Search results for: Fourier transform infrared

Authors: Abdullah H. Özcan, Dilara Hisar, Yetkin Sayar, Cem Ünsalan

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In this study, an automated building and tree detection method is proposed using DSM data and true orthophoto image. A multiscale matched filtering is used on DSM data. Therefore, first watershed transform is applied. Then, Otsu’s thresholding method is used as an adaptive threshold to segment each watershed region. Detected objects are masked with NDVI to separate buildings and trees. The proposed method is able to detect buildings and trees without entering any elevation threshold. We tested our method on ISPRS semantic labeling dataset and obtained promising results.

Keywords: building detection, local maximum filtering, matched filtering, multiscale

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Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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Authors: Ouardi Okkacha, Kaarour Abedlkrim, Meskine Mohamed

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The effective Hamiltonians are widely used in molecular spectroscopy for the interpretation of the vibration-rotation spectra. Their construction is an ambiguous procedure due to the existence of unitary transformations that change the effective Hamiltonian but do not change its eigenvalues. As a consequence of this ambiguity, it may happen that some parameters of effective Hamiltonians cannot be recovered from experimental data in a unique way. The type of admissible transformations which keeps the operator form of the effective Hamiltonian unaltered and the number of empirically determinable parameters strongly depend on the symmetry type of a molecule (asymmetric top, spherical top, and so on) and on the degeneracy of the vibrational state. In this work, we report the study of the ambiguity of effective Hamiltonian for the fundamental degenerate states v3 of the Molecule 12CD4.

Keywords: 12CD4, high-resolution infrared spectra, tetrahedral tensorial formalism, vibrational states, rovibrational line position analysis, XTDS, SPVIEW

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Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

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In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest

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Authors: Fengjuan Wang, Azilawati Jamaludin

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Developmental Dyscalculia (DD) is defined as a particular learning difficulty with continuous challenges in learning requisite math skills that cannot be explained by intellectual disability or educational deprivation. Recent studies have increasingly recognized that DD is a heterogeneous, instead of monolithic, learning disorder with not only cognitive and behavioral deficits but so too neural dysfunction. In recent years, neuroimaging studies employed group comparison to explore the neural underpinnings of DD, which contradicted the heterogenous nature of DD and may obfuscate critical individual differences. This research aimed to investigate the neural heterogeneity of DD using case studies with functional near-infrared spectroscopy (fNIRS). A total of 54 aged 6-7 years old of children participated in this study, comprising two comprehensive cognitive assessments, an 8-minute resting state, and an 8-minute one-digit addition task. Nine children met the criteria of DD and scored at or below 85 (i.e., the 16th percentile) on the Mathematics or Math Fluency subtest of the Wechsler Individual Achievement Test, Third Edition (WIAT-III) (both subtest scores were 90 and below). The remaining 45 children formed the typically developing (TD) group. Resting-state data and brain activation in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), and intraparietal sulcus (IPS) were collected for comparison between each case and the TD group. Graph theory was used to analyze the brain network under the resting state. This theory represents the brain network as a set of nodes--brain regions—and edges—pairwise interactions across areas to reveal the architectural organizations of the nervous network. Next, a single-case methodology developed by Crawford et al. in 2010 was used to compare each case’s brain network indicators and brain activation against 45 TD children’s average data. Results showed that three out of the nine DD children displayed significant deviation from TD children’s brain indicators. Case 1 had inefficient nodal network properties. Case 2 showed inefficient brain network properties and weaker activation in the IFG and IPS areas. Case 3 displayed inefficient brain network properties with no differences in activation patterns. As a rise above, the present study was able to distill differences in architectural organizations and brain activation of DD vis-à-vis TD children using fNIRS and single-case methodology. Although DD is regarded as a heterogeneous learning difficulty, it is noted that all three cases showed lower nodal efficiency in the brain network, which may be one of the neural sources of DD. Importantly, although the current “brain norm” established for the 45 children is tentative, the results from this study provide insights not only for future work in “developmental brain norm” with reliable brain indicators but so too the viability of single-case methodology, which could be used to detect differential brain indicators of DD children for early detection and interventions.

