Search results for: pig meat processing wastes
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4504

Search results for: pig meat processing wastes

3394 Effect of Some Metal Ions on the Activity of Lipase Produced by Aspergillus Niger Cultured on Vitellaria Paradoxa Shells

Authors: Abdulhakeem Sulyman, Olukotun Zainab, Hammed Abdulquadri

Abstract:

Lipases (triacylglycerol acyl hydrolases) (EC 3.1.1.3) are class of enzymes that catalyses the hydrolysis of triglycerides to glycerol and free fatty acids. They account for up to 10% of the enzyme in the market and have a wide range of applications in biofuel production, detergent formulation, leather processing and in food and feed processing industry. This research was conducted to study the effect of some metal ions on the activity of purified lipase produced by Aspergillus niger cultured on Vitellaria paradoxa shells. Purified lipase in 12.5 mM p-NPL was incubated with different metal ions (Zn²⁺, Ca²⁺, Mn²⁺, Fe²⁺, Na⁺, K⁺ and Mg²⁺). The final concentrations of metal ions investigated were 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 and 1.0 mM. The results obtained from the study showed that Zn²⁺, Ca²⁺, Mn²⁺ and Fe²⁺ ions increased the activity of lipase up to 3.0, 3.0, 1.0, and 26.0 folds respectively. Lipase activity was partially inhibited by Na⁺ and Mg²⁺ with up to 88.5% and 83.7% loss of activity respectively. Lipase activity was also inhibited by K⁺ with up to 56.7% loss in the activity as compared to in the absence of metal ions. The study concluded that lipase produced by Aspergillus niger cultured on Vitellaria paradoxa shells can be activated by the presence of Zn²⁺, Ca²⁺, Mn²⁺ and Fe²⁺ and inhibited by Na⁺, K⁺ and Mg²⁺.

Keywords: Aspergillus niger, Vitellaria paradoxa, lipase, metal ions

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3393 Online Monitoring Rheological Property of Polymer Melt during Injection Molding

Authors: Chung-Chih Lin, Chien-Liang Wu

Abstract:

The detection of the polymer melt state during manufacture process is regarded as an efficient way to control the molded part quality in advance. Online monitoring rheological property of polymer melt during processing procedure provides an approach to understand the melt state immediately. Rheological property reflects the polymer melt state at different processing parameters and is very important in injection molding process especially. An approach that demonstrates how to calculate rheological property of polymer melt through in-process measurement, using injection molding as an example, is proposed in this study. The system consists of two sensors and a data acquisition module can process the measured data, which are used for the calculation of rheological properties of polymer melt. The rheological properties of polymer melt discussed in this study include shear rate and viscosity which are investigated with respect to injection speed and melt temperature. The results show that the effect of injection speed on the rheological properties is apparent, especially for high melt temperature and should be considered for precision molding process.

Keywords: injection molding, melt viscosity, shear rate, monitoring

Procedia PDF Downloads 377
3392 Detection of Image Blur and Its Restoration for Image Enhancement

Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

Abstract:

Image restoration in the process of communication is one of the emerging fields in the image processing. The motion analysis processing is the simplest case to detect motion in an image. Applications of motion analysis widely spread in many areas such as surveillance, remote sensing, film industry, navigation of autonomous vehicles, etc. The scene may contain multiple moving objects, by using motion analysis techniques the blur caused by the movement of the objects can be enhanced by filling-in occluded regions and reconstruction of transparent objects, and it also removes the motion blurring. This paper presents the design and comparison of various motion detection and enhancement filters. Median filter, Linear image deconvolution, Inverse filter, Pseudoinverse filter, Wiener filter, Lucy Richardson filter and Blind deconvolution filters are used to remove the blur. In this work, we have considered different types and different amount of blur for the analysis. Mean Square Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the performance of the filters. The designed system has been implemented in Matlab software and tested for synthetic and real-time images.

Keywords: image enhancement, motion analysis, motion detection, motion estimation

Procedia PDF Downloads 282
3391 Efficient of Technology Remediation Soil That Contaminated by Petroleum Based on Heat without Combustion

Authors: Gavin Hutama Farandiarta, Hegi Adi Prabowo, Istiara Rizqillah Hanifah, Millati Hanifah Saprudin, Raden Iqrafia Ashna

Abstract:

The increase of the petroleum’s consumption rate encourages industries to optimize and increase the activity in processing crude oil into petroleum. However, although the result gives a lot of benefits to humans worldwide, it also gives negative impact to the environment. One of the negative impacts of processing crude oil is the soil will be contaminated by petroleum sewage sludge. This petroleum sewage sludge, contains hydrocarbon compound and it can be calculated by Total Petroleum Hydrocarbon (TPH).Petroleum sludge waste is accounted as hazardous and toxic. The soil contamination caused by the petroleum sludge is very hard to get rid of. However, there is a way to manage the soil that is contaminated by petroleum sludge, which is by using heat (thermal desorption) in the process of remediation. There are several factors that affect the success rate of the remediation with the help of heat which are temperature, time, and air pressure in the desorption column. The remediation process using the help of heat is an alternative in soil recovery from the petroleum pollution which highly effective, cheap, and environmentally friendly that produces uncontaminated soil and the petroleum that can be used again.

