Search results for: latent fingerprint
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 436

Search results for: latent fingerprint

406 High Power Thermal Energy Storage for Industrial Applications Using Phase Change Material Slurry

Authors: Anastasia Stamatiou, Markus Odermatt, Dominic Leemann, Ludger J. Fischer, Joerg Worlitschek

Abstract:

The successful integration of thermal energy storage in industrial processes is expected to play an important role in the energy turnaround. Latent heat storage technologies can offer more compact thermal storage at a constant temperature level, in comparison to conventional, sensible thermal storage technologies. The focus of this study is the development of latent heat storage solutions based on the Phase Change Slurry (PCS) concept. Such systems promise higher energy densities both as refrigerants and as storage media while presenting better heat transfer characteristics than conventional latent heat storage technologies. This technology is expected to deliver high thermal power and high-temperature stability which makes it ideal for storage of process heat. An evaluation of important batch processes in industrial applications set the focus on materials with a melting point in the range of 55 - 90 °C. Aluminium ammonium sulfate dodecahydrate (NH₄Al(SO₄)₂·12H₂O) was chosen as the first interesting PCM for the next steps of this study. The ability of this material to produce slurries at the relevant temperatures was demonstrated in a continuous mode in a laboratory test-rig. Critical operational and design parameters were identified.

Keywords: esters, latent heat storage, phase change materials, thermal properties

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405 Enhancement of Thermal Performance of Latent Heat Solar Storage System

Authors: Rishindra M. Sarviya, Ashish Agrawal

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Solar energy is available abundantly in the world, but it is not continuous and its intensity also varies with time. Due to above reason the acceptability and reliability of solar based thermal system is lower than conventional systems. A properly designed heat storage system increases the reliability of solar thermal systems by bridging the gap between the energy demand and availability. In the present work, two dimensional numerical simulation of the melting of heat storage material is presented in the horizontal annulus of double pipe latent heat storage system. Longitudinal fins were used as a thermal conductivity enhancement. Paraffin wax was used as a heat-storage or phase change material (PCM). Constant wall temperature is applied to heat transfer tube. Presented two-dimensional numerical analysis shows the movement of melting front in the finned cylindrical annulus for analyzing the thermal behavior of the system during melting.

Keywords: latent heat, numerical study, phase change material, solar energy

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404 Age and Sex Identification among Egyptian Population Using Fingerprint Ridge Density

Authors: Nazih Ramadan, Manal Mohy-Eldine, Amani Hanoon, Alaa Shehab

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Background and Aims: The study of fingerprints is widely used in providing a clue regarding identity. Age and gender identification from fingerprints is an important step in forensic anthropology in order to minimize the list of suspects search. The aim of this study was to determine finger ridge density and patterns among Egyptians, and to estimate age and gender using ridge densities. Materials and Methods: This study was conducted on 177 randomly-selected healthy Egyptian subjects (90 males and 87 females). They were divided into three age groups; Group (a): from 6-< 12 years, group (b) from 12-< 18 years and group (c) ≥ 18 years. Bilateral digital prints, from every subject, were obtained by the inking procedure. Ridge count per 25 mm² was determined together with assessment of ridge pattern type. Statistical analysis was done with references to different age and sex groups. Results: There was a statistical significant difference in ridge density between the different age groups; where younger ages had significantly higher ridge density than older ages. Females proved to have significantly higher ridge density than males. Also, there was a statistically significant negative correlation between age and ridge density. Ulnar loops were the most frequent pattern among Egyptians then whorls then arches then radial loops. Finally, different regression models were constructed to estimate age and gender from fingerprints ridge density. Conclusion: fingerprint ridge density can be used to identify both age and sex of subjects. Further studies are recommended on different populations, larger samples or using different methods of fingerprint recording and finger ridge counting.

Keywords: age, sex identification, Egyptian population, fingerprints, ridge density

Procedia PDF Downloads 327
403 Multinomial Dirichlet Gaussian Process Model for Classification of Multidimensional Data

Authors: Wanhyun Cho, Soonja Kang, Sanggoon Kim, Soonyoung Park

Abstract:

We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered an efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, importance sampling, approximate posterior distribution, marginal likelihood evidence

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402 Correlation between Potential Intelligence Explanatory Study in the Perspective of Multiple Intelligence Theory by Using Dermatoglyphics and Culture Approaches

Authors: Efnie Indrianie

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Potential Intelligence constitutes one essential factor in every individual. This intelligence can be a provision for the development of Performance Intelligence if it is supported by surrounding environment. Fingerprint analysis is a method in recognizing this Potential Intelligence. This method is grounded on pattern and number of finger print outlines that are assumed symmetrical with the number of nerves in our brain, in which these areas have their own function among another. These brain’s functions are later being transposed into intelligence components in accordance with the Multiple Intelligences theory. This research tested the correlation between Potential Intelligence and the components of its Performance Intelligence. Statistical test results that used Pearson correlation showed that five components of Potential Intelligence correlated with Performance Intelligence. Those five components are Logic-Math, Logic, Linguistic, Music, Kinesthetic, and Intrapersonal. Also, this research indicated that cultural factor had a big role in shaping intelligence.

