Search results for: sensory processing patterns

Authors: Jun-Yong Lee, Hyoung-Gook Kim

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In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

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Authors: Waqas A. Toor, Anis U. Baig, Nuaman Shafqat, Raafia Irfan, Muhammad Ashraf

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A 2.45GHz microwave plasma system and its few applications have been developed. Argon and helium plasma is produced by metallic nozzle and also in a quartz tube at atmospheric pressure, using WR-340 waveguide and its tapered version. The waveguide applicator is also simulated in HFSS and field patterns are analyzed for maximum power absorption in the load. The system is tuned to operate at less than 10% reflected power. Various experimental techniques are used to initiate and sustain the plasma at atmospheric pressure. Plasma of atmospheric air is also produced without using any other shielding gas. The plasma flame is also characterized by its spectrum. Spectral analyses of plasma flame can be used for online analysis of combustion gases produced in industry. The applications of the system include glass and quartz processing, vitrification, emission spectroscopy, plasma coating. Low pressure plasma applications of the system include intense UV light for water purification and ozone generation.

Keywords: HFSS high frequency structure simulator, Microwave plasma, UV ultraviolet, WR rectangular waveguide

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Narayan Gurung, Fawu Wang, Ranjan Kumar Dahal

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Nepal is highly prone to earthquakes and has witnessed at least one major earthquake in 80 to 90 years interval. The Gorkha earthquake, that measured 7.8 RS in magnitude and struck Nepal on 25th April 2015, after 81 years since Mw 8.3 Nepal Bihar earthquake in 1934, was the largest earthquake after Mw 8.3 Nepal Bihar earthquake. In this paper, an attempt has been made to highlight the lessons learnt from the MwW 7.8 Gorkha (Nepal) earthquake. Several types of damage patterns in buildings were observed for reinforced concrete buildings, as well as for unreinforced masonry and adobe houses in the earthquake of 25 April 2015. Many field visits in the affected areas were conducted, and thus, associated failure and damage patterns were identified and analyzed. Damage patterns in non-engineered buildings, middle and high-rise buildings, commercial complexes, administrative buildings, schools and other critical facilities are also included from the affected districts. For most buildings, the construction and structural deficiencies have been identified as the major causes of failure; however, topography, local soil amplification, foundation settlement, liquefaction associated damages and buildings built in hazard-prone areas were also significantly observed for the failure or damages to buildings and hence are reported. Finally, the lessons learnt from Mw 7.8 Gorkha (Nepal) earthquake are presented in order to mitigate impacts of future earthquakes in Nepal.

Keywords: Gorkha earthquake, reinforced concrete structure, Nepal, lesson learnt

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Authors: Cecile Laval, Harriet Lowe

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Processing Instruction is a psycholinguistic pedagogical approach drawing insights from the Input Processing Model which establishes the initial innate strategies used by second language learners to connect form and meaning of linguistic features. With the ever-growing use of technology in Second Language Acquisition research, the present study uses eye-tracking to measure the effectiveness of Processing Instruction in the acquisition of French and its effects on learner’s cognitive strategies. The experiment was designed using a TOBII Pro-TX300 eye-tracker to measure participants’ default strategies when processing French linguistic input and any cognitive changes after receiving Processing Instruction treatment. Participants were drawn from lower intermediate adult learners of French at the University of Greenwich and randomly assigned to two groups. The study used a pre-test/post-test methodology. The pre-tests (one per linguistic item) were administered via the eye-tracker to both groups one week prior to instructional treatment. One group received full Processing Instruction treatment (explicit information on the grammatical item and on the processing strategies, and structured input activities) on the primary target linguistic feature (French past tense imperfective aspect). The second group received Processing Instruction treatment except the explicit information on the processing strategies. Three immediate post-tests on the three grammatical structures under investigation (French past tense imperfective aspect, French Subjunctive used for the expression of doubt, and the French causative construction with Faire) were administered with the eye-tracker. The eye-tracking data showed the positive change in learners’ processing of the French target features after instruction with improvement in the interpretation of the three linguistic features under investigation. 100% of participants in both groups made a statistically significant improvement (p=0.001) in the interpretation of the primary target feature (French past tense imperfective aspect) after treatment. 62.5% of participants made an improvement in the secondary target item (French Subjunctive used for the expression of doubt) and 37.5% of participants made an improvement in the cumulative target feature (French causative construction with Faire). Statistically there was no significant difference between the pre-test and post-test scores in the cumulative target feature; however, the variance approximately tripled between the pre-test and the post-test (3.9 pre-test and 9.6 post-test). This suggests that the treatment does not affect participants homogenously and implies a role for individual differences in the transfer-of-training effect of Processing Instruction. The use of eye-tracking provides an opportunity for the study of unconscious processing decisions made during moment-by-moment comprehension. The visual data from the eye-tracking demonstrates changes in participants’ processing strategies. Gaze plots from pre- and post-tests display participants fixation points changing from focusing on content words to focusing on the verb ending. This change in processing strategies can be clearly seen in the interpretation of sentences in both primary and secondary target features. This paper will present the research methodology, design and results of the experimental study using eye-tracking to investigate the primary effects and transfer-of-training effects of Processing Instruction. It will then provide evidence of the cognitive benefits of Processing Instruction in Second Language Acquisition and offer suggestion in second language teaching of grammar.