Keywords: petroleum sewage sludge, remediation soil, thermal desorption, total petroleum hydrocarbon (TPH)

Procedia PDF Downloads 237
3390 Artificial Intelligence and Distributed System Computing: Application and Practice in Real Life

Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

Abstract:

In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

Procedia PDF Downloads 106
3389 Characteristics and Quality of Chilean Abalone Undergoing Different Drying Emerging Technologies

Authors: Mario Pérez-Won, Anais Palma-Acevedo, Luis González-Cavieres, Roberto Lemus-Mondaca, Gipsy Tabilo-Munizaga

Abstract:

The Chilean abalone (Concholepas Concholepas) is a gastropod mollusk; it has a high commercial value due to the qualities of its meat, especially hardness, as a critical acceptance parameter. However, its main problem is its short shelf-life which is usually extended using traditional technologies with high energy consumption. Therefore, applying different technologies for the pre-treatment and drying process is necessary. In this research, pulsed electric field (PEF) was used as a pre-treatment for vacuum microwave drying (VMD), freeze-drying (FD), and hot-air drying (HAD). Drying conditions and characteristics were set according to previous experiments. The Drying samples were analyzed in terms of physical quality (color, texture, microstructure, and rehydration capacity), protein quality (degree of hydrolysis and computer protein efficiency ratio), and energy parameters. Regarding quality, the treatment that obtained lower harness was PEF+FD (195 N ± 10), the lowest change of color was for treatment PEF+VMD (ΔE: 17 ± 1.5), and the best rehydration capacity was for treatment PEF+VMD (1.2 h for equilibrium). For protein quality, the highest Computer-Protein Efficiency Ratio was the sample 2.0 kV/ cm of PEF (index of 4.18 ± 0.26 at the end of the digestion). Moreover, about energetic consumption, results show that VMD decreases the drying process by 97% whether PEF was used or not. Consequently, it is possible to conclude that using PEF as a pre-treatment for VMD and FD treatments has advantages that must be used following the consumer’s needs or preferences.

Keywords: chilean abalone, freeze-drying, proteins, pulsed electric fields

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3388 Deep Learning Based Road Crack Detection on an Embedded Platform

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

Abstract:

It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

Procedia PDF Downloads 334
3387 Exploring the Intersection Between the General Data Protection Regulation and the Artificial Intelligence Act

Authors: Maria Jędrzejczak, Patryk Pieniążek

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The European legal reality is on the eve of significant change. In European Union law, there is talk of a “fourth industrial revolution”, which is driven by massive data resources linked to powerful algorithms and powerful computing capacity. The above is closely linked to technological developments in the area of artificial intelligence, which has prompted an analysis covering both the legal environment as well as the economic and social impact, also from an ethical perspective. The discussion on the regulation of artificial intelligence is one of the most serious yet widely held at both European Union and Member State level. The literature expects legal solutions to guarantee security for fundamental rights, including privacy, in artificial intelligence systems. There is no doubt that personal data have been increasingly processed in recent years. It would be impossible for artificial intelligence to function without processing large amounts of data (both personal and non-personal). The main driving force behind the current development of artificial intelligence is advances in computing, but also the increasing availability of data. High-quality data are crucial to the effectiveness of many artificial intelligence systems, particularly when using techniques involving model training. The use of computers and artificial intelligence technology allows for an increase in the speed and efficiency of the actions taken, but also creates security risks for the data processed of an unprecedented magnitude. The proposed regulation in the field of artificial intelligence requires analysis in terms of its impact on the regulation on personal data protection. It is necessary to determine what the mutual relationship between these regulations is and what areas are particularly important in the personal data protection regulation for processing personal data in artificial intelligence systems. The adopted axis of considerations is a preliminary assessment of two issues: 1) what principles of data protection should be applied in particular during processing personal data in artificial intelligence systems, 2) what regulation on liability for personal data breaches is in such systems. The need to change the regulations regarding the rights and obligations of data subjects and entities processing personal data cannot be excluded. It is possible that changes will be required in the provisions regarding the assignment of liability for a breach of personal data protection processed in artificial intelligence systems. The research process in this case concerns the identification of areas in the field of personal data protection that are particularly important (and may require re-regulation) due to the introduction of the proposed legal regulation regarding artificial intelligence. The main question that the authors want to answer is how the European Union regulation against data protection breaches in artificial intelligence systems is shaping up. The answer to this question will include examples to illustrate the practical implications of these legal regulations.

