Search results for: Signal Processing

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: 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

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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

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

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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

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Authors: Mohammed Arif, Abdessalam Kifouche

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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

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

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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

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Authors: Yair Bleiberg, Michael Werman

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Coordinate-based Multi-Layer Perceptrons (MLPs) are known to have difficulty reconstructing high frequencies of the training data. A common solution to this problem is Positional Encoding (PE), which has become quite popular. However, PE has drawbacks. It has high-frequency artifacts and adds another hyper hyperparameter, just like batch normalization and dropout do. We believe that under certain circumstances, PE is not necessary, and a smarter construction of the network architecture together with a smart training method is sufficient to achieve similar results. In this paper, we show that very simple MLPs can quite easily output a frequency when given input of the half-frequency and quarter-frequency. Using this, we design a network architecture in blocks, where the input to each block is the output of the two previous blocks along with the original input. We call this a Fibonacci Network. By training each block on the corresponding frequencies of the signal, we show that Fibonacci Networks can reconstruct arbitrarily high frequencies.

Keywords: neural networks, positional encoding, high frequency intepolation, fully connected

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Authors: Emanuela Paranhos Lima, Vitaly Félix Rodríguez Esquerre

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In this work, efficient directional coupler composed of dielectric waveguides and metallic film has been analyzed in details by simulations using finite element method (FEM). The structure consists of a step-index fiber with dielectric core, silica cladding, and a metal nanowire parallel to the core. The results show that an efficient conversion of optical dielectric modes to long range plasmonic is possible. Low insertion losses in conjunction with short coupling length and a broadband operation can be achieved under certain conditions. This kind of couplers has potential applications for the design of photonic integrated circuits for signal routing between dielectric/plasmonic waveguides, sensing, lithography, and optical storage systems. A high efficient focusing of light in a very small region can be obtained.

Keywords: directional coupler, finite element method, metallic nanowire, plasmonic, surface plasmon polariton, superfocusing

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Authors: Murna Muzaifa, Dian Hasni, Febriani, Anshar Patria, Amhar Abubakar

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Coffee flavour is influenced by many factors such as processing techniques. Civet coffee is known as one of premium coffee due to its unique processing technique and its superior cupping quality. The desirable aroma of coffee is foremost formed during roasting step at a high temperature from precursors that are present in the green bean. Sugars, proteins, acids and trigonelline are the principal flavor precursors compounds in green coffee bean. It is now widely accepted that amino acids act as precursors of the Maillard reaction during which the colour and aroma are formed. To investigate amino acids on civet coffee, concentration of 20 amino acids (L-Isoleucine, L-Valine, L-Proline, L-Phenylalanine, L-Arginine, L-Asparagine, L-Threonine, L-Tryptophan, L-Leucine, L-Serine, L-Glutamine, L-Methionine, L-Histidine, Aspartic acid, L-Tyrosine, L-Lysine, L-Glutamic acid, and L-Cysteine, L-Alanine and Glycine) were determined in green and roasted bean of civet coffee by LCMS analysis. The cup quality of civet coffee performed using professional Q-grader followed SCAA standard method. The measured parameters were fragrance/aroma, flavor, acidity, body, uniformity, clean up, aftertaste, balance, sweetness and overall. The work has been done by collecting samples of civet coffee from six locations in Gayo Higland, Aceh-Indonesia. The results showed that 18 amino acids were detected in green bean of civet coffee (L-Isoleucine, L-Valine, L-Proline, L-Phenylalanine, L-Arginine, L-Asparagine, L-Threonine, L-Tryptophan, L-Leucine, L-Serine, L-Glutamine, L-Methionine, L-Histidine, Aspartic acid, L-Tyrosine, L-Lysine, L-Glutamic acid, and L-Cysteine) and 2 amino acids were not detected (L-Alanine and Glycine). On the other hand, L-Tyrosine and Glycine were not detected in roasted been of civet coffee. Glutamic acid is the amino acid with highest concentration in both green and roasted bean (21,02 mg/g and 24,60 mg/g), followed by L- Valine (19,98 mg/g and 20,22 mg/g) and Aspartic acid (14,93 mg/g and 18,58 mg/g). Civet coffee has a fairly high cupping value (cup quality), ranging from 83.75 to 84.75, categorized as speciality coffee. Moreover, civet coffee noted to have nutty, chocolaty, fishy, herby and watery.