Keywords: eye-tracking, language teaching, processing instruction, second language acquisition

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Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

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Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

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Authors: Shepherd Manhokwe, Sheron Shoko, Cuthbert Zvidzai

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In the present study, the interactive effects of temperature and cultured bacteria on the performance of a biological treatment system of yeast processing wastewater were investigated. The main objective of this study was to investigate and optimize the operating parameters that reduce organic load and colour. Experiments were conducted based on a Central Composite Design (CCD) and analysed using Response Surface Methodology (RSM). Three dependent parameters were either directly measured or calculated as response. These parameters were total Chemical Oxygen Demand (COD) removal, colour reduction and total solids. COD removal efficiency of 26 % and decolourization efficiency of 44 % were recorded for the wastewater treatment. The optimized conditions for the biological treatment were found to be at 20 g/l cultured bacteria and 25 °C for COD reduction. For colour reduction optimum conditions were temperature of 30.35°C and bacterial formulation of 20g/l. Biological treatment of baker’s yeast processing effluent is a suitable process for the removal of organic load and colour from wastewater, especially when the operating parameters are optimized.

Keywords: COD reduction, optimisation, response surface methodology, yeast processing wastewater

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Authors: Sun H. Hwang, Young E. Lee, Yunhan Ga, Gilwon Yoon

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EEG is a very complex signal with noises and other bio-potential interferences. EOG is the most distinct interfering signal when EEG signals are measured and analyzed. It is very important how to process raw EEG signals in order to obtain useful information. In this study, the EEG signal processing techniques such as EOG filtering and outlier removal were examined to minimize unwanted EOG signals and other noises. The two different mental states of resting and focusing were examined through EEG analysis. A focused state was induced by letting subjects to watch a red dot on the white screen. EEG data for 32 healthy subjects were measured. EEG data after 60-Hz notch filtering were processed by a commercially available EOG filtering and our presented algorithm based on the removal of outliers. The ratio of beta wave to theta wave was used as a parameter for determining the degree of focusing. The results show that our algorithm was more appropriate than the existing EOG filtering.

Keywords: EEG, focus, mental state, outlier, signal processing

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Authors: Özlem Erzurumlu, Nazan Oskay, Ece Melek

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Knitting which is one of the textile manufacturing techniques is manufactured by using the system of single yarn. Knitting wares consisting of loops structurally have flexible structures. Knitting can be shaped and given volume easily due to increasing or decreasing the number of loops, being manufactured in circular form and its flexible structure. While the knitting wares are basically being manufactured to meet the requirements, it takes its place in the art field overflowing outside of industrial production later. Textile artist ensures his ideas to convert into artistic product by using textiles and non-textiles with aesthetic concerns and creative impulses. When textile crafts are observed at the present time we see that knitting technique has an extensive area of use such as sculpture, panel, installation art and performing art. It is examined how the knitting technique is used in textile crafts observing patterns obtained by this technique in textile crafts in this study.

