Search results for: detecting of envelope modulation on noise

Authors: Arina V. Tankanag, Gennady V. Krasnikov, Nikolai K. Chemeris

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The development of respiration-dependent oscillations in the peripheral blood flow may occur by at least two mechanisms. The first mechanism is related to the change of venous pressure due to mechanical activity of lungs. This phenomenon is known as ‘respiratory pump’ and is one of the mechanisms of venous return of blood from the peripheral vessels to the heart. The second mechanism is related to the vasomotor reflexes controlled by the respiratory modulation of the activity of centers of the vegetative nervous system. Early high phase synchronization of respiration-dependent blood flow oscillations of left and right forearm skin in healthy volunteers at rest was shown. The aim of the work was to study the effect of deep controlled breathing on the phase synchronization of skin blood flow oscillations. 29 normotensive non-smoking young women (18-25 years old) of the normal constitution without diagnosed pathologies of skin, cardiovascular and respiratory systems participated in the study. For each of the participants six recording sessions were carried out: first, at the spontaneous breathing rate; and the next five, in the regimes of controlled breathing with fixed breathing depth and different rates of enforced breathing regime. The following rates of controlled breathing regime were used: 0.25, 0.16, 0.10, 0.07 and 0.05 Hz. The breathing depth amounted to 40% of the maximal chest excursion. Blood perfusion was registered by laser flowmeter LAKK-02 (LAZMA, Russia) with two identical channels (wavelength 0.63 µm; emission power, 0.5 mW). The first probe was fastened to the palmar surface of the distal phalanx of left forefinger; the second probe was attached to the external surface of the left forearm near the wrist joint. These skin zones were chosen as zones with different dominant mechanisms of vascular tonus regulation. The degree of phase synchronization of the registered signals was estimated from the value of the wavelet phase coherence. The duration of all recording was 5 min. The sampling frequency of the signals was 16 Hz. The increasing of synchronization of the respiratory-dependent skin blood flow oscillations for all controlled breathing regimes was obtained. Since the formation of respiration-dependent oscillations in the peripheral blood flow is mainly caused by the respiratory modulation of system blood pressure, the observed effects are most likely dependent on the breathing depth. It should be noted that with spontaneous breathing depth does not exceed 15% of the maximal chest excursion, while in the present study the breathing depth was 40%. Therefore it has been suggested that the observed significant increase of the phase synchronization of blood flow oscillations in our conditions is primarily due to an increase of breathing depth. This is due to the enhancement of both potential mechanisms of respiratory oscillation generation: venous pressure and sympathetic modulation of vascular tone.

Keywords: deep controlled breathing, peripheral blood flow oscillations, phase synchronization, wavelet phase coherence

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Authors: I. V. Palamarchuk, N. V. Zaichko

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Background and Aims: Galectin-3 is a marker of subclinical cardiac injury and is elevated in individuals with type 2 diabetes mellitus; while hydrogen sulfide (H₂S), metabolite of sulfur-containing amino acids, is considered having antifibrogenic effects. This study was designed to investigate whether metformin and its combination with NaHS can influence plasma galectin-3 and cystathionine-γ-lyase/hydrogen sulfide (CSE/H₂S) system in diabetic rat’s heart. Methods: 32 healthy male rats (180-250 g) were divided into 4 groups. To induct diabetes, rats (group 2-4) were injected with streptozotocin (STZ, 40 mg/kg/i.p., 0.1 M citrate buffer (pH 4.5). Rats from 3d (STZ+Metf) and 4th (STZ+Metf+NaHS) groups were given metformin (500 mg/kg/day) orally, and rats from 4th (STZ+Metf+NaHS) group were injected sodium hydrosulfide (NaHS, 3 mg/kg/i.p.) once per day starting from 3 to 28 day after streptozotocin injection. Rats of first group (control) were administered the equivalent volumes of 0.9% NaCl. Plasma galectin-3 was measured by ELISA. Rats’ hearts were sampled for determination of H2S by reaction with N,N-Dimethyl-p-phenylenediamine. Determination of CSE gene expression was performed in real time using PCR in the presence of SYBR Green I, using DT-Light detecting amplifier ('DNA-technology', Russia). Results: Induction of streptozotocin diabetes (STZ-diabetes, group 2) was followed by low myocardial H2S concentration and CSE expression (by 35%, p < 0.05 and 60.5%, p < 0.001 respectively, than that in controls), while plasma galectin-3 in this group was significantly higher than in controls (by 3.8 times, p < 0.05). Administration of metformin (group 3) resulted in significantly higher H₂S concentration (by 28.5%, p < 0.05), whereas CSE expression was only by 6% more than that in STZ-diabetes, as well as plasma galectin-3 was only by 14.8% lower in comparison with untreated diabetic rats. The inhibition of H₂S generation and CSE activity by diabetes was greatly attenuated in STZ+Metf+NaHS group. The combination of metformin with NaHS significantly stimulated H₂S production (by 48%, p < 0.05 and 15%, p < 0.05 more than STZ-diabetes and STZ+Metf respectively) and CSE gene expression (by 64.8%, p < 0.05 compared to STZ-diabetes and by 55.4%,p < 0.05 compared to STZ+Metf). Besides, plasma galectin-3 in rats receiving metformin and NaHS was significantly lower by 42%, p < 0.05 and 32.5%, p < 0.05 compared to STZ-diabetes and STZ+Metf groups respectively. Conclusions: To summarize, dysfunction of CSE/H2S system and galectin-3 stimulation was found in streptozotocin-induced diabetic rats. Metformin and its combination with exogenous H2S effectively prevented the development of metabolic changes induced by diabetes. These findings suggest that CSE/H₂S system can be integrated into pathogenesis of diabetic complications through modulation of pro-inflammatory and pro-fibrogenic mediator galectin-3.

