Search results for: array signal processing

Authors: Eyob Messele Sefene, Atinkut Atinafu Yilma

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The highest strength-to-weight ratio criterion has fascinated increasing curiosity in virtually all areas where weight reduction is indispensable. One of the recent advances in manufacturing to achieve this intention endears friction stir welding (FSW). The process is widely used for joining similar and dissimilar non-ferrous materials. In FSW, the mechanical properties of the weld joints are impelled by property-selected process parameters. This paper presents verdicts of optimum process parameters in attempting to attain enhanced mechanical properties of the weld joint. The experiment was conducted on a 5 mm 6061 aluminum alloy sheet. A butt joint configuration was employed. Process parameters, rotational speed, traverse speed or feed rate, axial force, dwell time, tool material and tool profiles were utilized. Process parameters were also optimized, making use of a mixed L18 orthogonal array and the Grey relation analysis method with larger is better quality characteristics. The mechanical properties of the weld joint are examined through the tensile test, hardness test and liquid penetrant test at ambient temperature. ANOVA was conducted in order to investigate the significant process parameters. This research shows that dwell time, rotational speed, tool shape, and traverse speed have become significant, with a joint efficiency of about 82.58%. Nine confirmatory tests are conducted, and the results indicate that the average values of the grey relational grade fall within the 99% confidence interval. Hence the experiment is proven reliable.

Keywords: friction stir welding, optimization, 6061 AA, Taguchi

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Authors: Hafdaoui Hichem, Mehadjebia Cherifa, Benatia Djamel

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In this paper, we propose a new method for Bulk detection of an acoustic microwave signal during the propagation of acoustic microwaves in a piezoelectric substrate (Lithium Niobate LiNbO3). We have used the classification by probabilistic neural network (PNN) as a means of numerical analysis in which we classify all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity in order to build a model from which we note the Bulk waves easily. These singularities inform us of presence of Bulk waves in piezoelectric materials. By which we obtain accurate values for each of the coefficient attenuation and acoustic velocity for Bulk waves. This study will be very interesting in modeling and realization of acoustic microwaves devices (ultrasound) based on the propagation of acoustic microwaves.

Keywords: piezoelectric material, probabilistic neural network (PNN), classification, acoustic microwaves, bulk waves, the attenuation coefficient

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Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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Authors: Reji Thankachan, Varsha PS

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Both image capturing devices and human visual systems are nonlinear. Hence nonlinear filtering methods outperforms its linear counterpart in many applications. Linear methods are unable to remove impulsive noise in images by preserving its edges and fine details. In addition, linear algorithms are unable to remove signal dependent or multiplicative noise in images. This paper presents an approach to denoise and smoothen the Bipolar impulse noised images and videos using improved Kuwahara filter. It involves a 2 stage algorithm which includes a noise detection followed by filtering. Numerous simulation demonstrate that proposed method outperforms the existing method by eliminating the painting like flattening effect along the local feature direction while preserving edge with improvement in PSNR and MSE.

Keywords: bipolar impulse noise, Kuwahara, PSNR MSE, PDF

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Authors: Phong Nguyen, Phap Nguyen, Thang Nguyen

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High Efficiency Video Coding (HEVC) or H.265 Standard fulfills the demand of high resolution video storage and transmission since it achieves high compression ratio. However, it requires a huge amount of calculation. Since Motion Estimation (ME) block composes about 80 % of calculation load of HEVC, there are a lot of researches to reduce the computation cost. In this paper, we propose a new algorithm to lower the number of Motion Estimation’s searching points. The number of computing points in search pattern is down from 77 for Diamond Pattern and 81 for Square Pattern to only 31. Meanwhile, the Peak Signal to Noise Ratio (PSNR) and bit rate are almost equal to those of conventional patterns. The motion estimation time of new algorithm reduces by at 68.23%, 65.83%compared to the recommended search pattern of diamond pattern, square pattern, respectively.

Keywords: motion estimation, wide diamond, search pattern, H.265, test zone search, HM software

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Authors: Hechmi Saidi, Noureddine Hamdi

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The performance of decode and forward (DF) multihop free space optical (FSO) scheme deploying multiple input multiple output (MIMO) configuration under gamma-gamma (GG) statistical distribution, that adopts M-ary pulse position modulation (MPPM) coding, is investigated. We have extracted exact and estimated values of symbol-error rates (SERs) respectively. The probability density function (PDF)’s closed-form formula is expressed for our designed system. Thanks to the use of DF multihop MIMO FSO configuration and MPPM signaling, atmospheric turbulence is combatted; hence the transmitted signal quality is improved.