Keywords: data protection law, personal data, AI law, personal data breach

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3386 A Neural Network Based Clustering Approach for Imputing Multivariate Values in Big Data

Authors: S. Nickolas, Shobha K.

Abstract:

The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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3385 An ERP Study of Chinese Pseudo-Object Structures

Authors: Changyin Zhou

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Verb-argument relation is a very important aspect of syntax-semantics interaction in sentence processing. Previous ERP (event related potentials) studies in this field mainly concentrated on the relation between the verb and its core arguments. The present study aims to reveal the ERP pattern of Chinese pseudo-object structures (SOSs), in which a peripheral argument is promoted to occupy the position of the patient object, as compared with the patient object structures (POSs). The ERP data were collected when participants were asked to perform acceptability judgments about Chinese phrases. Our result shows that, similar to the previous studies of number-of-argument violations, Chinese SOSs show a bilaterally distributed N400 effect. But different from all the previous studies of verb-argument relations, Chinese SOSs demonstrate a sustained anterior positivity (SAP). This SAP, which is the first report related to complexity of argument structure operation, reflects the integration difficulty of the newly promoted arguments and the progressive nature of well-formedness checking in the processing of Chinese SOSs.

Keywords: Chinese pseudo-object structures, ERP, sustained anterior positivity, verb-argument relation

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3384 Thermo-Mechanical Processing Scheme to Obtain Micro-Duplex Structure Favoring Superplasticity in an As-Cast and Homogenized Medium Alloyed Nickel Base Superalloy

Authors: K. Sahithya, I. Balasundar, Pritapant, T. Raghua

Abstract:

Ni-based superalloy with a nominal composition Ni-14% Cr-11% Co-5.8% Mo-2.4% Ti-2.4% Nb-2.8% Al-0.26 % Fe-0.032% Si-0.069% C (all in wt %) is used as turbine discs in a variety of aero engines. Like any other superalloy, the primary processing of the as-cast superalloy poses a major challenge due to its complex alloy chemistry. The challenge was circumvented by characterizing the different phases present in the material, optimizing the homogenization treatment, identifying a suitable thermomechanical processing window using dynamic materials modeling. The as-cast material was subjected to homogenization at 1200°C for a soaking period of 8 hours and quenched using different media. Water quenching (WQ) after homogenization resulted in very fine spherical γꞌ precipitates of sizes 30-50 nm, whereas furnace cooling (FC) after homogenization resulted in bimodal distribution of precipitates (primary gamma prime of size 300nm and secondary gamma prime of size 5-10 nm). MC type primary carbides that are stable till the melting point of the material were found in both WQ and FC samples. Deformation behaviour of both the materials below (1000-1100°C) and above gamma prime solvus (1100-1175°C) was evaluated by subjecting the material to series of compression tests at different constant true strain rates (0.0001/sec-1/sec). An in-detail examination of the precipitate dislocation interaction mechanisms carried out using TEM revealed precipitate shearing and Orowan looping as the mechanisms governing deformation in WQ and FC, respectively. Incoherent/semi coherent gamma prime precipitates in the case of FC material facilitates better workability of the material, whereas the coherent precipitates in WQ material contributed to higher resistance to deformation of the material. Both the materials exhibited discontinuous dynamic recrystallization (DDRX) above gamma prime solvus temperature. The recrystallization kinetics was slower in the case of WQ material. Very fine grain boundary carbides ( ≤ 300 nm) retarded the recrystallisation kinetics in WQ. Coarse carbides (1-5 µm) facilitate particle stimulated nucleation in FC material. The FC material was cogged (primary hot working) 1120˚C, 0.03/sec resulting in significant grain refinement, i.e., from 3000 μm to 100 μm. The primary processed material was subjected to intensive thermomechanical deformation subsequently by reducing the temperature by 50˚C in each processing step with intermittent heterogenization treatment at selected temperatures aimed at simultaneous coarsening of the gamma prime precipitates and refinement of the gamma matrix grains. The heterogeneous annealing treatment carried out, resulted in gamma grains of 10 μm and gamma prime precipitates of 1-2 μm. Further thermo mechanical processing of the material was carried out at 1025˚C to increase the homogeneity of the obtained micro-duplex structure.

