Search results for: feature selection feature subset selection feature extraction/transformation

Authors: Akrem Sellami, Imed Riadh Farah

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Hyperspectral imagery (HSI) typically provides a wealth of information captured in a wide range of the electromagnetic spectrum for each pixel in the image. Hence, a pixel in HSI is a high-dimensional vector of intensities with a large spectral range and a high spectral resolution. Therefore, the semantic interpretation is a challenging task of HSI analysis. We focused in this paper on object classification as HSI semantic interpretation. However, HSI classification still faces some issues, among which are the following: The spatial variability of spectral signatures, the high number of spectral bands, and the high cost of true sample labeling. Therefore, the high number of spectral bands and the low number of training samples pose the problem of the curse of dimensionality. In order to resolve this problem, we propose to introduce the process of dimensionality reduction trying to improve the classification of HSI. The presented approach is a semi-supervised band selection method based on spatial hypergraph embedding model to represent higher order relationships with different weights of the spatial neighbors corresponding to the centroid of pixel. This semi-supervised band selection has been developed to select useful bands for object classification. The presented approach is evaluated on AVIRIS and ROSIS HSIs and compared to other dimensionality reduction methods. The experimental results demonstrate the efficacy of our approach compared to many existing dimensionality reduction methods for HSI classification.

Keywords: dimensionality reduction, hyperspectral image, semantic interpretation, spatial hypergraph

Procedia PDF Downloads 306

Authors: Berfin Yildiz

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These days, increasing global warming effects, limited amount of energy resources, etc., necessitates the awareness that must be present in every profession group. The architecture and construction sectors are responsible for both the embodied and operational energy of the materials. This responsibility has led designers to seek alternative solutions for energy-efficient material selection. The choice of energy-efficient material requires consideration of the entire life cycle, including the building's production, use, and disposal energy. The aim of this study is to investigate the method of material selection of external thermal insulation composite systems (ETICS). Embodied and in-use energy values of material alternatives were used for the evaluation in this study. The operational energy is calculated according to the u-value calculation method defined in the TS 825 (Thermal Insulation Requirements) standard for Turkey, and the embodied energy is calculated based on the manufacturer's Energy Performance Declaration (EPD). ETICS consists of a wall, adhesive, insulation, lining, mechanical, mesh, and exterior finishing materials. In this study, lining, mechanical, and mesh materials were ignored because EPD documents could not be obtained. The material selection problem is designed as a hypothetical volume area (5x5x3m) and defined as a multi-objective discrete optimization problem for external thermal insulation composite systems. Defining the problem as a discrete optimization problem is important in order to choose between materials of various thicknesses and sizes. Since production and use energy values, which are determined as optimization objectives in the study, are often conflicting values, material selection is defined as a multi-objective optimization problem, and it is aimed to obtain many solution alternatives by using Hypervolume (HypE) algorithm. The enrollment process started with 100 individuals and continued for 50 generations. According to the obtained results, it was observed that autoclaved aerated concrete and Ponce block as wall material, glass wool, as insulation material gave better results.

Keywords: embodied energy, multi-objective discrete optimization, performative design, thermal insulation

Procedia PDF Downloads 143

Authors: Ahmed Abdullah, Lyndon Murphy, Brychan Thomas

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Increasingly, in developed and developing countries, small and medium-sized enterprises (SMEs) are becoming more important to national economies due to their strategic significance in developing different industrial sectors Worldwide. SMEs play a major role in an economy by significantly contributing to the enhancement of the countries’ gross domestic product and its labor force by creating more job opportunities and developing skilled labor. Rapid development has been witnessed in the World within different aspects of life, especially the technological revolution such as e-business. This has become a feature of this era requiring us to ‘keep-up’ in our daily society, losing the traditional pattern of our daily lives and combining scientific methodology of an analytical and experimental nature. In the past few years the emergence of e-business and e-commerce in the world has been carefully surveyed. There is widespread use of the internet in every aspect and phase of business.