Keywords: brain activation, brain network, case study, developmental dyscalculia, functional near-infrared spectroscopy, graph theory, neural heterogeneity

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Authors: Nazmi Mat Nawi, Muhamad Najib Mohamad Nor, Che Dini Maryani Ishkandar

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This study was conducted to evaluate the capability of spectroscopic methods to detect the presence of pesticide residues on leaf mustard. A total of 105 leaf mustard used were divided into five batches, four batches were treated with four different types of pesticides whereas one batch with no pesticide applied. Spectral data were obtained using visible shortwave near infrared spectrometer (VSWNIRS) which is Ocean Optics HR4000 High-resolution Miniature Fiber Optic Spectrometer. Reflectance value was collected to determine the difference between one pesticide to the other. The obtained spectral data were pre-processed for optimum performance. The effective wavelength of approximate 880 nm, 675-710 nm also 550 and 700 nm indicates the overtones -CH stretching vibration, tannin, also chlorophyll content present in the leaf mustard respectively. This study has successfully demonstrated that the spectroscopic method was able to differentiate between leaf mustard sample with and without pesticide residue.

Keywords: detect, leaf mustard, non-destructive, pesticide residue

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Authors: Bingquan Shen

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Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

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Authors: Simone B. K. Aires, Cinthia O. de A. Freitas, Luiz E. S. Oliveira

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This paper contributes to the CBIR systems applied to trademark retrieval. The proposed model includes aspects from visual perception of the shapes, by means of feature extractor associated to a non-symmetrical perceptual zoning mechanism based on the Principles of Gestalt. Thus, the feature set were performed using Scale Invariant Feature Transform (SIFT). We carried out experiments using four different zonings strategies (Z = 4, 5H, 5V, 7) for matching and retrieval tasks. Our proposal method achieved the normalized recall (Rn) equal to 0.84. Experiments show that the non-symmetrical zoning could be considered as a tool to build more reliable trademark retrieval systems.

Keywords: CBIR, Gestalt, matching, non-symmetrical zoning, SIFT

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Authors: Shashank Patidar, Sumit Kumar, Atul Srivastava, Suneet Singh

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Present work is concerned with the numerical investigation of thermal response of biological tissues during laser-based photo-thermal therapy for destroying cancerous/abnormal cells with minimal damage to the surrounding normal cells. Light propagation through the biological sample is mathematically modelled by transient radiative transfer equation. In the present work, application of the Lattice Boltzmann Method is extended to analyze transport of short-pulse radiation in a participating medium.In order to determine the two-dimensional temperature distribution inside the tissue medium, the RTE has been coupled with Penne’s bio-heat transfer equation based on Fourier’s law by several researchers in last few years.

Keywords: lattice Boltzmann method, transient radiation transfer equation, dual phase lag model

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Authors: Lina Paola Orozco Marin, Yuliet Montoya Osorio, John Bustamante Osorno