Keywords: art, textile, knitting art, textile crafts

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Authors: Sulhee Lee, Geon Kim, Young-Seo Park

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Unlike the traditional milk sterilization methods (LTLT, HTST, or UHT), pulsed electric field (PEF) technology is a non-thermal pasteurization process. This technology minimizes energy required for heat treatment in food processing, changes in sensory properties, and physical losses. In this study, structural changes of bovine milk proteins, the amount of immunoproteins such as IgG, and their storability by PEF treatment were examined. When the changes of protein content in PEF-treated milk were examined using HPLC, the amounts of α-casein and β-lactoglobulin were reduced over 40% each, whereas those of κ-casein and β-casein did not change. The amount of α-casein in HTST milk was reduced to 50%. When PEF was applied to milk at the energy level of 250 kJ, the amounts of IgG, IgA, β-lactoglobulin (β-LG), lactoferrin, and α-lactalbumin (α-LA) decreased by 43, 41, 35, 63, and 45%, respectively. When milk was sterilized by LTLT process followed by PEF process at the level of 150 kJ, the concentrations of IgG, IgA, β-LG, lactoferrin, and α-LA were 56.6, 10.6, 554, 2.8 and 660.1 μg/mL, respectively. When the bovine milk was sterilized by LTLT process followed by PEF process at the energy level of 180 kJ, storability of immunoproteins of milk was the highest and the concentrations of IgG, IgA, and β-LG decreased by 79.5, 6.5, and 134.5 μg/mL, respectively, when compared with the initial concentrations of those proteins. When bovine milk was stored at 4℃ after sterilization through HTST sterilizer followed by PEF process at the energy level of 200 kJ, the amount of lactoferrin decreased 7.3% after 36 days of storage, whereas that of lactoferrin of raw milk decreased 16.4%. Our results showed that PEF treatment did not change the protein structure nor induce protein denaturation in milk significantly when compared with LTLT or HTST sterilization. Also, LTLT or HTST process in combination with PEF were more effective than LTLT only or HTST only process in the conservation of immunoproteins in bovine milk.

Keywords: pulsed electric field, bovine milk, immunoproteins, sterilization

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Authors: Farusil Najeeb Mullaveettil, Rolanas Dauksevicius

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Cellular structures produced by additive manufacturing have earned wide research attention due to their unique specific strength and energy absorption potentiality. The literature review concludes that pattern type and density are vital parameters that affect the mechanical properties of parts formed by additive manufacturing techniques and have an influence on printing time and material consumption. Fused deposition modeling technique (FDM) is used here to produce Polyvinylidene fluoride (PVDF) parts. In this work, patterns are based on triply periodic minimal surfaces (TPMS) produced by PVDF-based filaments using the FDM technique. PVDF homopolymer filament Fluorinar-H™ and PVDF copolymer filament Fluorinar-C™ are printed with three types of TPMS patterns. The patterns printed are Gyroid, Schwartz diamond, and Schwartz primitive. Tensile, flexural, and compression tests under quasi-static loading conditions are performed in compliance with ISO standards. The investigation elucidates the deformation mechanisms and a study that establishes a relationship between the printed and nominal specimens' dimensional accuracy. In comparison to the examined TPMS pattern, Schwartz diamond showed a higher relative elastic modulus and strength than the other patterns in tensile loading, and the Gyroid pattern showed the highest mechanical characteristics in flexural loading. The concluded results could be utilized to produce informed cellular designs for biomedical and mechanical applications.

Keywords: additive manufacturing, FDM, PVDF, gyroid, schwartz primitive, schwartz diamond, TPMS, tensile, flexural

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Oludare Olupemi Ezekiel

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This research examines the rhythmic structure of Sakara music by tracing its roots and analyzing the various rhythmic patterns of this neo-traditional genre, as well as the contributions of the major exponents and contemporary practitioners, using these as a model for understanding and establishing African rhythms. Biography of the major exponents and contemporary practitioners, interviews and participant observational methods were used to elicit information. Samples of the genre which were chosen at random were transcribed, notated and analyzed for academic use and documentation. The research affirmed that rhythms such as the Hemiola, Cross-rhythm, Clave or Bell rhythm, Percussive, Speech and Melodic rhythm and other relevant rhythmic theories were prevalent and applicable to Sakara music, while making important contributions to musical scholarship through its analysis of the music. The analysis and discussions carried out in the research pointed towards a conclusion that the Yoruba musicians are guided by some preconceptions and sound musical considerations in making their rhythmic patterns, used as compositional techniques and not mere incidental occurrence. These rhythmic patterns, with its consequential socio-cultural connotations, enhance musical values and national identity in Nigeria. The study concludes by recommending that musicologists need to carry out more research into this and other neo-traditional genres in order to advance the globalisation of African music.

