Search results for: unknown input observer

Authors: Chengcao Sun, Cuili Yang, Shujun Li, Ruilin Xue, Yongyong Xi, Liang Wang, Dejia Li

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Backgrounds: A few lines of evidence show that Sulforaphane (SFN) has anti-fibrosis effect in liver tissue via Nrf2-mediated inhibition of TGF-β/Smad signaling. However, its effects on muscular dystrophic fibrosis remain unknown. This work was undertaken to evaluate the effects of SFN on fibrosis in dystrophic muscle. Methods: 3-month-old male mdx mice were treated with SFN by gavage (2 mg/kg body weight per day) for 3 months. Gastrocnemius, tibial anterior and triceps brachii muscles were collected for related analysis. Fibrosis in skeletal muscles was analyzed by Sirius red staining. Histology and morphology of skeletal muscles were investigated by H&E staining. Moreover, the expressions of Nrf2, NQO1, HO-1, and TGF-β/Smad signaling pathway were detected by western blot, qRT-PCR, immunohistochemistry and immunofluorescence assays. Results: Our results demonstrated that SFN treatment significantly decreased and improved morphological features in mdx muscles. Moreover, SFN increased the expression of muscle phase II enzymes NQO1 and HO-1 and significantly decreased the expression of TGF-β1，p-smad2, p-smad3, α-SMA, fibronectin, collagen I, PAI-1, and TIMP-1 in Nrf2 dependent manner. Additionally, SFN significantly decreased the expression of CD45 and TNF-α. Conclusions: Collectively, these results show that SFN can ameliorate muscle fibrosis in mdx mice by Nrf2-induced inhibition of TGF-β/Smad signaling pathway, which indicate Nrf2 may be useful for the treatment of muscular dystrophy.

Keywords: sulforaphane, Nrf2, TGF-β/smad signaling, duchenne muscular dystrophy, fibrosis

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Authors: Mohamed Bendoukha, Mustapha Mosbah

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The Radiographic apparent assumed that the asymptomatic adjacent segment disease ASD is common after lumbar fusion, but this does not correlate with the functional outcomes while compensatory increased motion and stresses at the adjacent level of fusion is well-known to be associated to ASD. Newly developed, the hybrid stabilization are allocated to substituted for mostly the superior level of the fusion in an attempt to reduce the number of fusion levels and likelihood of degeneration process at the adjacent levels during the fusion with pedicle screws. Nevertheless, its biomechanical efficiencies still remain unknown and complications associated with failure of constructs such screw loosening and toggling should be elucidated In the current study, a finite element (FE) study was performed using a validated L2/S1 model subjected to a moment of 7.5 Nm and follower load of 400 N to assess the biomedical behavior of hybrid constructs based on dynamic topping off, semi rigid fusion. The residual range of motion (ROM), stress distribution at the fused and adjacent levels, stress distribution at the disc and the cage-endplate interface with respect to changes of bone quality were investigated. The hybrid instrumentation was associated with a reduction in compressive stresses compared to the fusion construct in the adjacent-level disc and showed high substantial axial force in the implant while fusion instrumentation increased the motion for both flexion and extension.

Keywords: intervertebral disc, lumbar spine, degenerative nuclesion, L4-L5, range of motion finite element model, hyperelasticy

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Authors: Dalvinder Kaur Mangal

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For the past decade, noise corrupted output measurements have been a fundamental research problem to be investigated. On the other hand, the estimation of the parameters for linear dynamic systems when also the input is affected by noise is recognized as more difficult problem which only recently has received increasing attention. Representations where errors or measurement noises/disturbances are present on both the inputs and outputs are usually called errors-in-variables (EIV) models. These disturbances may also have additive effects which are also considered in this paper. Parameter estimation of false EIV problem using equation error, output error and iterative prefiltering identification schemes with and without additive uncertainty, when only the output observation is corrupted by noise has been dealt in this paper. The comparative study of these three schemes has also been carried out.

