Search results for: modal identification

Authors: Siti Aishah Hasbullah

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Studies on identification of pork content in food have grown rapidly to meet the Halal food standard in Malaysia. The used mitochondria DNA (mtDNA) approaches for the identification of pig species is thought to be the most precise marker due to the mtDNA genes are present in thousands of copies per cell, the large variability of mtDNA. The standard method commonly used for DNA detection is based on polymerase chain reaction (PCR) method combined with gel electrophoresis but has major drawback. Its major drawbacks are laborious, need longer time and toxic to handle. Therefore, the need for simplicity and fast assay of DNA is vital and has triggered us to develop DNA biosensors for porcine DNA detection. Therefore, the aim of this project is to develop electrochemical DNA biosensor based on ruthenium (II) complex, [Ru(bpy)2(p-PIP)]2+ as DNA hybridization label. The interaction of DNA and [Ru(bpy)2(p-HPIP)]2+ will be studied by electrochemical transduction using Gold Screen-Printed Electrode (GSPE) modified with gold nanoparticles (AuNPs) and succinimide acrylic microspheres. The electrochemical detection by redox active ruthenium (II) complex was measured by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The results indicate that the interaction of [Ru(bpy)2(PIP)]2+ with hybridization complementary DNA has higher response compared to single-stranded and mismatch complementary DNA. Under optimized condition, this porcine DNA biosensor incorporated modified GSPE shows good linear range towards porcine DNA.

Keywords: gold, screen printed electrode, ruthenium, porcine DNA

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Authors: J. R. Ashrapov, G. A. Alihodzhaeva, D. E. Abdullaev, N. R. Kadirbekov

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Diagnosis of brain tumors is one of the challenges, as several central nervous system diseases run the same symptoms. Modern diagnostic techniques such as CT, MRI helps to significantly improve the surgery in the operating period, after surgery, after allowing time to identify postoperative complications in neurosurgery. Purpose: To study the MRI characteristics and localization of brain tumors in children and to detect the postoperative complications in the postoperative period. Materials and methods: A retrospective study of treatment of 62 children with brain tumors in age from 2 to 5 years was performed. Results of the review: MRI scan of the brain of the 62 patients 52 (83.8%) case revealed a brain tumor. Distribution on MRI of brain tumors found in 15 (24.1%) - glioblastomas, 21 (33.8%) - astrocytomas, 7 (11.2%) - medulloblastomas, 9 (14.5%) - a tumor origin (craniopharyngiomas, chordoma of the skull base). MRI revealed the following characteristic features: an additional sign of the heterogeneous MRI signal of hyper and hypointensive T1 and T2 modes with a different perifocal swelling degree with involvement in the process of brain vessels. The main objectives of postoperative MRI study are the identification of early or late postoperative complications, evaluation of radical surgery, the identification of the extended-growing tumor that (in terms of 3-4 weeks). MRI performed in the following cases: 1. Suspicion of a hematoma (3 days or more) 2. Suspicion continued tumor growth (in terms of 3-4 weeks). Conclusions: Magnetic resonance tomography is a highly informative method of diagnostics of brain tumors in children. MRI also helps to determine the effectiveness and tactics of treatment and the follow up in the postoperative period.

Keywords: brain tumors, children, MRI, treatment

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Authors: Manveen Singh

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Since the very advent of law enforcement, eyewitness testimony has played a pivotal role in identifying, arresting and convicting suspects. Reliant heavily on the accuracy of human memory, nothing seems to carry more weight with the judiciary than the testimony of an actual witness. The acceptance of eyewitness testimony as a substantive piece of evidence lies embedded in the assumption that the human mind is adept at recording and storing events. Research though, has proven otherwise. Having carried out extensive study in the field of eyewitness testimony for the past 40 years, psychologists have concluded that human memory is fragile and needs to be treated carefully. The question that arises then, is how reliable is eyewitness testimony? The credibility of eyewitness testimony, simply put, depends on several factors leaving it reliable at times while not so much at others. This is further substantiated by the fact that as per scientific research, over 75 percent of all eyewitness testimonies may stand in error; quite a few of these cases resulting in life sentences. Although the advancement of scientific techniques, especially DNA testing, helped overturn many of these eyewitness testimony-based convictions, yet eyewitness identifications continue to form the backbone of most police investigations and courtroom decisions till date. What then is the solution to this long standing concern regarding the accuracy of eyewitness accounts? The present paper shall analyze the linkage between human memory and eyewitness identification as well as look at the various factors governing the credibility of eyewitness testimonies. Furthermore, it shall elaborate upon some best practices developed over the years to help reduce mistaken identifications. Thus, in the process, trace out the changing landscape of eyewitness testimony amidst the evolution of DNA and trace evidence.

Keywords: DNA, eyewitness, identification, testimony, evidence

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have played an indispensable role in controlling illness and death associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global healthcare problem. Many antibiotics had lost their effectiveness since the beginning of the antibiotic era because many bacteria have adapted defenses against these antibiotics. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing require the isolation of the pathogen from a clinical specimen by culturing on the appropriate media (this culturing stage lasts 24 h-first culturing). Then, chosen colonies are grown on media containing antibiotic(s), using micro-diffusion discs (second culturing time is also 24 h) in order to determine its bacterial susceptibility. Other methods, genotyping methods, E-test and automated methods were also developed for testing antimicrobial susceptibility. Most of these methods are expensive and time-consuming. Fourier transform infrared (FTIR) microscopy is rapid, safe, effective and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria; nonetheless, its true potential in routine clinical diagnosis has not yet been established. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The UTI E.coli bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 700 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 90% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E.coli, FTIR, multivariate analysis, susceptibility, UTI

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Authors: Sabitha Rani A., Nagamani V.