Keywords: e-business, e-business activities, SMEs, e-adoption ladder

Procedia PDF Downloads 532

Authors: Moustafa Gabr

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Galectin-3 has been identified as a critical player in driving the neuroinflammatory responses in Alzheimer's disease (AD). A key feature of this function of galectin-3 is associated with its interaction with the triggering receptor expressed on myeloid cells-2 (TREM2). Herein, we report a high-throughput screening (HTS) platform that can be used for the identification of inhibitors of TREM2 and galectin-3 interaction. We have utilized this HTS assay to screen a focused library of compounds optimized for central nervous system (CNS)-related diseases. MG-257 was identified from this screen as the first example of a small molecule that can attenuate TREM2 signaling based on its high affinity to galectin-3 (endogenous ligand of TREM2). Remarkably, MG-257 reduced the levels of proinflammatory cytokines in activated microglial cells, which highlights its ability to inhibit the neuroinflammatory response associated with AD.

Keywords: medicinal chemistry, Alzheimer's disease, drug discovery, therapeutics

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Authors: Yardfon Tanongkankit, Kanjana Narkprasom, Nukrob Narkprasom, Khwanruthai Saiupparat, Phatthareeya Siriwat

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Gac fruit (Momordica cochinchinensis (Lour.) Spreng) possesses high potential for health food as it contains high lycopene contents. The objective of this study was to optimize the extraction of lycopene from gac arils using the microwave extraction method. Response surface method was used to find the conditions that optimize the extraction of lycopene from gac arils. The parameters of extraction used in this study were extraction time (120-600 seconds), the solvent to sample ratio (10:1, 20:1, 30:1, 40:1 and 50:1 mL/g) and set microwave power (100-800 watts). The results showed that the microwave extraction condition at the extraction time of 360 seconds, the sample ratio of 30:1 mL/g and the microwave power of 450 watts were suggested since it exhibited the highest value of lycopene content of 9.86 mg/gDW. It was also observed that lycopene contents extracted from gac arils by microwave method were higher than that by the conventional method.

Keywords: conventional extraction, Gac arils, microwave-assisted extraction, Lycopene

Procedia PDF Downloads 391

Authors: Sara Kamalisiahroudi, Jun Huang, Zhe Li, Jianbo Zhang

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Two types of commercial cylindrical lithium ion batteries (Panasonic 3.4 Ah NCR-18650B and Samsung 2.9 Ah INR-18650), were investigated experimentally. The capacities of these samples were individually measured using constant current-constant voltage (CC-CV) method at different ambient temperatures (-10 ℃, 0 ℃, 25 ℃). Their internal resistance was determined by electrochemical impedance spectroscopy (EIS) and pulse discharge methods. The cells with different configurations of parallel connection NCR-NCR, INR-INR and NCR-INR were charged/discharged at the aforementioned ambient temperatures. The results showed that the difference of internal resistance between cells much more evident at low temperatures. Furthermore, the parallel connection of NCR-NCR exhibits the most uniform temperature distribution in cells at -10 ℃, this feature is quite favorable for the safety of the battery pack.

Keywords: batteries in parallel connection, internal resistance, low temperature, temperature difference, current distribution

Procedia PDF Downloads 480

Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

Procedia PDF Downloads 90

Authors: Mohammad Shams Esfand Abadi, Mohammad Ranjbar, Reza Ebrahimpour

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This work presents the distributed processing solution problem in a diffusion network based on the adapt then combine (ATC) and combine then adapt (CTA)selective partial update normalized least mean squares (SPU-NLMS) algorithms. Also, we extend this approach to dynamic selection affine projection algorithm (DS-APA) and ATC-DS-APA and CTA-DS-APA are established. The purpose of ATC-SPU-NLMS and CTA-SPU-NLMS algorithm is to reduce the computational complexity by updating the selected blocks of weight coefficients at every iteration. In CTA-DS-APA and ATC-DS-APA, the number of the input vectors is selected dynamically. Diffusion cooperation strategies have been shown to provide good performance based on these algorithms. The good performance of introduced algorithm is illustrated with various experimental results.