Keywords: cystathionine-γ-lyase, diabetic heart, galectin-3, hydrogen sulfide, metformin, sodium hydrosulfide

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Mohammed Belalia Douma

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Interactive learning is considered as the most effective strategy of learning, it is an educational philosophy based on the learner's contribution and involvement mainly in classroom and how he interacts toward his small society “classroom”, and the level of his collaboration into challenge, discovering, games, participation, all these can be provided through the interactive learning, which aims to activate the learner's role in the operation of learning, which focuses on research and experimentation, and the learner's self-reliance in obtaining information, acquiring skills, and forming values and attitudes. Whereas not based on memorization only, but rather on developing thinking and the ability to solve problems, on teamwork and collaborative learning. With the exchange or roles - teacher to student- , when the student will be more active and performing operations more than the student under the interactive learning method; we might face a several issues dealing with class controlling management, noise, and stability of learning… etc. This research paper is observing the application of the interactive learning on reality “classroom” and answers several assumptions and analyzes the issues coming up of these strategies mainly: noise, class control…etc The research sample was about 150 student of the 3rd year primary school in “Chlef” district, Algeria, level: beginners in the range of age 08 to 10 years old . We provided a questionnaire of confidential fifteen questions and also analyzing the attitudes of learners during three months. it have witnessed as teachers a variety of strategies dealing with applying the interactive learning but with a different issues; time management, noise, uncontrolled classes, overcrowded classes. Finally, it summed up that although the active education is an inevitably effective method of teaching, however, there are drawbacks to this, in addition to the fact that not all theoretical strategies can be applied and we conclude with solutions of this case study.

Keywords: interactive learning, student, learners, strategies.

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Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

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Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

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Authors: Mohammed Benmostefa

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In the industrial production of large series or even medium series, there are vibration problems. In continuous operations, technical devices result in vibrations in solid bodies and machine components, which generate solid noise and/or airborne noise. This is because vibrations are the mechanical oscillations of an object near its equilibrium point. In response to the problems resulting from these vibrations, a number of remedial acts and solutions have been put forward. These include insulation of machines, insulation of concrete masses, insulation under screeds, insulation of sensitive equipment, point insulation of machines, linear insulation of machines, full surface insulation of machines, and the like. Following this, the researcher sought not only to raise awareness on the possibility of lowering the vibration frequency in industrial machines but also to stress the significance of procedures involving the pre-installation process of machinery, namely, setting appropriate installation and start-up methods of the machine, allocating and updating imprint folders to each machine, and scheduling maintenance of each machine all year round to have reliable equipment, gain cost reduction and maintenance efficiency to eventually ensure the overall economic performance of the company.

Keywords: maintenance, vibration, efficiency, production, machinery

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Authors: A. Casale, J. Alessi, C. N. Bianchi, G. Bozzini, M. Brunoldi, V. Cappanera, P. Corvisiero, G. Fanciulli, D. Grosso, N. Magnoli, A. Mandich, C. Melchiorre, C. Morri, P. Povero, N. Stasi, M. Taiuti, G. Viano, M. Wurtz

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This work describes a real-time algorithm for detecting, tracking and classifying single motorboats, developed using the acoustic data recorded by a hydrophone array within the framework of EU LIFE + project ARION (LIFE09NAT/IT/000190). The project aims to improve the conservation status of bottlenose dolphins through a real-time simultaneous monitoring of their population and surface ship traffic. A Passive Acoustic Monitoring (PAM) system is installed on two autonomous permanent marine buoys, located close to the boundaries of the Marine Protected Area (MPA) of Portofino (Ligurian Sea- Italy). Detecting surface ships is also a necessity in many other sensible areas, such as wind farms, oil platforms, and harbours. A PAM system could be an effective alternative to the usual monitoring systems, as radar or active sonar, for localizing unauthorized ship presence or illegal activities, with the advantage of not revealing its presence. Each ARION buoy consists of a particular type of structure, named meda elastica (elastic beacon) composed of a main pole, about 30-meter length, emerging for 7 meters, anchored to a mooring of 30 tons at 90 m depth by an anti-twist steel wire. Each buoy is equipped with a floating element and a hydrophone tetrahedron array, whose raw data are send via a Wi-Fi bridge to a ground station where real-time analysis is performed. Bottlenose dolphin detection algorithm and ship monitoring algorithm are operating in parallel and in real time. Three modules were developed and commissioned for ship monitoring. The first is the detection algorithm, based on Time Difference Of Arrival (TDOA) measurements, i.e., the evaluation of angular direction of the target respect to each buoy and the triangulation for obtaining the target position. The second is the tracking algorithm, based on a Kalman filter, i.e., the estimate of the real course and speed of the target through a predictor filter. At last, the classification algorithm is based on the DEMON method, i.e., the extraction of the acoustic signature of single vessels. The following results were obtained; the detection algorithm succeeded in evaluating the bearing angle with respect to each buoy and the position of the target, with an uncertainty of 2 degrees and a maximum range of 2.5 km. The tracking algorithm succeeded in reconstructing the real vessel courses and estimating the speed with an accuracy of 20% respect to the Automatic Identification System (AIS) signals. The classification algorithm succeeded in isolating the acoustic signature of single vessels, demonstrating its temporal stability and the consistency of both buoys results. As reference, the results were compared with the Hilbert transform of single channel signals. The algorithm for tracking multiple targets is ready to be developed, thanks to the modularity of the single ship algorithm: the classification module will enumerate and identify all targets present in the study area; for each of them, the detection module and the tracking module will be applied to monitor their course.