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Embelia ribes Burm.f (Family-Myrsinaceae) commonly known as Vidanga or Baibirang, is one of the important medicinal plants of India. The seed extract is reported to be antidiabetic, antitumour, analgesic, anti-inflammatory, antispermatogenic, free radical scavenging activities and widely used in more than 75 Ayurvedic commercial formulations. Among the 100 different species of Embelia, E. ribes is considered as a major source of Embelin, a bioactive compound. Because of high demand and low availability, the seeds of E. ribes are substituted with many cheaper alternatives. Therefore, the present study of RAPD-PCR analysis was undertaken to develop molecular markers for identification of E. ribes. A total of 13 different seed samples of Embelia were collected from different agro-climatic regions of India. The seeds of E.ribes were collected from Kalpetta, Kerala and three different seed samples were collected from traders of Odisha, Madhya Pradesh, Maharastra. The other nine seed samples were collected from local traders which they have collected from different regions of India. Genomic DNA was isolated from different seed samples E. ribes and RAPD-PCR was performed on 13 different seed samples using 47 random primers. Out of all the primers, only 22 primers produced clear and highly-reproducible banding patterns. The 22 selected RAPD primers generated a total of 280 alleles with an average of 12 alleles per primer pair. In the present study, we have identified three RAPD-PCR markers i.e. OPF5_480 bp, OPH11_520 bp and OPH4_530 bp which can be used for genetic fingerprinting of E. ribes. This methodology can be employed for identification of original E. ribes and also distinguishing it from other substitutes and adulterants.

Keywords: Embelia ribes, RAPD-PCR, primers, genetic analysis

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Authors: Md. Khayrul Bashar, Md. Saiful Islam, Kimiko Yamashita, Yano Midori

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Despite having some progress in human authentication, conventional biometrics (e.g., facial features, fingerprints, retinal scans, gait, voice patterns) are not robust against falsification because they are neither confidential nor secret to an individual. As a non-invasive tool, electrocardiogram (ECG) has recently shown a great potential in human recognition due to its unique rhythms characterizing the variability of human heart structures (chest geometry, sizes, and positions). Moreover, ECG has a real-time vitality characteristic that signifies the live signs, which ensure legitimate individual to be identified. However, the detection accuracy of the current ECG-based methods is not sufficient due to a high variability of the individual’s heartbeats at a different instance of time. These variations may occur due to muscle flexure, the change of mental or emotional states, and the change of sensor positions or long-term baseline shift during the recording of ECG signal. In this study, a new method is proposed for human identification, which is based on the extraction of the local roughness of ECG heartbeat signals. First ECG signal is preprocessed using a second order band-pass Butterworth filter having cut-off frequencies of 0.00025 and 0.04. A number of local binary patterns are then extracted by applying a moving neighborhood window along the ECG signal. At each instant of the ECG signal, the pattern is formed by comparing the ECG intensities at neighboring time points with the central intensity in the moving window. Then, binary weights are multiplied with the pattern to come up with the local roughness description of the signal. Finally, histograms are constructed that describe the heartbeat signals of individual subjects in the database. One advantage of the proposed feature is that it does not depend on the accuracy of detecting QRS complex, unlike the conventional methods. Supervised recognition methods are then designed using minimum distance to mean and Bayesian classifiers to identify authentic human subjects. An experiment with sixty (60) ECG signals from sixty adult subjects from National Metrology Institute of Germany (NMIG) - PTB database, showed that the proposed new method is promising compared to a conventional interval and amplitude feature-based method.

Keywords: human identification, ECG biometrics, local roughness patterns, supervised classification

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Authors: C. V. Aravinda, H. N. Prakash

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In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.

Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages

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Authors: Vahidreza Mahmoudabadi, Omid Bahar, Mohammad Kazem Jafari

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In many applied engineering problems, structural analysis is usually conducted by assuming a rigid bed, while imposing the effect of structure bed flexibility can affect significantly on the structure response. This article focuses on investigation and evaluation of the effects arising from considering a soil-structure system in evaluation of dynamic characteristics of a steel structure with respect to elastic and inelastic behaviors. The recorded structure acceleration during Taiwan’s strong Chi-Chi earthquake on different floors of the structure was our evaluation criteria. The respective structure is an eight-story steel bending frame structure designed using a displacement-based direct method assuring weak beam - strong column function. The results indicated that different identification methods i.e. reverse Fourier transform or transfer functions, is capable to determine some of the dynamic parameters of the structure precisely, rather than evaluating all of them at once (mode frequencies, mode shapes, structure damping, structure rigidity, etc.). Response evaluation based on the input and output data elucidated that the structure first mode is not significantly affected, even considering the soil-structure interaction effect, but the upper modes have been changed. Also, it was found that the response transfer function of the different stories, in which plastic hinges have occurred in the structure components, provides similar results.

