Search results for: laser applications

Authors: Numair Ahmed Siddiqui, Abdul Hadi bin Abd Rahman, Chow Weng Sum, Wan Ismail Wan Yousif, Asif Zameer, Joel Ben-Awal

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Advances in data capturing from outcrop studies have made possible the acquisition of high-resolution digital data, offering improved and economical reservoir modelling methods. Terrestrial laser scanning utilizing LiDAR (Light detection and ranging) provides a new method to build outcrop based reservoir models, which provide a crucial piece of information to understand heterogeneities in sandstone facies with high-resolution images and data set. This study presents the detailed application of outcrop based sandstone facies connectivity model by acquiring information gathered from traditional fieldwork and processing detailed digital point-cloud data from LiDAR to develop an intermediate small-scale reservoir sandstone facies model of the Miocene Sandakan Formation, Sabah, East Malaysia. The software RiScan pro (v1.8.0) was used in digital data collection and post-processing with an accuracy of 0.01 m and point acquisition rate of up to 10,000 points per second. We provide an accurate and descriptive workflow to triangulate point-clouds of different sets of sandstone facies with well-marked top and bottom boundaries in conjunction with field sedimentology. This will provide highly accurate qualitative sandstone facies connectivity model which is a challenge to obtain from subsurface datasets (i.e., seismic and well data). Finally, by applying this workflow, we can build an outcrop based static connectivity model, which can be an analogue to subsurface reservoir studies.

Keywords: LiDAR, outcrop, high resolution, sandstone faceis, connectivity model

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Authors: A: Annis Fathima, V. Vaidehi, S. Ajitha

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Face recognition system finds many applications in surveillance and human computer interaction systems. As the applications using face recognition systems are of much importance and demand more accuracy, more robustness in the face recognition system is expected with less computation time. In this paper, a hybrid approach for face recognition combining Gabor Wavelet and Linear Discriminant Analysis (HGWLDA) is proposed. The normalized input grayscale image is approximated and reduced in dimension to lower the processing overhead for Gabor filters. This image is convolved with bank of Gabor filters with varying scales and orientations. LDA, a subspace analysis techniques are used to reduce the intra-class space and maximize the inter-class space. The techniques used are 2-dimensional Linear Discriminant Analysis (2D-LDA), 2-dimensional bidirectional LDA ((2D)2LDA), Weighted 2-dimensional bidirectional Linear Discriminant Analysis (Wt (2D)2 LDA). LDA reduces the feature dimension by extracting the features with greater variance. k-Nearest Neighbour (k-NN) classifier is used to classify and recognize the test image by comparing its feature with each of the training set features. The HGWLDA approach is robust against illumination conditions as the Gabor features are illumination invariant. This approach also aims at a better recognition rate using less number of features for varying expressions. The performance of the proposed HGWLDA approaches is evaluated using AT&T database, MIT-India face database and faces94 database. It is found that the proposed HGWLDA approach provides better results than the existing Gabor approach.

Keywords: face recognition, Gabor wavelet, LDA, k-NN classifier

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Authors: Chen-En Lin, Lih-Rou Rau, Jiunn-Woei Liaw, Shiao-Wen Tsai

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The unique optical properties of plasmon resonance metallic particles have attracted considerable applications in the fields of physics, chemistry and biology. Metal-Enhanced Fluorescence (MEF) effect is one of the useful applications. MEF effect stated that fluorescence intensity can be quenched or be enhanced depending on the distance between fluorophores and the metal nanoparticles. Silver nanoparticles have used widely in antibacterial studies. However, the major limitation for silver nanoparticles (AgNPs) in biomedical application is well-known cytotoxicity on cells. There were numerous literatures have been devoted to overcome the disadvantage. The aim of the study is to evaluate the cytotoxicity and biocompatibility of silica coated AgNPs against NIH-3T3 cells. The results were shown that NIH-3T3 cells started to detach, shrink, become rounded and finally be irregular in shape after 24 h of exposure at 10 µg/ml AgNPs. Besides, compared with untreated cells, the cell viability significantly decreased to 60% and 40% which were exposed to 10 µg/ml and 20 µg/ml AgNPs respectively. The result was consistent with previously reported findings that AgNPs induced cytotoxicity was concentration dependent. However, the morphology and cell viability of cells appeared similar to the control group when exposed to 20 µg/ml of silica coated AgNPs. We further utilized the dark-field hyperspectral imaging system to analysis the optical properties of the intracellular nanoparticles. The image displayed that the red shift of the surface plasmonic resonances band of the enclosed AgNPs further confirms the agglomerate of the AgNPs rather than their distribution in cytoplasm. In conclusion, the study demonstrated the silica coated of AgNPs showed well biocompatibility and significant lower cytotoxicity compared with bare AgNPs.