Keywords: acoustic-noise, bottlenose-dolphin, hydrophone, motorboat

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Authors: Chung-Hyeon Ryu, Do-Hyoung Kim, Hak-Sung Kim

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As the use of the composites was increased, the detecting method of hidden damages which have an effect on performance of the composite was important. Terahertz (THz) spectroscopy was assessed as one of the new powerful nondestructive evaluation (NDE) techniques for fiber reinforced composite structures because it has many advantages which can overcome the limitations of conventional NDE techniques such as x-rays or ultrasound. The THz wave offers noninvasive, noncontact and nonionizing methods evaluating composite damages, also it gives a broad range of information about the material properties. In additions, it enables to detect the multiple-delaminations of various nonmetallic materials. In this study, the pulse type THz spectroscopy imaging system was devised and used for detecting and evaluating the hidden delamination in the glass fiber reinforced plastic (GFRP) composite laminates. The interaction between THz and the GFRP composite was analyzed respect to the type of delamination, including their thickness, size and numbers of overlaps among multiple-delaminations in through-thickness direction. Both of transmission and reflection configurations were used for evaluation of hidden delaminations and THz wave propagations through the delaminations were also discussed. From these results, various hidden delaminations inside of the GFRP composite were successfully detected using time-domain THz spectroscopy imaging system and also compared to the results of C-scan inspection. It is expected that THz NDE technique will be widely used to evaluate the reliability of composite structures.

Keywords: terahertz, delamination, glass fiber reinforced plastic composites, terahertz spectroscopy

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Authors: Shirin Jalili, Sadegh Hasannia, Hadi Shirzad, Afshin Khara

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Morphine is one of the most medicinally important analgesics and narcotics. Structurally, it is classified as an alkaloid because of the presence of nitrogen. Its structure is similar to that of codeine, thebaine, and heroin. An immunoassay to accurately discriminate between these analogous alkaloids would be highly beneficial. A key factor for such an assay is specificity with high sensitivity, which is totally dependent on the antibody employed. However, most antibodies against haptens are polyclonal serum antibodies that exhibit significant cross-reactivities with closely related compounds. The camel-derived single-chain antibody fragments (VHH) are the smallest molecules with antigen-binding capacity, possessing unique properties compared to other conventional antibodies. In this study, a library containing the VHH genes of a camel immunized with with morphine conjugated BSA following phage display technology was generated. By screening the camel-derived variable region of the heavy chain cDNA phage display library with the ability to bind the desired hapten, we obtained some nanobodies that recognize this hapten. Phage display expression of the Nbs from this library and pannings against this hapten resulted in a clear enrichment of four distinct Nb-displaying phages with specificity for morphine that could be a potential target site for the development of new strategies for the development of a biosensor for detecting illicit drug.

Keywords: phage display, nanobody, Morphine-3, glucuronide, ELISA, biosensor

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Authors: Bivek Bhusal, Ana Legrand

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Detection of crop stress is one of the major applications of remote sensing in agriculture. Multiple studies have demonstrated the capability of remote sensing using Unmanned Aerial Vehicle (UAV)-based multispectral imagery for detection of plant stress, but none so far on Nitrogen (N) stress and PLH feeding stress on green beans. In view of its wide host range, geographical distribution, and damage potential, Potato leafhopper- Empoasca fabae (Harris) has been emerging as a key pest in several countries. Monitoring methods for potato leafhopper (PLH) damage, as well as the laboratory techniques for detecting Nitrogen deficiency, are time-consuming and not always easily affordable. A study was initiated to demonstrate if the multispectral sensor attached to a drone can detect PLH stress and N deficiency in beans. Small-plot trials were conducted in the summer of 2023, where cages were used to manipulate PLH infestation in green beans (Provider cultivar) at their first-trifoliate stage. Half of the bean plots were introduced with PLH, and the others were kept insect-free. Half of these plots were grown with the recommended amount of N, and the others were grown without N. Canopy reflectance was captured using a five-band multispectral sensor. Our findings indicate that drone imagery could detect stress due to a lack of N and PLH damage in beans.