Keywords: bending steel frame structure, dynamic characteristics, displacement-based design, soil-structure system, system identification

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Authors: Érick Aragão Ribeiro, George André Pereira Thé, José Marques Soares

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Several problems in industrial supervision software development projects may lead to the delay or cancellation of projects. These problems can be avoided or contained by using identification methods, analysis and control of risks. These procedures can give an overview of the possible problems that can happen in the projects and what are the immediate solutions. Therefore, we propose a risk management method applied to the teaching and development of industrial supervision software. The method is developed through a literature review and previous projects can be divided into phases of management and have basic features that are validated with experimental research carried out by mechatronics engineering students and professionals. The management is conducted through the stages of identification, analysis, planning, monitoring, control and communication of risks. Programmers use a method of prioritizing risks considering the gravity and the possibility of occurrence of the risk. The outputs of the method indicate which risks occurred or are about to happen. The first results indicate which risks occur at different stages of the project and what risks have a high probability of occurring. The results show the efficiency of the proposed method compared to other methods, showing the improvement of software quality and leading developers in their decisions. This new way of developing supervision software helps students identify design problems, evaluate software developed and propose effective solutions. We conclude that the risk management optimizes the development of the industrial process control software and provides higher quality to the product.

Keywords: supervision software, risk management, industrial supervision, project management

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Authors: Chia-Yi Wu, Jung-Chen Chang, Wen-Yu Hu, Ming-Been Lee

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In nearly all physical health conditions, suicide risk is increased compared to healthy people even after adjustment for age, gender, mental health, and substance use diagnoses. In order to highlight the importance of suicide risk assessment for the inpatients and early identification and engagement for inpatients’ mental health problems, a study was designed aiming at developing a comprehensive psychosomatic nursing engagement (PSNE) model with standardized operation procedures informing how nurses communicate, assess, and engage with the inpatients with emotional distress. The purpose of the study was to promote the gatekeeping role of clinical nurses in performing brief assessment and interventions to detect depression and anxiety symptoms among the inpatients, particularly in non-psychiatric wards. The study will be carried out in a 2000-bed university hospital in Northern Taiwan in 2019. We will select a ward for trial and develop feasible procedures and in-job training course for the nurses to offer mental health care, which will also be validated through professional consensus meeting. The significance of the study includes the following three points: (1) The study targets at an important but less-researched area of PSNE model in the cultural background of Taiwan, where hospital service is highly accessible, but mental health and suicide risk assessment are hardly provided by non-psychiatric healthcare personnel. (2) The issue of PSNE could be efficient and cost-effective in the identification of suicide risks at an early stage to prevent inpatient suicide or to reduce future suicide risk by early treatment of mental illnesses among the high-risk group of hospitalized patients who are more than three-times lethal to suicide. (3) Utilizing a brief tool with its established APP ('The Five-item Brief Symptom Rating Scale, BSRS-5'), we will invent the standardized procedure of PSNE and referral steps in collaboration with the medical teams across the study hospital. New technological tools nested within nursing assessment/intervention will concurrently be invented to facilitate better care quality. The major outcome measurements will include tools for early identification of common mental distress and suicide risks, i.e., the BSRS-5, revised BSRS-5, and the 9-item Concise Mental Health Checklist (CMHC-9). The main purpose of using the CMHC-9 in clinical suicide risk assessment is mainly to provide care and build-up therapeutic relationship with the client, so it will also be used to nursing training highlighting the skills of supportive care. Through early identification of the inpatients’ depressive symptoms or other mental health care needs such as insomnia, anxiety, or suicide risk, the majority of the nursing clinicians would be able to engage in critical interventions that alleviate the inpatients’ suffering from mental health problems, given a feasible nursing input.

Keywords: mental health care, clinical outcome improvement, clinical nurses, suicide prevention, psychosomatic nursing

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Authors: Jingjie Li, Wenjie Hu

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Phraseological units in academic English texts have been a central focus in recent corpus linguistic research. A wide variety of phraseological units have been explored, including collocations, chunks, lexical bundles, patterns, semantic sequences, etc. This paper describes a special category of clause-level phraseological units, namely, Characteristic Sentence Stems (CSSs), with a view to describing their defining criteria and extraction method. CSSs are contiguous lexico-grammatical sequences which contain a subject-predicate structure and which are frame expressions characteristic of academic writing. The extraction of CSSs consists of six steps: Part-of-speech tagging, n-gram segmentation, structure identification, significance of occurrence calculation, text range calculation, and overlapping sequence reduction. Significance of occurrence calculation is the crux of this study. It includes the computing of both the internal association and the boundary independence of a CSS and tests the occurring significance of the CSS from both inside and outside perspectives. A new normalization algorithm is also introduced into the calculation of LocalMaxs for reducing overlapping sequences. It is argued that many sentence stems are so recurrent in academic texts that the most typical of them have become the habitual ways of making meaning in academic writing. Therefore, studies of CSSs could have potential implications and reference value for academic discourse analysis, English for Academic Purposes (EAP) teaching and writing.