Keywords: potential intelligence, performance intelligence, multiple intelligences, fingerprint, environment, brain

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401 Recurrent Neural Networks with Deep Hierarchical Mixed Structures for Chinese Document Classification

Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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400 Parameter Estimation in Dynamical Systems Based on Latent Variables

Authors: Arcady Ponosov

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A novel mathematical approach is suggested, which facilitates a compressed representation and efficient validation of parameter-rich ordinary differential equation models describing the dynamics of complex, especially biology-related, systems and which is based on identification of the system's latent variables. In particular, an efficient parameter estimation method for the compressed non-linear dynamical systems is developed. The method is applied to the so-called 'power-law systems' being non-linear differential equations typically used in Biochemical System Theory.

Keywords: generalized law of mass action, metamodels, principal components, synergetic systems

Procedia PDF Downloads 327
399 Chromatographic Fingerprint Analysis of Methanolic Extract of Camellia sinensis Linn. Leaves

Authors: Babar Ali, Mohammad Rashid, Showkat Rasool Mir, Mohammad Ali, Saiba Shams

Abstract:

Background: The plant Camellia sinensis (Theaceae) is an evergreen shrub indigenous to Assam (India) and parts of China and Japan. Traditional Chinese medicine has recommended green tea for headaches, body aches and pains, digestion, enhancement of immune defense, detoxification, as an energizer and to prolong life. The leaves have more than 700 chemical constituents, among which flavanoids, amino acids, vitamins (C, E, K), caffeine and polysaccharides. Adulteration and substitution may affect the quality of formulation containing tea leaves. Standardization of medicinal preparation is essential for further therapeutic results and for global acceptance. Hence, chromatographic fingerprint profiles were carried out for establishing the standards. Materials and methods: TLC studies for methanolic extracts of the leaves of Camellia sinensis were carried out in a new developed solvent system, Toluene: Ethyl acetate: Formic acid (7:3:1). TLC plates were dried in air, visualized in UV at wavelengths 254 nm and 366 nm and photographed. Results: Results provide valuable clue regarding their polarity and selection of solvents for separation of phytochemicals. Fingerprinting of methanolic extract of Camellia sinensis leaves revealed the presence of various phytochemicals in UV at 254 nm and 366 nm. Conclusion: Fingerprint profile is quite helpful in setting up of standards and thus to keep a check on intentional/unintentional adulteration. TLC offers major advantages over other conventional chromatographic techniques such as unsurpassed flexibility (esp. stationary and mobile phase), choice of detection wavelength, user friendly, rapid and cost effective.

Keywords: Cammelia sinensis Linn., standardization, methanolic extract, thin layer chromatography

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398 Novel Inference Algorithm for Gaussian Process Classification Model with Multiclass and Its Application to Human Action Classification

Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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397 Variational Explanation Generator: Generating Explanation for Natural Language Inference Using Variational Auto-Encoder

Authors: Zhen Cheng, Xinyu Dai, Shujian Huang, Jiajun Chen

Abstract:

Recently, explanatory natural language inference has attracted much attention for the interpretability of logic relationship prediction, which is also known as explanation generation for Natural Language Inference (NLI). Existing explanation generators based on discriminative Encoder-Decoder architecture have achieved noticeable results. However, we find that these discriminative generators usually generate explanations with correct evidence but incorrect logic semantic. It is due to that logic information is implicitly encoded in the premise-hypothesis pairs and difficult to model. Actually, logic information identically exists between premise-hypothesis pair and explanation. And it is easy to extract logic information that is explicitly contained in the target explanation. Hence we assume that there exists a latent space of logic information while generating explanations. Specifically, we propose a generative model called Variational Explanation Generator (VariationalEG) with a latent variable to model this space. Training with the guide of explicit logic information in target explanations, latent variable in VariationalEG could capture the implicit logic information in premise-hypothesis pairs effectively. Additionally, to tackle the problem of posterior collapse while training VariaztionalEG, we propose a simple yet effective approach called Logic Supervision on the latent variable to force it to encode logic information. Experiments on explanation generation benchmark—explanation-Stanford Natural Language Inference (e-SNLI) demonstrate that the proposed VariationalEG achieves significant improvement compared to previous studies and yields a state-of-the-art result. Furthermore, we perform the analysis of generated explanations to demonstrate the effect of the latent variable.