Keywords: compositional techniques, globalisation, identity, neo-traditional, rhythmic theory, Sakara music

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Authors: Do-Jin Jang, Sung-Ah Kim

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A kinetic façade responds to user requirements and environmental conditions.  In designing a kinetic façade, kinetic patterns play a key role in determining its performance. This paper proposes a biomimetic method for the multi-objective optimization for kinetic façade design. The autonomous decentralized control system is combined with flocking algorithm. The flocking agents are autonomously reacting to sensor values and bring about kinetic patterns changing over time. A series of experiments were conducted to verify the potential and limitations of the flocking based decentralized control. As a result, it could show the highest performance balancing multiple objectives such as solar radiation and openness among the comparison group.

Keywords: biomimicry, flocking algorithm, autonomous decentralized control, multi-objective optimization

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Authors: Hyun-Woo Cho

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Earlier detection of incipient abnormal operations in terms of plant-wide process management is quite necessary in order to improve product quality and process safety. And generating warning signals or alarms for operating personnel plays an important role in process automation and intelligent plant health monitoring. Various methodologies have been developed and utilized in this area such as expert systems, mathematical model-based approaches, multivariate statistical approaches, and so on. This work presents a nonlinear empirical monitoring methodology based on the real-time analysis of massive process data. Unfortunately, the big data includes measurement noises and unwanted variations unrelated to true process behavior. Thus the elimination of such unnecessary patterns of the data is executed in data processing step to enhance detection speed and accuracy. The performance of the methodology was demonstrated using simulated process data. The case study showed that the detection speed and performance was improved significantly irrespective of the size and the location of abnormal events.

Keywords: detection, monitoring, process data, noise

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Authors: M. V. Manoj Kumar, Likewin Thomas, Annappa

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Process mining provides methods and techniques for analyzing event logs recorded in modern information systems that support real-world operations. While analyzing an event-log, state-of-the-art techniques available in process mining believe that the operational process as a static entity (stationary). This is not often the case due to the possibility of occurrence of a phenomenon called concept drift. During the period of execution, the process can experience concept drift and can evolve with respect to any of its associated perspectives exhibiting various patterns-of-change with a different pace. Work presented in this paper discusses the main aspects to consider while addressing concept drift phenomenon and proposes a method for detecting and localizing the sudden concept drifts in control-flow perspective of the process by using features extracted by processing the traces in the process log. Our experimental results are promising in the direction of efficiently detecting and localizing concept drift in the context of process mining research discipline.

Keywords: abrupt drift, concept drift, sudden drift, control-flow perspective, detection and localization, process mining

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8

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Authors: Miroslav Dumbrovsky, Lucie Larisova

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The infiltration characteristic of the soil surface is one of the major factors that determines the potential soil degradation risk. The physical, chemical and biological characteristic of soil is changed by the processing of soil. The infiltration soil ability has an important role in soil and water conservation. The subject of the contribution is the evaluation of the influence of the conventional tillage and reduced tillage technology on soil surface crusting processing and infiltration properties of the soil in the North Bohemia region. Field experimental work at the area was carried out in the years 2013-2016 on Cambisol district medium-heavy clayey soil. The research was conducted on sloping erosion-endangered blocks of compacted arable land. The areas were chosen each year in the way that one of the experimental areas was handled by conventional tillage technologies and the other by reduced tillage technologies. Intact soil samples were taken into Kopecký´s cylinders in the three landscape positions, at a depth of 10 cm (representing topsoil) and 30 cm (representing subsoil). The cumulative infiltration was measured using a mini-disc infiltrometer near the consumption points. The Zhang method (1997), which provides an estimate of the unsaturated hydraulic conductivity K(h), was used for the evaluation of the infiltration tests of the mini-disc infiltrometer. The soil profile processed by conventional tillage showed a higher degree of compaction and soil crusting processing. The bulk density was between 1.10–1.67 g.cm⁻³, compared to the land processed by the reduced tillage technology, where the values were between 0.80–1.29 g.cm⁻³. Unsaturated hydraulic conductivity values were about one-third higher within the reduced tillage technology soil processing.