Keywords: characteristic sentence stem, extraction method, phraseological unit, the statistical measure

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Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: Andres Pinilla Palacios, Ricardo Tamayo

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Emotional contagion is characterized as an automatic tendency to synchronize behaviors that facilitate emotional convergence among humans. It might thus play a pivotal role to understand the dynamics of key social interactions. However, a few research has investigated its potential mechanisms. We suggest two complementary but independent processes that may underlie emotional contagion. The efficient contagion hypothesis, based on fast and implicit bottom-up processes, modulated by familiarity and spread of activation in the emotional associative networks of memory. Secondly, the emotional contrast hypothesis, based on slow and explicit top-down processes guided by deliberated appraisal and hypothesis-testing. In order to assess these two hypotheses, an experiment with 39 participants was conducted. In the first phase, participants were induced (between-groups) to an emotional state (positive, neutral or negative) using a standardized video taken from the FilmStim database. In the second phase, participants classified and rated (within-subject) the emotional state of 15 faces (5 for each emotional state) taken from the POFA database. In the third phase, all participants were returned to a baseline emotional state using the same neutral video used in the first phase. In a fourth phase, participants classified and rated a new set of 15 faces. The accuracy in the identification and rating of emotions was partially explained by the efficient contagion hypothesis, but the speed with which these judgments were made was partially explained by the emotional contrast hypothesis. However, results are ambiguous, so a follow-up experiment is proposed in which emotional expressions and activation of the sympathetic system will be measured using EMG and EDA respectively.

Keywords: electromyography, emotional contagion, emotional valence, identification of emotions, imitation

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Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: H. M. El-Rafie, A. H. Abou Zeid, R. S. Mohammed, A. A. Sleem

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Acrocarpus is a genus of flowering plants in the legume family Fabaceae which considered as a large and economically important family. This study aimed to investigate the phytoconstituents of the petroleum ether extract (PEE) of Acrocarpus fraxinofolius bark by Gas chromatography coupled with mass spectrometry (GC/MS) analysis of its fractions (fatty acid and unsaponifiable matter). Concerning this, identification of 52 compounds constituting 97.03 % of the total composition of the unsaponifiable matter fraction. Cycloeucalenol was found to be the major compound representing 32.52% followed by 4a, 14a-dimethyl-A8~24(28)-ergostadien (26.50%) and ß-sitosterol(13.74%), furthermore Gas liquid chromatography (GLC) analysis of the sterol fraction revealed the identification of cholesterol (7.22 %), campesterol (13.30 %), stigmasterol (10.00 %) and β - sitosterol (69.48 %). Meanwhile, the identification of 33 fatty acids representing 90.71% of the total fatty acid constituents. Methyl-9,12-octadecadienoate (40.39%) followed by methyl hexadecanoate (23.64%) were found to be the major compounds. On the other hand, column chromatography and Thin layer chromatography (TLC) fractionation of PEE separate the triterpenoid: 21β-hydroxylup-20(29)-en-3-one and β- amyrin which were structurally identified by spectroscopic analysis (NMR, MS and IR). PEE has been biologically evaluated for 1: management of diabetes in alloxan induced diabetic rats 2: cytotoxic activity against four human tumor cell lines (Cervix carcinoma cell line[HELA], Breast carcinoma cell line [MCF7], Liver carcinoma cell line[HEPG2] and Colon carcinoma cell line[HCT-116] 3: hepatoprotective activity against CCl4-induced hepatotoxicity in rats and the activity was studied by assaying the serum marker enzymes like AST, ALT, and ALP. Concerning this, the anti-diabetic activity exhibited by 100mg of PEE extract was 74.38% relative to metformin (100% potency). It also showed a significant anti-proliferative activity against MCF-7 (IC50= 2.35µg), Hela(IC50=3.85µg) and HEPG-2 (IC50= 9.54µg) compared with Doxorubicin as reference drug. The hepatoprotective activity was evidenced by significant decrease in liver function enzymes, i.e. AST, ALT and ALP by (29.18%, 28.26%, and 34.11%, respectively using silymarin as the reference drug, compared to their concentration levels in an untreated group with liver damage induced by CCl₄. This study was performed for the first time on the bark of this species.

Keywords: Acrocarpus fraxinofolius, antidiabetic, cytotoxic, hepatoprotective

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Authors: Josephine Mirador

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Too often, one hears teachers complaining about how uncritical students can be, yet the notion of ‘criticality’ may be subject to variable understandings or interpretations. One challenge facing postgraduate students is the writing of essays responding to a specific reading assignment. Such an essay requires students not only to summarise, but to engage in a discussion of the significant points of the article, pointing out its strengths as well as its weaknesses. This paper presents the results of an investigation on criticality in written assignments of postgraduate students in applied linguistics and TESOL. The guiding questions for this investigation were: -How ‘critical’ are postgraduate students when writing their assignments? -What kind of ‘critical’ comments are they able to offer? A total of 70 essays were analysed, using two sets of corpora in the initial and follow-through phases of the research from three different universities in Asia. The essays were written by MA applied linguistics and TESOL students. Students were told that the response essay should definitely not just summarise, but should offer a reflection or critique on the ideas presented in the subject article. The initial findings from the investigation include: the identification of at least 10 general ‘moves’ each of which has a number of possible specific categories; presence of critique ‘nodes’ as distinguished from ‘support’ comments; and the identification of at least 4 moves as the most recurrent and possibly obligatory categories. This investigation has unearthed a few more questions or issues that are definitely worth investigating as extensions of this research, and will be of interest (most especially) to genre analysts and teachers of writing.