Keywords: selective partial update, affine projection, dynamic selection, diffusion, adaptive distributed networks

Procedia PDF Downloads 708

Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

Procedia PDF Downloads 58

Authors: Till Gramberg, Max Kellner, Erwin Gross

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This paper presents a comprehensive investigation into the topic of smart services and IIoT-Platforms, focusing on their selection and prioritization in manufacturing organizations. First, a literature review is conducted to provide a basic understanding of the current state of research in the area of smart services. Based on discussed and established definitions, a definition approach for this paper is developed. In addition, value propositions for smart services are identified based on the literature and expert interviews. Furthermore, the general requirements for the provision of smart services are presented. Subsequently, existing approaches for the selection and development of smart services are identified and described. In order to determine the requirements for the selection of smart services, expert opinions from successful companies that have already implemented smart services are collected through semi-structured interviews. Based on the results, criteria for the evaluation of existing methods are derived. The existing methods are then evaluated according to the identified criteria. Furthermore, a novel method for the selection of smart services in manufacturing companies is developed, taking into account the identified criteria and the existing approaches. The developed concept for the method is verified in expert interviews. The method includes a collection of relevant smart services identified in the literature. The actual relevance of the use cases in the industrial environment was validated in an online survey. The required data and sensors are assigned to the smart service use cases. The value proposition of the use cases is evaluated in an expert workshop using different indicators. Based on this, a comparison is made between the identified value proposition and the required data, leading to a prioritization process. The prioritization process follows an established procedure for evaluating technical decision-making processes. In addition to the technical requirements, the prioritization process includes other evaluation criteria such as the economic benefit, the conformity of the new service offering with the company strategy, or the customer retention enabled by the smart service. Finally, the method is applied and validated in an industrial environment. The results of these experiments are critically reflected upon and an outlook on future developments in the area of smart services is given. This research contributes to a deeper understanding of the selection and prioritization process as well as the technical considerations associated with smart service implementation in manufacturing organizations. The proposed method serves as a valuable guide for decision makers, helping them to effectively select the most appropriate smart services for their specific organizational needs.

Keywords: smart services, IIoT, industrie 4.0, IIoT-platform, big data

Procedia PDF Downloads 90

Authors: Daohong Yang, Xiang Zhang, Lei Li, Wanting Zhou

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Visual Simultaneous Localization and Mapping (VSLAM) is a technology that obtains information in the environment for self-positioning and mapping. It is widely used in computer vision, robotics and other fields. Many visual SLAM systems, such as OBSLAM3, employ a constant-speed motion model that provides the initial pose of the current frame to improve the speed and accuracy of feature matching. However, in actual situations, the constant velocity motion model is often difficult to be satisfied, which may lead to a large deviation between the obtained initial pose and the real value, and may lead to errors in nonlinear optimization results. Therefore, this paper proposed a motion model based on acceleration, which can be applied on most SLAM systems. In order to better describe the acceleration of the camera pose, we decoupled the pose transformation matrix, and calculated the rotation matrix and the translation vector respectively, where the rotation matrix is represented by rotation vector. We assume that, in a short period of time, the changes of rotating angular velocity and translation vector remain the same. Based on this assumption, the initial pose of the current frame is estimated. In addition, the error of constant velocity model was analyzed theoretically. Finally, we applied our proposed approach to the ORBSLAM3 system and evaluated two sets of sequences on the TUM dataset. The results showed that our proposed method had a more accurate initial pose estimation and the accuracy of ORBSLAM3 system is improved by 6.61% and 6.46% respectively on the two test sequences.

Keywords: error estimation, constant acceleration motion model, pose estimation, visual SLAM