Keywords: natural language inference, explanation generation, variational auto-encoder, generative model

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396 Modelling of Solidification in a Latent Thermal Energy Storage with a Finned Tube Bundle Heat Exchanger Unit

Authors: Remo Waser, Simon Maranda, Anastasia Stamatiou, Ludger J. Fischer, Joerg Worlitschek

Abstract:

In latent heat storage, a phase change material (PCM) is used to store thermal energy. The heat transfer rate during solidification is limited and considered as a key challenge in the development of latent heat storages. Thus, finned heat exchangers (HEX) are often utilized to increase the heat transfer rate of the storage system. In this study, a new modeling approach to calculating the heat transfer rate in latent thermal energy storages with complex HEX geometries is presented. This model allows for an optimization of the HEX design in terms of costs and thermal performance of the system. Modeling solidification processes requires the calculation of time-dependent heat conduction with moving boundaries. Commonly used computational fluid dynamic (CFD) methods enable the analysis of the heat transfer in complex HEX geometries. If applied to the entire storage, the drawback of this approach is the high computational effort due to small time steps and fine computational grids required for accurate solutions. An alternative to describe the process of solidification is the so-called temperature-based approach. In order to minimize the computational effort, a quasi-stationary assumption can be applied. This approach provides highly accurate predictions for tube heat exchangers. However, it shows unsatisfactory results for more complex geometries such as finned tube heat exchangers. The presented simulation model uses a temporal and spatial discretization of heat exchanger tube. The spatial discretization is based on the smallest possible symmetric segment of the HEX. The heat flow in each segment is calculated using finite volume method. Since the heat transfer fluid temperature can be derived using energy conservation equations, the boundary conditions at the inner tube wall is dynamically updated for each time step and segment. The model allows a prediction of the thermal performance of latent thermal energy storage systems using complex HEX geometries with considerably low computational effort.

Keywords: modelling of solidification, finned tube heat exchanger, latent thermal energy storage

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395 A Multimodal Approach to Improve the Performance of Biometric System

Authors: Chander Kant, Arun Kumar

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Biometric systems automatically recognize an individual based on his/her physiological and behavioral characteristics. There are also some traits like weight, age, height etc. that may not provide reliable user recognition because of there common and temporary nature. These traits are called soft bio metric traits. Although soft bio metric traits are lack of permanence to uniquely and reliably identify an individual, yet they provide some beneficial evidence about the user identity and may improve the system performance. Here in this paper, we have proposed an approach for integrating the soft bio metrics with fingerprint and face to improve the performance of personal authentication system. In our approach we have proposed a combined architecture of three different sensors to elevate the system performance. The approach includes, soft bio metrics, fingerprint and face traits. We have also proven the efficiency of proposed system regarding FAR (False Acceptance Ratio) and total response time, with the help of MUBI (Multimodal Bio metrics Integration) software.

Keywords: FAR, minutiae point, multimodal bio metrics, primary bio metric, soft bio metric

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394 2D Fingerprint Performance for PubChem Chemical Database

Authors: Fatimah Zawani Abdullah, Shereena Mohd Arif, Nurul Malim

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The study of molecular similarity search in chemical database is increasingly widespread, especially in the area of drug discovery. Similarity search is an application in the field of Chemoinformatics to measure the similarity between the molecular structure which is known as the query and the structure of chemical compounds in the database. Similarity search is also one of the approaches in virtual screening which involves computational techniques and scoring the probabilities of activity. The main objective of this work is to determine the best fingerprint when compared to the other five fingerprints selected in this study using PubChem chemical dataset. This paper will discuss the similarity searching process conducted using 6 types of descriptors, which are ECFP4, ECFC4, FCFP4, FCFC4, SRECFC4 and SRFCFC4 on 15 activity classes of PubChem dataset using Tanimoto coefficient to calculate the similarity between the query structures and each of the database structure. The results suggest that ECFP4 performs the best to be used with Tanimoto coefficient in the PubChem dataset.