Keywords: free space optical, gamma gamma channel, radio frequency, decode and forward, multiple-input multiple-output, M-ary pulse position modulation, symbol error rate

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Authors: Preetham Shankapal, Jill King, Kori Murray, Corby Martin, Paula Giselman, Jason Hicks, Owen Carmicheal

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Activation of reward and satiety networks in the brain while processing palatable food cues, as well as functional connectivity during rest has been studied using functional Magnetic Resonance Imaging of the brain in various obesity phenotypes. However, functional connectivity within the reward and satiety network during food cue processing is understudied. 14 obese individuals underwent two fMRI scans during viewing of Macronutrient Picture System images. Each scan included two blocks of images of High Sugar/High Fat (HSHF), High Carbohydrate/High Fat (HCHF), Low Sugar/Low Fat (LSLF) and also non-food images. Seed voxels within seven food reward relevant ROIs: Insula, putamen and cingulate, precentral, parahippocampal, medial frontal and superior temporal gyri were isolated based on a prior meta-analysis. Beta series correlation for task-related functional connectivity between these seed voxels and the rest of the brain was computed. Voxel-level differences in functional connectivity were calculated between: first and the second scan; individuals who saw novel (N=7) vs. Repeated (N=7) images in the second scan; and between the HC/HF, HSHF blocks vs LSLF and non-food blocks. Computations and analysis showed that during food image viewing, reward network ROIs showed significant functional connectivity with each other and with other regions responsible for attentional and motor control, including inferior parietal lobe and precentral gyrus. These functional connectivity values were heightened among individuals who viewed novel HS/HF images in the second scan. In the second scan session, functional connectivity was reduced within the reward network but increased within attention, memory and recognition regions, suggesting habituation to reward properties and increased recollection of previously viewed images. In conclusion it can be inferred that Functional Connectivity within reward network and between reward and other brain regions, varies by important experimental conditions during food photography viewing, including habituation to shown foods.

Keywords: fMRI, functional connectivity, task-based, beta series correlation

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Authors: Salman Naveed, Nitant Gandhi, Grant Billings, Zachary Jones, B. Todd Campbell, Michael Jones, Sachin Rustgi

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Cotton (Gossypium spp.) is the primary source of natural fiber in the U.S. and a major crop in the Southeastern U.S. Despite constant efforts to increase the cotton fiber yield, the yield gain has stagnated. Therefore, we undertook a novel approach to improve the cotton fiber yield by altering its growth habit from perennial to annual. In this effort, we identified genotypes with high-expression alleles of five floral induction and meristem identity genes (FT, SOC1, FUL, LFY, and AP1) from an upland cotton mini-core collection and crossed them in various combinations to develop cotton lines with annual growth habit, optimal flowering time and enhanced productivity. To facilitate the characterization of genotypes with the desired combinations of stacked alleles, we identified markers associated with the gene expression traits via genome-wide association analysis using a 63K SNP Array (Hulse-Kemp et al. 2015 G3 5:1187). Over 14,500 SNPs showed polymorphism and were used for association analysis. A total of 396 markers showed association with expression traits. Out of these 396 markers, 159 mapped to genes, 50 to untranslated regions, and 187 to random genomic regions. Biased genomic distribution of associated markers was observed where more trait-associated markers mapped to the cotton D sub-genome. Many quantitative trait loci coincided at specific genomic regions. This observation has implications as these traits could be bred together. The analysis also allowed the identification of candidate regulators of the expression patterns of these floral induction and meristem identity genes whose functions will be validated via virus-induced gene silencing.

Keywords: cotton, GWAS, QTL, expression traits

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Authors: Reza Rezaeipour Honarmandzad

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In this paper we propose an ANN for detection and localization of fatigue damage in aircraft structures. We used network of piezoelectric transducers for Lamb-wave measurements in order to calculate damage indices. Data gathered by the sensors was given to neural network classifier. A set of neural network electors of different architecture cooperates to achieve consensus concerning the state of each monitored path. Sensed signal variations in the ROI, detected by the networks at each path, were used to assess the state of the structure as well as to localize detected damage and to filter out ambient changes. The classifier has been extensively tested on large data sets acquired in the tests of specimens with artificially introduced notches as well as the results of numerous fatigue experiments. Effect of the classifier structure and test data used for training on the results was evaluated.