Keywords: criticality, discourse and genre analysis, postgraduate students, applied linguistics

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Authors: O. Ubani, H. I. Atagana, M. S. Thantsha, R. Adeleke

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The oil sludge components (polycyclic aromatic hydrocarbons, PAHs) have been found to be cytotoxic, mutagenic and potentially carcinogenic and microorganisms such as bacteria and fungi can degrade the oil sludge to less toxic compounds such as carbon dioxide, water and salts. In the present study, we isolated different bacteria with PAH-degrading potentials from the co-composting of oil sludge and different animal manure. These bacteria were isolated on the mineral base medium and mineral salt agar plates as a growth control. A total of 31 morphologically distinct isolates were carefully selected from 5 different compost treatments for identification using polymerase chain reaction (PCR) of the 16S rDNA gene with specific primers (16S-P1 PCR and 16S-P2 PCR). The amplicons were sequenced and sequences were compared with the known nucleotides from the gene bank database. The phylogenetical analyses of the isolates showed that they belong to 3 different clades namely Firmicutes, Proteobacteria and Actinobacteria. These bacteria identified were closely related to genera Bacillus, Arthrobacter, Staphylococcus, Brevibacterium, Variovorax, Paenibacillus, Ralstonia and Geobacillus species. The results showed that Bacillus species were more dominant in all treated compost piles. Based on their characteristics these bacterial isolates have high potential to utilise PAHs of different molecular weights as carbon and energy sources. These identified bacteria are of special significance in their capacity to emulsify the PAHs and their ability to utilize them. Thus, they could be potentially useful for bioremediation of oil sludge and composting processes.

Keywords: bioaugmentation, biodegradation, bioremediation, composting, oil sludge, PAHs, animal manures

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Authors: Latifat Afolake Ogunfolabo, Hakeem Babafemi Ogunfolabo

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The gastrointestinal tract is densely populated with micro-organism which closely and intensively interacts with the host and ingested feed. Food borne infections are some of the major international challenges that lead to high mortality and also, antimicrobial resistance, which has been classified as a serious threat by World Health Organization. Samples of slaughtered cattle and goats intestines were collected and standard culture methods were used for bacteria isolation and identification. Minimum inhibitory concentration of commonly used antibiotic using modification of the disk diffusion method was carried out on isolates. The samples cultured were all positive to Pseudomonas aeruginosa (95% and 90%), Escherichia coli (85%), Salmonella typhi (70% and 60%), Staphylococcus aureus (75%and 100%), Micrococcus luteus (55% and35%), Bacillus macerans (60% and 5%), Bacillus cereus (25% and 20%), Clostridium perfringens (20% and 5%), Micrococcus varians (20% and 5%), Bacillus subtilis (25% and 5%), Streptococcus faecalis (40% and 25%) and Streptococcus faecium (15% and 10%) in goat and cattle respectively. Also, Proteus mirabilis (40%), Micrococcus luteus (35%), Proteus vulgaris (30%), Klebsiella aerogenes(15%) were isolated from cattle. The total coliform (13.55 x10⁵cfu/gm ± 1.77) and (20.30 x10⁵cfu/gm ± 1.27) counts were significantly higher than the total bacteria count (8.3 x10⁵cfu/gm ± 1.41) and (16.60 x10⁵cfu/gm ±0.49) for goat and cattle respectively. Selected Bacteria count of isolates showed that Staphylococcus aureus had the highest significant value (6.9 x10⁵cfu/gm ± 0.57) and (16.80 x10⁵cfu/gm ± 0.57) Escherichia coli (4.60 x10⁵cfu/gm ± 0.42) and (7.05 x10⁵cfu/gm ± 0.64) while the lowest significant value was obtained in Salmonella/Shigella (1.7 x10⁵cfu/gm ± 0.00) and (1.5 x10⁵cfu/gm ± 0.00) for goat and cattle respectively. Susceptibility of bacteria isolated from slaughtered goat and cattle intestine to commonly used antibiotics showed that the highest statistical significant value for zone of inhibition for goat was obtained for Ciprofloxacin (30.00 ± 2.25, 23.75 ± 2.49, 17.17 ± 1.40) followed by Augmentin (28.33 ± 1.22, 21. 83 ± 2.44, 16.67 ± 1.49), Erythromycin (27.75 ±1.48, 20.25 ± 1.29, 16.67 ± 1.26) while the lowest values were obtained for Ofloxacin (27.17 ± 1.89, 21.42 ± 2.19, 16.83 ± 1.26) respectively and values obtained for cattle are Ciprofloxacin (30.64 ± 1.6, 25.79 ± 1.76, 8.07 ± 11.49) followed by Augmentin (28.29 ± 1.33, 22.64 ± 1.82, 17.43 ± 1.55) Ofloxacin (26.57 ± 2.02, 20.79 ± 2.75, 16.21 ± 1.19) while the lowest values were obtained for Erythromycin (26.64 ± 1.49, 20.29 ± 1.49, 16.29 ± 1.33) at different dilution factor (10⁻¹, 10⁻², 10⁻³) respectively. The isolates from goat and cattle were all susceptible to Augmentin at the three different dilution factors. Some goat isolates are intermediate to Ciprofloxacin and Erythromycin at 10⁻² and 10⁻³, while resistance to Ciprofloxacin at 10⁻³ dilution factor. Ciprofloxacin and Ofloxacin at the dilution factors of 10⁻³ and 10⁻¹ for some cattle isolate and resistance were observed for Ofloxacin and Erythromycin at dilution of 10⁻³. These results indicate the susceptibilities and the antimicrobial resistance to commonly used antibiotic.