Keywords: potato leafhopper, nitrogen, remote sensing, spectral reflectance, beans

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Authors: Qianhua He, Weili Zhou, Aiwu Chen

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A sparse representation speech denoising method based on adapted stopping residue error was presented in this paper. Firstly, the cross-correlation between the clean speech spectrum and the noise spectrum was analyzed, and an estimation method was proposed. In the denoising method, an over-complete dictionary of the clean speech power spectrum was learned with the K-singular value decomposition (K-SVD) algorithm. In the sparse representation stage, the stopping residue error was adaptively achieved according to the estimated cross-correlation and the adjusted noise spectrum, and the orthogonal matching pursuit (OMP) approach was applied to reconstruct the clean speech spectrum from the noisy speech. Finally, the clean speech was re-synthesised via the inverse Fourier transform with the reconstructed speech spectrum and the noisy speech phase. The experiment results show that the proposed method outperforms the conventional methods in terms of subjective and objective measure.

Keywords: speech denoising, sparse representation, k-singular value decomposition, orthogonal matching pursuit

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Authors: Paras Gupta, Rohit Goyal, Yamini Chauhan, Pyare Lal Sharma

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Background: Bombax ceiba Linn., commonly called as Semal, is used in various gastro-intestinal disturbances. It contains lupeol which inhibits PTP-1B, adipogenesis, TG synthesis and accumulation of lipids in adipocytes and adipokines whereas the flavonoids isolated from B. ceiba has FAS inhibitory activity. The present study was aimed to investigate ameliorative potential of Bombax ceiba to experimental obesity in Wistar rats, and its possible mechanism of action. Methods: Male Wistar albino rats weighing 180–220 g were employed in present study. Experimental obesity was induced by feeding high fat diet for 10 weeks. Methanolic extract of B. ceiba extract 100, 200 and 400 mg/kg and Gemfibrozil 50 mg/kg as standard drug were given orally from 7th to 10th week. Results: Induction with HFD for 10 weeks caused significant (p < 0.05) increase in % body wt, BMI, LEE indices; serum glucose, triglyceride, LDL, VLDL, cholesterol, free fatty acid, ALT, AST; tissue TBARS, nitrate/nitrite levels; different fat pads and relative liver weight; and significant decrease in food intake (g and kcal), serum HDL and tissue glutathione levels in HFD control rats. Treatment with B. ceiba extract and Gemfibrozil significantly attenuated these HFD induced changes, as compared to HFD control. The effect of B. ceiba 200 and 400 mg/kg was more pronounced in comparison to Gemfibrozil. Conclusion: On the basis of results obtained, it may be concluded that the methanolic extract of stem bark of Bombax ceiba has significant ameliorative potential against HFD induced obesity in rats, possibly through modulation of FAS and PTP-1B signaling due to the presence of flavonoids and lupeol.

Keywords: obesity, Bombax ceiba, free fatty acid, protein tyrosine phosphatase-1B, fatty acid synthase

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Authors: Wei Feilong

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In this study, an local invariant generalized Houghtransform (LI-GHT) method is proposed for integrated circuit (IC) visual positioning. The original generalized Hough transform (GHT) is robust to external noise; however, it is not suitable for visual positioning of IC chips due to the four-dimensionality (4D) of parameter space which leads to the substantial storage requirement and high computational complexity. The proposed LI-GHT method can reduce the dimensionality of parameter space to 2D thanks to the rotational invariance of local invariant geometric feature and it can estimate the accuracy position and rotation angle of IC chips in real-time under noise and blur influence. The experiment results show that the proposed LI-GHT can estimate position and rotation angle of IC chips with high accuracy and fast speed. The proposed LI-GHT algorithm was implemented in IC visual positioning system of radio frequency identification (RFID) packaging equipment.

Keywords: Integrated Circuit Visual Positioning, Generalized Hough Transform, Local invariant Generalized Hough Transform, ICpacking equipment

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Authors: S. Yessengabulov, A. Uyzbayeva

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Residential buildings fund of Kazakhstan was built in the Soviet time about 35-60 years ago without considering energy efficiency measures. Currently, most of these buildings are in a rundown condition and fail to meet the minimum of hygienic, sanitary and comfortable living requirements. The paper aims to examine the reports of recent building energy survey activities in the country and provide a possible solution for retrofitting existing housing stock built before 1989 which could be applicable for building envelope in cold climate. Methodology also includes two-dimensional modeling of possible practical solutions and further recommendations.