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Ischemic events can culminate in acute myocardial infarction by irreversible cardiac lesions that cannot be restored due to the limited regenerative capacity of the heart. Cell therapy seeks to replace these injured or necrotic cells by transplanting healthy and functional cells. The therapeutic alternatives proposed by tissue engineering and cardiovascular regenerative medicine are the use of biomaterials to mimic the native extracellular medium, which is full of proteins, proteoglycans, and glycoproteins. The selected biomaterials must provide structural support to the encapsulated cells to avoid their migration and death in the host tissue. In this context, the present research work focused on developing a natural thermosensitive hydrogel, its physical and chemical characterization, and the determination of its biocompatibility in vitro. The hydrogel was developed by mixing hydrolyzed bovine and porcine collagen at 2% w/v, chitosan at 2.5% w/v, and beta-glycerolphosphate at 8.5% w/w and 10.5% w/w in magnetic stirring at 4°C. Once obtained, the thermosensitivity and gelation time were determined, incubating the samples at 37°C and evaluating them through the inverted tube method. The morphological characterization of the hydrogels was carried out through scanning electron microscopy. Chemical characterization was carried out employing infrared spectroscopy. The biocompatibility was determined using the MTT cytotoxicity test according to the ISO 10993-5 standard for the hydrogel’s precursors using the fetal human ventricular cardiomyocytes cell line RL-14. The RL-14 cells were also seeded on the top of the hydrogels, and the supernatants were subculture at different periods to their observation under a bright field microscope. Four types of thermosensitive hydrogels were obtained, which differ in their composition and concentration, called A1 (chitosan/bovine collagen/beta-glycerolphosphate 8.5%w/w), A2 (chitosan/porcine collagen/beta-glycerolphosphate 8.5%), B1 (chitosan/bovine collagen/beta-glycerolphosphate 10.5%) and B2 (chitosan/porcine collagen/beta-glycerolphosphate 10.5%). A1 and A2 had a gelation time of 40 minutes, and B1 and B2 had a gelation time of 30 minutes at 37°C. Electron micrographs revealed a three-dimensional internal structure with interconnected pores for the four types of hydrogels. This facilitates the exchange of nutrients, oxygen, and the exit of metabolites, allowing to preserve a microenvironment suitable for cell proliferation. In the infrared spectra, it was possible to observe the interaction that occurs between the amides of polymeric compounds with the phosphate groups of beta-glycerolphosphate. Finally, the biocompatibility tests indicated that cells in contact with the hydrogel or with each of its precursors are not affected in their proliferation capacity for a period of 16 days. These results show the potential of the hydrogel to increase the cell survival rate in the cardiac cell therapies under investigation. Moreover, the results lay the foundations for its characterization and biological evaluation in both in vitro and in vivo models.

Keywords: cardiac cell therapy, cardiac ischemia, natural polymers, thermosensitive hydrogel

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Authors: Daniella R. Mulinari, Araujo J. F. Marina, Gabriella S. Lopes

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Natural fibers are used in polymer composites to improve mechanical properties, substituting inorganic reinforcing agents produced by non-renewable resources. The present study investigates the tensile, flexural and impact behaviors of palm fibers-high density polyethylene (HDPE) composite as a function of volume fraction. The surface of the fibers was modified by mercerization treatments to improve the wetting behavior of the apolar HDPE. The treatment characterization was obtained by scanning electron microscopy, X-Ray diffraction and infrared spectroscopy. Results evidence that a good adhesion interfacial between fibers-matrix causing an increase strength and modulus flexural as well as impact strength in the modified fibers/HDPE composites when compared to the pure HDPE and unmodified fibers reinforced composites.

Keywords: palm fibers, polymer composites, mechanical properties, high density polyethylene (HDPE)

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Authors: Somkait Udomhunsakul

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In this paper, a multi-focus image fusion method using Spatial Frequency Measurements (SFM) and Wavelet Packet was proposed. The proposed fusion approach, firstly, the two fused images were transformed and decomposed into sixteen subbands using Wavelet packet. Next, each subband was partitioned into sub-blocks and each block was identified the clearer regions by using the Spatial Frequency Measurement (SFM). Finally, the recovered fused image was reconstructed by performing the Inverse Wavelet Transform. From the experimental results, it was found that the proposed method outperformed the traditional SFM based methods in terms of objective and subjective assessments.