Keywords: soil crusting processing, unsaturated hydraulic conductivity, cumulative infiltration, bulk density, porosity

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Authors: Hala Zaghloul, Taymoor Nazmy

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One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

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Authors: Van Chung Nguyen

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The purpose of this study is to study the current status of the value chain for fish distribution at Quang Binh Fishing Port with 360 research samples in which the research subjects are fishermen, traders, retailers, and businesses. The research uses the approach of applying the value chain theoretical framework of Kaplinsky and Morris to quantify and describe market channels and actors participating in the value chain and analyze the value-added process of these companies according to market channels. The analysis results show that fishermen directly catch fish with high economic efficiency, but processing enterprises and, especially retailers, are the agents to obtain higher added value. Processing enterprises play a role that is not really clear due to outdated processing technology; in contrast, retailers have the highest added value. This shows that the added value of the fish supply chain at Quang Binh fishing port is still limited, leading to low output quality. Therefore, the selling price of fish to the market is still high compared to the abundant fish resources, leading to low consumption and limiting exports due to the quality of processing enterprises. This reduces demand and fishing capacity, and productivity is lower than potential. To improve the fish value chain at fishing ports, it is necessary to focus on improving product quality, strengthening linkages between actors, building brands and product consumption markets at the same time, improving the capacity of export processing enterprises.

Keywords: Quang Binh fishing port, value chain, market, distributions channel

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Authors: Ghaleb Y. Abbasi, Israa Abu Rumman

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This paper modeled sales history archived from 2012 to 2015 bulked in monthly bins for five products for a medical supply company in Jordan. The sales forecasts and extracted consistent patterns in the sales demand history from the Enterprise Resource Planning (ERP) system were used to predict future forecasting and generate sales demand forecasting using time series analysis statistical technique called Auto Regressive Integrated Moving Average (ARIMA). This was used to model and estimate realistic sales demand patterns and predict future forecasting to decide the best models for five products. Analysis revealed that the current replenishment system indicated inventory overstocking.

Keywords: ARIMA models, sales demand forecasting, time series, R code

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Authors: Mamdouh Omran, Timo Fabritius

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A growing interest in microwave heating has emerged recently. Many researchers have begun to pay attention to microwave energy as an alternative technique for processing various primary and secondary raw materials. Compared to conventional methods, microwave processing offers several advantages, such as selective heating, rapid heating, and volumetric heating. The present study gives a summary on our recent works related to the use of microwave energy for the recovery of valuable metals from primary and secondary raw materials. The research is mainly focusing on: Application of microwave for the recovery and recycling of metals from different metallurgical industries wastes (i.e. electric arc furnace (EAF) dust, blast furnace (BF), basic oxygen furnace (BOF) sludge). Application of microwave for upgrading and recovery of valuable metals from primary raw materials (i.e. iron ore). The results indicated that microwave heating is a promising and effective technique for processing primary and secondary steelmaking wastes. After microwave treatment of iron ore for 60 s and 900 W, about a 28.30% increase in grindability.Wet high intensity magnetic separation (WHIMS) indicated that the magnetic separation increased from 34% to 98% after microwave treatment for 90 s and 900 W. In the case of EAF dust, after microwave processing at 1100 W for 20 min, Zinc removal from 64 % to ~ 97 %, depending on mixture ratio and treatment time.

Keywords: dielectric properties, microwave heating, raw materials, secondary raw materials

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Authors: Homa Ghave, Parmis Shahmaleki

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This paper presents a new multi-criteria stochastic mathematical model for a single machine scheduling with outsourcing allowed. There are multiple jobs processing in batch. For each batch, all of job or a quantity of it can be outsourced. The jobs have stochastic processing time and lead time and deterministic due dates arrive randomly. Because of the stochastic inherent of processing time and lead time, we use the chance constrained programming for modeling the problem. First, the problem is formulated in form of stochastic programming and then prepared in a form of deterministic mixed integer linear programming. The objectives are considered in the model to minimize the maximum tardiness and outsourcing cost simultaneously. Several procedures have been developed to deal with the multi-criteria problem. In this paper, we utilize the concept of satisfaction functions to increases the manager’s preference. The proposed approach is tested on instances where the random variables are normally distributed.