Keywords: ANN, fatigue damage, aircraft structures, piezoelectric transducers, lamb-wave measurements

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Authors: Mayoorika Shukla, Pramila Jakhar, Tejendra Dixit, I. A. Palani, Vipul Singh

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Biosensors are analytical devices with wide range of applications in biological, chemical, environmental and clinical analysis. It comprises of bio-recognition layer which has biomolecules (enzymes, antibodies, DNA, etc.) immobilized over it for detection of analyte and transducer which converts the biological signal into the electrical signal. The performance of biosensor primarily the depends on the bio-recognition layer and therefore it has to be chosen wisely. In this regard, nanostructures of metal oxides such as ZnO, SnO2, V2O5, and TiO2, etc. have been explored extensively as bio-recognition layer. Recently, ZnO has the attracted attention of researchers due to its unique properties like high iso-electric point, biocompatibility, stability, high electron mobility and high electron binding energy, etc. Although there have been many reports on usage of ZnO as bio-recognition layer but to the authors’ knowledge, none has ever observed correlation between optical properties like defect suppression and biosensing capability of the sensor. Here, ZnO nanorods (ZNR) have been synthesized by a low cost, simple and low-temperature hydrothermal growth process, over Platinum (Pt) coated glass substrate. The ZNR have been synthesized in two steps viz. initially a seed layer was coated over substrate (Pt coated glass) followed by immersion of it into nutrient solution of Zinc nitrate and Hexamethylenetetramine (HMTA) with in situ addition of KMnO4. The addition of KMnO4 was observed to have a profound effect over the growth rate anisotropy of ZnO nanostructures. Clustered and powdery growth of ZnO was observed without addition of KMnO4, although by addition of it during the growth, uniform and crystalline ZNR were found to be grown over the substrate. Moreover, the same has resulted in suppression of defects as observed by Normalized Photoluminescence (PL) spectra since KMnO4 is a strong oxidizing agent which provides an oxygen rich growth environment. Further, to explore the correlation between defect suppression and biosensing capability of the ZNR Glucose oxidase (Gox) was immobilized over it, using physical adsorption technique followed by drop casting of nafion. Here the main objective of the work was to analyze effect of defect suppression over biosensing capability, and therefore Gox has been chosen as model enzyme, and electrochemical amperometric glucose detection was performed. The incorporation of KMnO4 during growth has resulted in variation of optical and charge transfer properties of ZNR which in turn were observed to have deep impact on biosensor figure of merits. The sensitivity of biosensor was found to increase by 12-18 times, due to variations introduced by addition of KMnO4 during growth. The amperometric detection of glucose in continuously stirred buffer solution was performed. Interestingly, defect suppression has been observed to contribute towards the improvement of biosensor performance. The detailed mechanism of growth of ZNR along with the overall influence of defect suppression on the sensing capabilities of the resulting enzymatic electrochemical biosensor and different figure of merits of the biosensor (Glass/Pt/ZNR/Gox/Nafion) will be discussed during the conference.

Keywords: biosensors, defects, KMnO4, ZnO nanorods

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Authors: Won Jung

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In automotive, propeller shaft is the device for transferring power from engine to axle via transmission, and the slip yoke is one of the main parts in the component. Since the propeller shafts are subject to torsion and shear stress, they need to be strong enough to bear the stress. The purpose of this research is to improve the productivity of slip yoke for automotive propeller shaft. We present how to redesign the component that currently manufactured as a forged single body type. The research was focused on not only reducing processing time but insuring durability of the component simultaneously.

Keywords: automotive, propeller shaft, productivity, durability, slip yoke

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Authors: Veronika Sharok

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Research relevance on psychological determinants of risky behaviors is caused by high prevalence of such behaviors, particularly among youth. Risky sexual behavior, including unprotected and casual sex, frequent change of sexual partners, drug and alcohol use lead to negative social consequences and contribute to the spread of HIV infection and other sexually transmitted diseases. Data were obtained from 302 respondents aged 15-35 which were divided into 3 empirical groups: persons prone to risky sexual behavior, drug users and alcohol users; and 3 control groups: the individuals who are not prone to risky sexual behavior, persons who do not use drugs and the respondents who do not use alcohol. For processing, we used the following methods: Qualitative method for nominative data (Chi-squared test) and quantitative methods for metric data (student's t-test, Fisher's F-test, Pearson's r correlation test). Statistical processing was performed using Statistica 6.0 software. The study identifies two groups of factors that prevent risky behaviors. Internal factors, which include the moral and value attitudes; significance of existential values: love, life, self-actualization and search for the meaning of life; understanding independence as a responsibility for the freedom and ability to get attached to someone or something up to a point when this relationship starts restricting the freedom and becomes vital; awareness of risky behaviors as dangerous for the person and for others; self-acknowledgement. External factors (prevent risky behaviors in case of absence of the internal ones): absence of risky behaviors among friends and relatives; socio-demographic characteristics (middle class, marital status); awareness about the negative consequences of risky behaviors; inaccessibility to psychoactive substances. These factors are common for proneness to each type of risky behavior, because it usually caused by the same reasons. It should be noted that if prevention of risky behavior is based only on elimination of external factors, it is not as effective as it may be if we pay more attention to internal factors. The results obtained in the study can be used to develop training programs and activities for prevention of risky behaviors, for using values preventing such behaviors and promoting healthy lifestyle.