Keywords: multi-focus image fusion, wavelet packet, spatial frequency measurement

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Authors: Khalifa Al Baloushi, Hongwei Zhang, Terrence Perera

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Over the last few decades, the government of the UAE has been taking actions to consolidate defense manufacturing entities with the view to build a coherent and modern defense manufacturing base. Whilst these actions have significantly improved the overall capabilities of defense manufacturing; further opportunities exist to radically transform the sector. A comprehensive literature review and data collected from a survey identified three potential areas of improvements, (a) integration of Industry 4.0 technologies and other smart technologies, (b) stronger engagement of small and Medium-sized defense manufacturing companies and (c) Enhancing the national defense policies by embedding best practices from other nations. This research paper presents the design and development of a conceptual framework for the UAE defense industrial ecosystem.

Keywords: industry 4.0, defense manufacturing, eco-systems, integration

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Authors: A. Albar, D. B. Granato, U. Schwingenschlogl

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Tin monoxide (SnO) has promising properties to be applied as a p-type semiconductor in transparent electronics. To this end, it is necessary to understand the behavior of defects in order to control them. We use density functional theory to study native defects of SnO under tensile and compressive strain. We show that Sn vacancies are more stable under tension and less stable under compression, irrespectively of the charge state. In contrast, O vacancies behave differently for different charge. It turns out that the most stable defect under compression is the +1 charged O vacancy in a Sn-rich environment and the charge neutral O interstitial in an O-rich environment. Therefore, compression can be used to transform SnO from an n-type into un-doped semiconductor.

Keywords: native defects, ab-initio, point defect, tension, compression, semiconductor

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Authors: M. Riaz, Inamur Rehman, Abhishek Sharma

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The present work is the development of an experimental method for determining the thermal diffusivity variations with temperature of selected regular shaped solid fruits and vegetables subjected to forced convection cooling. Experimental investigations were carried on the sample chosen (potato and brinjal), which is approximately of spherical geometry. The variation of temperature within the food product is measured at several locations from centre to skin, under forced convection environment using a deep freezer, maintained at -10°C.This method uses one dimensional Fourier equation applied to regular shapes. For this, the experimental temperature data obtained from cylindrical and spherical shaped products during pre-cooling was utilised. Such temperature and thermal diffusivity profiles can be readily used with other information such as degradation rate, etc. to evaluate thermal treatments based on cold air cooling methods for storage of perishable food products.

Keywords: thermal diffusivity, skin temperature, precooling, forced convection, regular shaped

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Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

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Authors: Badis Kahouadji, Lakhdar Guerbous, Lyes Lamiri

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For many years, the luminescent materials were investigated principally in the infrared and visible areas, because the ultraviolet (UV) and especially in vacuum Ultraviolet (VUV) are technically more difficult to explore, especially absence of applications requiring of materials suitable to short wavelengths.Recent necessary, related to the development of certain technologies, encouraged research in these spectra domains. It is in this context that the 4Fn-4Fn-1 5d transitions of rare earth in insulating materials, lying in the UV and VUV, are the aim of large number of studies. These studies relate in particular to search for new scintillator materials used for spectroscopy and X-ray, ɤ, as well as medical imaging. The 4Fn- 4Fn-15d transitions of the rare earth dependent to the host-matrix, several matrices ions were used to study these transitions, in this work we are suggeting to study on a very specific class of inorganic scintillators that are orthophosphate doped with rare earth ions, this study focused on the Pr3+ concentration on the structural and optical properties of Pr3+ doped YPO4 (yttriumorthophosphate) with powder form prepared by the Sol Gel method.

Keywords: rare earth, scintillator, YPO4:Pr3+ nanophosphors, sol gel, 4Fn-4Fn-15d transitions

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Authors: Mehmet Kargaci

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It is more important to access information than to get the correct information and to transform it to the knowledge in a proper way. Every person, organizations or governments who have the knowledge now become the target. Cyber security involves the range of measures to be taken from individual to the national level. The National institutions refer to academic, military and major public and private institutions, which are very important for the national security. Thus they need further cyber security measures. It appears that the traditional cyber security measures in the national level are alone not sufficient, while the individual measures remain in a restricted level. It is evaluated that the most appropriate method for preventing the cyber vulnerabilities rather than existing measures are to develop institutional measures. This study examines the cyber security measures to be taken, especially in the national institutions.