Keywords: amino acids, civet coffee, cupping quality, luwak

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Authors: Vijay Goud, Ramasamy Alagirusamy, Apurba Das, Dinesh Kalyanasundaram

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Thermoplastic composites render new opportunities as effective processing technology while crafting newer complications into processing. One of the notable challenges is in achieving thorough wettability that is significantly deterred by the high viscosity of the long molecular chains of the thermoplastics. As a result of high viscosity, it is very difficult to impregnate the resin into a tightly interlaced textile structure to fill the voids present in the structure. One potential solution to the above problem, is to pre-deposit resin on the fiber, prior to consolidation. The current study compares DREF spinning, powder coating and film stacking methods of predeposition of resin onto fibers. An investigation into the flexural properties of unidirectional composites (UDC) produced from blending of carbon fiber and polypropylene (PP) matrix in varying forms of fiber, powder and film are reported. Dr. Ernst Fehrer (DREF) yarns or friction spun hybrid yarns were manufactured from PP fibers and carbon tows. The DREF yarns were consolidated to yield unidirectional composites (UDCs) referred to as UDC-D. PP in the form of powder was coated on carbon tows by electrostatic spray coating. The powder-coated towpregs were consolidated to form UDC-P. For the sake of comparison, a third UDC referred as UDC-F was manufactured by the consolidation of PP films stacked between carbon tows. The experiments were designed to yield a matching fiber volume fraction of about 50 % in all the three UDCs. A comparison of mechanical properties of the three composites was studied to understand the efficiency of matrix wetting and impregnation. Approximately 19% and 68% higher flexural strength were obtained for UDC-P than UDC-D and UDC-F respectively. Similarly, 25% and 81% higher modulus were observed in UDC-P than UDC-D and UDC-F respectively. Results from micro-computed tomography, scanning electron microscopy, and short beam tests indicate better impregnation of PP matrix in UDC-P obtained through electrostatic spray coating process and thereby higher flexural strength and modulus.

Keywords: DREF spinning, film stacking, flexural strength, powder coating, thermoplastic composite

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Authors: M. Rezki, A. Belaidi

Abstract:

This paper deals with a method of learning to solve a real problem in biomedical engineering from a technical study of muscle fatigue. Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles (viewpoint: anatomical and physiological). EMG is used as a diagnostics tool for identifying neuromuscular diseases, assessing low-back pain and muscle fatigue in general. In order to study the EMG signal for detecting fatigue in a muscle, we have taken a real problem which touches the tramway conductor the handle bar. For the study, we have used a typical autonomous platform in order to get signals at real time. In our case study, we were confronted with complex problem to do our experiments in a tram. This type of problem is recurring among students. To teach our students the method to solve this kind of problem, we built a similar system. Through this study, we realized a lot of objectives such as making the equipment for simulation, the study of detection of muscle fatigue and especially how to manage a study of biomedical looking.

Keywords: EMG, health platform, conductor’s tram, muscle fatigue

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Authors: Mohammad Alqahtani, Eric Atwell

Abstract:

This paper reviews and classifies most of the important types of search techniques that have been applied on the holy Quran. Then, it addresses the limitations in these techniques. Additionally, this paper surveys most existing Quranic ontologies and what are their deficiencies. Finally, it explains a new search tool called: A semantic search tool for Al Quran based on Qur’anic ontologies. This tool will overcome all limitations in the existing Quranic search applications.