Keywords: existential values, prevention, psychological features, risky behavior

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Authors: Frederick Anlimah, Vinod Gopaldasani, Catherine MacPhail, Brian Davies

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The construction industry, particularly tunnel construction, exposes workers to respirable crystalline silica (RCS), which can cause incurable illnesses such as silicosis and lung cancer. Despite various control measures, exposures remain inadequately controlled. This research aimed to identify the barriers and challenges hindering the implementation of effective controls and the adoption of safe work practices to protect workers from RCS exposure in tunnelling. A mixed-method approach was employed for this research. Tunnel construction workers were observed, surveyed and interviewed to gauge their knowledge and attitudes and understand their challenges in reducing RCS exposure. The preliminary analysis of the data reveals a diverse array of sociotechnical factors interacting to influence RCS exposure. It is noteworthy that participants consistently emphasised the project as the most exemplary one they have been involved in, although there is room for improvement. While there is a commendable level of knowledge about RCS exposure and control in tunnelling, there is a striking lack of perceived satisfaction regarding dust control. Several factors were identified as interacting to prevent the effective management of dust. These include perceived time pressure, absence of on-tool dust controls, low risk perceptions among workers, and inadequate enforcement of controls. Moreover, participants highlighted communication and heat-related challenges as hindrances to the continuous wear of respirators. This research highlights the need for a paradigm shift in tunnel construction to address the barriers associated with RCS exposure reduction. It emphasises the importance of collaboration among various stakeholders, advocating for more effective controls and enforcement strategies and enhanced worker education through knowledge sharing.

Keywords: respirable crystalline silica, dust control, worker practices, exposure prevention, silicosis

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Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha

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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Keywords: TDNN, neural networks, noise, speech recognition

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Authors: Koichi Kurita

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In this study, we propose a real-time data collection technique for the detection of human walking motion from the charge generated on the human body. This technique is based on the detection of a sub-picoampere electrostatic induction current, generated by the motion, flowing through the electrode of a wireless portable sensor attached to the subject. An FFT analysis of the wave-forms of the electrostatic induction currents generated by the walking motions showed that the currents generated under normal and restricted walking conditions were different. Moreover, we carried out a cepstrum analysis to detect any differences in the walking style. Results suggest that a slight difference in motion, either due to the individual’s gait or a splinted leg, is directly reflected in the electrostatic induction current generated by the walking motion. The proposed wireless portable sensor enables the detection of even subtle differences in walking motion.

Keywords: human walking motion, motion measurement, current measurement, electrostatic induction

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Robert Lenzie

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Transcranial electrical stimulation (tES) is significant in the research literature. However, the effects of tES on brain activity are still poorly understood at the surface level, the Brodmann Area level, and the impact on neural networks. Using a method like electroencephalography (EEG) in conjunction with tES might make it possible to comprehend the brain response and mechanisms behind published observed alterations in more depth. Using a method to directly see the effect of tES on EEG may offer high temporal resolution data on the brain activity changes/modulations brought on by tES that correlate to various processing stages within the brain. This paper provides unpublished information on a cutting-edge methodology that may reveal details about the dynamics of how the human brain works beyond what is now achievable with existing methods.

Keywords: tACS, frequency, EEG, optimal

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Authors: Javad Yarmahmoudi, Alireza Mirzaee

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Many active and passive structural health monitoring (SHM) techniques have been developed for detection of the defects of plates. Generally, riveted joints hold the plates together and their failure may create accidents. In this study, well known active and passive methods were modified for the evaluation of the health of the riveted joints between the plates. The active method generated Lamb waves and monitored their propagation by using lead zirconate titanate (PZT) disks. The signal was analyzed by using the wavelet transformations. The passive method used the Fiber Bragg Grating (FBG) sensors and evaluated the spectral characteristics of the signals by using Fast Fourier Transformation (FFT). The results indicated that the existing methods designed for the evaluation of the health of individual plates may be used for inspection of riveted joints with software modifications.

Keywords: structural health monitoring, SHM, active SHM, passive SHM, fiber bragg grating sensor, lead zirconate titanate, PZT

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Authors: Attaullah Khawaja, Amna Shabbir

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Channel inversion is one of the simplest techniques for multiuser downlink systems with single-antenna users. In this paper regularized channel inversion under equal power constraint in the multiuser multiple input multiple output (MU-MIMO) broadcast channels has been considered. Sum capacity with plain channel inversion also known as Zero Forcing Beam Forming (ZFBF) and optimum sum capacity using Dirty Paper Coding (DPC) has also been investigated. Analysis and simulations show that regularization enhances the system performance and empower linear growth in Sum Capacity and specially work well at low signal to noise ratio (SNRs) regime.