Keywords: cyber defence, information, critical infrastructure, security

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Authors: Murtala Marafa

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It’s been 50 years now since we began the desperate search for a genuine all round development as a nation. Painfully though, like a wild goose chase, the search for that promised land had remain elusive. In this piece, recourse is made to the sound administrative qualities of the 19th century Sokoto Caliphate leaders. It enabled them to administer the vast entity on the basis of mutual peace and justice. It also guaranteed a just political order built on a sound and viable economy. The paper is of the view that if the Nigerian society can allow for a replication of such moral virtues as exemplified by the founding fathers of the Caliphate, Nigeria could transform into a politically coherent and economically viable nation aspired by all.

Keywords: administration, religion, sokoto caliphate, moral teachings

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Authors: Veronica Onyemauwa

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This research work examines the socio-ethical issues embedded in resource management and wealth creation in Nigeria, using Akwa Ibom State as a case study. The work is poised to proffer answers to the problematic questions raised, “why is the wealth of Akwa Ibom State not prudently managed, and wastages curbed in order to cater for the satisfaction of the indigent citizens, as Jesus Christ did in the feeding of five thousand people (John 6:12) ? Could ethical and responsible resource management not solve the paradox of poverty stricken people of Akwa Ibom in a rich economy? What ought to be done to better the lot of Akwa Ibomites? The research adopts phenomenological and sociological research methodology with primary and secondary sources of information to explore the socio-ethical issues embedded in resource management and wealth creation in Akwa Ibom State. Findings revealed that, reckless exploitation and mismanagement of the rich natural and human resources of Akwa Ibom State have spelt doom to the economic progress and survival of Akwa Ibomites in particular and Nigerians in general. Hence, hunger and poverty remain adversaries to majority of the people. Again, the culture of diversion of funds and squandermania institutionalized within the confine of Akwa Ibom State government, deter investment in economic enterprises, job and wealth creation that would have yielded economic dividends for Akwa Ibomites. These and many other unwholesome practices are responsible for the present deplorable condition of Akwa Ibom State in particular and Nigerian society in general. As a way out of this economic quagmire, it is imperative that, every unwholesome practice within the State be tackled more proactively and innovatively in the interest of the masses through responsible resource management and wealth creation. It is believed that, an effective leadership, a statesman with vision and commitment would transform the abundant resources to achieve meaningful development, create wealth and reduce poverty. Ethical leadership is required in all the tiers of government and public organizations to transform resources into more wealth. Thus, this paper advocates for ethics of virtue: a paradigm shift from exploitative leadership style to productive leadership style; change from atomistic human relation to corporative human relation; change from being subsistence to abundant in other to maximize the available resources in the State. To do otherwise is unethical and lack moral justification.

Keywords: corrective, mismanagement, resources, virtue ethics

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Authors: Aissa Belmeguenai, Oulaya Berrak, Khaled Mansouri

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In this work, efficiency implementation and security evaluation of the keystream generator of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written with MATLAB.7.5. First of all, two different original images are used to validate the proposed design. The developed program is used to transform the original images data into digital image file. Finally, the proposed program is implemented to encrypt and decrypt images data. Several tests are done to prove the design performance, including visual tests and security evaluation.