Procedia PDF Downloads 95

Authors: P. Crosby, Shiva Krishna Pavuluri, S. Rajkumar

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Purpose: Occupied built-up space can be broadly classified as air-conditioned and naturally ventilated. Regardless of the building type, the objective of all occupied built-up space is to provide a thermally acceptable environment for human occupancy. Considering this aspect, air-conditioned spaces allow a greater degree of flexibility to control and modulate the comfort parameters during the operation phase. However, in the case of naturally ventilated space, a number of design features favoring indoor thermal comfort should be mandatorily conceptualized starting from the design phase. One such primary design feature that requires to be prioritized is, selection of building envelope material, as it decides the flow of energy from outside environment to occupied spaces. Research Methodology: In India and many countries across globe, the standardized material used for building envelope is re-enforced concrete (i.e. M-25 grade concrete). The comfort inside the RC built environment for warm & humid climate (i.e. mid-day temp of 30-35˚C, diurnal variation of 5-8˚C & RH of 70-90%) is unsatisfying to say the least. This study is mainly focused on reviewing the impact of mix design of conventional M25 grade concrete on inside thermal comfort. In this mix design, air entrainment in the range of 2000 to 2100 kg/m3 is introduced to reduce the density of M-25 grade concrete. Thermal performance parameters & indoor comfort indices are analyzed for the proposed mix and compared in relation to the conventional M-25 grade. There are diverse methodologies which govern indoor comfort calculation. In this study, three varied approaches specifically a) Indian Adaptive Thermal comfort model, b) Tropical Summer Index (TSI) c) Air temperature less than 33˚C & RH less than 70% to calculate comfort is adopted. The data required for the thermal comfort study is acquired by field measurement approach (i.e. for the new mix design) and simulation approach by using design builder (i.e. for the conventional concrete grade). Findings: The analysis points that the Tropical Summer Index has a higher degree of stringency in determining the occupant comfort band whereas also providing a leverage in thermally tolerable band over & above other methodologies in the context of the study. Another important finding is the new mix design ensures a 10% reduction in indoor air temperature (IAT) over the outdoor dry bulb temperature (ODBT) during the day. This translates to a significant temperature difference of 6 ˚C IAT and ODBT.

Keywords: Indian adaptive thermal comfort, indoor air temperature, thermal comfort, tropical summer index

Procedia PDF Downloads 322

Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

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Model transformation, as a pivotal aspect of Model-driven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: cross-domain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.

Keywords: automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons

Procedia PDF Downloads 398

Authors: Salman Ali Nisar, Koshi Suzuki

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Precedence Diagram Method (PDM) with its additional relationships i.e., start-to-start, finish-to-finish, and start-to-finish, between activities provides more flexible schedule than traditional Critical Path Method (CPM). But, changing the duration of critical activities in PDM network will have anomalous effect on critical path. Researchers have proposed some classification of critical activity effects. In this paper, we do further study on classifications of critical activity effect and provide more information in detailed. Furthermore, we determine the maximum amount of time for each class of critical activity effect by which the project managers can control the dynamic feature (shortening/lengthening) of critical activities and project duration more efficiently.

Keywords: construction project management, critical path method, project scheduling, precedence diagram method

Procedia PDF Downloads 512

Authors: Tom Turner

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The recent financial crisis in 2008 and the growing inequality in developed industrial societies would appear to present significant challenges to capitalism and the free market. Yet there have been few substantial mainstream political or economic challenges to the dominant capitalist and market paradigm to-date. There is no dearth of critical and theoretical (academic) analyses regarding the prevailing systems failures. Yet despite the growing inequality in the developed industrial societies and the financial crisis in 2008 few commentators have advocated the comprehensive socialization or state ownership of the means of production to our knowledge – a core principle of radical Marxism in the 19th and early part of the 20th century. Undoubtedly the experience in the Soviet Union and satellite countries in the 20th century has cast a dark shadow over the notion of centrally controlled economies and state ownership of the means of production. In this paper, we explore the history of a doctrine advocating the socialization or state ownership of the means of production that was central to Marxism and socialism generally. Indeed this doctrine provoked an intense and often acrimonious debate especially for left-wing parties throughout the 20th century. The debate within the political economy tradition has historically tended to divide into a radical and a revisionist approach to changing or reforming capitalism. The radical perspective views the conflict of interest between capital and labor as a persistent and insoluble feature of a capitalist society and advocates the public or state ownership of the means of production. Alternatively, the revisionist perspective focuses on issues of distribution rather than production and emphasizes the possibility of compromise between capital and labor in capitalist societies. Over the 20th century, the radical perspective has faded and even the social democratic revisionist tradition has declined in recent years. We conclude with the major challenges that confront both the radical and revisionist perspectives in the development of viable policy agendas in mature developed democratic societies. Additionally, we consider whether state ownership of the means of production still has relevance in the 21st century and to what extent state ownership is off the agenda as a political issue in the political mainstream in developed industrial societies. A central argument in the paper is that state ownership of the means of production is unlikely to feature as either a practical or theoretical solution to the problems of capitalism post the financial crisis among mainstream political parties of the left. Although the focus here is solely on the shifting views of the radical and revisionist socialist perspectives in the western European tradition the analysis has relevance for the wider socialist movement.