Keywords: broadcast channel, channel inversion, multiple antenna multiple-user wireless, multiple-input multiple-output (MIMO), regularization, dirty paper coding (DPC), sum capacity

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Authors: Thomas Vlasak, Tanja Dujlociv, Alfred Barth

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Shift work is an essential element of modern labor, ensuring ideal conditions of service for today’s economy and society. Despite the beneficial properties, its impact on the neurobehavioral performance of exposed subjects remains controversial. This meta-analysis aims to provide first summarizing the effects regarding the association between shift work exposure and different cognitive functions. A literature search was performed via the databases PubMed, PsyINFO, PsyARTICLES, MedLine, PsycNET and Scopus including eligible studies until December 2020 that compared shift workers with non-shift workers regarding neurobehavioral performance tests. A random-effects model was carried out using Hedge’s g as a meta-analytical effect size with a restricted likelihood estimator to summarize the mean differences between the exposure group and controls. The heterogeneity of effect sizes was addressed by a sensitivity analysis using funnel plots, egger’s tests, p-curve analysis, meta-regressions, and subgroup analysis. The meta-analysis included 18 studies resulting in a total sample of 18,802 participants and 37 effect sizes concerning six different neurobehavioral outcomes. The results showed significantly worse performance in shift workers compared to non-shift workers in the following cognitive functions with g (95% CI): processing speed 0.16 (0.02 - 0.30), working memory 0.28 (0.51 - 0.50), psychomotor vigilance 0.21 (0.05 - 0.37), cognitive control 0.86 (0.45 - 1.27) and visual attention 0.19 (0.11 - 0.26). Neither significant moderating effects of publication year or study quality nor significant subgroup differences regarding type of shift or type of profession were indicated for the cognitive outcomes. These are the first meta-analytical findings that associate shift work with decreased cognitive performance in processing speed, working memory, psychomotor vigilance, cognitive control, and visual attention. Further studies should focus on a more homogenous measurement of cognitive functions, a precise assessment of experience of shift work and occupation types which are underrepresented in the current literature (e.g., law enforcement). In occupations where shift work is fundamental (e.g., healthcare, industries, law enforcement), protective countermeasures should be promoted for workers.

Keywords: meta-analysis, neurobehavioral performance, occupational psychology, shift work

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Authors: G. Yakubova, A. Kavetskiy, S. A. Prior, H. A. Torbert

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In-situ soil carbon determination over large soil surface areas (several hectares) is required in regard to carbon sequestration and carbon credit issues. This capability is important for optimizing modern agricultural practices and enhancing soil science knowledge. Collecting and processing representative field soil cores for traditional laboratory chemical analysis is labor-intensive and time-consuming. The neutron-stimulated gamma analysis method can be used for in-situ measurements of primary elements in agricultural soils (e.g., Si, Al, O, C, Fe, and H). This non-destructive method can assess several elements in large soil volumes with no need for sample preparation. Neutron-gamma soil elemental analysis utilizes gamma rays issued from different neutron-nuclei interactions. This process has become possible due to the availability of commercial portable pulse neutron generators, high-efficiency gamma detectors, reliable electronics, and measurement/data processing software complimented by advances in state-of-the-art nuclear physics methods. In Pulsed Fast Thermal Neutron Analysis (PFTNA), soil irradiation is accomplished using a pulsed neutron flux, and gamma spectra acquisition occurs both during and between pulses. This method allows the inelastic neutron scattering (INS) gamma spectrum to be separated from the thermal neutron capture (TNC) spectrum. Based on PFTNA, a mobile system for field-scale soil elemental determinations (primarily carbon) was developed and constructed. Our scanning methodology acquires data that can be directly used for creating soil elemental distribution maps (based on ArcGIS software) in a reasonable timeframe (~20-30 hectares per working day). Created maps are suitable for both agricultural purposes and carbon sequestration estimates. The measurement system design, spectra acquisition process, strategy for acquiring field-scale carbon content data, and mapping of agricultural fields will be discussed.

Keywords: neutron gamma analysis, soil elemental content, carbon sequestration, carbon credit, soil gamma spectroscopy, portable neutron generators, ArcMap mapping

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Authors: S. Hellam, Y. Oulahrir, F. El Mounchid, A. Sadiq, S. Mbarki

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In this paper, we propose a method for three-dimensional (3-D)-model indexing based on defining a new descriptor, which we call new descriptor using spherical harmonics. The purpose of the method is to minimize, the processing time on the database of objects models and the searching time of similar objects to request object. Firstly we start by defining the new descriptor using a new division of 3-D object in a sphere. Then we define a new distance which will be used in the search for similar objects in the database.

