 9%, 18% and 4% higher in PSE samples. The Pearson correlation between the L* values and CL, PD and MFI was positive, while that SF and pH values presented negative correlation. Under light microscopy, a shrinking of PSE muscle cell diameter was approximately 16% shorter in relation to normal samples and an extracellular enlargement of endomysium and perimysium sheaths as the consequence of higher water contents lost as observed previously by lower WHC values. Thus, the results showed that PSE turkey breast meat presented significant changes in their physical, chemical and histological characteristics that may impair its functional properties.

Keywords: functional properties, histological evaluation, meat quality, PSE

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4806 Remote Sensing and GIS-Based Environmental Monitoring by Extracting Land Surface Temperature of Abbottabad, Pakistan

Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

Abstract:

Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

Procedia PDF Downloads 355
4805 Classification of Barley Varieties by Artificial Neural Networks

Authors: Alper Taner, Yesim Benal Oztekin, Huseyin Duran

Abstract:

In this study, an Artificial Neural Network (ANN) was developed in order to classify barley varieties. For this purpose, physical properties of barley varieties were determined and ANN techniques were used. The physical properties of 8 barley varieties grown in Turkey, namely thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain, were determined and it was found that these properties were statistically significant with respect to varieties. As ANN model, three models, N-l, N-2 and N-3 were constructed. The performances of these models were compared. It was determined that the best-fit model was N-1. In the N-1 model, the structure of the model was designed to be 11 input layers, 2 hidden layers and 1 output layer. Thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain were used as input parameter; and varieties as output parameter. R2, Root Mean Square Error and Mean Error for the N-l model were found as 99.99%, 0.00074 and 0.009%, respectively. All results obtained by the N-l model were observed to have been quite consistent with real data. By this model, it would be possible to construct automation systems for classification and cleaning in flourmills.

Keywords: physical properties, artificial neural networks, barley, classification

Procedia PDF Downloads 178
4804 The Incidental Linguistic Information Processing and Its Relation to General Intellectual Abilities

Authors: Evgeniya V. Gavrilova, Sofya S. Belova

Abstract:

The present study was aimed at clarifying the relationship between general intellectual abilities and efficiency in free recall and rhymed words generation task after incidental exposure to linguistic stimuli. The theoretical frameworks stress that general intellectual abilities are based on intentional mental strategies. In this context, it seems to be crucial to examine the efficiency of incidentally presented information processing in cognitive task and its relation to general intellectual abilities. The sample consisted of 32 Russian students. Participants were exposed to pairs of words. Each pair consisted of two common nouns or two city names. Participants had to decide whether a city name was presented in each pair. Thus words’ semantics was processed intentionally. The city names were considered to be focal stimuli, whereas common nouns were considered to be peripheral stimuli. Along with that each pair of words could be rhymed or not be rhymed, but this phonemic aspect of stimuli’s characteristic (rhymed and non-rhymed words) was processed incidentally. Then participants were asked to produce as many rhymes as they could to new words. The stimuli presented earlier could be used as well. After that, participants had to retrieve all words presented earlier. In the end, verbal and non-verbal abilities were measured with number of special psychometric tests. As for free recall task intentionally processed focal stimuli had an advantage in recall compared to peripheral stimuli. In addition all the rhymed stimuli were recalled more effectively than non-rhymed ones. The inverse effect was found in words generation task where participants tended to use mainly peripheral stimuli compared to focal ones. Furthermore peripheral rhymed stimuli were most popular target category of stimuli that was used in this task. Thus the information that was processed incidentally had a supplemental influence on efficiency of stimuli processing as well in free recall as in word generation task. Different patterns of correlations between intellectual abilities and efficiency in different stimuli processing in both tasks were revealed. Non-verbal reasoning ability correlated positively with free recall of peripheral rhymed stimuli, but it was not related to performance on rhymed words’ generation task. Verbal reasoning ability correlated positively with free recall of focal stimuli. As for rhymed words generation task, verbal intelligence correlated negatively with generation of focal stimuli and correlated positively with generation of all peripheral stimuli. The present findings lead to two key conclusions. First, incidentally processed stimuli had an advantage in free recall and word generation task. Thus incidental information processing appeared to be crucial for subsequent cognitive performance. Secondly, it was demonstrated that incidentally processed stimuli were recalled more frequently by participants with high nonverbal reasoning ability and were more effectively used by participants with high verbal reasoning ability in subsequent cognitive tasks. That implies that general intellectual abilities could benefit from operating by different levels of information processing while cognitive problem solving. This research was supported by the “Grant of President of RF for young PhD scientists” (contract № is 14.Z56.17.2980- MK) and the Grant № 15-36-01348a2 of Russian Foundation for Humanities.