Keywords: 2D fingerprints, Tanimoto, PubChem, similarity searching, chemoinformatics

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393 Adversarial Disentanglement Using Latent Classifier for Pose-Independent Representation

Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

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392 Focus-Latent Dirichlet Allocation for Aspect-Level Opinion Mining

Authors: Mohsen Farhadloo, Majid Farhadloo

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Aspect-level opinion mining that aims at discovering aspects (aspect identification) and their corresponding ratings (sentiment identification) from customer reviews have increasingly attracted attention of researchers and practitioners as it provides valuable insights about products/services from customer's points of view. Instead of addressing aspect identification and sentiment identification in two separate steps, it is possible to simultaneously identify both aspects and sentiments. In recent years many graphical models based on Latent Dirichlet Allocation (LDA) have been proposed to solve both aspect and sentiment identifications in a single step. Although LDA models have been effective tools for the statistical analysis of document collections, they also have shortcomings in addressing some unique characteristics of opinion mining. Our goal in this paper is to address one of the limitations of topic models to date; that is, they fail to directly model the associations among topics. Indeed in many text corpora, it is natural to expect that subsets of the latent topics have higher probabilities. We propose a probabilistic graphical model called focus-LDA, to better capture the associations among topics when applied to aspect-level opinion mining. Our experiments on real-life data sets demonstrate the improved effectiveness of the focus-LDA model in terms of the accuracy of the predictive distributions over held out documents. Furthermore, we demonstrate qualitatively that the focus-LDA topic model provides a natural way of visualizing and exploring unstructured collection of textual data.

Keywords: aspect-level opinion mining, document modeling, Latent Dirichlet Allocation, LDA, sentiment analysis

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391 The Comparison Study of Methanol and Water Extract of Chuanxiong Rhizoma: A Fingerprint Analysis

Authors: Li Chun Zhao, Zhi Chao Hu, Xi Qiang Liu, Man Lai Lee, Chak Shing Yeung, Man Fei Xu, Yuen Yee Kwan, Alan H. M. Ho, Nickie W. K. Chan, Bin Deng, Zhong Zhen Zhao, Min Xu

Abstract:

Background: Chuangxiong Rhizoma (Chuangxion, CX) is one of the most frequently used herbs in Chinese medicine because of its wide therapeutic effects such as vasorelaxation and anti-inflammation. Aim: The purposes of this study are (1) to perform non-targeted / targeted analyses of CX methanol extract and water extract, and compare the present data with previously LC-MS or GC-MS fingerprints; (2) to examine the difference between CX methanol extract and water extract for preliminarily evaluating whether current compound markers of methanol extract from crude CX materials could be suitable for quality control of CX water extract. Method: CX methanol extract was prepared according to the Hong Kong Chinese Materia Medica Standards. DG water extract was prepared by boiling with pure water for three times (one hour each). UHPLC-Q-TOF-MS/MS fingerprint analysis was performed by C18 column (1.7 µm, 2.1 × 100 mm) with Agilent 1290 Infinity system. Experimental data were analyzed by Agilent MassHunter Software. A database was established based on 13 published LC-MS and GC-MS CX fingerprint analyses. Total 18 targeted compounds in database were selected as markers to compare present data with previous data, and these markers also used to compare CX methanol extract and water extract. Result: (1) Non-targeted analysis indicated that there were 133 compounds identified in CX methanol extract, while 325 compounds in CX water extract that was more than double of CX methanol extract. (2) Targeted analysis further indicated that 9 in 18 targeted compounds were identified in CX methanol extract, while 12 in 18 targeted compounds in CX water extract that showed a lower lose-rate of water extract when compared with methanol extract. (3) By comparing CX methanol extract and water extract, Senkyunolide A (+1578%), Ferulic acid (+529%) and Senkyunolide H (+169%) were significantly higher in water extract when compared with methanol extract. (4) Other bioactive compounds such as Tetramethylpyrazine were only found in CX water extract. Conclusion: Many new compounds in both CX methanol and water extracts were found by using UHPLC Q-TOF MS/MS analysis when compared with previous published reports. A new standard reference including non-targeted compound profiling and targeted markers functioned especially for quality control of CX water extract (herbal decoction) should be established in future. (This project was supported by Hong Kong Baptist University (FRG2/14-15/109) & Natural Science Foundation of Guangdong Province (2014A030313414)).

Keywords: Chuanxiong rhizoma, fingerprint analysis, targeted analysis, quality control

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390 Integrated Passive Cooling Systems for Tropical Residential Buildings: A Review through the Lens of Latent Heat Assessment

Authors: O. Eso, M. Mohammadi, J. Darkwa, J. Calautit

Abstract:

Residential buildings are responsible for 22% of the global end-use energy demand and 17% of global CO₂ emissions. Tropical climates particularly present higher latent heat gains, leading to more cooling loads. However, the cooling processes are all based on conventional mechanical air conditioning systems which are energy and carbon intensive technologies. Passive cooling systems have in the past been considered as alternative technologies for minimizing energy consumption in buildings. Nevertheless, replacing mechanical cooling systems with passive ones will require a careful assessment of the passive cooling system heat transfer to determine if suitable to outperform their conventional counterparts. This is because internal heat gains, indoor-outdoor heat transfer, and heat transfer through envelope affects the performance of passive cooling systems. While many studies have investigated sensible heat transfer in passive cooling systems, not many studies have focused on their latent heat transfer capabilities. Furthermore, combining heat prevention, heat modulation and heat dissipation to passively cool indoor spaces in the tropical climates is critical to achieve thermal comfort. Since passive cooling systems use only one of these three approaches at a time, integrating more than one passive cooling system for effective indoor latent heat removal while still saving energy is studied. This study is a systematic review of recently published peer review journals on integrated passive cooling systems for tropical residential buildings. The missing links in the experimental and numerical studies with regards to latent heat reduction interventions are presented. Energy simulation studies of integrated passive cooling systems in tropical residential buildings are also discussed. The review has shown that comfortable indoor environment is attainable when two or more passive cooling systems are integrated in tropical residential buildings. Improvement occurs in the heat transfer rate and cooling performance of the passive cooling systems when thermal energy storage systems like phase change materials are included. Integrating passive cooling systems in tropical residential buildings can reduce energy consumption by 6-87% while achieving up to 17.55% reduction in indoor heat flux. The review has highlighted a lack of numerical studies regarding passive cooling system performance in tropical savannah climates. In addition, detailed studies are required to establish suitable latent heat transfer rate in passive cooling ventilation devices under this climate category. This should be considered in subsequent studies. The conclusions and outcomes of this study will help researchers understand the overall energy performance of integrated passive cooling systems in tropical climates and help them identify and design suitable climate specific options for residential buildings.

Keywords: energy savings, latent heat, passive cooling systems, residential buildings, tropical residential buildings

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389 Proposing an Architecture for Drug Response Prediction by Integrating Multiomics Data and Utilizing Graph Transformers

Authors: Nishank Raisinghani

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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

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388 Paraffin/Expanded Perlite Composite as a Novel Form-Stable Phase Change Material for Latent Heat Energy Storage

Authors: Awni Alkhazaleh

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Latent heat storage using Phase Change Materials (PCMs) has attracted growing attention recently in the renewable energy utilization and building energy efficiency. Paraffin (PA) of low melting temperature, which is close to human comfort temperature in the range of 24-28 °C has been considered to be used in building applications. A form-stable composite Paraffin/Expanded perlite (PA-EP) has been prepared by retaining PA into porous particles of EP. DSC (Differential scanning calorimeter) is used to measure the thermal properties of PA in the form-stable composite with/without building materials. TGA (Thermal gravimetric analysis) shows that the composite is thermally stable. SEM (Scanning electron microscope) demonstrates that the layer structure of the EP particles is uniformly absorbed by PA. The mechanical properties in flexural mode have been discussed. The thermal energy storage performance has been evaluated using a small test room (100 mm ×100 mm ×100 mm) with thickness 10 mm. The flammability test of modified sample has been discussed using a cone calorimeter. The results confirm that the form-stable composite PA has the function of reducing building energy consumption.

Keywords: flammability, latent heat storage, paraffin, plasterboard

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387 X-Ray Crystallographic, Hirshfeld Surface Analysis and Docking Study of Phthalyl Sulfacetamide

Authors: Sanjay M. Tailor, Urmila H. Patel

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Phthalyl Sulfacetamide belongs to well-known member of antimicrobial sulfonamide family. It is a potent antitumor drug. Structural characteristics of 4-amino-N-(2quinoxalinyl) benzene-sulfonamides (Phthalyl Sulfacetamide), C14H12N4O2S has been studied by method of X-ray crystallography. The compound crystallizes in monoclinic space group P21/n with unit cell parameters a= 7.9841 Ǻ, b= 12.8208 Ǻ, c= 16.6607 Ǻ, α= 90˚, β= 93.23˚, γ= 90˚and Z=4. The X-ray based three-dimensional structure analysis has been carried out by direct methods and refined to an R-value of 0.0419. The crystal structure is stabilized by intermolecular N-H…N, N-H…O and π-π interactions. The Hirshfeld surfaces and consequently the fingerprint analysis have been performed to study the nature of interactions and their quantitative contributions towards the crystal packing. An analysis of Hirshfeld surfaces and fingerprint plots facilitates a comparison of intermolecular interactions, which are the key elements in building different supramolecular architectures. Docking is used for virtual screening for the prediction of the strongest binders based on various scoring functions. Docking studies are carried out on Phthalyl Sulfacetamide for better activity, which is important for the development of a new class of inhibitors.