Keywords: holy Quran, natural language processing (NLP), semantic search, information retrieval (IR), ontology

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Authors: Sang-Tae Ji, Jeong-Woo Park, Jun-Ho Park, Kwang-Woo Nam

Abstract:

This study aims is to suggest the basic factors by considering the priority of intersection in the diffusion project of Smart intersection. Busan Metropolitan City is conducting a smart intersection project for efficient traffic management. The smart intersection project aims to make breakthrough improvement of the intersection congestion by optimizing the signal system using CCTV (closed-circuit television camera) image analysis technology. This study investigated trends of existing researches and analyzed by setting three things of traffic volume, characteristics of intersection road, and whether or not to conduct the main arterial road as factors for selecting new intersection when spreading smart intersection. Using this, we presented the priority of the newly installed intersection through the present situation and analysis for the Busan Metropolitan City which is the main destination of the spreading project of the smart intersection. The results of this study can be used as a consideration in the implementation of smart intersection business.

Keywords: CCTV, GIS, ICT, Smart City, smart intersection

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

Abstract:

This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Hakan Aydogan, Fatih Bozkurt, Huseyin Coskun

Abstract:

In this study, the signal of brain electrical activities of the sixteen students selected from the Department of Electrical and Energy at Usak University have been recorded during a lecturer performed happiness emotions for the first group and anger emotions for the second group in different time while the groups were in the classroom separately. The attention and meditation data extracted from the recorded signals have been analyzed and evaluated toward the teacher’s specific emotion states simultaneously. Attention levels of students who are under influence of happiness emotions of the lecturer have a positive trend and attention levels of students who are under influence of anger emotions of the lecturer have a negative trend. The meditation or mental relaxation levels of students who are under influence of happiness emotions of the lecturer are 34.3% higher comparing with the mental relaxation levels of students who are under influence of anger emotions of the lecturer.

Keywords: brainwave, attention, meditation, education

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Authors: M. Salvador, J. C. Martinez-Garcia, A. Moyano, M. C. Blanco-Lopez, M. Rivas

Abstract:

Biosensors play a crucial role in the detection of molecules nowadays due to their advantages of user-friendliness, high selectivity, the analysis in real time and in-situ applications. Among them, Lateral Flow Immunoassays (LFIAs) are presented among technologies for point-of-care bioassays with outstanding characteristics such as affordability, portability and low-cost. They have been widely used for the detection of a vast range of biomarkers, which do not only include proteins but also nucleic acids and even whole cells. Although the LFIA has traditionally been a positive/negative test, tremendous efforts are being done to add to the method the quantifying capability based on the combination of suitable labels and a proper sensor. One of the most successful approaches involves the use of magnetic sensors for detection of magnetic labels. Bringing together the required characteristics mentioned before, our research group has developed a biosensor to detect biomolecules. Superparamagnetic nanoparticles (SPNPs) together with LFIAs play the fundamental roles. SPMNPs are detected by their interaction with a high-frequency current flowing on a printed micro track. By means of the instant and proportional variation of the impedance of this track provoked by the presence of the SPNPs, quantitative and rapid measurement of the number of particles can be obtained. This way of detection requires no external magnetic field application, which reduces the device complexity. On the other hand, the major limitations of LFIAs are that they are only qualitative or semiquantitative when traditional gold or latex nanoparticles are used as color labels. Moreover, the necessity of always-constant ambient conditions to get reproducible results, the exclusive detection of the nanoparticles on the surface of the membrane, and the short durability of the signal are drawbacks that can be advantageously overcome with the design of magnetically labeled LFIAs. The approach followed was to coat the SPIONs with a specific monoclonal antibody which targets the protein under consideration by chemical bonds. Then, a sandwich-type immunoassay was prepared by printing onto the nitrocellulose membrane strip a second antibody against a different epitope of the protein (test line) and an IgG antibody (control line). When the sample flows along the strip, the SPION-labeled proteins are immobilized at the test line, which provides magnetic signal as described before. Preliminary results using this practical combination for the detection and quantification of the Prostatic-Specific Antigen (PSA) shows the validity and consistency of the technique in the clinical range, where a PSA level of 4.0 ng/mL is the established upper normal limit. Moreover, a LOD of 0.25 ng/mL was calculated with a confident level of 3 according to the IUPAC Gold Book definition. Its versatility has also been proved with the detection of other biomolecules such as troponin I (cardiac injury biomarker) or histamine.

Keywords: biosensor, lateral flow immunoassays, point-of-care devices, superparamagnetic nanoparticles

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