Keywords: sate ownership, ownership means of production, radicals, revisionists

Procedia PDF Downloads 122

Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

Procedia PDF Downloads 122

Authors: Amrane Meriem, Oukid Salyha

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The presence of defects or bugs in software can lead to costly setbacks, operational inefficiencies, and compromised user experiences. The integration of Machine Learning(ML) techniques has emerged to predict and preemptively address software defects. ML represents a proactive strategy aimed at identifying potential anomalies, errors, or vulnerabilities within code before they manifest as operational issues. By analyzing historical data, such as code changes, feature im- plementations, and defect occurrences. This en- ables development teams to anticipate and mitigate these issues, thus enhancing software quality, reducing maintenance costs, and ensuring smoother user interactions. In this work, we used a recommendation system to improve the performance of ML models in terms of predicting the code severity and effort estimation.

Keywords: software engineering, machine learning, bugs detection, effort estimation

Procedia PDF Downloads 87

Authors: Mounir Gaci, Salim Meziani, Atmane Fouathia

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The purpose of the present paper is to model the behavior of metal alloy, type TRIP steel (Transformation Induced Plasticity), during solid/solid phase transition. A two-dimensional micromechanical model is implemented in finite element software (ZEBULON) to simulate the martensitic transformation in Fe-Ni-C steel grain under mechanical tensile stress of 250 MPa. The effects of non-uniform grain boundary and the criterion of mechanical shear load on the transformation and on the TRIP value during martensitic transformation are studied. The suggested mechanical criterion is favourable to the influence of the shear phenomenon on the progression of the martensitic transformation (Magee’s mechanism). The obtained results are in satisfactory agreement with experimental ones and show the influence of the grain boundary shape and the chosen mechanical criterion (SMF) on the transformation parameters.

Keywords: martensitic transformation, non-uniform Grain Boundary, TRIP, shear Mechanical force (SMF)

Procedia PDF Downloads 261

Authors: Elena E. Lyakso, Olga V. Frolova, Yuri N. Matveev, Aleksey S. Grigorev, Alexander S. Nikolaev, Viktor A. Gorodnyi

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The study of the children’s emotional sphere depending on age and psychoneurological state is of great importance for the design of educational programs for children and their social adaptation. Atypical development may be accompanied by violations or specificities of the emotional sphere. To study characteristics of the emotional state reflection in the voice and speech features of children, the perceptual study with the participation of adults and the automatic recognition of speech were conducted. Speech of children with typical development (TD), with Down syndrome (DS), and with autism spectrum disorders (ASD) aged 6-12 years was recorded. To obtain emotional speech in children, model situations were created, including a dialogue between the child and the experimenter containing questions that can cause various emotional states in the child and playing with a standard set of toys. The questions and toys were selected, taking into account the child’s age, developmental characteristics, and speech skills. For the perceptual experiment by adults, test sequences containing speech material of 30 children: TD, DS, and ASD were created. The listeners were 100 adults (age 19.3 ± 2.3 years). The listeners were tasked with determining the children’s emotional state as “comfort – neutral – discomfort” while listening to the test material. Spectrographic analysis of speech signals was conducted. For automatic recognition of the emotional state, 6594 speech files containing speech material of children were prepared. Automatic recognition of three states, “comfort – neutral – discomfort,” was performed using automatically extracted from the set of acoustic features - the Geneva Minimalistic Acoustic Parameter Set (GeMAPS) and the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS). The results showed that the emotional state is worse determined by the speech of TD children (comfort – 58% of correct answers, discomfort – 56%). Listeners better recognized discomfort in children with ASD and DS (78% of answers) than comfort (70% and 67%, respectively, for children with DS and ASD). The neutral state is better recognized by the speech of children with ASD (67%) than by the speech of children with DS (52%) and TD children (54%). According to the automatic recognition data using the acoustic feature set GeMAPSv01b, the accuracy of automatic recognition of emotional states for children with ASD is 0.687; children with DS – 0.725; TD children – 0.641. When using the acoustic feature set eGeMAPSv01b, the accuracy of automatic recognition of emotional states for children with ASD is 0.671; children with DS – 0.717; TD children – 0.631. The use of different models showed similar results, with better recognition of emotional states by the speech of children with DS than by the speech of children with ASD. The state of comfort is automatically determined better by the speech of TD children (precision – 0.546) and children with ASD (0.523), discomfort – children with DS (0.504). The data on the specificities of recognition by adults of the children’s emotional state by their speech may be used in recruitment for working with children with atypical development. Automatic recognition data can be used to create alternative communication systems and automatic human-computer interfaces for social-emotional learning. Acknowledgment: This work was financially supported by the Russian Science Foundation (project 18-18-00063).