Keywords: phthalyl sulfacetamide, crystal structure, hirshfeld surface analysis, docking

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386 Uniqueness of Fingerprint Biometrics to Human Dynasty: A Review

Authors: Siddharatha Sharma

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With the advent of technology and machines, the role of biometrics in society is taking an important place for secured living. Security issues are the major concern in today’s world and continue to grow in intensity and complexity. Biometrics based recognition, which involves precise measurement of the characteristics of living beings, is not a new method. Fingerprints are being used for several years by law enforcement and forensic agencies to identify the culprits and apprehend them. Biometrics is based on four basic principles i.e. (i) uniqueness, (ii) accuracy, (iii) permanency and (iv) peculiarity. In today’s world fingerprints are the most popular and unique biometrics method claiming a social benefit in the government sponsored programs. A remarkable example of the same is UIDAI (Unique Identification Authority of India) in India. In case of fingerprint biometrics the matching accuracy is very high. It has been observed empirically that even the identical twins also do not have similar prints. With the passage of time there has been an immense progress in the techniques of sensing computational speed, operating environment and the storage capabilities and it has become more user convenient. Only a small fraction of the population may be unsuitable for automatic identification because of genetic factors, aging, environmental or occupational reasons for example workers who have cuts and bruises on their hands which keep fingerprints changing. Fingerprints are limited to human beings only because of the presence of volar skin with corrugated ridges which are unique to this species. Fingerprint biometrics has proved to be a high level authentication system for identification of the human beings. Though it has limitations, for example it may be inefficient and ineffective if ridges of finger(s) or palm are moist authentication becomes difficult. This paper would focus on uniqueness of fingerprints to the human beings in comparison to other living beings and review the advancement in emerging technologies and their limitations.

Keywords: fingerprinting, biometrics, human beings, authentication

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385 Chemical Fingerprinting of the Ephedrine Pathway to Methamphetamine

Authors: Luke Andrighetto, Paul G. Stevenson, Luke C. Henderson, Jim Pearson, Xavier A. Conlan

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As pseudoephedrine, a common ingredient in cold and flu medications is closely monitored and restricted in Australia, alternative methods of accessing it are of interest. The impurities and by-products of every reaction step of pseudoephedrine/ephedrine and methamphetamine synthesis have been mapped in order to develop a chemical fingerprint based on synthetic route. Likewise, seized methamphetamine contains a combination of different cutting agents and starting materials. Therefore, in-silico optimised two-dimensional HPLC with DryLab® and OpenMS® software has been used to efficiently separate complex seizure samples. An excellent match between simulated and real separations was observed. Targeted separation of model compounds was completed with significantly reduced method development time. This study produced a two-dimensional separation regime that offers unprecedented separation power (separation space) while maintaining a rapid analysis time that is faster than those previously reported for gas chromatography, single dimension high performance liquid chromatography or capillary electrophoresis.

Keywords: chemical fingerprint, ephedrine, methamphetamine, two-dimensional HPLC

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384 Exposing Latent Fingermarks on Problematic Metal Surfaces Using Time of Flight Secondary Ion Mass Spectroscopy

Authors: Tshaiya Devi Thandauthapani, Adam J. Reeve, Adam S. Long, Ian J. Turner, James S. Sharp

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Fingermarks are a crucial form of evidence for identifying a person at a crime scene. However, visualising latent (hidden) fingermarks can be difficult, and the correct choice of techniques is essential to develop and preserve any fingermarks that might be present. Knives, firearms and other metal weapons have proven to be challenging substrates (stainless steel in particular) from which to reliably obtain fingermarks. In this study, time of flight secondary ion mass spectroscopy (ToF-SIMS) was used to image fingermarks on metal surfaces. This technique was compared to a conventional superglue based fuming technique that was accompanied by a series of contrast enhancing dyes (basic yellow 40 (BY40), crystal violet (CV) and Sudan black (SB)) on three different metal surfaces. The conventional techniques showed little to no evidence of fingermarks being present on the metal surfaces after a few days. However, ToF-SIMS images revealed fingermarks on the same and similar substrates with an exceptional level of detail demonstrating clear ridge definition as well as detail about sweat pore position and shape, that persist for over 26 days after deposition when the samples were stored under ambient conditions.