Keywords: errors-in-variable (EIV), false EIV, equation error, output error, iterative prefiltering, Gaussian noise

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Authors: Ramesh Chandra Majhi

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Saturation flow is a very important input variable for the design of signalized intersections. Saturation flow measurement is well established for homogeneous traffic. However, saturation flow measurement and modeling is a challenging task in heterogeneous characterized by multiple vehicle types and non-lane based movement. Present study focuses on proposing a field procedure for Saturation flow measurement and the effect of typical mixed traffic behavior at the signal as far as non-lane based traffic movement is concerned. Data collected during peak and off-peak hour from five intersections with varying approach width is used for validating the saturation flow model. The insights from the study can be used for modeling saturation flow and delay at signalized intersection in heterogeneous traffic conditions.

Keywords: optimization, passenger car unit, saturation flow, signalized intersection

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Authors: Dong-Bo Hsu

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Universal Grammar (UG) claims that the constraints that are derived from this should operate in language users’ L2 grammars. This study investigated this hypothesis on knowledge of Subjacency and resumptive pronoun usage among Chinese learners of English. Chinese fulfills two requirements to examine the existence of UG, i.e., Subjacency does not operate in Chinese and resumptive pronouns in English are very different from those in Chinese and second L2 input undermines the knowledge of Subjacency. The results indicated that Chinese learners of English demonstrated a nearly identical pattern as English native speakers do but the resumptive pronoun in the embedding clauses. This may be explained in terms of the case that Chinese speakers’ usage of pronouns is not influenced by the number of embedding clauses. Chinese learners of English have full access to knowledge endowed by UG but their processing of English sentences may be different from native speakers as a general slow rate for processing in their L2 English.

Keywords: universal grammar, Chinese, English, wh-questions, resumption

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Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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Authors: Nesrine Bouguerra

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Entrepreneurship is seen as a necessary ingredient for stimulating economic growth and employment opportunities in all societies. SMEs account for a wide share of economic activity and development. they are the primary engine of job creation, income growth and poverty reduction. Indeed, government support for entrepreneurship is a strategic option to foster economic growth and females’ input in this regard, is of equal significance not only for employability and productivity but also to narrow the gender gap created by social attitudes and beliefs. This study investigates the impact of socio–cultural factors, among other barriers on female entrepreneurial intention in Algeria. Data will be collected using a mixed method approach (Questionnaires and Interviews) from women intending to become entrepreneurs and those already in the field. This study has conceptual, theoretical and empirical contributions to the field of entrepreneurship which will be unveiled throughout.

Keywords: female entrepreneurship, SMEs, women, socio –cultural values, barriers

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Authors: Rupert G. S. Legg

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The connection between poor health outcomes and living near contaminated land has long been understood. Less examined has been the impact of remediation on residents’ health. The cleaning process undoubtedly changes the local area in which it occurs, leading to the possibility that local housing and rental prices could increase resulting in the displacement of those least able to cope. Whether or not this potential displacement resulting from remediation has a considerable impact on health remains unknown. This review aims to determine how these health effects have been approached in the health geography literature. A systematic review of health geographies literature was conducted, searching for two-word clusters: ‘health’ and ‘remediation’ (100 articles); and ‘health’, ‘displacement’ and ‘gentrification’ (43 articles). 43 articles were selected for their relevance (7 from the first cluster, 20 from the second, and 16 from those cited within the reviewed articles). Several of the reviewed cases identified that potential displacement was a contributor to stress and worry in residents living near remediation projects. Likewise, the experience of displacement in other cases beyond remediation was linked with several mental health issues. However, no remediation cases followed-up on the ultimate effects of experiencing displacement on residents’ health. A reason identified for this was a tendency for reviewed studies to adopt a contextual or compositional approach, as opposed to a relational approach, which is more concerned with dimensions of mobility and temporality. Given that remediation and displacement both involve changing mobility and temporality, focussing solely on contextual or compositional factors is problematic. This review concludes by suggesting that more thorough, relational research is conducted into the extent to which potential displacement resulting from remediation affects health.