Keywords: superalloys, dynamic material modeling, nickel alloys, dynamic recrystallization, superplasticity

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3383 Modeling Water Resources Carrying Capacity, Optimizing Water Treatment, Smart Water Management, and Conceptualizing a Watershed Management Approach

Authors: Pius Babuna

Abstract:

Sustainable water use is important for the existence of the human race. Water resources carrying capacity (WRCC) measures the sustainability of water use; however, the calculation and optimization of WRCC remain challenging. This study used a mathematical model (the Logistics Growth of Water Resources -LGWR) and a linear objective function to model water sustainability. We tested the validity of the models using data from Ghana. Total freshwater resources, water withdrawal, and population data were used in MATLAB. The results show that the WRCC remains sustainable until the year 2132 ±18, when half of the total annual water resources will be used. The optimized water treatment cost suggests that Ghana currently wastes GHȼ 1115.782± 50 cedis (~$182.21± 50) per water treatment plant per month or ~ 0.67 million gallons of water in an avoidable loss. Adopting an optimized water treatment scheme and a watershed management approach will help sustain the WRCC.

Keywords: water resources carrying capacity, smart water management, optimization, sustainable water use, water withdrawal

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3382 Functional Neural Network for Decision Processing: A Racing Network of Programmable Neurons Where the Operating Model Is the Network Itself

Authors: Frederic Jumelle, Kelvin So, Didan Deng

Abstract:

In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

Procedia PDF Downloads 121
3381 Solid Waste Characterization and Recycling Potential in Hawassa University, Ethiopia

Authors: Hunachew Beyene Mengesha, Biruck Desalegn Yirsaw

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Owing to the dramatic expansion of universities in Ethiopia, understanding the composition and nature of solid waste at the source of generation plays an important role in designing a program for an integrated waste management program. In this study, we report the quantity, quality and recycling potential of the waste generated in the three campuses of the Hawassa University, Southern Ethiopia. A total of 3.5 tons of waste was generated per day in the three campuses of the university. More than 95% of the waste constituents were with potential to be recovered. It was a lesson from the study that there was no source reduction, recycling, composting, proper land filling or incineration practices in-place. The considerably high waste generation associated with the expansion of educational programs in the university appears worthwhile requiring implementation of programs for an integrated solid waste management to minimize health risk to humans and reduce environmental implications as a result of improper handling and disposal of wastes.

Keywords: Hawassa University, integrated solid waste management, solid waste generation, energy management, waste management

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3380 An Event-Related Potential Investigation of Speech-in-Noise Recognition in Native and Nonnative Speakers of English

Authors: Zahra Fotovatnia, Jeffery A. Jones, Alexandra Gottardo

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Speech communication often occurs in environments where noise conceals part of a message. Listeners should compensate for the lack of auditory information by picking up distinct acoustic cues and using semantic and sentential context to recreate the speaker’s intended message. This situation seems to be more challenging in a nonnative than native language. On the other hand, early bilinguals are expected to show an advantage over the late bilingual and monolingual speakers of a language due to their better executive functioning components. In this study, English monolingual speakers were compared with early and late nonnative speakers of English to understand speech in noise processing (SIN) and the underlying neurobiological features of this phenomenon. Auditory mismatch negativities (MMNs) were recorded using a double-oddball paradigm in response to a minimal pair that differed in their middle vowel (beat/bit) at Wilfrid Laurier University in Ontario, Canada. The results did not show any significant structural and electroneural differences across groups. However, vocabulary knowledge correlated positively with performance on tests that measured SIN processing in participants who learned English after age 6. Moreover, their performance on the test negatively correlated with the integral area amplitudes in the left superior temporal gyrus (STG). In addition, the STG was engaged before the inferior frontal gyrus (IFG) in noise-free and low-noise test conditions in all groups. We infer that the pre-attentive processing of words engages temporal lobes earlier than the fronto-central areas and that vocabulary knowledge helps the nonnative perception of degraded speech.

Keywords: degraded speech perception, event-related brain potentials, mismatch negativities, brain regions

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3379 Using Analytical Hierarchy Process and TOPSIS Approaches in Designing a Finite Element Analysis Automation Program

Authors: Ming Wen, Nasim Nezamoddini

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Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: finite element analysis, FEA, random vibration fatigue, process automation, analytical hierarchy process, AHP, TOPSIS, multiple-criteria decision-making, MCDM

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3378 Trash Dash: An Educational Android Game Application for Proper Waste Segregation

Authors: Marylene S. Eder, Dorothy M. Jao, Paolo Marc Nicolas S. Laspiñas, Pukilan A. Malim, Sarah Jean D. Raterta

Abstract:

Trash Dash is an android game application developed to serve as an alternative tool to practice proper waste segregation for children ages 3 years old and above. The researchers designed the application using Unity 3D and developed the text file that served as the database of the game application. An observation of a pre-school teacher shows that children know how to throw their garbage but they do not know yet how to segregate wastes. After launching the mobile application to K-2 pupils 4 – 5 years of age, the researchers have noticed that children within this age are active and motivated to learn the difference between biodegradable and non-biodegradable. Based on the result of usability test conducted, it was concluded that the game is easy to use and children will most likely use this application frequently. Furthermore, the children may need assistance from their parents and teachers when playing the game. An actual testing of the application has been conducted to different devices as well as functionality test by Thwack Application and it can be concluded that the mobile application can be launched and installed on a device with a minimum API requirement of Gingerbread (2.3.1).