Keywords: antibiotic susceptibility, bacteria, cattle, goat, identification

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Authors: O. J. Makinde, O. A. Abiola

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Background: Hazards and injuries are two common phenomena that have been associated with the building construction profession. Apart from injuries, deaths from injuries sustained at work have been high in this profession. This study, therefore, attempts to determine the attitude, practice, and prevalence of injuries among this group of workers. Methods: This was a cross-sectional study with 285 respondents. The sampling was multi-staged. Interviewer-administered questionnaires were used to elicit information such as socio-demographic characteristics of the respondents, attitude and practice of occupational safety and prevalence of injuries among the workers. The data were analyzed using epi-info 3.5.1 statistical software. Result: The modal age group is 25-34yrs which made up 40% of the respondents. Most of the respondents were male (86.3%). Most of the respondent (52.3%) have their highest educational level as the secondary school. Most of the respondents (64.9%) had a poor attitude to occupational safety while 91.6% had poor occupational safety practices. The prevalence of occupational injury was very high (64.9%). Particles in the eyes have the highest prevalence (52.3%) while electric shock has the least prevalence (19.6%).None of the respondent working at a height used safety belt while working. Conclusion: Attitude and practice of occupational safety are poor among this group of workers and prevalence of injuries was high.

Keywords: building, construction, Hazard, injury, workers

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Authors: Salma Krafessi

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The financial markets have a multifaceted, intricate environment, and enormous volumes of data are produced every day. To find investment possibilities, possible fraudulent activity, and market oddities, accurate anomaly identification in this data is essential. Conventional methods for detecting anomalies frequently fail to capture the complex organization of financial data. In order to improve the identification of abnormalities in financial time series data, this study presents Tucker Decomposition as a reliable multi-way analysis approach. We start by gathering closing prices for the S&P 500 index across a number of decades. The information is converted to a three-dimensional tensor format, which contains internal characteristics and temporal sequences in a sliding window structure. The tensor is then broken down using Tucker Decomposition into a core tensor and matching factor matrices, allowing latent patterns and relationships in the data to be captured. A possible sign of abnormalities is the reconstruction error from Tucker's Decomposition. We are able to identify large deviations that indicate unusual behavior by setting a statistical threshold. A thorough examination that contrasts the Tucker-based method with traditional anomaly detection approaches validates our methodology. The outcomes demonstrate the superiority of Tucker's Decomposition in identifying intricate and subtle abnormalities that are otherwise missed. This work opens the door for more research into multi-way data analysis approaches across a range of disciplines and emphasizes the value of tensor-based methods in financial analysis.

Keywords: tucker decomposition, financial markets, financial engineering, artificial intelligence, decomposition models

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Authors: Ali Almadan, Anoop Krishnan, Ajita Rattani

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Facial recognition is a widely adopted technology in surveillance, border control, healthcare, banking services, and lately, in mobile user authentication with Apple introducing “Face ID” moniker with iPhone X. A lot of research has been conducted in the area of face recognition on datasets captured by surveillance cameras, DSLR, and mobile devices. Recently, face recognition technology has also been deployed on body-worn cameras to keep officers safe, enabling situational awareness and providing evidence for trial. However, limited academic research has been conducted on this topic so far, without the availability of any publicly available datasets with a sufficient sample size. This paper aims to advance research in the area of face recognition using body-worn cameras. To this aim, the contribution of this work is two-fold: (1) collection of a dataset consisting of a total of 136,939 facial images of 102 subjects captured using body-worn cameras in in-door and daylight conditions and (2) evaluation of various deep-learning architectures for face identification on the collected dataset. Experimental results suggest a maximum True Positive Rate(TPR) of 99.86% at False Positive Rate(FPR) of 0.000 obtained by SphereFace based deep learning architecture in daylight condition. The collected dataset and the baseline algorithms will promote further research and development. A downloadable link of the dataset and the algorithms is available by contacting the authors.

Keywords: face recognition, body-worn cameras, deep learning, person identification

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Authors: Amal A. Mashali, Omar Eltaweel, Elerian Ekladious

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Stature of an individual has an important role in identification, which is often required in medico-legal practice. The estimation of stature is an important step in the identification of dismembered remains or when only a part of a skeleton is only available as in major disasters or with mutilation. There is no published data on anthropological data among Jordanian population. The present study was designed in order to find out relationship of stature to some anthropometric measures among a sample of Jordanian population and to determine the most accurate and reliable one in predicting the stature of an individual. A cross sectional study was conducted on 336 adult healthy volunteers , free of bone diseases, nutritional diseases and abnormalities in the extremities after taking their consent. Students of Faculty of Medicine, Mutah University helped in collecting the data. The anthropometric measurements (anatomically defined) were stature, humerus length, hand length and breadth, foot length and breadth, foot index and knee height on both right and left sides of the body. The measurements were typical on both sides of the bodies of the studied samples. All the anthropologic data showed significant relation with age except the knee height. There was a significant difference between male and female measurements except for the foot index where F= 0.269. There was a significant positive correlation between the different measures and the stature of the individuals. Three equations were developed for estimation of stature. The most sensitive measure for prediction of a stature was found to be the humerus length.