Keywords: contamination, displacement, health geography, remediation

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Authors: Emmanuel Ademola Anigilaje, Ibraheem Ishola

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Background: Childhood steroid-sensitive idiopathic nephrotic syndrome (SSINS) is plagued with relapses that contribute to its morbidity and the cost of treatment. Materials and Methods: This is a retrospective review of relapses among children with SSINS at the University of Abuja Teaching Hospital from January 2016 to July 2020. Triggers related to relapse incidents were noted. Chi-square test was deployed for predictors (factors at the first clinical presentations that associate with subsequent relapses) of relapses. Predictors with p-values of less than 0.05 were considered significant and 95% confidence intervals (CI) and odd ratio (OR) were described. Results: Sixty SSINS comprising 52 males (86.7%), aged 23 months to 18 years, with a mean age of 7.04±4.16 years were studied. Thirty-eight (63.3%) subjects had 126 relapses including infrequent relapses in 30 (78.9%) and frequent relapses in 8 (21.1%). The commonest triggers were acute upper respiratory tract infections (68, 53.9%) and urinary tract infections (UTIs) in 25 (19.8%) relapses. In 4 (3.2%) relapses, no trigger was identified. The time-to-first relapse ranged 14 days to 365 days with a median time of 60 days. The significant predictors were hypertension (OR=3.4, 95% CI; 1.04-11.09, p=0.038), UTIs (OR=9.9, 95% CI; 1.16-80.71, p= 0.014), malaria fever (OR=8.0, 95% CI; 2.45-26.38, p˂0.001), micro-haematuria (OR=4.9, 95% CI; 11.58-15.16, p=0.004), elevated serum creatinine (OR=12.3, 95%CI; 1.48-101.20, p=0.005) and hypercholesterolaemia (OR=4.1, 95%CI; 1.35-12.63, p=0.011). Conclusion: While the pathogenesis of relapses remains unknown, it is prudent to consider relapse-specific preventive strategies against triggers and predictors of relapses in our setting.

Keywords: Patterns, triggers, predictors, steroid-sensitive idiopathic nephrotic syndrome, relapses, Nigeria

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Authors: Treder Natalia, Siemiński Mariusz

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Takotsubo cardiomyopathy (TC) is a recently defined clinical entity. First described by Japanese researchers, today is diagnosed worldwide in 1-2% of patients admitted with the preliminary diagnosis of Acute Coronary Syndrome. The etiology of takotsubo cardiomyopathy remains still largely unknown. Currently, the most likely cause of takotsubo is direct cytotoxicity caused by catecholamine surge triggered by emotional stress. There is a strong relation between recent severe emotional stress and TC. The aim of this study was to analysis the role of stress and personality as a risk factor of TT. The presented research involves 35 people who are diagnosed TC. All patients were women, mean age 60 years. The methods used in the research are popular psychological tests: Perceived Stress Scale, DS14 scale to measure type D personality, The Neo-Five Factor Inventory of Personality and psychological interview. The obtained results prove that stress events may directly precede or even release TC. The stressful events occurred directly before the symptoms in 75% examined. 65% assessed their family life as very stressful. Examiners have also a high level of experienced stress. Only 25% of the TC were classified as having type D personality but they have a high level of negative affectivity. The subjects had a high level of extraversion, openness to experiences and an average level of neuroticism. The results suggested that such a type of personality profile may predispose to the development of takotsubo cardiomyopathy. Patients with TT are the individuals who reveal joint tendency to the experience of negative emotions and very stressful family life.