Keywords: conventional techniques, latent fingermarks, metal substrates, time of flight secondary ion mass spectroscopy

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383 Soybean Oil Based Phase Change Material for Thermal Energy Storage

Authors: Emre Basturk, Memet Vezir Kahraman

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In many developing countries, with the rapid economic improvements, energy shortage and environmental issues have become a serious problem. Therefore, it has become a very critical issue to improve energy usage efficiency and also protect the environment. Thermal energy storage system is an essential approach to match the thermal energy claim and supply. Thermal energy can be stored by heating, cooling or melting a material with the energy and then enhancing accessible when the procedure is reversed. The overall thermal energy storage techniques are sorted as; latent heat or sensible heat thermal energy storage technology segments. Among these methods, latent heat storage is the most effective method of collecting thermal energy. Latent heat thermal energy storage depend on the storage material, emitting or discharging heat as it undergoes a solid to liquid, solid to solid or liquid to gas phase change or vice versa. Phase change materials (PCMs) are promising materials for latent heat storage applications due to their capacities to accumulate high latent heat storage per unit volume by phase change at an almost constant temperature. Phase change materials (PCMs) are being utilized to absorb, collect and discharge thermal energy during the cycle of melting and freezing, converting from one phase to another. Phase Change Materials (PCMs) can generally be arranged into three classes: organic materials, salt hydrates and eutectics. Many kinds of organic and inorganic PCMs and their blends have been examined as latent heat storage materials. Organic PCMs are rather expensive and they have average latent heat storage per unit volume and also have low density. Most organic PCMs are combustible in nature and also have a wide range of melting point. Organic PCMs can be categorized into two major categories: non-paraffinic and paraffin materials. Paraffin materials have been extensively used, due to their high latent heat and right thermal characteristics, such as minimal super cooling, varying phase change temperature, low vapor pressure while melting, good chemical and thermal stability, and self-nucleating behavior. Ultraviolet (UV)-curing technology has been generally used because it has many advantages, such as low energy consumption , high speed, high chemical stability, room-temperature operation, low processing costs and environmental friendly. For many years, PCMs have been used for heating and cooling industrial applications including textiles, refrigerators, construction, transportation packaging for temperature-sensitive products, a few solar energy based systems, biomedical and electronic materials. In this study, UV-curable, fatty alcohol containing soybean oil based phase change materials (PCMs) were obtained and characterized. The phase transition behaviors and thermal stability of the prepared UV-cured biobased PCMs were analyzed by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The heating process phase change enthalpy is measured between 30 and 68 J/g, and the freezing process phase change enthalpy is found between 18 and 70 J/g. The decomposition of UVcured PCMs started at 260 ºC and reached a maximum of 430 ºC.

Keywords: fatty alcohol, phase change material, thermal energy storage, UV curing

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382 Grandiose Narcissists’ Adaptive Trade-Offs: Mating, Parental, and Somatic Investment

Authors: Jasmine H. Gagnon

Abstract:

The present study examined how grandiose narcissists make adaptive trade-offs between mating investment, parenting investment, and somatic investment relative to individuals without narcissistic personalities. A sample of 509 males and females between the ages of 24 and 35 years old (49.31% female) completed a personality inventory assessing Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness to Experience. In a Latent Profile Analysis (LPA), personality inventory scores were used to classify participants into latent groups. The model of best fit identified one grandiose narcissist group and three groups with non-narcissistic personalities. Covariate analyses revealed that individuals with narcissistic traits made significantly more significant somatic investments in comparison to two of the three non-narcissistic latent groups. No other significant differences between the narcissistic and non-pathological groups were found. Thus, grandiose narcissists trade off parenting and mating investments to make more significant somatic investments. That is, they expend a larger portion of their energetic resources on maintaining their physical health and careers and similar quantities of energetic resources on maintaining relationships with their offspring and potential romantic partners as individuals without narcissistic personalities.

Keywords: narcissism, grandiose narcissism, HEXACO, trade-offs, mating, parenting, somatic, dark triad

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381 Simulating the Hot Hand Phenomenon in Basketball with Bayesian Hidden Markov Models

Authors: Gabriel Calvo, Carmen Armero, Luigi Spezia

Abstract:

A basketball player is said to have a hot hand if his/her performance is better than expected in different periods of time. A way to deal with this phenomenon is to make use of latent variables, which can indicate whether the player is ‘on fire’ or not. This work aims to model the hot hand phenomenon through a Bayesian hidden Markov model (HMM) with two states (cold and hot) and two different probability of success depending on the corresponding hidden state. This task is illustrated through a comprehensive simulation study. The simulated data sets emulate the field goal attempts in an NBA season from different profile players. This model can be a powerful tool to assess the ‘streakiness’ of each player, and it provides information about the general performance of the players during the match. Finally, the Bayesian HMM allows computing the posterior probability of any type of streak.