Keywords: autism spectrum disorders, automatic recognition of speech, child’s emotional speech, Down syndrome, perceptual experiment

Procedia PDF Downloads 190

Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

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This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

Procedia PDF Downloads 190

Authors: Aida Sheeta, M. Nashat Fors, Sherwet El Gholmy, Marwa Issa

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Globalization has raised the customer preferences not only towards the high-quality garments but also the right fitting, comfort and aesthetic apparels. This only can be accomplished by the good interaction between fabric mechanical and physical properties as well as the required style. Consequently, this paper provides an integrated review of the fabric drape terminology because it is considered as an essential feature in which the fabric can form folds with the help of the gravity. Moreover, an instrument has been fabricated in order to analyze the static and dynamic drape behaviors using different fabric types. In addition, the obtained results find out the parameters affecting the drape coefficient using digital image processing for various kind of commercial fabrics. This was found to be an essential first step in order to analyze the behavior of this fabric when it is fabricated in a certain 3-D garment design.

Keywords: cloth fitting, fabric drape nodes, garment silhouette, image processing

Procedia PDF Downloads 188

Authors: Z. S. Yip, T. K. Tan, C. C. Geh, T. T. Ting

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The mobile phone is an indispensable device in today’s daily living. The arising new brands in the market with different specification are targeting at the different population. The most promising market would be the younger generation who are IT savvy. Therefore, it is beneficial to find out their factors of consideration in purchasing a mobile phone. A survey is carried out in Malaysia to discover the current youngster’s mobile phone buying behavior. This study has found that the most influencing factor of consideration is Price, followed by Feature, and Battery Lifespan. Gender and Income have no relationship with certain factors of consideration. It is important to discover the factors of consideration in order to provide industry insight into the current trend of smartphone in Malaysia.

Keywords: buying behavior, smart phone, mobile brand, mobile operating system, specification, battery lifespan

Procedia PDF Downloads 356

Authors: Tugba Ayas Onol

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The paper revisits Jean-François Lyotard’s interpretation of the Kantian Sublime as a tool for understanding politics after modernity. In 1985 Lyotard announces the end of rational politics based on consensus and claims that new strategies are urged to recognize the political imperatives of marginalized groups. The charm of the sublime as a reflective judgment is grounded on the fact that the judgment of sublime is free from any notion of consensus or common sense in particular. Lyotard interprets this feature of the sublime as a respect for heterogeneity and for him aesthetic judgments can be a model for understanding justice in postmodern times, in which it seems hard to follow a single universal law among different phrase regimes. More importantly, the Kantian sublime speaks to what Lyotard addresses as the incommensurability of phase genres. The present paper shall try to evaluate Lyotard’s employment of the Kantian notion of the sublime in relation to its possible political import.

Keywords: Kant, Lyotard, sublime, politics

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Authors: Hefzollah Mohammadiyan, Mohammad Bagher Heidari, Ensiyeh Hajeb

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In this paper investigates and analyses the structure of nano sensors will be discussed. The structure can be classified based of nano sensors: quantum points, carbon nanotubes and nano tools, which details into each other and in turn are analyzed. Then will be fully examined to the Carbon nanotubes as chemical and mechanical sensors. The following discussion, be examined compares the advantages and disadvantages as different types of sensors and also it has feature and a wide range of applications in various industries. Finally, the structure and application of Chemical sensor transistors and the sensors will be discussed in air pollution control.