Keywords: stress, personality trails, familiar problems, Takotsubo cardiomyopathy

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Authors: Hamza Nejib, Okba Taouali

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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

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Authors: Hassan Sher

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God has made this world with all of his essences and beautified it with his countless blessings. In Islam, no doubt, beauty is a very important characteristic but also an aspect of the body and the heart. In a world where the standards of beauty seem to change from year to year according to trends and norms. Moreover, in this world, many people want to look good and feel satisfied and will be willing to go through many ways for their ideal look. likewise, several products came into use for beautifying, cleansing, and promoting attractiveness. These products include components of cosmetics, they are utilized for health and beauty purposes. There are concerns regarding the existence of harmful or ḥarām chemicals, but With the advancement in (technology), it results in the transformation of unlawful and forbidden cosmetic products into permissible several new ingredients and products. The process of transforming certain items or products from one form to another, Muslim jurists tend to use terms like Istiḥālah (transformation).Istiḥālah is an Islamic principle unknown to many Muslims. LinguisticallyIstiḥālah carries the meaning of a transformation or a change in the nature of a thing into something else.According to the religious contact, Istiḥālah signifies a turning of a matter from a state of impurity or inedibility into a matter of different nature, name, properties, and characteristics (colour, taste, and smell) (Zuhayli, 1997). This principle, which is unanimously accepted by Muslim scholars, are breaths of fresh air to Muslims suffering from the suffocation of excessive prohibition. This will allow the invention to be utilized fully. This research tends to highlight the different ideological concepts of Istiḥālah from the perspective of Islamic Shariah and jurisprudence and its application in cosmetic products. However, the study focuses on the issues related to alcohol and pig ingredients in beauty products.

Keywords: istiḥālah. harām, jurisprudence, cosmetic, pig

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Authors: Hae-Yeoun Lee

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Mosaic refers to a technique that makes image by gathering lots of small materials in various colours. This paper presents an automatic algorithm that makes the photomosaic image using photos. The algorithm is composed of four steps: Partition and feature extraction, block matching, redundancy removal and colour adjustment. The input image is partitioned in the small block to extract feature. Each block is matched to find similar photo in database by comparing similarity with Euclidean difference between blocks. The intensity of the block is adjusted to enhance the similarity of image by replacing the value of light and darkness with that of relevant block. Further, the quality of image is improved by minimizing the redundancy of tiles in the adjacent blocks. Experimental results support that the proposed algorithm is excellent in quantitative analysis and qualitative analysis.

Keywords: photomosaic, Euclidean distance, block matching, intensity adjustment

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Authors: Wilaiwan Sornpoon, Sébastien Bonnet, Savitri Garivait

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Open burning of sugarcane fields is recognized to have a negative impact on soil by degrading its properties, especially soil organic carbon (SOC) content. Better understating the effect of open burning on soil carbon dynamics is crucial for documenting the carbon sequestration capacity of agricultural soils. In this study, experiments to investigate soil carbon stocks under burned and unburned sugarcane plantation systems in Thailand were conducted. The results showed that cultivation fields without open burning during 5 consecutive years enabled to increase the SOC content at a rate of 1.37 Mg ha-1y-1. Also it was found that sugarcane fields burning led to about 15% reduction of the total carbon stock in the 0-30 cm soil layer. The overall increase in SOC under unburned practice is mainly due to the large input of organic material through the use of sugarcane residues.

Keywords: soil organic carbon, soil inorganic carbon, carbon sequestration, open burning, sugarcane

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Authors: Pocholo Rodriguez, Anne Bernadine Ocampo, Ian Benedict Chan, Janric Micah Gray

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The state of an electric power system may be classified as either stable or unstable. The borderline of stability is at any condition for which a slight change in an unfavourable direction of any pertinent quantity will cause instability. Voltage instability in power distribution systems could lead to voltage collapse and thus power blackouts. The researchers will present an intelligent system using back propagation algorithm that can detect voltage instability and output voltage of a power distribution and classify it as stable or unstable. The researchers’ work is the use of parameters involved in voltage instability as input parameters to the neural network for training and testing purposes that can provide faster detection and monitoring of the power distribution system.