Keywords: energy audit, energy efficient buildings in Kazakhstan, retrofit, two-dimensional conduction heat transfer analysis

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Authors: Deborah Eric, Abbas Ahmad Khan

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Lead halide perovskites quantum dots have attracted immense scientific and technological interest for successful photovoltaic applications because of their remarkable optoelectronic properties. In this paper, we have simulated CsMAPbI3-xBrx based quantum dots to implement their use in intermediate band solar cells (IBSC). These types of materials exhibit optical and electrical properties distinct from their bulk counterparts due to quantum confinement. The conceptual framework provides a route to analyze the electronic properties of quantum dots. This layer of quantum dots optimizes the position and bandwidth of IB that lies in the forbidden region of the conventional bandgap. A three-dimensional MAPbI3 quantum dot (QD) with geometries including spherical, cubic, and conical has been embedded in the CsPbBr3 matrix. Bound energy wavefunction gives rise to miniband, which results in the formation of IB. If there is more than one miniband, then there is a possibility of having more than one IB. The optimization of QD size results in more IBs in the forbidden region. One band time-independent Schrödinger equation using the effective mass approximation with step potential barrier is solved to compute the electronic states. Envelope function approximation with BenDaniel-Duke boundary condition is used in combination with the Schrödinger equation for the calculation of eigen energies and Eigen energies are solved for the quasi-bound states using an eigenvalue study. The transfer matrix method is used to study the quantum tunneling of MAPbI3 QD through neighbor barriers of CsPbI3. Electronic states are computed using Schrödinger equation with effective mass approximation by considering quantum dot and wetting layer assembly. Results have shown the varying the quantum dot size affects the energy pinning of QD. Changes in the ground, first, second state energies have been observed. The QD is non-zero at the center and decays exponentially to zero at boundaries. Quasi-bound states are characterized by envelope functions. It has been observed that conical quantum dots have maximum ground state energy at a small radius. Increasing the wetting layer thickness exhibits energy signatures similar to bulk material for each QD size.

Keywords: perovskite, intermediate bandgap, quantum dots, miniband formation

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Authors: John Zacharias, Bin Wang

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Travel comfort is increasingly seen as crucial to effecting the switch from private motorized modes to public transit. Surveys suggest that travel comfort is closely related to perceived crowding, that may involve lack of available seating, difficulty entering and exiting, jostling and other physical contacts with strangers. As found in studies on environmental stress, other factors may moderate perceptions of crowding–in this case, we hypothesize that the ambient environment may play a significant role. Travel comfort was measured by applying a structured survey to randomly selected passengers (n=369) on 3 lines of the Beijing metro on workdays. Respondents were standing with all seats occupied and with car occupancy at 14 levels. A second research assistant filmed the metro car while passengers were interviewed, to obtain the total number of passengers. Metro lines 4, 6 and 10 were selected that travel through the central city north-south, east-west and circumferentially. Respondents evaluated the following factors: crowding, noise, smell, air quality, temperature, illumination, vibration and perceived safety as they experienced them at the time of interview, and then were asked to rank these 8 factors according to their importance for their travel comfort. Evaluations were semantic differentials on a 7-point scale from highly unsatisfactory (-3) to highly satisfactory (+3). The control variables included age, sex, annual income and trip purpose. Crowding was assessed most negatively, with 41% of the scores between -3 and -2. Noise and air quality were also assessed negatively, with two-thirds of the evaluations below 0. Illumination was assessed most positively, followed by crime, vibration and temperature, all scoring at indifference (0) or slightly positive. Perception of crowding was linearly and positively related to the number of passengers in the car. Linear regression tested the impact of ambient environmental factors on perception of crowding. Noise intensity accounted for more than the actual number of individuals in the car in the perception of crowding, with smell also contributing. Other variables do not interact with the crowding variable although the evaluations are distinct. In all, only one-third of the perception of crowding (R2=.154) is explained by the number of people, with the other ambient environmental variables accounting for two-thirds of the variance (R2=.316). However, when ranking the factors by their importance to travel comfort, perceived crowding made up 69% of the first rank, followed by noise at 11%. At rank 2, smell dominates (25%), followed by noise and air quality (17%). Commuting to work induces significantly lower evaluations of travel comfort with shopping the most positive. Clearly, travel comfort is particularly important to commuters. Moreover, their perception of crowding while travelling on metro is highly conditioned by the ambient environment in the metro car. Focussing attention on the ambient environmental conditions of the metro is an effective way to address the primary concerns of travellers with overcrowding. In general, the strongly held opinions on travel comfort require more attention in the effort to induce ridership in public transit.

Keywords: ambient environment, mass rail transit, public transit, travel comfort

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Authors: Aussara Panya, Nunghathai Sawasdee, Mutita Junking, Chatchawan Srisawat, Kiattawee Choowongkomon, Pa-Thai Yenchitsomanus