Keywords: carbon nanotubes, quantum points, chemical sensors, mechanical sensors, chemical sensor transistors, single walled nanotube (SWNT), atomic force microscope (AFM)

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Authors: Anqi Wang, Linye Zhang

Abstract:

With the proliferation and development of mobile devices, various mobile apps have appeared to satisfy people’s needs. Metro, with the feature of convenient, punctuality and economic, is one of the most popular modes of transportation in cities. Yet, there are still some inconveniences brought by various factors, impacting tourists’ riding experience. The aim of this study is to help tourists to shorten the time of purchasing tickets, to provide them clear metro information and direct navigation, detailed schedule as well as a way to collect metro cards as souvenir. The study collects data through three phases, including observation, survey and test. Data collected from 106 tourists totally in Wuhan metro stations are discussed in the study. The result reflects tourists’ demand when they take the metro. It also indicates the feasibility of using mobile technology to improve passenger’s experience.

Keywords: mobile app, metro, public transportation, ticket, mobile payment, indoors positioning, tourists

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Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

Procedia PDF Downloads 756

Authors: Ya-Ting Chuang, Krystle Leung, Ya-Jen Chang, Rosemarie H. DeKruyff, Paul B. Savage, Richard Cruse, Christophe Benoit, Dirk Elewaut, Nicole Baumgarth, Dale T. Umetsu

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We examined characteristics of a Natural Killer T (NKT) cell subpopulation that developed during influenza infection in neonatal mice, and that suppressed the subsequent development of allergic asthma in a mouse model. This NKT cell subset expressed CD38 but not CD4, produced IFN-γ, but not IL-17, IL-4 or IL-13, and inhibited the development of airway hyperreactivity (AHR) through contact-dependent suppressive activity against helper CD4 T cells. The NKT subset expanded in the lungs of neonatal mice after infection with influenza, but also after treatment of neonatal mice with a Th1-biasing α-GalCer glycolipid analogue, Nu-α-GalCer. These results suggest that early/neonatal exposure to infection or to antigenic challenge can affect subsequent lung immunity by altering the profile of cells residing in the lung and that some subsets of NKT cells can have direct inhibitory activity against CD4+ T cells in allergic asthma. Importantly, our results also suggest a potential therapy for young children that might provide protection against the development of asthma.

Keywords: NKT subset, asthma, airway hyperreactivity, hygiene hypothesis, influenza

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Ahmed Boucherit, Hussein Khalaf, Eduardo Paredes, José Luis Todolí

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Solvent extraction studies of molybdenum (VI) with two organophosphorus reagents namely TBP and D2EHPA have been carried out from aqueous acidic solutions of HCl, H2SO4 and H3PO4 under microwave irradiations. The extraction efficiencies of the investigated extractants in the extraction of molybdenum (Vl) were compared. Extraction yield was found unchanged when microwave power varied in the range 20-100 Watts from H2SO4 or H3PO4 but it decreases in the range 20-60 Watts and increases in the range 60-100 Watts when TBP is used for extraction of molybdenum (VI) from 1 M HCl solutions. Extraction yield of molybdenum (VI) was found higher with TBP for HCl molarities greater than 1 M than with D2EHPA for H3PO4 molarities lower than 1 M. Extraction yield increases with HCl molarities in the range 0.50 - 1.80 M but it decreases with the increase in H2SO4 and H3PO4 molarities in the range of 0.05 - 1 M and 0.50 - 1 M, respectively.

Keywords: extraction, molybdenum, microwave, solvent

Procedia PDF Downloads 643

Authors: Bhupeshwaran Mani, S. Radha, A. Jawahar, A. Sivasubramanian

Abstract:

Here, we study the characteristic feature of conventional (ON-OFF keying) and soliton based transmission system. We consider 20 Gbps transmission system implemented with Conventional Single Mode Fiber (C-SMF) to examine the role of Gaussian pulse which is the characteristic of conventional propagation and hyperbolic-secant pulse which is the characteristic of soliton propagation in it. We note the influence of these pulses with respect to different dispersion lengths and soliton period in conventional and soliton system, respectively, and evaluate the system performance in terms of quality factor. From the analysis, we could prove that the soliton pulse has more consistent performance even for long distance without dispersion compensation than the conventional system as it is robust to dispersion. For the length of transmission of 200 Km, soliton system yielded Q of 33.958 while the conventional system totally exhausted with Q=0.

Keywords: dispersion length, retrun-to-zero (rz), soliton, soliton period, q-factor

Procedia PDF Downloads 346