Keywords: back-propagation algorithm, load instability, neural network, power distribution system

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Authors: Sachin Nagargoje

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Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

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Authors: Luay Alsalmi

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Background: Facial filler is the most common type of cosmetic surgery next to botox. Permanent filler is preferred nowadays due to the low cost brought about by non-recurring injection appointments. However, such fillers pose a higher risk for complications, with even greater adverse effects when the procedure is done using unknown dermal filler injections. AIM: This study aimed to establish an algorithm to categorize and manage patients that receive permanent fillers. Materials and Methods: Twelve participants were presented to the service through emergency or as outpatient from November 2015 to May 2021. Demographics such as age, sex, date of injection, time of onset, and types of complications were collected. After examination, all cases were managed based on an algorithm established. FACE-Q was used to measure overall satisfaction and psychological well-being. Results: The algorithm to diagnose and manage these patients effectively with a high satisfaction rate was established in this study. All participants were non-smoker females with no known medical comorbidities. The algorithm presented determined the treatment plan when faced with complications. Results revealed high appearance-related psychosocial distress was observed prior to surgery, while it significantly dropped after surgery. FACE-Q was able to establish evidence of satisfactory ratings among patients prior to and after surgery. Conclusion: This treatment algorithm can guide the surgeon in formulating a suitable plan with fewer complications and a high satisfaction rate.

Keywords: facial filler, FACE-Q, psycho-social stress, botox, treatment algorithm

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Authors: Yulin Rao, Zhixuan Li, Burra Venkata Durga Kumar

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Intrusion detection refers to monitoring the actions of internal and external intruders on the system and detecting the behaviours that violate security policies in real-time. In intrusion detection, there has been much discussion about the application of neural network technology and artificial immune system (AIS). However, many solutions use static methods (signature-based and stateful protocol analysis) or centralized intrusion detection systems (CIDS), which are unsuitable for real-time intrusion detection systems that need to process large amounts of data and detect unknown intrusions. This article proposes a framework for a distributed intrusion detection system (DIDS) with multi-agents based on the concept of AIS and neural network technology to detect anomalies and intrusions. In this framework, multiple agents are assigned to each host and work together, improving the system's detection efficiency and robustness. The trainer agent in the central server of the framework uses the artificial neural network (ANN) rather than the negative selection algorithm of AIS to generate mature detectors. Mature detectors can distinguish between self-files and non-self-files after learning. Our analyzer agents use genetic algorithms to generate memory cell detectors. This kind of detector will effectively reduce false positive and false negative errors and act quickly on known intrusions.

Keywords: artificial immune system, distributed artificial intelligence, multi-agent, intrusion detection system, neural network

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Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

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Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

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The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the support-vectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: discrete wavelet transform, electroencephalogram, pattern recognition, principal component analysis, support vector machine

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Authors: Sikiru Ademola Adewale, Joe Thomas, Bolanle Hafiz Matti, Tosin Ige

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This project demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness.

Keywords: decoder, encoder, many-to-many mapping, video captioning, 2-gram BLEU

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Authors: Jamie R. Chua, Christina Irene D. Mejia, Regina P. Berba

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Disseminated tuberculosis is an infectious disease caused by Mycobacterium tuberculosis involving two or more non-contiguous sites identified through bacteriologic confirmation or clinical diagnosis. Over the five year period included in the study, the UP-PGH TB DOTS clinic had total of 3,967 referrals, and the prevalence of disseminated tuberculosis is 1% (68/3967). The mean age was 33.9 years (range 19-64 years) with a male: female ratio of 1:1. 67% (52 patients) had no predisposing comorbid illness or immune disorder. The most common presenting symptoms were abdominal pain (19%), back pain (13%), abdominal enlargement (11%) and mass (10.2%). Anemia, leukocytosis, hypoalbuminemia, and high-normal serum calcium were common biochemical and hematologic findings. Around 36% (25) of patients were diagnosed clinically with disseminated tuberculosis despite lacking bacteriologic evidence of multi-organ involvement. The lungs (86%) is still the most commonly involved site, followed by intestinal (22%), vertebral/Pott’s (27%), and pelvic/genital (19%). The mean time from presentation to initiation of therapy was 22 days (SD 32.7). Only 18 patients (29.3%) were properly recorded to have been referred to local TB DOTs facilities. Of the 68 patients, only 16% (11 patients) continued follow-up at PGH, and all had documented treatment completion. Treatment outcomes of the remaining were unknown. Due to the variety of involved sites, a high index of suspicion is required. Knowledge on clinical features, common radiographic findings, and histopathologic characteristics of disseminated TB is important as bacteriologic evidence of infection is not always apparent.