Keywords: Bernoulli trials, field goals, latent variables, posterior distribution

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380 Multidimensional Item Response Theory Models for Practical Application in Large Tests Designed to Measure Multiple Constructs

Authors: Maria Fernanda Ordoñez Martinez, Alvaro Mauricio Montenegro

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This work presents a statistical methodology for measuring and founding constructs in Latent Semantic Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations present on Item Response Theory. More precisely, we propose initially reducing dimensionality with specific use of Principal Component Analysis for the linguistic data and then, producing axes of groups made from a clustering analysis of the semantic data. This approach allows the user to give meaning to previous clusters and found the real latent structure presented by data. The methodology is applied in a set of real semantic data presenting impressive results for the coherence, speed and precision.

Keywords: semantic analysis, factorial analysis, dimension reduction, penalized logistic regression

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379 Typology of Customers in Fitness Centres

Authors: Josef Voracek, Jan Sima

Abstract:

The main purpose of our study is to state the basic types of fitness customers. This paper aims to create a specific customer typology in today’s fitness centres in the region of Prague. Our suggested typology of Prague fitness centres customers is based on answers to the questions: What are the customers like, what are their preferences, and what kinds of services do they use more often in Prague fitness centres? These are the main aspects of the presented typology. A survey was conducted on a sample of 1004 respondents from 48 fitness centres, which ran during May 2012. We used questionnaires and latent class analysis for the assessment and interpretation of data. Gender was especially the main filter criterion. In the population, there were 522 males and 482 females. Data were analysed using the LCA method. We identified 6 segments of typical customers, of which three are male and three are female. Each segment is influenced primarily by the age of customers, from which we can develop further characteristics, such as education, income, marital status, etc. Male segments use the main workout area above all, whilst female segments use a much wider range of services offered, for example, group exercises, personal training, and cardio theatres. LCA method was found to be the most suitable tool, because cluster analysis is very limited in the forms and numbers of variables and indicators. Models of 3 latent classes for each gender are optimal, as it is demonstrated by entropy indices and matrices of the likelihood of the membership to the classes. A probable weak point of the survey is the selection of fitness centres, because of the market in Prague is really specific.

Keywords: customer, fitness, latent class analysis, typology

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378 Providing a Secure, Reliable and Decentralized Document Management Solution Using Blockchain by a Virtual Identity Card

Authors: Meet Shah, Ankita Aditya, Dhruv Bindra, V. S. Omkar, Aashruti Seervi

Abstract:

In today's world, we need documents everywhere for a smooth workflow in the identification process or any other security aspects. The current system and techniques which are used for identification need one thing, that is ‘proof of existence’, which involves valid documents, for example, educational, financial, etc. The main issue with the current identity access management system and digital identification process is that the system is centralized in their network, which makes it inefficient. The paper presents the system which resolves all these cited issues. It is based on ‘blockchain’ technology, which is a 'decentralized system'. It allows transactions in a decentralized and immutable manner. The primary notion of the model is to ‘have everything with nothing’. It involves inter-linking required documents of a person with a single identity card so that a person can go anywhere without having the required documents with him/her. The person just needs to be physically present at a place wherein documents are necessary, and using a fingerprint impression and an iris scan print, the rest of the verification will progress. Furthermore, some technical overheads and advancements are listed. This paper also aims to layout its far-vision scenario of blockchain and its impact on future trends.

Keywords: blockchain, decentralized system, fingerprint impression, identity management, iris scan

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377 Effect of Manual Progressive Ischemic Pressure versus Post Isometric Facilitation in the Treatment of Latent Myofascial Trigger Points in Mechanical Neck Pain

Authors: Mohamed M. Diab, Fahmy E. Mohamed, Alaa Balbaa

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Background: Myofascial pain syndrome a common type of non-articular musculoskeletal pain, is a condition associated with regional pain and muscle tenderness characterized by the presence of hypersensitive nodules. Objectives: the purpose of this study is to compare between the effects of manual progressive ischemic pressure versus the effect of post isometric facilitation in the treatment of Rhomboid latent myofascial trigger points. Methods: six patients had participated in this study. Patients divided into two groups. Group A treated by manual progressive ischemic pressure and traditional physical therapy program. Group B treated by post isometric facilitation and traditional physical therapy program. Treatment program was for 6 sessions over two week’s period. Result: Statistical analysis revealed that there is no significant difference in post treatment from pretreatment in pain severity (VAS) in myofascial trigger points with Rhomboid muscles) and Pain pressure threshold (PPT) for tenderness at both groups (A,B). Conclusion: ischemic pressure technique appear to be no more effective than post isometric facilitation in treatment of rhomboids latent myofacial trigger point.

Keywords: Rhmoiboid trigger point, myofacila trigger point, ischemic pressure, post isometric facilitation

Procedia PDF Downloads 283