Keywords: foot index, foot length, hand length, humerus length, stature

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Authors: Ayoub Moufid, Najib Bennis, Soumia El Hani

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The objective of greenhouse climate control is to improve the culture development and to minimize the production costs. A greenhouse is an open system to external environment and the challenge is to regulate the internal climate despite the strong meteorological disturbances. The internal state of greenhouse considered in this work is defined by too relevant and coupled variables, namely inside temperature and hygrometry. These two variables are chosen to describe the internal state of greenhouses due to their importance in the development of plants and their sensitivity to external climatic conditions, sources of weather disturbances. A multivariable model is proposed and validated by considering a greenhouse as black-box system and the least square method is applied to parameters identification basing on collected experimental measures. To regulate the internal climate, we propose a Model Predictive Control (MPC) scheme. This one considers the measured meteorological disturbances and the physical and operational constraints on the control and state variables. A successful feasibility study of the proposed controller is presented, and simulation results show good performances despite the high interaction between internal and external variables and the strong external meteorological disturbances. The inside temperature and hygrometry are tracking nearly the desired trajectories. A comparison study with an On/Off control applied to the same greenhouse confirms the efficiency of the MPC approach to inside climate control.

Keywords: climate control, constraints, identification, greenhouse, model predictive control, optimization

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Authors: Bakhrouri Sarah

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The city of Algiers constitutes the first commercial pole of the country; 56.3% of its economic entities come from the commercial sector. Shopping centers are the new form of commerce that has emerged in the city since the 2000s. They are considered to be commercial and leisure poles and major generators of travel. However, shopping centers in the capital Algiers are poorly served by public transport, and their choice of location is mainly conditioned by the availability of land; accessibility by public transport does not appear to be an important criterion in the choice of their location. As a result, travel to and from these commercial centers is mainly by car, which breaks with the sustainability objectives of national transportation policy. Our study attempts to examine the impact of public transport accessibility of shopping centers on consumers' travel behaviour. The main objective of this research is to determine the link between the accessibility of these facilities, the use of private cars, and public transport modes. To this end, we analyze the choice of travel mode of consumers and the different factors that determine it by focusing on the influence of accessibility. The results showed a considerable influence of the accessibility on the travel behavior of the consumer in Algiers, so it is recommended to improve the accessibility of shopping centers by public transport in order to contribute to a modal shift.

Keywords: accessibility, shopping centers trips, public transportation, Algiers

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Authors: Pooja Ahuja, Tejal Bhutani, M. S. Dahiya

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Cheiloscopy, the study of lip prints, is a tool in forensic investigation technique that deals with identification of individuals based on lips patterns. The objective of this study is to determine predominant lip print pattern found among the Gujarati population, to evaluate whether any sex difference exists and to study the permanence of the pattern over six months duration. The study comprised of 100 healthy individuals (50 males and 50 females), in the age group of 18 to 25 years of Gujarati population of the Gandhinagar region of the Gujarat state, India. By using Suzuki and Tsuchihashi classification, Lip prints were then divided into four quadrants and also classified on the basis of peripheral shape of the lips. Materials used to record the lip prints were dark brown colored lipstick, cellophane tape, and white bond paper. Lipstick was applied uniformly, and lip prints were taken on the glued portion of cellophane tape and then stuck on to a white bond paper. These lip prints were analyzed with magnifying lens and virtually with stereo microscope. On the analysis of the subject population, results showed Branched pattern Type II (29.57 percentage) to be most predominant in the Gujarati population. Branched pattern Type II (35.60 percentage) and long vertical Type I (28.28 percentage) were most prevalent in males and females respectively and large full lips were most predominantly present in both the sexes. The study concludes that lip prints in any form can be an effective tool for identification of an individual in a closed or open group forms.

Keywords: cheiloscopy, lip pattern, predomianant, Gujarati population

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Authors: Manal Hassan Abdel Aziz, Fatma Mohamed Magdy Badr El Dine, Nourhan Mohamed Mohamed Saeed

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Establishing association between lip print patterns and those of fingerprints as well as blood groups is of fundamental importance in the forensic identification domain. The first aim of the current study was to determine the prevalent types of ABO blood groups, lip prints and fingerprints patterns in both studied populations. Secondly, to analyze any relation found between the different print patterns and the blood groups, which would be valuable in identification purposes. The present study was conducted on 60 healthy volunteers, (30 males and 30 females) from each of the studied population. Lip prints and fingerprints were obtained and classified according to Tsuchihashi's classification and Michael Kuchen’s classification, respectively. The results show that the ulnar loop was the most frequent among both populations. Blood group A was the most frequent among Egyptians, while blood groups O and B were the predominant among Malaysians. Significant relations were observed between lip print patterns and fingerprint (in the second quadrant for Egyptian males and the first one for Malaysian). For Malaysian females, a statistically significant association was proved in the fourth quadrant. Regarding the blood groups, 89.5% of ulnar loops were significantly related to blood group A among Egyptian males. The results proved an association between the fingerprint pattern and the lip prints, as well as between the ABO blood group and the pattern of fingerprints. However, further researches with larger sample sizes need to be directed to approve the current results.