Keywords: 3D indexation, spherical harmonic, similarity of 3D objects, measurement similarity

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Authors: Zeineb Yousse, Fakher Kharrat

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Mosaic is a part of a broad universal cultural heritage; sometimes it represents a rather essential source for the researches on the everyday life of some of the previous civilizations. Tunisia has one of the finest and largest collections of mosaics in the world, which is essentially exhibited in the Museums of Bardo and Sousse. Restored and reconstituted, they bear witnesses to hard work. Our paper deals with the discipline of conservation of Roman mosaics based on the proceedings of the workshop of the Museum of Sousse. Thus, we highlight two main objectives. In the first place, it is a question of revealing the techniques adopted by professionals to handle mosaics and to which school of conservation these techniques belong. In the second place, we are going to interpret the works initiated to preserve the archaeological heritage in order to protect it in present time and transmit it to future generations. To this end, we paid attention to four Roman mosaics currently exhibited in the Museum of Sousse. These Mosaics show different voids or gaps at the level of their surfaces and the method used to fill these gaps seems to be interesting to analyze. These mosaics are known under the names of: Orpheus Charming the Animals, Gladiator and Bears, Stud farm of Sorothus and finally Head of Medusa. The study on the conservation passes through two chained phases. We start with a small historical overview in order to gather information related to the original location, the date of its composition as well as the description of its image. Afterward, the intervention process is analyzed by handling three complementary elements which are: diagnosis of the existing state, the study of the medium processing and the study of the processing of the tesselatum surface which includes the pictorial composition of the mosaic. Furthermore, we have implemented an evaluation matrix with six operating principles allowing the assessment of the appropriateness of the intervention. These principles are the following: minimal intervention, reversibility, compatibility, visibility, durability, authenticity and enhancement. Various accumulated outcomes are pointing out the techniques used to fill the gaps as well as the level of compliance with the principles of conservation. Accordingly, the conservation of mosaics in Tunisia is a practice that combines various techniques without really arguing about the choice of a particular theory.

Keywords: conservation, matrix, museum of Sousse, operating particular theory, principles, Roman mosaics

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Authors: Po-Chin Liang, Yung-Chu Chen, Chi-Feng Chiang, Yun-Ping Lin, Wen-Yuan Hsieh, Win-Li Lin

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The aim of this study was to develop super paramagnetic iron oxide (SPIO) nano-particles comprised of a magnetic Fe3O4 core and a shell of aqueous stable self-doped polyethylene glycol (PEG) with a high loading of doxorubicin (SPIO-PEG-D) for tumor theranostics. The in-vivo MRI study showed that there was a stronger T2-weighted signal enhancement for the group under a magnetic field, and hence it indicated that this group had a better accumulation of SPIO-PEG than the group without a magnetic field. In the anticancer evaluation of SPIO-PEG-D, the group with a magnetic field displayed a significantly smaller tumor size than the group without. The overall results show that SPIO-PEG-D nanoparticles have the potential for the application of MRI/monitoring chemotherapy and the therapy can be locally enhanced by applying an external magnetic field.

Keywords: super paramagnetic iron oxide nano particles, doxorubicin, chemotherapy, MRI, magnetic fields

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Authors: Małgorzata Golonka, Jadwiga Laska

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Among self-healing materials, the most unexplored group are thermoplastic polymers. These polymers are used not only to produce packaging with a relatively short life but also to obtain coatings, insulation, casings, or parts of machines and devices. Due to its exceptional resistance to weather conditions, hydrophobicity, sufficient mechanical strength, and ease of extrusion, polyethylene is used in the production of polymer pipelines and as an insulating layer for steel pipelines. Polyethylene or PE coated steel pipelines can be used in difficult conditions such as underground or underwater installations. Both installation and use under such conditions are associated with high stresses and consequently the formation of microdamages in the structure of the material, loss of its integrity and final applicability. The ideal solution would be to include a self-healing system in the polymer material. In the presented study the behavior of resin-coated microcapsules in the extrusion process of low-density polyethylene was examined. Microcapsules are a convenient element of the repair system because they can be filled with appropriate reactive substances to ensure the repair process, but the main problem is their durability under processing conditions. Rapeseed oil, which has a relatively high boiling point of 240⁰C and low volatility, was used as the core material that simulates the reactive agents. The capsule shell, which is a key element responsible for its mechanical strength, was obtained by in situ polymerising urea-formaldehyde, melamine-urea-formaldehyde or melamine-formaldehyde resin on the surface of oil droplets dispersed in water. The strength of the capsules was compared based on the shell material, and in addition, microcapsules with single- and multilayer shells were obtained using different combinations of the chemical composition of the resins. For example, the first layer of appropriate tightness and stiffness was made of melamine-urea-formaldehyde resin, and the second layer was a melamine-formaldehyde reinforcing layer. The size, shape, distribution of capsule diameters and shell thickness were determined using digital optical microscopy and electron microscopy. The efficiency of encapsulation (i.e., the presence of rapeseed oil as the core) and the tightness of the shell were determined by FTIR spectroscopic examination. The mechanical strength and distribution of microcapsules in polyethylene were tested by extruding samples of crushed low-density polyethylene mixed with microcapsules in a ratio of 1 and 2.5% by weight. The extrusion process was carried out in a mini extruder at a temperature of 150⁰C. The capsules obtained had a diameter range of 70-200 µm. FTIR analysis confirmed the presence of rapeseed oil in both single- and multilayer shell microcapsules. Microscopic observations of cross sections of the extrudates confirmed the presence of both intact and cracked microcapsules. However, the melamine-formaldehyde resin shells showed higher processing strength compared to that of the melamine-urea-formaldehyde coating and the urea-formaldehyde coating. Capsules with a urea-formaldehyde shell work very well in resin coating systems and cement composites, i.e., in pressureless processing and moulding conditions. The addition of another layer of melamine-formaldehyde coating to both the melamine-urea-formaldehyde and melamine-formaldehyde resin layers significantly increased the number of microcapsules undamaged during the extrusion process. The properties of multilayer coatings were also determined and compared with each other using computer modelling.