Keywords: single machine scheduling, multi-criteria mathematical model, outsourcing strategy, uncertain lead times and processing times, chance constrained programming, satisfaction function

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Authors: Dalya M. Hassan

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Marketplaces and commercial streets represent some of the most used and lively urban public spaces. Not only do they provide an outlet for commercial exchange, but they also facilitate social and recreational encounters. Such encounters can be influenced by both formal as well as informal vending activities. This paper explores and documents forms of informal vending practices and how they relate to social patterns that occur along the sidewalks of Commercial Streets in Cairo. A qualitative single case study approach of ‘Midan El Gami’ marketplace in Heliopolis, Cairo is adopted. The methodology applied includes direct and walk-by observations for two main commercial streets in the marketplace. Four zoomed-in activity maps are also done for three sidewalk segments that displayed varying vending and social features. Main findings include a documentation and classification of types of informal vending practices as well as a documentation of vendors’ distribution patterns in the urban space. Informal vending activities mainly included informal street vendors and shop spillovers, either as product or seating spillovers. Results indicated that staying and lingering activities were more prevalent in sidewalks that had certain physical features, such as diversity of shops, shaded areas, open frontages, and product or seating spillovers. Moreover, differences in social activity patterns were noted between sidewalks with street vendors and sidewalks with spillovers. While the first displayed more buying, selling, and people watching activities, the latter displayed more social relations and bonds amongst traders’ communities and café patrons. Ultimately, this paper provides a documentation, which suggests that informal vending can have a positive influence on creating a lively commercial street and on resulting patterns of use on the sidewalk space. The results can provide a basis for further investigations and analysis concerning this topic. This could aid in better accommodating informal vending activities within the design of future commercial streets.

Keywords: commercial streets, informal vending practices, sidewalks, social encounters

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Authors: Yili Chen, Jixiang Fu, Zhihua Liu, Zhicheng Zhang, Rongmao Li, Nan Fu, Yaoqin Xie

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Retinal prothesis is designed to help the blind to get some sight.It is made up of internal part and external part.In external part ,there is made up of camera, image processing, and RF transmitter.In internal part, there is RF receiver, implant chip,micro-electrode.The image got from the camera should be processed by suitable stragies to corresponds to stimulus the electrode.Nowadays, the number of the micro-electrode is hundreds and we don’t know the mechanism how the elctrode stimulus the optic nerve, an easy way to the hypothesis is that the pixel in the image is correspondence to the electrode.So it is a question how to get the important information of the image captured from the picture.There are many strategies to experimented to get the most important information as soon as possible, due to the real time system.ROI is a useful algorithem to extract the region of the interest.Our paper will explain the details of the orinciples and functions of the ROI.And based on this, we simplified the ROI algrithem,and used it in outside image prcessing DSP system of the retinal prothesis.Results show that our image processing stratiges is suitable for real-time retinal prothesis and can cut redundant information and help useful information to express in the low-size image.

Keywords: image processing, region of interest, saliency map, low-size image, useful information express, cut redundant information in image

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Authors: J. Hash, J. Converse, L. Gibson

Abstract:

Plant medicines are of growing interest for addressing mental health concerns. Ayahuasca, a traditional plant-based medicine, has established itself as a powerful way of processing trauma and precipitating healing and mood stabilization. Eye Movement Desensitization and Reprocessing (EMDR) is another treatment modality that aids in the rapid processing and resolution of trauma. We investigated group EMDR therapy, G-TEP, as a preparatory practice before Ayahuasca ceremonies to determine if the combination of these modalities supports participants in their journeys of letting go of past experiences negatively impacting mental health, thereby accentuating the healing of the plant medicine. We surveyed 96 participants (51 experimental G-TEP, 45 control grounding prior to their ceremony; age M=38.6, SD=9.1; F=57, M=34; white=39, Hispanic/Latinx=23, multiracial=11, Asian/Pacific Islander=10, other=7) in a pre-post, mixed methods design. Participants were surveyed for demographic characteristics, symptoms of PTSD and cPTSD (International Trauma Questionnaire (ITQ), depression (Beck Depression Inventory, BDI), and stress (Perceived Stress Scale, PSS) before the ceremony and at the end of the ceremony weekend. Open-ended questions also inquired about their expectations of the ceremony and results at the end. No baseline differences existed between the control and experimental participants. Overall, participants reported a decrease in meeting the threshold for PTSD symptoms (p<0.01); surprisingly, the control group reported significantly fewer thresholds met for symptoms of affective dysregulation, 2(1)=6.776, p<.01, negative self-concept, 2 (1)=7.122, p<.01, and disturbance in relationships, 2 (1)=9.804, p<.01, on subscales of the ITQ as compared to the experimental group. All participants also experienced a significant decrease in scores on the BDI, t(94)=8.995, p<.001, and PSS, t(91)=6.892, p<.001. Similar to patterns of PTSD symptoms, the control group reported significantly lower scores on the BDI, t(65.115)=-2.587, p<.01, and a trend toward lower PSS, t(90)=-1.775, p=.079 (this was significant with a one-sided test at p<.05), compared to the experimental group following the ceremony. Qualitative interviews among participants revealed a potential explanation for these relatively higher levels of depression and stress in the experimental group following the ceremony. Many participants reported needing more time to process their experience to gain an understanding of the effects of the Ayahuasca medicine. Others reported a sense of hopefulness and understanding of the sources of their trauma and the necessary steps to heal moving forward. This suggests increased introspection and openness to processing trauma, therefore making them more receptive to their emotions. The integration process of an Ayahuasca ceremony is a week- to months-long process that was not accessible in this stage of research, yet it is an integral process to understanding the full effects of the Ayahuasca medicine following the closure of a ceremony. Our future research aims to assess participants weeks into their integration process to determine the effectiveness of EMDR, and if the higher levels of depression and stress indicate the initial reaction to greater awareness of trauma and receptivity to healing.