Keywords: ABO, cheiloscopy, dactylography, Egyptians, Malaysians

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Authors: Katherine Maurer

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Background and purpose: Violence that occurs within families is a global social problem. Children who are victims or witness to family violence are at risk for many negative effects both proximally and distally. One of the most disconcerting long-term effects occurs when child victims become adult perpetrators: the intergenerational transmission of family violence (ITFV). Early identification of those children most at risk for ITFV is needed to inform interventions to prevent future family violence perpetration and victimization. Only about 25-30% of child family violence victims become perpetrators of adult family violence (either child abuse, partner abuse, or both). Prior research has primarily been conducted using dichotomous measures of exposure (yes; no) to predict ITFV, given the low incidence rate in community samples. It is often assumed that exposure to greater amounts of violence predicts greater risk of ITFV. However, no previous longitudinal study with a community sample has tested a dose-response model of exposure to physical child abuse and parental physical intimate partner violence (IPV) using count data of frequency and severity of violence to predict adult ITFV. The current study used advanced statistical methods to test if increased childhood exposure would predict greater risk of ITFV. Methods: The study utilized 3 panels of prospective data from a cohort of 15 year olds (N=338) from the Project on Human Development in Chicago Neighborhoods longitudinal study. The data were comprised of a stratified probability sample of seven ethnic/racial categories and three socio-economic status levels. Structural equation modeling was employed to test a hurdle regression model of dose-response to predict ITFV. A version of the Conflict Tactics Scale was used to measure physical violence victimization, witnessing parental IPV and young adult IPV perpetration and victimization. Results: Consistent with previous findings, past 12 months incidence rates severity and frequency of interpersonal violence were highly skewed. While rates of parental and young adult IPV were about 40%, an unusually high rate of physical child abuse (57%) was reported. The vast majority of a number of acts of violence, whether minor or severe, were in the 1-3 range in the past 12 months. Reported frequencies of more than 5 times in the past year were rare, with less than 10% of those reporting more than six acts of minor or severe physical violence. As expected, minor acts of violence were much more common than acts of severe violence. Overall, regression analyses were not significant for the dose-response model of ITFV. Conclusions and implications: The results of the dose-response model were not significant due to a lack of power in the final sample (N=338). Nonetheless, the value of the approach was confirmed for the future research given the bi-modal nature of the distributions which suggest that in the context of both child physical abuse and physical IPV, there are at least two classes when frequency of acts is considered. Taking frequency into account in predictive models may help to better understand the relationship of exposure to ITFV outcomes. Further testing using hurdle regression models is suggested.

Keywords: intergenerational transmission of family violence, physical child abuse, intimate partner violence, structural equation modeling

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Authors: N. Manoj

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The aeroelastic behavior of engine nacelle strake when subjected to unsteady aerodynamic flows is investigated in this paper. Geometric nonlinear characteristics and modal parameters of nacelle strake are studied when it is under dynamic loading condition. Here, an N-S based Finite Volume solver is coupled with Finite Element (FE) based nonlinear structural solver to investigate the nonlinear characteristics of nacelle strake over a range of dynamic pressures at various phases of flight like takeoff, climb, and cruise conditions. The combination of high fidelity models for both aerodynamics and structural dynamics is used to predict the nonlinearities of strake (chine). The methodology adopted for present aeroelastic analysis is partitioned-based time domain coupled CFD and CSD solvers and it is validated by the consideration of experimental and numerical comparison of aeroelastic data for a cropped delta wing model which has a proven record. The present strake geometry is derived from theoretical formulation. The amplitude and frequency obtained from the coupled solver at various dynamic pressures is discussed, which gives a better understanding of its impact on aerodynamic design-sizing of strake.

Keywords: aeroelasticity, finite volume, geometric nonlinearity, limit cycle oscillations, strake

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Authors: Francisco Borja de Lara, Ali Ravanbakhsh, Robert F. Wimmer-Schweingruber, Lars Seimetz, Fermín Navarro

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The intense structural loads during the launch of a spacecraft represent a challenge for the space structure designers because enough resistance has to be achieved while maintaining at the same time the mass and volume within the allowable margins of the mission requirements and inside the limits of the budget project. In this conference, we present the structural analysis of the Lunar Lander Neutron Dosimetry (LND) experiment on the Chang'E4 mission, the first probe to land on the moon’s far side included in the Chinese’ Moon Exploration Program by the Chinese National Space Administration. To this target, the software Nastran/Patran has been used: a structural model in Patran and a structural analysis through Nastran have been realized. Next, the results obtained are used both for the optimization process of the spacecraft structure, and as input parameters for the model structural test campaign. In this way, the feasibility of the lunar instrument structure is demonstrated in terms of the modal modes, stresses, and random vibration and a better understanding of the structural tests design is provided by our results.

Keywords: Chang’E4, Chinese national space administration, lunar lander neutron dosimetry, nastran-patran, structural analysis

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Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

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To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine

Procedia PDF Downloads 93