Keywords: self-healing polymers, polyethylene, microcapsules, extrusion

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Authors: Luqman Shah

Abstract:

The myopic gender discrimination is now a well-documented and recognized fact. However, gender is only one facet of an individual’s multiple identities. The aim of this work is to investigate gender discrimination highlighted in print media in the subcontinent with a specific focus on Pakistan and India. In this study, an approach is adopted by using the James Paul Gee model for the identification of gender discrimination. As a matter of fact, gender discrimination is not consistent in its nature and intensity across global societies and varies as social, geographical, and cultural background change. The World has been changed enormously in every aspect of life, and there are also obvious changes towards gender discrimination, prejudices, and biases, but still, the world has a long way to go to recognize women as equal as men in every sphere of life. The history of the world is full of gender-based incidents and violence. Now the time came that this issue must be seriously addressed and to eradicate this evil, which will lead to harmonize society and consequently heading towards peace and prosperity. The study was carried out by a mixed model research method. The data was extracted from the contents of five Pakistani English newspapers out of a total of 23 daily English newspapers, and likewise, five Indian daily English newspapers out of 52 those were published 2018-2019. Two news stories from each of these newspapers, in total, twenty news stories were taken as sampling for this research. Content and semiotic analysis techniques were used to analyze through James Paul Gee's seven building tasks of language. The resources of renowned e-papers are utilized, and the highlighted cases in Pakistani newspapers of Indian gender-based stories and vice versa are scrutinized as per the requirement of this research paper. For analysis of the written stretches of discourse taken from e-papers and processing of data for the focused problem, James Paul Gee 'Seven Building Tasks of Language' is used. Tabulation of findings is carried to pinpoint the issue with certainty. Findings after processing the data showed that there is a gross human rights violation on the basis of gender discrimination. The print media needs a more realistic representation of what is what not what seems to be. The study recommends the equality and parity of genders.

Keywords: gender discrimination, print media, Paul Gee model, subcontinent

Procedia PDF Downloads 221

Authors: Asma Rebaya, Imen Amari, Kaouther Gasmi, Salem Hasnaoui

Abstract:

Over these last years, the number of cores witnessed a spectacular increase in digital signal and general use processors. Concurrently, significant researches are done to get benefit from the high degree of parallelism. Indeed, these researches are focused to provide an efficient scheduling from hardware/software systems to multicores architecture. The scheduling process consists on statically choose one core to execute one task and to specify an execution order for the application tasks. In this paper, we describe an efficient scheduler that calculates the optimal number of cores required to schedule an application, gives a heuristic scheduling solution and evaluates its cost. Our proposal results are evaluated and compared with Preesm scheduler results and we prove that ours allows better scheduling in terms of latency, computation time and number of cores.

Keywords: computation time, hardware/software system, latency, optimization, multi-cores platform, scheduling

Procedia PDF Downloads 283

Authors: Mohammed Arif, Abdessalam Kifouche

Abstract:

Optical character recognition (OCR) has a main role in the present time. It's capable to solve many serious problems and simplify human activities. The OCR yields to 70's, since many solutions has been proposed, but unfortunately, it was supportive to nothing but Latin languages. This work proposes a system of recognition of an off-line Arabic handwriting. This system is based on a structural segmentation method and uses support vector machines (SVM) in the classification phase. We have presented a state of art of the characters segmentation methods, after that a view of the OCR area, also we will address the normalization problems we went through. After a comparison between the Arabic handwritten characters & the segmentation methods, we had introduced a contribution through a segmentation algorithm.