Keywords: Achterbahn-128, keystream generator, stream cipher, image encryption, security analysis

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Authors: Bokolombe Pitchou Ngoy, John Mack, Tebello Nyokong

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Synthesis and photochemical studies of BODIPY dyes have been investigated in this work in order to have a broad benchmark of this functionalized photosensitizer for biological applications such as photodynamic therapy or antimicrobial activity. The common acid catalyzed synthetic method was used, and BODIPY dyes were obtained in quite a good yield (25 %) followed by bromination and Knoevenagel condensation to afford the BODIPY dyes conjugated with maximum absorbance in the near-infrared region of the electromagnetic spectrum. The fluorescence lifetimes, fluorescence quantum yield, and Singlet oxygen quantum yield of the conjugated BODIPY dyes were determined in different solvents by using Time Correlation Single Photon Counting (TCSPC), fluorimeter, and Laser Flash Photolysis respectively. It was clearly shown that the singlet oxygen quantum yield was higher in THF followed by DMSO compared to another solvent. The same trend was observed for the fluorescence lifetimes.

Keywords: BODIPY, photodynamic therapy, photosensitizer, singlet oxygen

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Authors: Ruzanna Muradyan

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Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

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Authors: Srushti R. Joshi, Ujjwal Rakesh, Spoorthi Sripad

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The rapid advancement of remote sensing technologies has revolutionized plant health monitoring, offering valuable insights for precision agriculture and environmental management. This paper presents a comprehensive comparative analysis between the widely employed normalized difference vegetation index (NDVI) and state-of-the-art hyperspectral sensors in the context of plant health assessment. The study aims to elucidate the weigh ups of spectral resolution. Employing a diverse range of vegetative environments, the research utilizes simulated datasets to evaluate the performance of NDVI and hyperspectral sensors in detecting subtle variations indicative of plant stress, disease, and overall vitality. Through meticulous data analysis and statistical validation, this study highlights the superior performance of hyperspectral sensors across the parameters used.

Keywords: normalized difference vegetation index, hyperspectral sensor, spectral resolution, infrared

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Authors: Kemi Olalekan Oduntan

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Transformation is a strong word that portends a radical, structural and basic reappraisal of the basic assumptions that underline our economic reform and developmental efforts. The challenges before government are how to move the nation away from an oil-dominated economy, institute the basics for a private sector-driven economy, build the local economy on international best practices, transform a passive oil industry to a more pro-active one and reposition the country along the lines of a more decentralized federalism. But beyond this, Nigeria is faced with management and leadership challenges to contend with building an efficient and effective polity, inspiring a shared vision, remodeling a corrupt polity, redefining the essentials of transformational leadership and creating Nigerian dream that will inspire patriotism and commitment in the citizenry.

Keywords: economic, economic growth, patriotism, polity, transformational

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Authors: Mohamed H. El-Newehy, Sameh M. Osman, Moamen S. Refat, Salem S. Al-Deyab, Ayman El-Faham

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The two copolymers itaconic acid-methyl methacrylate and itaconic acid-acrylamide have been prepared in different ratio by radical copolymerization in the presence of azobisisobutyronitrile (AIBN) as initiator and using 2-butanone as reaction medium using microwave irradiation. The microwave technique is safe, fast, and gives high yield of the products with high purity in an optimum time, comparing to the traditional conventional heating. All the prepared copolymers were characterized by FT-IR, thermal analysis and elemental microanalysis. The itaconic acid-based copolymers showed a good sensitivity in alkaline media for scavenging Cu (II) and Pb (II). The chelation behavior of both Cu (II) and Pb (II) complexes were checked using FT-IR, thermogravimetric analysis (TGA), and differential scanning calorimetery (DSC). The infrared data are in a good agreement with the coordination through carboxylate-to-metal, in which the copolymers acting as a bidentate ligand.

Keywords: microwave synthesis, itaconic acid, copolymerization, scavenging, thermal stability

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Authors: Tanish Mittal, Preyansh Agrawal, Esha Pahwa, Aarya Makwana

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Multi-Scale and U-shaped Networks are widely used in various image restoration problems, including deblurring. Keeping in mind the wide range of applications, we present a comparison of these architectures and their effects on image deblurring. We also introduce a new block called as NFResblock. It consists of a Fast Fourier Transformation layer and a series of modified Non-Linear Activation Free Blocks. Based on these architectures and additions, we introduce NFResnet and NFResnet+, which are modified multi-scale and U-Net architectures, respectively. We also use three differ-ent loss functions to train these architectures: Charbonnier Loss, Edge Loss, and Frequency Reconstruction Loss. Extensive experiments on the Deep Video Deblurring dataset, along with ablation studies for each component, have been presented in this paper. The proposed architectures achieve a considerable increase in Peak Signal to Noise (PSNR) ratio and Structural Similarity Index (SSIM) value.