Keywords: disseminated tuberculosis, Mycobacterium tuberculosis, miliary tuberculosis, tuberculosis

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Authors: Denis Özdemir, Max Senges

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There are many examples of AI-supported apps for better health and wellbeing. Generally, these applications help people to achieve their goals based on scientific research and input data. Still, they do not always explain how those three are related, e.g. by making implicit assumptions about goals that hold for many but not for all. We present a seven-step method for designing health and wellbeing AIs considering goal setting, measurable results, real-time indicators, analytics, visual representations, communication, and feedback. It can help engineers as guidance in developing apps, recommendation algorithms, and interfaces that support humans in their decision-making without patronization. To illustrate the method, we create a recommender AI for tiny wellbeing habits and run a small case study, including a survey. From the results, we infer how people perceive the relationship between them and the AI and to what extent it helps them to achieve their goals. We review our seven-step engineering method and suggest modifications for the next iteration.

Keywords: recommender systems, natural language processing, health apps, engineering methods

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Juan P. Silva, T. R. Canchala, H. J. Lubberding, E. J. Peña, H. J. Gijzen

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This study measured the fluxes of greenhouse gases (GHGs) i.e. CO₂, CH₄ and N₂O from a tropical eutrophic freshwater wetland (“Sonso Lagoon”) which receives input loading nutrient from several sources i.e. agricultural run-off, domestic sewage, and a polluted river. The flux measurements were carried out at four different points using the static chamber technique. CO₂ fluxes ranged from -8270 to 12210 mg.m^-2.d^-1 (median = 360; SD = 4.11; n = 50), CH₄ ranged between 0.2 and 5270 mg.m^-2.d^-1 (median = 60; SD = 1.27; n = 45), and N₂O ranged from -31.12 to 15.4 mg N₂O m^-2.d^-1 (median = 0.05; SD = 9.36; n = 42). Although some negative fluxes were observed in the zone dominated by floating plants i.e. Eichornia crassipes, Salvinia sp., and Pistia stratiotes L., the mean values indicated that the Sonso Lagoon was a net source of CO₂, CH₄ and N₂O. In addition, an effect of the eutrophication on GHG emissions could be observed in the positive correlation found between CO₂, CH₄ and N₂O generation and COD, PO₄^-3, NH₃-N, TN and NO₃^-N. The eutrophication impact on GHG production highlights the necessity to limit the anthropic activities on freshwater wetlands.

Keywords: eutrophication, greenhouse gas emissions, freshwater wetlands, climate change

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Authors: S. J. Ha, S. J. Baik, T. O. Kim, S. W. Han

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For computing the seismic responses of structures, current seismic design provisions permit response history analyses (RHA) that can be used without limitations in height, seismic design category, and building irregularity. In order to obtain accurate seismic responses using RHA, it is important to use adequate input ground motions. Current seismic design provisions provide criteria for selecting ground motions. In this study, the accurate and computationally efficient algorithm is proposed for accurately selecting ground motions that satisfy the requirements specified in current seismic design provisions. The accuracy of the proposed algorithm is verified using single-degree-of-freedom systems with various natural periods and yield strengths. This study shows that the mean seismic responses obtained from RHA with seven and ten ground motions selected using the proposed algorithm produce errors within 20% and 13%, respectively.