Keywords: focal and peripheral stimuli, general intellectual abilities, incidental information processing

Procedia PDF Downloads 231
4803 Autonomous Ground Vehicle Navigation Based on a Single Camera and Image Processing Methods

Authors: Auday Al-Mayyahi, Phil Birch, William Wang

Abstract:

A vision system-based navigation for autonomous ground vehicle (AGV) equipped with a single camera in an indoor environment is presented. A proposed navigation algorithm has been utilized to detect obstacles represented by coloured mini- cones placed in different positions inside a corridor. For the recognition of the relative position and orientation of the AGV to the coloured mini cones, the features of the corridor structure are extracted using a single camera vision system. The relative position, the offset distance and steering angle of the AGV from the coloured mini-cones are derived from the simple corridor geometry to obtain a mapped environment in real world coordinates. The corridor is first captured as an image using the single camera. Hence, image processing functions are then performed to identify the existence of the cones within the environment. Using a bounding box surrounding each cone allows to identify the locations of cones in a pixel coordinate system. Thus, by matching the mapped and pixel coordinates using a projection transformation matrix, the real offset distances between the camera and obstacles are obtained. Real time experiments in an indoor environment are carried out with a wheeled AGV in order to demonstrate the validity and the effectiveness of the proposed algorithm.

Keywords: autonomous ground vehicle, navigation, obstacle avoidance, vision system, single camera, image processing, ultrasonic sensor

Procedia PDF Downloads 302
4802 Biogas Production from Pistachio (Pistacia vera L.) Processing Waste

Authors: İ. Çelik, Goksel Demirer

Abstract:

Turkey is the third largest producer of pistachio (Pistacia vera L.) after Iran and United States. Harvested pistachio nuts are covered with organic hull which is removed by de-hulling process. Most of the pistachio by-products which are produced during de-hulling process are considered as agricultural waste and often mixed with soil, to a lesser extent are used as feedstuff by local livestock farmers and a small portion is used as herbal medicine. Due to its high organic and phenolic content as well as high solids concentration, pistachio processing wastes create significant waste management problems unless they are properly managed. However, there is not a well-established waste management method compensating the waste generated during the processing of pistachios. This study investigated the anaerobic treatability and biogas generation potential of pistachio hull waste. The effect of pre-treatment on biogas generation potential was investigated. For this purpose, Biochemical Methane Potential (BMP) Assays were conducted for two Chemical Oxygen Demand (COD) concentrations of 22 and 33 g tCOD l-1 at the absence and presence of chemical and thermal pre-treatment methods. The results revealed anaerobic digestion of the pistachio de-hulling wastes and subsequent biogas production as a renewable energy source are possible. The observed percent COD removal and methane yield values of the pre-treated pistachio de-hulling waste samples were significantly higher than the raw pistachio de-hulling waste. The highest methane yield was observed as 213.4 ml CH4/g COD.

Keywords: pistachio de-hulling waste, biogas, renewable energy, pre-treatment

Procedia PDF Downloads 215
4801 Sign Language Recognition of Static Gestures Using Kinect™ and Convolutional Neural Networks

Authors: Rohit Semwal, Shivam Arora, Saurav, Sangita Roy

Abstract:

This work proposes a supervised framework with deep convolutional neural networks (CNNs) for vision-based sign language recognition of static gestures. Our approach addresses the acquisition and segmentation of correct inputs for the CNN-based classifier. Microsoft Kinect™ sensor, despite complex environmental conditions, can track hands efficiently. Skin Colour based segmentation is applied on cropped images of hands in different poses, used to depict different sign language gestures. The segmented hand images are used as an input for our classifier. The CNN classifier proposed in the paper is able to classify the input images with a high degree of accuracy. The system was trained and tested on 39 static sign language gestures, including 26 letters of the alphabet and 13 commonly used words. This paper includes a problem definition for building the proposed system, which acts as a sign language translator between deaf/mute and the rest of the society. It is then followed by a focus on reviewing existing knowledge in the area and work done by other researchers. It also describes the working principles behind different components of CNNs in brief. The architecture and system design specifications of the proposed system are discussed in the subsequent sections of the paper to give the reader a clear picture of the system in terms of the capability required. The design then gives the top-level details of how the proposed system meets the requirements.

Keywords: sign language, CNN, HCI, segmentation

Procedia PDF Downloads 157
4800 Research on Pilot Sequence Design Method of Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing System Based on High Power Joint Criterion

Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

Abstract:

For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.

Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation

Procedia PDF Downloads 149
4799 A Cognitive Training Program in Learning Disability: A Program Evaluation and Follow-Up Study

Authors: Krisztina Bohacs, Klaudia Markus

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To author’s best knowledge we are in absence of studies on cognitive program evaluation and we are certainly short of programs that prove to have high effect sizes with strong retention results. The purpose of our study was to investigate the effectiveness of a comprehensive cognitive training program, namely BrainRx. This cognitive rehabilitation program target and remediate seven core cognitive skills and related systems of sub-skills through repeated engagement in game-like mental procedures delivered one-on-one by a clinician, supplemented by digital training. A larger sample of children with learning disability were given pretest and post-test cognitive assessments. The experimental group completed a twenty-week cognitive training program in a BrainRx center. A matched control group received another twenty-week intervention with Feuerstein’s Instrumental Enrichment programs. A second matched control group did not receive training. As for pre- and post-test, we used a general intelligence test to assess IQ and a computer-based test battery for assessing cognition across the lifespan. Multiple regression analyses indicated that the experimental BrainRx treatment group had statistically significant higher outcomes in attention, working memory, processing speed, logic and reasoning, auditory processing, visual processing and long-term memory compared to the non-treatment control group with very large effect sizes. With the exception of logic and reasoning, the BrainRx treatment group realized significantly greater gains in six of the above given seven cognitive measures compared to the Feuerstein control group. Our one-year retention measures showed that all the cognitive training gains were above ninety percent with the greatest retention skills in visual processing, auditory processing, logic, and reasoning. The BrainRx program may be an effective tool to establish long-term cognitive changes in case of students with learning disabilities. Recommendations are made for treatment centers and special education institutions on the cognitive training of students with special needs. The importance of our study is that targeted, systematic, progressively loaded and intensive brain training approach may significantly change learning disabilities.

Keywords: cognitive rehabilitation training, cognitive skills, learning disability, permanent structural cognitive changes

Procedia PDF Downloads 202
4798 Study and Conservation of Cultural and Natural Heritages with the Use of Laser Scanner and Processing System for 3D Modeling Spatial Data

Authors: Julia Desiree Velastegui Caceres, Luis Alejandro Velastegui Caceres, Oswaldo Padilla, Eduardo Kirby, Francisco Guerrero, Theofilos Toulkeridis

Abstract:

It is fundamental to conserve sites of natural and cultural heritage with any available technique or existing methodology of preservation in order to sustain them for the following generations. We propose a further skill to protect the actual view of such sites, in which with high technology instrumentation we are able to digitally preserve natural and cultural heritages applied in Ecuador. In this project the use of laser technology is presented for three-dimensional models, with high accuracy in a relatively short period of time. In Ecuador so far, there are not any records on the use and processing of data obtained by this new technological trend. The importance of the project is the description of the methodology of the laser scanner system using the Faro Laser Scanner Focus 3D 120, the method for 3D modeling of geospatial data and the development of virtual environments in the areas of Cultural and Natural Heritage. In order to inform users this trend in technology in which three-dimensional models are generated, the use of such tools has been developed to be able to be displayed in all kinds of digitally formats. The results of the obtained 3D models allows to demonstrate that this technology is extremely useful in these areas, but also indicating that each data campaign needs an individual slightly different proceeding starting with the data capture and processing to obtain finally the chosen virtual environments.

Keywords: laser scanner system, 3D model, cultural heritage, natural heritage

Procedia PDF Downloads 306
4797 Physical Properties of Nine Nigerian Staple Food Flours Related to Bulk Handling and Processing

Authors: Ogunsina Babatunde, Aregbesola Omotayo, Adebayo Adewale, Odunlami Johnson

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The physical properties of nine Nigerian staple food flours related to bulk handling and processing were investigated following standard procedures. The results showed that the moisture content, bulk density, angle of repose, water absorption capacity, swelling index, dispersability, pH and wettability of the flours ranged from 9.95 to 11.98%, 0.44 to 0.66 g/cm3, 31.43 to 39.65o, 198.3 to 291.7 g of water/100 g of sample, 5.53 to 7.63, 60.3 to 73.8%, 4.43 to 6.70, and 11 to 150 s. The particle size analysis of the flour samples indicated significant differences (p<0.05). The least gelation concentration of the flour samples ranged from 6 to 14%. The colour of the flours fell between light and saturated, with the exception of cassava, millet and maize flours which appear dark and dull. The properties of food flours depend largely on the inherent property of the food material and may influence their functional behaviour as food materials.

Keywords: properties, flours, staple food, bulk handling

Procedia PDF Downloads 481