Keywords: silver nanoparticles, silica, cell viability, morphology

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Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

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Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

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The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: coupled Markov random field (MRF), environment, object-based analysis, polarimetric SAR (PolSAR) images

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Mona Hassan Aburahma, Alaa Hamed Salama

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Ufasomes “unsaturated fatty acids liposomes” are unique nano-sized self-assembled bilayered vesicles that can be easily created from the readily available unsaturated fatty acid. Ufasomes are formed due to weak associative interaction of the fully ionized and unionized fatty acids into bilayers structures. In the ufasomes constructs, the fatty acid molecules are oriented with their hydrocarbon tails directed toward the membrane interior and the carboxyl groups are in contact with water. Although ufasomes can be employed as a safe vesicular carrier for drugs, the extreme instability of their aqueous dispersions hinders their effective use in drug delivery field. Accordingly, in our study, lyophilized gels containing ufasomes were prepared using a simple assembling technique form the readily available oleic acid to overcome the colloidal instability of the ufasomes dispersions and convert them into accurate unit dosage forms. The influence of changing cholesterol percentage relative to oleic acid on the ufasomes vesicles were investigated using factorial design. The optimized oleic acid ufasomes comprised nanoscaled spherical vesicles. Scanning electron micrographs of the lyophilized gels revealed that the included ufasomes were intact, non-aggregating, and preserved their spherical morphology. Rheological characterization (viscosity and shear stress versus shear rate) of reconstituted ufasomal lyophilized gel ensured the ease of application. The capability of the ufasomes, included in the gel, to penetrate deep through the mucosa layers was illustrated using ex-vivo confocal laser imaging, thereby, highlighting the feasibility of stabilizing ufasomes using lyophilized gel platforms.

Keywords: ufasomes, lyophilized gel, confocal scanning microscopy, rheological characterization, oleic acid

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Authors: K. Swapna, Sk. Mahamuda, Ch, Annapurna, A. Srinivasa Rao, G. Vijaya Prakash

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Samarium ions doped Alkali Fluoro Tungsten Tellurite (AFTT) Glasses have been prepared by using the melt quenching technique and characterized through various spectroscopic techniques such as optical absorption, excitation, emission and decay spectral studies. From the measured absorption spectra of Sm3+ ions in AFTT glasses, the optical band gap and Urbach energies have been evaluated. The spectroscopic parameters such as oscillator strengths (f), Judd-Ofelt (J-O) intensity parameters (Ωλ), spontaneous emission probability (AR), branching ratios (βR) and radiative lifetimes (τR) of various excited levels have been determined from the absorption spectrum by using J-O analysis. A strong luminescence in the reddish-orange spectral region has been observed for all the Sm3+ ions doped AFTT glasses. It consisting four emission transitions occurring from the 4G5/2metastable state to the lower lying states 6H5/2, 6H7/2, 6H9/2 and 6H11/2 upon exciting the sample with a 478 nm line of an argon ion laser. The stimulated emission cross-sections (σe) and branching ratios (βmeas) were estimated from the emission spectra for all emission transitions. Correlation of the radiative lifetime with the experimental lifetime measured from the day curves allows us to measure the quantum efficiency of the prepared glasses. In order to know the colour emission of the prepared glasses under near UV excitation, the emission intensities were analyzed using CIE 1931 colour chromaticity diagram. The aforementioned spectral studies carried out on Sm3+ ions doped AFTT glasses allowed us to conclude that, these glasses are best suited for orange-red visible lasers.

Keywords: fluoro tungsten tellurite glasses, judd-ofelt intensity parameters, lifetime, stimulated emission cross-section

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Authors: Radhamanohar Aepuru, R. V. Mangalaraja

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Flexible electronic devices have drawn potential interest and provide significant new insights to develop energy conversion and storage devices such as photodetectors and nanogenerators. Recently, self-powered electronic systems have captivated huge attention for next generation MEMS/NEMS devices that can operate independently by generating built-in field without any need of external bias voltage and have wide variety of applications in telecommunication, imaging, environmental and defence sectors. The basic physical process involved in these devices are charge generation, separation, and charge flow across the electrodes. Many inorganic nanostructures have been exploring to fabricate various optoelectronic and electromechanical devices. However, the interaction of nanostructures and their excited charge carrier dynamics, photoinduced charge separation, and fast carrier mobility are yet to be studied. The proposed research is to address one such area and to realize the self-powered electronic devices. In the present work, nanocomposites of inorganic nanostructures based on ZnO, metal halide perovskites; and polyvinylidene fluoride (PVDF) based nanocomposites are realized for photodetectors and nanogenerators. The characterization of the inorganic nanostructures is carried out through steady state optical absorption and luminescence spectroscopies as well as X-ray diffraction and high-resolution transmission electron microscopy (TEM) studies. The detailed carrier dynamics is investigated using various spectroscopic techniques. The developed composite nanostructures exhibit significant optical and electrical properties, which have wide potential applications in various MEMS/NEMS devices such as photodetectors and nanogenerators.