Keywords: waste segregation, android application, biodegradable, non-biodegradable

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3377 Supplementation of Mannan Oligosaccharides in Guinea Pigs: Mortality and Growth Performance

Authors: C. Minguez, J. Bueso-Rodenas, C. Ibanez, A. Calvo

Abstract:

Mannan oligosaccharides (MOS) is one of the prebiotic most used in livestock nutrition. In this research, the effect of MOS dietary supplementation on growth performance and mortality in meat guinea pigs were studied. Three different experimental groups were compared: Control group (no additives); MOS 1 (1.5 g kg−1); MOS 2 (2 g kg−1). Guinea pigs were housed in 15 collective cages (n = 50 animals in each trial; 10 animals per cage). The young guinea pigs were weaning at day 28 and individually identified by a little ear tag. The fattening period was 49 days. Guinea pigs in both groups were fed ad libitum, with a standard commercial pellet diet (10 MJ of digestible energy/kg, 17% crude protein, 11% crude fiber, and 4.5% crude fat) and alfalfa (Medicago sativa) as forage. Growth traits, including body weight (BW), average daily gain (ADG), feed intake (FI), and feed conversion ratio (FCR), were measured weekly. On day 74, the animals were slaughtered. Contrasts between groups were obtained by calculated generalized least squares values. Mortality were evaluated by Fisher's exact test. Between MOS groups no significant differences were observed for growth traits and mortality. However, significant differences against the control group were observed for traits studied (pvalue < 0.05). In conclusion, the use of MOS could be a good prebiotic supplement to raise guinea pigs because it MOS has shown positive effects in growth traits and immune response in animals.

Keywords: guinea pig, growth, mannan oligosaccharides, mortality

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3376 Neural Correlates of Diminished Humor Comprehension in Schizophrenia: A Functional Magnetic Resonance Imaging Study

Authors: Przemysław Adamczyk, Mirosław Wyczesany, Aleksandra Domagalik, Artur Daren, Kamil Cepuch, Piotr Błądziński, Tadeusz Marek, Andrzej Cechnicki

Abstract:

The present study aimed at evaluation of neural correlates of humor comprehension impairments observed in schizophrenia. To investigate the nature of this deficit in schizophrenia and to localize cortical areas involved in humor processing we used functional magnetic resonance imaging (fMRI). The study included chronic schizophrenia outpatients (SCH; n=20), and sex, age and education level matched healthy controls (n=20). The task consisted of 60 stories (setup) of which 20 had funny, 20 nonsensical and 20 neutral (not funny) punchlines. After the punchlines were presented, the participants were asked to indicate whether the story was comprehensible (yes/no) and how funny it was (1-9 Likert-type scale). fMRI was performed on a 3T scanner (Magnetom Skyra, Siemens) using 32-channel head coil. Three contrasts in accordance with the three stages of humor processing were analyzed in both groups: abstract vs neutral stories - incongruity detection; funny vs abstract - incongruity resolution; funny vs neutral - elaboration. Additionally, parametric modulation analysis was performed using both subjective ratings separately in order to further differentiate the areas involved in incongruity resolution processing. Statistical analysis for behavioral data used U Mann-Whitney test and Bonferroni’s correction, fMRI data analysis utilized whole-brain voxel-wise t-tests with 10-voxel extent threshold and with Family Wise Error (FWE) correction at alpha = 0.05, or uncorrected at alpha = 0.001. Between group comparisons revealed that the SCH subjects had attenuated activation in: the right superior temporal gyrus in case of irresolvable incongruity processing of nonsensical puns (nonsensical > neutral); the left medial frontal gyrus in case of incongruity resolution processing of funny puns (funny > nonsensical) and the interhemispheric ACC in case of elaboration of funny puns (funny > neutral). Additionally, the SCH group revealed weaker activation during funniness ratings in the left ventro-medial prefrontal cortex, the medial frontal gyrus, the angular and the supramarginal gyrus, and the right temporal pole. In comprehension ratings the SCH group showed suppressed activity in the left superior and medial frontal gyri. Interestingly, these differences were accompanied by protraction of time in both types of rating responses in the SCH group, a lower level of comprehension for funny punchlines and a higher funniness for absurd punchlines. Presented results indicate that, in comparison to healthy controls, schizophrenia is characterized by difficulties in humor processing revealed by longer reaction times, impairments of understanding jokes and finding nonsensical punchlines more funny. This is accompanied by attenuated brain activations, especially in the left fronto-parietal and the right temporal cortices. Disturbances of the humor processing seem to be impaired at the all three stages of the humor comprehension process, from incongruity detection, through its resolution to elaboration. The neural correlates revealed diminished neural activity of the schizophrenia brain, as compared with the control group. The study was supported by the National Science Centre, Poland (grant no 2014/13/B/HS6/03091).