Keywords: multi-scale, Unet, deblurring, FFT, resblock, NAF-block, nfresnet, charbonnier, edge, frequency reconstruction

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

Abstract:

The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Chien-Lin Wang, Cha-Ling Ko, Tainsong Chen

Abstract:

Pulse wave velocity (PWV) of blood flow provides important information of vessel property and blood pressure which can be used to assess cardiovascular disease. However, the above measurements need expensive equipment, such as Doppler ultrasound, MRI, angiography etc. The photoplethysmograph (PPG) signals are commonly utilized to detect blood volume changes. In this study, two infrared (IR) probes are designed and placed at a fixed distance from finger base and fingertip. An analog circuit with automatic gain adjustment is implemented to get the stable original PPG signals from above two IR probes. In order to obtain the time delay precisely between two PPG signals, we obtain the pulse transit time from the second derivative of the original PPG signals. To get a portable, wireless and low power consumption PWV measurement device, the low energy Bluetooth 4.0 (BLE) and the microprocessor (Cortex™-M3) are used in this study. The PWV is highly correlated with blood pressure. This portable device has potential to be used for continuous blood pressure monitoring.

Keywords: pulse wave velocity, photoplethysmography, portable device, biomedical engineering

Procedia PDF Downloads 527

Authors: Raphael M. Rettig, Tessa C. Flatten

Abstract:

This empirical study answer calls for research on Absorptive Capacity and Process Innovation. Due to the fourth industrial revolution, manufacturing companies face the biggest disruption of their production processes since the rise of advanced manufacturing technologies in the last century. Therefore, process innovation will become a critical task to master in the future for many manufacturing firms around the world. The general ability of organizations to acquire, assimilate, transform, and exploit external knowledge, known as Absorptive Capacity, was proven to positively influence product innovation and is already conceptually associated with process innovation. The presented research provides empirical evidence for this influence. The findings are based on an empirical analysis of 732 companies from seven leading and emerging countries: Brazil, China, France, Germany, India, Japan, and the United States of America. The answers to the survey were collected in February and March 2018 and addressed senior- and top-level management with a focus on operations departments. The statistical analysis reveals the positive influence of potential and Realized Absorptive Capacity on successful process innovation taking the implementation of new digital manufacturing processes as an example. Potential Absorptive Capacity covering the acquisition and assimilation capabilities of an organization showed a significant positive influence (β = .304, p < .05) on digital manufacturing implementation success and therefore on process innovation. Realized Absorptive Capacity proved to have significant positive influence on process innovation as well (β = .461, p < .01). The presented study builds on prior conceptual work in the field of Absorptive Capacity and process innovation and contributes theoretically to ongoing research in two dimensions. First, the already conceptually associated influence of Absorptive Capacity on process innovation is backed by empirical evidence in a broad international context. Second, since Absorptive Capacity was measured with a focus on new product development, prior empirical research on Absorptive Capacity was tailored to the research and development departments of organizations. The results of this study highlight the importance of Absorptive Capacity as a capability in mechanical engineering and operations departments of organizations. The findings give managers an indication of the importance of implementing new innovative processes into their production system and fostering the right mindset of employees to identify new external knowledge. Through the ability to transform and exploit external knowledge, own production processes can be innovated successfully and therefore have a positive influence on firm performance and the competitive position of their organizations.

Keywords: absorptive capacity, digital manufacturing, dynamic capabilities, process innovation

Procedia PDF Downloads 143