Keywords: ayahuasca, EMDR, PTSD, mental health

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Authors: Farnaz Fotovvatikhah, Javad Akbari

Abstract:

Test time of a test architecture is an important factor which depends on the architecture's delay and test patterns. Here a new architecture to store the test results based on network on chip is presented. In addition, simple analytical model is proposed to calculate link test time for built in self-tester (BIST) and external tester (Ext) in multiprocessor systems. The results extracted from the model are verified using FPGA implementation and experimental measurements. Systems consisting 16, 25, and 36 processors are implemented and simulated and test time is calculated. In addition, BIST and Ext are compared in terms of test time at different conditions such as at different number of test patterns and nodes. Using the model the maximum frequency of testing could be calculated and the test structure could be optimized for high speed testing.

Keywords: test, nano on-chip network, JTAG, modelling

Procedia PDF Downloads 478

Authors: Sadiq J. Abou-Loukh, Hanan M. Habbi

Abstract:

This paper presents a steganography to hide the transmitted information without excite suspicious and also illustrates the level of secrecy that can be increased by using cryptography techniques. The proposed system has been implemented firstly by encrypted image file one time pad key and secondly encrypted message that hidden to perform encryption followed by image embedding. Then the new image file will be created from the original image by using four triangles operation, the new image is processed by one of two image processing techniques. The proposed two processing techniques are thresholding and differential predictive coding (DPC). Afterwards, encryption or decryption keys are generated by functional key generator. The generator key is used one time only. Encrypted text will be hidden in the places that are not used for image processing and key generation system has high embedding rate (0.1875 character/pixel) for true color image (24 bit depth).

Keywords: encryption, thresholding, differential predictive coding, four triangles operation

Procedia PDF Downloads 483

Authors: Youssef Chahir, Messaoud Mostefai, Salah Khodja

Abstract:

This paper presents the development of a 2D visual marker, derived from a recent patented work in the field of numbering systems. The proposed fiducial uses a group of projective invariant straight-line patterns, easily detectable and remotely recognizable. Based on an efficient data coding scheme, the developed marker enables producing a large panel of unique real time identifiers with highly distinguishable patterns. The proposed marker Incorporates simultaneously decimal and binary information, making it readable by both humans and machines. This important feature opens up new opportunities for the development of efficient visual human-machine communication and monitoring protocols. Extensive experiment tests validate the robustness of the marker against acquisition and geometric distortions.

Keywords: visual markers, projective invariants, distance map, level sets

Procedia PDF Downloads 153

Authors: Samane Sharifi Monfared, Lavdie Rada

Abstract:

Nowadays, autonomous vehicles are developing rapidly toward facilitating human car driving. One of the main issues is road lane detection for a suitable guidance direction and car accident prevention. This paper aims to improve and optimize road line detection based on a combination of camera calibration, the Hough transform, and Canny edge detection. The video processing is implemented using the Open CV library with the novelty of having a scale able region masking. The aim of the study is to introduce automatic road lane detection techniques with the user’s minimum manual intervention.

Keywords: hough transform, canny edge detection, optimisation, scaleable masking, camera calibration, improving the quality of image, image processing, video processing

Procedia PDF Downloads 81