Keywords: communication skills, functional magnetic resonance imaging, humor, schizophrenia

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3375 Biocarbon for High-Performance Supercapacitors Derived from the Wastewater Treatment of Sewage Sludge

Authors: Santhosh Ravichandran, F. J. Rodríguez-Varela

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In this study, a biocarbon (BC) was made from sewage sludge from the water treatment plant (PTAR) in Saltillo, Coahuila, Mexico. The sludge was carbonized in water and then chemically activated by pyrolysis. The biocarbon was evaluated physicochemically using XRD, SEM-EDS, and FESEM. A broad (002) peak attributable to graphitic structures indicates that the material is amorphous. The resultant biocarbon has a high specific surface area (412 m2 g-1), a large pore volume (0.39 cm3 g-1), interconnected hierarchical porosity, and outstanding electrochemical performance. It is appropriate for high-performance supercapacitor electrode materials due to its high specific capacitance of 358 F g-1, great rate capability, and outstanding cycling stability (around 87% capacitance retention after 10,000 cycles, even at a high current density of 19 A g-1). In an aqueous solution, the constructed BC/BC symmetric supercapacitor exhibits increased super capacitor behavior with a high energy density of 29.5 Whkg-1. The concept provides an efficient method for producing high-performance electrode materials for supercapacitors from conventional water treatment biomass wastes.

Keywords: supercapacitors, carbon, material science, batteries

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3374 Design of a Graphical User Interface for Data Preprocessing and Image Segmentation Process in 2D MRI Images

Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

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The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

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3373 Recycling of Plastic Waste into Composites Using Kaolin as Reinforcement

Authors: Gloria P. Manu, Johnson K. Efavi, Abu Yaya, Grace K. Arkorful, Frank Godson

Abstract:

Plastics have been used extensively in both food and water packaging and other applications because of their inherent properties of low bulk densities and inertness as well as its low cost. Waste management of these plastics after usage is troubling in Ghana. One way of addressing the environmental problems associated with these plastic wastes is by recycling into useful products such as composites for energy and construction applications using natural or local materials as reinforcement. In this work, composites have been formed from waste low-density polyethylene (LDPE) and kaolin at temperatures as low as 70 ֯C using low-cost solvents like kerosene. Chemical surface modifications have been employed to improve the interfacial bonding resulting in the enhancement of properties of the composites. Kaolin particles of sizes ≤ 90µm were dispersed in the polyethylene matrix. The content of the LDPE was varied between 10, 20, 30, 40, 50, 60, and 70 %wt. Results obtained indicated that all the composites exhibited impressive compressive and flexural strengths with the 50%wt. composition having the highest strength. The hardness value of the composites increased as the polyethylene composition reduces and that of the kaolin increased. The average density and water of absorption of the composites were 530kg/m³ and 1.3% respectively.

Keywords: polyethylene, recycling, waste, composite, kaolin

Procedia PDF Downloads 168
3372 Application of Natural Language Processing in Education

Authors: Khaled M. Alhawiti

Abstract:

Reading capability is a major segment of language competency. On the other hand, discovering topical writings at a fitting level for outside and second language learners is a test for educators. We address this issue utilizing natural language preparing innovation to survey reading level and streamline content. In the connection of outside and second-language learning, existing measures of reading level are not appropriate to this errand. Related work has demonstrated the profit of utilizing measurable language preparing procedures; we expand these thoughts and incorporate other potential peculiarities to measure intelligibility. In the first piece of this examination, we join characteristics from measurable language models, customary reading level measures and other language preparing apparatuses to deliver a finer technique for recognizing reading level. We examine the execution of human annotators and assess results for our finders concerning human appraisals. A key commitment is that our identifiers are trainable; with preparing and test information from the same space, our finders beat more general reading level instruments (Flesch-Kincaid and Lexile). Trainability will permit execution to be tuned to address the needs of specific gatherings or understudies.