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Dengue virus (DENV) infection is a global public health problem with approximately 100 million infected cases a year. Presently, there is no approved vaccine or effective drug available; therefore, the development of anti-DENV drug is urgently needed. The clinical reports revealing the positive association between the disease severity and viral titer has been reported previously suggesting that the anti-DENV drug therapy can possibly ameliorate the disease severity. Although several anti-DENV agents showed inhibitory activities against DENV infection, to date none of them accomplishes clinical use in the patients. The surface envelope (E) protein of DENV is critical for the viral entry step, which includes attachment and membrane fusion; thus, the blocking of envelope protein is an attractive strategy for anti-DENV drug development. To search the safe anti-DENV agent, this study aimed to search for novel peptide inhibitors to counter DENV infection through the targeting of E protein using a structure-based in silico design. Two selected strategies has been used including to identify the peptide inhibitor which interfere the membrane fusion process whereby the hydrophobic pocket on the E protein was the target, the destabilization of virion structure organization through the disruption of the interaction between the envelope and membrane proteins, respectively. The molecular docking technique has been used in the first strategy to search for the peptide inhibitors that specifically bind to the hydrophobic pocket. The second strategy, the peptide inhibitor has been designed to mimic the ectodomain portion of membrane protein to disrupt the protein-protein interaction. The designed peptides were tested for the effects on cell viability to measure the toxic to peptide to the cells and their inhibitory assay to inhibit the DENV infection in Vero cells. Furthermore, their antiviral effects on viral replication, intracellular protein level and viral production have been observed by using the qPCR, cell-based flavivirus immunodetection and immunofluorescence assay. None of tested peptides showed the significant effect on cell viability. The small peptide inhibitors achieved from molecular docking, Glu-Phe (EF), effectively inhibited DENV infection in cell culture system. Its most potential effect was observed for DENV2 with a half maximal inhibition concentration (IC50) of 96 μM, but it partially inhibited other serotypes. Treatment of EF at 200 µM on infected cells also significantly reduced the viral genome and protein to 83.47% and 84.15%, respectively, corresponding to the reduction of infected cell numbers. An additional approach was carried out by using peptide mimicking membrane (M) protein, namely MLH40. Treatment of MLH40 caused the reduction of foci formation in four individual DENV serotype (DENV1-4) with IC50 of 24-31 μM. Further characterization suggested that the MLH40 specifically blocked viral attachment to host membrane, and treatment with 100 μM could diminish 80% of viral attachment. In summary, targeting the hydrophobic pocket and M-binding site on the E protein by using the peptide inhibitors could inhibit DENV infection. The results provide proof of-concept for the development of antiviral therapeutic peptide inhibitors to counter DENV infection through the use of a structure-based design targeting conserved viral protein.

Keywords: dengue virus, dengue virus infection, drug design, peptide inhibitor

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Authors: C. Temaneh-Nyah

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Electromagnetic compatibility (EMC) is the ability of a Radio Communication Equipment (RCE) to operate with a desired quality of service in a given Electromagnetic Environment (EME) and not to create harmful interference with other RCE. This paper presents an algorithm which improves the simulation speed of estimating EMC of RCE in a complex EME, based on a stage by stage frequency-energy criterion of filtering. This algorithm considers different interference types including: Blocking and intermodulation. It consist of the following steps: simplified energy criterion where filtration is based on comparing the free space interference level to the industrial noise, frequency criterion which checks whether the interfering emissions characteristic overlap with the receiver’s channels characteristic and lastly the detailed energy criterion where the real channel interference level is compared to the noise level. In each of these stages, some interference cases are filtered out by the relevant criteria. This reduces the total number of dual and different combinations of RCE involved in the tedious detailed energy analysis and thus provides an improved simulation speed.

Keywords: electromagnetic compatibility, electromagnetic environment, simulation of communication network

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Authors: Michalis Michael, Mauro Overend

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Buildings, in which we spend 87-90% of our time, act as a shelter protecting us from environmental conditions and weather phenomena. The building's overall performance is significantly dependent on the envelope’s glazing part, which is particularly critical as it is the most vulnerable part to heat gain and heat loss. However, conventional glazing technologies have relatively low-performance thermo-optical characteristics. In this regard, during winter, the heat losses due to the glazing part of a building envelope are significantly increased as well as the heat gains during the summer period. In this study, the contribution of an innovative glazing technology, namely Closed Cavity Façade (CCF) in improving energy efficiency and IEQ in office buildings is examined, aiming to optimize various design configurations of CCF. Using Energy Plus and IDA ICE packages, the performance of several CCF configurations and geometries for various climate types were investigated, aiming to identify the optimum solution. The model used for the simulations and optimization process was MATELab, a recently constructed outdoor test facility at the University of Cambridge (UK). The model was previously experimentally calibrated. The study revealed that the use of CCF technology instead of conventional double or triple glazing leads to important benefits. Particularly, the replacement of the traditional glazing units, used as the baseline, with the optimal configuration of CCF led to a decrease in energy consumption in the range of 18-37% (depending on the location). This mainly occurs due to integrating shading devices in the cavity and applying proper glass coatings and control strategies, which lead to improvement of thermal transmittance and g-value of the glazing. Since the solar gain through the façade is the main contributor to energy consumption during cooling periods, it was observed that a higher energy improvement is achieved in cooling-dominated locations. Furthermore, it was shown that a suitable selection of the constituents of a closed cavity façade, such as the colour and type of shading devices and the type of coatings, leads to an additional improvement of its thermal performance, avoiding overheating phenomena and consequently ensuring temperatures in the glass cavity below the critical value, and reducing the radiant discomfort providing extra benefits in terms of Indoor Environmental Quality (IEQ).