Keywords: OCR, segmentation, Arabic characters, PAW, post-processing, SVM

Procedia PDF Downloads 71

Authors: Raj Raghupathy

Abstract:

Recurrent Spontaneous Miscarriage (RSM) is a common form of pregnancy loss, 50% of which are due to ‘unexplained’ causes. Evidence exists to suggest that RSM may be caused by immunologic factors such as cytokines which are critical molecules of the immune system, with an impressive array of capabilities. An association appears to exist between Th2-type reactivity (mediated by Th2 or anti-inflammatory cytokines) and normal, successful pregnancy, and between unexplained RSM and Th1 cytokine dominance. If pro-inflammatory cytokines are indeed associated with pregnancy loss, the suppression of these cytokines, and thus the ‘redirection’ of maternal reactivity, may help prevent cytokine-mediated pregnancy loss. The objective of this study was to explore the possibility of modulating cytokine production using Dydrogesterone (Duphaston®), an orally-administered progestogen. Peripheral blood mononuclear cells from 34 women with a history of at least 3 unexplained recurrent miscarriages were stimulated in vitro with a mitogen (to elicit cytokine production) in the presence and absence of dydrogesterone. Levels of selected pro- and anti-inflammatory cytokines produced by peripheral blood mononuclear cells were measured after exposure to these progestogens. Dydrogesterone down-regulates the production of pro-inflammatory cytokines and up-regulates the production of anti-inflammatory cytokines. The ratios of Th2 to Th1 cytokines are markedly elevated in the presence of dydrogesterone, indicating a shift from potentially harmful maternal Th1 reactivity to a more pregnancy-conducive Th2 profile. We used a progesterone receptor antagonist to show that this cytokine-modulating effect of dydrogesterone is mediated via the progesterone receptor. Dydrogesterone also induces the production of the Progesterone-Induced Blocking Factor (PIBF); lymphocytes exposed to PIBF produce higher levels of Th2 cytokines, affecting a Th1 → Th2 cytokine shift which could be favourable to the success of pregnancy. We conclude that modulation of maternal cytokine production profiles is possible with dydrogesterone which has the merits that it can be administered orally and that it is safe.

Keywords: cytokines, dydrogesterone, progesterone, recurrent spontaneous miscarriage

Procedia PDF Downloads 289

Authors: Gordana Ćetković, Vesna Tumbas Šaponjac, Jasna Čanadanović-Brunet, Sonja Đilas, Slađana Stajčić, Jelena Vulić, Mirjana Jakišić

Abstract:

Despite the recommended amount of daily intake of fruits, the consumption in modern age remains very low. Therefore there is a need for delivering valuable phytochemicals into the human body through different foods by developing functional food products fortified with natural bioactive compounds from plant sources. Recently, a growing interest rises in exploiting the fruit and vegetable by-products as sources of phytochemicals such as polyphenols, carotenoids, vitamins etc. Cherry contain high amounts of polyphenols, which are known to display a wide range of biological activities like antioxidant, anti-inflammatory, antimicrobial or anti-carcinogenic activities, improvement of vision, induction of apoptosis and neuroprotective effects. Also, cherry pomace, a by-product in juice processing, can also be promising source of phenolic compounds. However, the application of polyphenols as food additives is limited because after extraction these compounds are susceptible to degradation. Microencapsulation is one of the alternative approaches to protect bioactive compounds from degradation during processing and storage. Freeze-drying is one of the most used microencapsulation methods for the protection of thermosensitive and unstable molecules. In this study sour cherry pomace was extracted with food-grade solvent (50% ethanol) to be suitable for application in products for human use. Extracted polyphenols have been concentrated and stabilized on whey (WP) and soy (SP) proteins. Encapsulation efficiency in SP was higher (94.90%), however not significantly (p<0.05) from the one in WP (90.10%). Storage properties of WP and SP encapsulate in terms of total polyphenols, anthocyanins and antioxidant activity was tested for 6 weeks. It was found that the retention of polyphenols after 6 weeks in WP and SP (67.33 and 69.30%, respectively) was similar. The content of anthocyanins has increased in WP (for 47.97%), while their content in SP has very slightly decreased (for 1.45%) after 6-week storage period. In accordance with anthocyanins the decrease in antioxidant activity in WP (87.78%) was higher than in SP (43.02%). According to the results obtained in this study, the technique reported herewith can be used for obtaining quality encapsulates for their further use as functional food additives, and, on the other hand, for fruit waste valorization.

Keywords: cherry pomace, microencapsulation, polyphenols, storage

Procedia PDF Downloads 368