Keywords: natural language processing, trainability, syntactic simplification tools, education

Procedia PDF Downloads 484
3371 Effects of Packaging Method, Storage Temperature and Storage Time on the Quality Properties of Cold-Dried Beef Slices

Authors: Elif Aykın Dinçer, Mustafa Erbaş

Abstract:

The effects of packaging method (modified atmosphere packaging (MAP) and aerobic packaging (AP)), storage temperature (4 and 25°C) and storage time (0, 15, 30, 45, 60, 75 and 90 days) on the chemical, microbiological and sensory properties of cold-dried beef slices were investigated. Beef slices were dried at 10°C and 3 m/s after pasteurization with hot steam and then packaged in order to determine the effect of different storage conditions. As the storage temperature and time increased, it was determined that the amount of CO2 decreased in the MAP packed samples and that the amount of O2 decreased while the amount of CO2 increased in the AP packed samples. The water activity value of stored beef slices decreased from 0.91 to 0.88 during 90 days of storage. The pH, TBARS and NPN-M values of stored beef slices were higher in the AP packed samples and pH value increased from 5.68 to 5.93, TBARS increased from 25.25 to 60.11 μmol MDA/kg and NPN-M value increased from 4.37 to 6.66 g/100g during the 90 days of storage. It was determined that the microbiological quality of MAP packed samples was higher and the mean counts of TAMB, TPB, Micrococcus/Staphylococcus, LAB and yeast-mold were 4.10, 3.28, 3.46, 2.99 and 3.14 log cfu/g, respectively. As a result of sensory evaluation, it was found that the quality of samples packed MAP and stored at low temperature was higher and the shelf life of samples was 90 days at 4°C and 75 days at 25°C for MAP treatment, and 60 days at 4°C and 45 days at 25°C for AP treatment.

Keywords: cold drying, dried meat, packaging, storage

Procedia PDF Downloads 147
3370 Effect of High Pressure Treatment on the Microbial Contamination and on Some Chemical and Physical Properties of Minced Chicken

Authors: Siddig H. Hamad, Salah M. Al-Eid, Fahad M. Al-Jassas

Abstract:

Composite samples of minced chicken were vacuum-packaged and pressure treated at 300, 400, 450 and 500 MPa in a Stansted 'FOOD-LAB' model S-FL-850-9-W high hydrostatic pressure research apparatus (Stansted Fluid Power Ltd., Stansted, UK). Treated and untreated samples were then stored at 3°C, and microbial content as well as some chemical and physical properties monitored. The microbial load of the untreated samples reached the spoilage level of 107 cfu/g in about one week, resulting in bad smell and dark brown color. The pressure treatments reduced total bacterial counts by about 1.8 to 3.2 log10 cycles and reduced counts of Enterobacteriaceae and Salmonella to non-detectable levels. The color of meat was slightly affected, but pH, moisture content and the oxidation products of lipids were not substantially changed. The treatment killed mainly gram negative bacteria but also caused sub-lethal injury to part of the population resulting in prolonged lag phase. The population not killed by the 350 to 450 MPa treatments grew relatively slowly during storage, and its loads reached spoilage level in 4 to 6 weeks, while the load of the population treated at 500 MPa did not reach this level till the end of a storage period of 9 weeks.

Keywords: chicken, cold storage, microbial spoilage, high hydrostatic pressure

Procedia PDF Downloads 239
3369 Removal of Heavy Metals from Water in the Presence of Organic Wastes: Fruit Peels

Authors: Özge Yılmaz Gel, Berk Kılıç, Derin Dalgıç, Ela Mia Sevilla Levi, Ömer Aydın

Abstract:

In this experiment, our goal was to remove heavy metals from water. Most recent studies have used removing toxic heavy elements: Cu⁺², Cr⁺³ and Fe⁺³ ions from aqueous solutions has been previously investigated with different kinds of plants like kiwi and tangerines. However, in this study, three different fruit peels were used. We tested banana, peach, and potato peels to remove heavy metal ions from their solution. The first step of the experiment was to wash the peels with distilled water and then dry the peels in an oven for 48 hrs at 80°C. Once the peels were washed and dried, 0.2 grams were weighed and added into 200 mL of %0.1 percent heavy metal solutions by mass. The mixing process was done via a magnetic stirrer. Each sample was taken in 15-minute intervals, and absorbance changes of the solutions were detected using a UV-Vis Spectrophotometer. Among the used waste products, banana peel was the most efficient one. Moreover, the amount of fruit peel, pH values of the initial heavy metal solution, and initial concentration of heavy metal solutions were investigated to determine the effect of fruit peels.

Keywords: absorbance, heavy metal, removal of heavy metals, fruit peels

Procedia PDF Downloads 72
3368 Developing Drought and Heat Stress Tolerant Chickpea Genotypes

Authors: Derya Yucel, Nigar Angın, Dürdane Mart, Meltem Turkeri, Volkan Catalkaya, Celal Yucel

Abstract:

Chickpea (Cicer arietinum L.) with high protein content is a vital food, especially in under-developed and developing countries for the people who do not consume enough meat due to low-income level. The objective of the proposed study is to evaluate growing, yield and yield components of chickpea genotypes under Mediterranean condition so determine tolerance of chickpea genotypes against drought and heat stress. For this purpose, a total of 34 chickpea genotypes were used as material. The experiment was conducted according to factorial randomized complete block design with 3 reps at the Eastern Mediterranean Research Institute, Adana, TURKEY for 2014-15 growing season under three different growing conditions (Winter sowing, irrigated-late sowing and non-irrigated- late sowing). According to results of this experiment, vegetative period, flowering time, poding time, maturity time, plant height, height of first pod, seed yield and 100 seed weight were ranged between 68.33 to 78.77 days, 94.22 to 85.00 days, 94.11 to 106.44 days, 198.56 to 214.44 days, 37.18 to 64.89 cm, 18.33 to 34.83 cm, 417.1 to 1746.4 kg/ha and 14.02 to 45.02 g, respectively. Among the chickpea genotypes, the Aksu, Arda, Çakır, F4 09 (X 05 TH 21-16189), FLIP 03-108 were least affected by drought and heat stress. Therefore, these genotypes can be used as sources of drought and heat tolerance in further breeding programme for evolving the drought and heat tolerant genotypes in chickpea.

Keywords: chickpea, drought stress, heat stress, yield

Procedia PDF Downloads 223
3367 Effect of Core Puncture Diameter on Bio-Char Kiln Efficiency

Authors: W. Intagun, T. Khamdaeng, P. Prom-ngarm, N. Panyoyai

Abstract:

Biochar has been used as a soil amendment since it has high porous structure and has proper nutrients and chemical properties for plants. Product yields produced from biochar kiln are dependent on process parameters and kiln types used. The objective of this research is to investigate the effect of core puncture diameter on biochar kiln efficiency, i.e., yields of biochar and produced gas. Corncobs were used as raw material to produce biochar. Briquettes from agricultural wastes were used as fuel. Each treatment was performed by changing the core puncture diameter. From the experiment, it is revealed that the yield of biochar at the core puncture diameter of 3.18 mm, 4.76 mm, and 6.35 mm was 10.62 wt. %, 24.12 wt. %, and 12.24 wt. %, of total solid yields, respectively. The yield of produced gas increased with increasing the core puncture diameter. The maximum percentage by weight of the yield of produced gas was 81.53 wt. % which was found at the core puncture diameter of 6.35 mm. The core puncture diameter was furthermore found to affect the temperature distribution inside the kiln and its thermal efficiency. In conclusion, the high efficient biochar kiln can be designed and constructed by using the proper core puncture diameter.

Keywords: anila stove, bio-char, soil conditioning materials, temperature distribution

Procedia PDF Downloads 225
3366 Finite Element Modeling of the Mechanical Behavior of Municipal Solid Waste Incineration Bottom Ash with the Mohr-Coulomb Model

Authors: Le Ngoc Hung, Abriak Nor Edine, Binetruy Christophe, Benzerzour Mahfoud, Shahrour Isam, Patrice Rivard

Abstract:

Bottom ash from Municipal Solid Waste Incineration (MSWI) can be viewed as a typical granular material because these industrial by-products result from the incineration of various domestic wastes. MSWI bottom ashes are mainly used in road engineering in substitution of the traditional natural aggregates. As the characterization of their mechanical behavior is essential in order to use them, specific studies have been led over the past few years. In the first part of this paper, the mechanical behavior of MSWI bottom ash is studied with triaxial tests. After analysis of the experiment results, the simulation of triaxial tests is carried out by using the software package CESAR-LCPC. As the first approach in modeling of this new class material, the Mohr-Coulomb model was chosen to describe the evolution of material under the influence of external mechanical actions.

Keywords: bottom ash, granular material, triaxial test, mechanical behavior, simulation, Mohr-Coulomb model, CESAR-LCPC

Procedia PDF Downloads 304
3365 Design and Field Programmable Gate Array Implementation of Radio Frequency Identification for Boosting up Tag Data Processing

Authors: G. Rajeshwari, V. D. M. Jabez Daniel

Abstract:

Radio Frequency Identification systems are used for automated identification in various applications such as automobiles, health care and security. It is also called as the automated data collection technology. RFID readers are placed in any area to scan large number of tags to cover a wide distance. The placement of the RFID elements may result in several types of collisions. A major challenge in RFID system is collision avoidance. In the previous works the collision was avoided by using algorithms such as ALOHA and tree algorithm. This work proposes collision reduction and increased throughput through reading enhancement method with tree algorithm. The reading enhancement is done by improving interrogation procedure and increasing the data handling capacity of RFID reader with parallel processing. The work is simulated using Xilinx ISE 14.5 verilog language. By implementing this in the RFID system, we can able to achieve high throughput and avoid collision in the reader at a same instant of time. The overall system efficiency will be increased by implementing this.

Keywords: antenna, anti-collision protocols, data management system, reader, reading enhancement, tag

Procedia PDF Downloads 298