Keywords: building energy efficiency, closed cavity façade, optimization, occupants comfort

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Authors: Sorore Benabid

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The Q-enhanced LC filters are the most used architecture in the Bandpass (BP) Continuous-Time (CT) Delta-Sigma (ΣΔ) modulators, due to their: high frequencies operation, high linearity than the active filters and a high quality factor obtained by Q-enhanced technique. This technique consists of the use of a negative resistance that compensate the ohmic losses in the on-chip inductor. However, this technique introduces a zero in the filter transfer function which will affect the modulator performances in term of Dynamic Range (DR), stability and in-band noise (Signal-to-Noise Ratio (SNR)). In this paper, we study the effect of this zero and we demonstrate that a calibration of the excess loop delay (ELD) is required to ensure the best performances of the modulator. System level simulations are done for a 2ndorder BP CT (ΣΔ) modulator at a center frequency of 300MHz. Simulation results indicate that the optimal ELD should be reduced by 13% to achieve the maximum SNR and DR compared to the ideal LC-based ΣΔ modulator.

Keywords: continuous-time bandpass delta-sigma modulators, excess loop delay, on-chip inductor, Q-enhanced LC filter

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Authors: Harsh Vikram Singh, Ankur Rai, Anand Mohan

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In this paper, we propose secure and robust data hiding algorithm based on DCT by Arnold transform and chaotic sequence. The watermark image is scrambled by Arnold cat map to increases its security and then the chaotic map is used for watermark signal spread in middle band of DCT coefficients of the cover image The chaotic map can be used as pseudo-random generator for digital data hiding, to increase security and robustness .Performance evaluation for robustness and imperceptibility of proposed algorithm has been made using bit error rate (BER), normalized correlation (NC), and peak signal to noise ratio (PSNR) value for different watermark and cover images such as Lena, Girl, Tank images and gain factor .We use a binary logo image and text image as watermark. The experimental results demonstrate that the proposed algorithm achieves higher security and robustness against JPEG compression as well as other attacks such as addition of noise, low pass filtering and cropping attacks compared to other existing algorithm using DCT coefficients. Moreover, to recover watermarks in proposed algorithm, there is no need to original cover image.

Keywords: data hiding, watermarking, DCT, chaotic sequence, arnold transforms

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Authors: Shirin jalili, Hadi Shirzad, Samaneh Nabavi, Somayeh Khanjani

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Biosensors in forensic analysis are ideal biological tools that can be used for rapid and sensitive initial screening and testing to detect of suspicious components like biological and chemical agent in crime scenes. The wide use of different biomolecules such as proteins, nucleic acids, microorganisms, antibodies and enzymes makes it possible. These biosensors have great advantages such as rapidity, little sample manipulation and high sensitivity, also Because of their stability, specificity and low cost they have become a very important tool to Forensic analysis and detection of crime. In crime scenes different substances such as rape samples, Semen, saliva fingerprints and blood samples, act as a detecting elements for biosensors. On the other hand, successful fluid recovery via biosensor has the propensity to yield a highly valuable source of genetic material, which is important in finding the suspect. Although current biological fluid testing techniques are impaired for identification of body fluids. But these methods have disadvantages. For example if they are to be used simultaneously, Often give false positive result. These limitations can negatively result the output of a case through missed or misinterpreted evidence. The use of biosensor enable criminal researchers the highly sensitive and non-destructive detection of biological fluid through interaction with several fluid-endogenous and other biological and chemical contamination at the crime scene. For this reason, using of the biosensors for detecting the biological fluid found at the crime scenes which play an important role in identifying the suspect and solving the criminal.

Keywords: biosensors, forensic analysis, biological fluid, crime detection

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Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

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Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

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The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

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Authors: Nassim Bessaad, Qilian Bao, Zhao Jiangkang

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The fiber optics gyroscope in the strap-down inertial navigation system (FOG-SINS) suffers from precision degradation due to the influence of random errors. In this work, an enhanced Allan variance (AV) stochastic modeling method combined with discrete wavelet transform (DWT) for signal denoising is implemented to estimate the random process in the FOG signal. Furthermore, we devise a measurement-based iterative adaptive Sage-Husa nonlinear filter with augmented states to integrate a star tracker sensor with SINS. The proposed filter adapts the measurement noise covariance matrix based on the available data. Moreover, the enhanced stochastic modeling scheme is invested in tuning the process noise covariance matrix and the augmented state Gauss-Markov process parameters. Finally, the effectiveness of the proposed filter is investigated by employing the collected data in laboratory conditions. The result shows the filter's improved accuracy in comparison with the conventional Kalman filter (CKF).