Keywords: algorithm, ground motion, response history analysis, selection

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Authors: Katerina Samartzi

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This study focuses on the teacher’s discourses in Greece, about the relation between the children and the media, concerning sex education and widely the childhood. The teachers’ input reflect the anxieties and the dominant discourses that exist around these issues. The study begins with the critical discussion of the available literature concerning the potential impact of media and the ‘moral panics’, their role in sex education and the children’s use of sexual material. Moreover, the study analyses the social construction of childhood and sexuality. Given the lack of explicit and official protocol for the sex education in Greece and due the fact that the young people are familiar with all the material provided by the New Media and their part as an informal education, this project aims to point out the factors that reinforce these gaps. This study focuses on the way the adults and specifically teachers contextualize the children’s relation with media, their sexuality, the sex education, the use of sexual material and the childhood.

Keywords: childhood, children's sexuality, media, moral panics, pornography, sex education

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Authors: Odejayi Adedayo Olugbenga, Aina Adebisi

Abstract:

Weather variables (rainfall and temperature) affect the diversity and abundance of both fauna and flora species. This study compared the weather variables with spider abundance in two ecological zones of Ogun State, Nigeria namely Ago-iwoye (Rainforest) in the Ijebu axis and Aiyetoro (Derived Savannah) in the Yewa axis. Seven study sites chosen by Simple Random Sampling in each ecosystem were used for the study. In each sampling area, a 60 m x 120 m land area was marked and sampled, spider collection techniques were; hand picking, use of sweep netting, and Pitfall trap. Adult spiders were identified to the species level. Species richness was estimated by a non-parametric species estimator while the diversity of spider species was assessed by Simpson Diversity Index and Species Richness by One-way Analysis of Variance. Results revealed that spiders were more abundant in rainforest zones than in derived savannah ecosystems. However, the pattern of spider abundance in rainforest zone and residential areas were similar. During high temperatures, the activities of spiders tended to increase according to this study. In contrast, results showed that there was a negative correlation between rainfall and spider species abundance in addition to a negative and weak correlation between rainfall and species richness. It was concluded that heavy downpour has lethal effects on both immature and sometimes matured spiders, which could lead to the extinction of some unknown species of spiders. Tree planting should be encouraged, as this shelters the spider.

Keywords: spider, abundance, species richness, species diversity

Procedia PDF Downloads 78

Authors: Jiewei Li, Hongyan Cui, Chunqi Chang, Yong Hu

Abstract:

It was expected to benefit patient with hemiparesis after stroke by extensive arm rehabilitation, to partially regain forearm and hand function. This paper propose a robotic rehabilitation arm in assisting the hemiparetic patient to learn new ways of using and moving their weak arms. In this study, the robotic arm was driven by a somatosensory stimulated brain computer interface (BCI), which is a new modality BCI. The use of somatosensory stimulation is not only an input for BCI, but also a electrical stimulation for treatment of hemiparesis to strengthen the arm and improve its range of motion. A trial of this robotic rehabilitation arm was performed in a stroke patient with pure motor hemiparesis. The initial trial showed a promising result from the patient with great motivation and function improvement. It suggests that robotic rehabilitation arm driven by somatosensory BCI can enhance the rehabilitation performance and progress for hemiparetic patients after stroke.

Keywords: robotic rehabilitation arm, brain computer interface (BCI), hemiparesis, stroke, somatosensory stimulation

Procedia PDF Downloads 384

Authors: Shubham Jaiswal

Abstract:

In this study, the numerical solution of two-dimensional solute transport system in a homogeneous porous medium of finite-length is obtained. The considered transport system have the terms accounting for advection, dispersion and first-order decay with first-type boundary conditions. Initially, the aquifer is considered solute free and a constant input-concentration is considered at inlet boundary. The solution is describing the solute concentration in rectangular inflow-region of the homogeneous porous media. The numerical solution is derived using a powerful method viz., spectral collocation method. The numerical computation and graphical presentations exhibit that the method is effective and reliable during solution of the physical model with complicated boundary conditions even in the presence of reaction term.

Keywords: two-dimensional solute transport system, spectral collocation method, Chebyshev polynomials, Chebyshev differentiation matrix

Procedia PDF Downloads 226