Keywords: inertial navigation, adaptive filtering, star tracker, FOG

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Emre Kishalı, Neslihan TürkmenoğLu Bayraktar

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Historical buildings may face various impacts throughout their life cycle. There have been environmental, structural, public works actions on old monuments influencing sustainability and maintenance issues. As a result, ancient monuments can have been undergone various changes in the context of restoration and repair. Currently, these buildings face integrated conditions including city planning macro solutions, old intervention methods, modifications in building envelope and artefacts in terms of conservation. Moreover, documentation of phases is an essential for assessing the historical building, yet it can result in highly complicated and interwoven issues. Herein, two monuments constructed in the 16th century are selected as case studies in Kocaeli, Turkey which are located in different micro climatic conditions and/or exposed to different interventions and which are important for the city as cultural property. Pertev Paşa Mosque (also known as Yenicuma Mosque) -constructed by Architect Sinan-; Gebze Çoban Mustafa Paşa Mosque -constructed in 1523 and known as the work of Architect Sinan but various names asserted as the architect of building according to resources. Active water infiltration and damages, recent material interventions, hidden niches, and foundation techniques of the mosque are investigated via Infrared Thermography under the project of 114K284, “Non-Destructive Test Applications, in the Context of Planned Conservation, through Historical Mosques of Kocaeli: Coban Mustafa Pasa Mosque, Fevziye Mosque and Pertev Pasa Mosque” funded by TUBITAK. It is aimed to reveal active deteriorations on building elements generated by unwanted effects of structural and climatic conditions, historical interventions, and modifications by monitoring the variation of surface temperature and humidity by IRT visualization method which is an important non- destructive process for investigation of monuments in the conservation field in the context of planned conservation. It is also concluded that in-situ monitoring process via IRT through different climatic conditions give substantial information on the behaviour of the envelope to the physical environmental conditions by observation of thermal performance, degradations. However, it is obvious that monitoring of historical buildings cannot be pursued by implementing a single non-destructive technique to have complete data of the structure.

Keywords: IRT, non-destructive test, planned conservation, mosque

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Authors: Hamidreza Akbari

Abstract:

In this paper, for detection of inclined eccentricity in an induction motor, time–frequency analysis of the stator startup current is carried out. For this purpose, the discrete wavelet transform is used. Data are obtained from simulations, using winding function approach. The results show the validity of the approach for detecting the fault and discriminating with respect to other faults.

Keywords: induction machine, fault, DWT, electric

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Authors: Gadiri Sabiha

Abstract:

Introduction: Current allergy diagnostic tools using Multiplex technology have made it possible to increase the efficiency of the search for specific IgE. This opportunity is provided by the newly developed “Alex Biochip”, consisting of a panel of 282 allergens in native and molecular form, a CCD inhibitor, and the potential for detecting cross-reactive allergens. We evaluated the performance of this technology in detecting cross-reactivity in previously explored patients. Material/Method: The sera of 39 patients presenting sensitization and polysensitization profiles were explored. The search for specific IgE is carried out by the Alex ® IgE Biochip, and the results are analyzed by nature and by molecular family of allergens using specific software. Results/Discussion: The analysis gave a particular profile of cross-reactivity allergens: 33% for the Ole e1 family, 31% for NPC2, 26% for storage proteins, 20% for Tropomyosin, 10% for LTPs, 10% for Arginine Kinase and 10% for Uteroglobin CCDs were absent in all patients. The “Ole e1” allergen is responsible for a pollen-pollen cross allergy. The storage proteins found and LTP are not species-specific, causing cross-pollen-food allergy. The nDer p2 of the NPC2 family is responsible for cross-reactivity between mite species. Conclusion: The cross-reactivities responsible for mixed syndromes at diagnosis in our patients were dominated by pollen-pollen and pollen-food syndromes. They allow the identification of severity factors linked to the prognosis and the best-adapted immunotherapy.

Keywords: specific IgE, allergy, cross reactivity, molecular allergens

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Authors: Hadj Sahraoui Omar, Kebir Lahcen Wahib, Bennia Ahmed

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Interferometric Synthetic Aperture Radar (InSAR) coherence is a crucial parameter for accurately monitoring ground deformation and environmental changes. However, coherence can be degraded by various factors such as temporal decorrelation, atmospheric disturbances, and geometric misalignments, limiting the reliability of InSAR measurements (Omar Hadj‐Sahraoui and al. 2019). To address this challenge, we propose an innovative hybrid approach that combines artificial intelligence (AI) with advanced filtering techniques to optimize interferometric coherence in InSAR data. Specifically, we introduce a Convolutional Neural Network (CNN) integrated with the Lee filter to enhance the performance of radar interferometry. This hybrid method leverages the strength of CNNs to automatically identify and mitigate the primary sources of decorrelation, while the Lee filter effectively reduces speckle noise, improving the overall quality of interferograms. We develop a deep learning-based model trained on multi-temporal and multi-frequency SAR datasets, enabling it to predict coherence patterns and enhance low-coherence regions. This hybrid CNN-SAR with Lee filtering significantly reduces noise and phase unwrapping errors, leading to more precise deformation maps. Experimental results demonstrate that our approach improves coherence by up to 30% compared to traditional filtering techniques, making it a robust solution for challenging scenarios such as urban environments, vegetated areas, and rapidly changing landscapes. Our method has potential applications in geohazard monitoring, urban planning, and environmental studies, offering a new avenue for enhancing InSAR data reliability through AI-powered optimization combined with robust filtering techniques.

Keywords: CNN-SAR, Lee Filter, hybrid optimization, coherence, InSAR phase unwrapping, speckle noise reduction

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