Keywords: dielectrics, nanocomposites, nanogenerators, photodetectors

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Authors: Kiran Nair, Jincy George, Suhaib Anagreh

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Artificial intelligence (AI) in a marketing context is a form of a deterministic tool designed to optimize and enhance marketing tasks, research tools, and techniques. It is on the verge of transforming marketing roles and revolutionize the entire industry. This paper aims to explore the current dissemination of the application of artificial intelligence (AI) in the marketing mix, reviewing the scope and application of AI in various aspects of sales and distribution management. The paper also aims at identifying the areas of the strong impact of AI in factors of sales and distribution management such as distribution channel, purchase automation, customer service, merchandising automation, and shopping experiences. This is a qualitative research paper that aims to examine the impact of AI on sales and distribution management of 30 multinational brands in six different industries, namely: airline; automobile; banking and insurance; education; information technology; retail and telecom. Primary data is collected by means of interviews and questionnaires from a sample of 100 marketing managers that have been selected using convenient sampling method. The data is then analyzed using descriptive statistics, correlation analysis and multiple regression analysis. The study reveals that AI applications are extensively used in sales and distribution management, with a strong impact on various factors such as identifying new distribution channels, automation in merchandising, customer service, and purchase automation as well as sales processes. International brands have already integrated AI extensively in their day-to-day operations for better efficiency and improved market share while others are investing heavily in new AI applications for gaining competitive advantage.

Keywords: artificial intelligence, sales and distribution, marketing mix, distribution channel, customer service

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Authors: Yousef Farhaoui

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An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS).

Keywords: intrusion detection, architectures, characteristic, tools, security, web server

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Authors: Afsheen Aman, Shah Ali Ul Qader

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Dextransucrase [EC 2.4.1.5] is a glucosyltransferase that catalysis the biosynthesis of a natural biopolymer called dextran. It can catalyze the transfer of D-glucopyranosyl residues from sucrose to the main chain of dextran. This unique biopolymer has multiple applications in several industries and the key utilization of dextran lies on its molecular weight and the type of branching. Extracellular dextransucrase from Leuconostoc mesenteroides is most extensively studied and characterized. Limited data is available regarding cell-bound or intracellular dextransucrase and on the characterization of dextran produced by in-vitro reaction of intracellular dextransucrase. L. mesenteroides AA1 is reported to produce extracellular dextransucrase that catalyzes biosynthesis of a high molecular weight dextran with only α-(1→6) linkage. Current study deals with the characterization of an intracellular dextransucrase and in vitro biosynthesis of low molecular weight dextran from L. mesenteroides AA1. Intracellular dextransucrase was extracted from cytoplasm and purified to homogeneity for characterization. Kinetic constants, molecular weight and N-terminal sequence analysis of intracellular dextransucrase reveal unique variation with previously reported extracellular dextransucrase from the same strain. In vitro synthesized biopolymer was characterized using NMR spectroscopic techniques. Intracellular dextransucrase exhibited Vmax and Km values of 130.8 DSU ml-1 hr-1 and 221.3 mM, respectively. Optimum catalytic activity was detected at 35°C in 0.15 M citrate phosphate buffer (pH-5.5) in 05 minutes. Molecular mass of purified intracellular dextransucrase is approximately 220.0 kDa on SDS-PAGE. N-terminal sequence of the intracellular enzyme is: GLPGYFGVN that showed no homology with previously reported sequence for the extracellular dextransucrase. This intracellular dextransucrase is capable of in vitro synthesis of dextran under specific conditions. This intracellular dextransucrase is capable of in vitro synthesis of dextran under specific conditions and this biopolymer can be hydrolyzed into different molecular weight fractions for various applications.

Keywords: characterization, dextran, dextransucrase, leuconostoc mesenteroides

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Authors: Jessica Pinheiro Silva, Brenda Rabello De Camargo, Daniel Gusmao De Morais, Eliane Ferreira Noronha

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The utilization of lignocellulosic biomass as source of polysaccharides for industrial applications requires an arsenal of enzymes with different mode of action able to hydrolyze its complex and recalcitrant structure. Clostridium thermocellum is gram-positive, thermophilic bacterium producing lignocellulosic hydrolyzing enzymes in the form of multi-enzyme complex, termed celulossomes. This complex has several hydrolytic enzymes attached to a large and enzymically inactive protein known as Cellulosome-integrating protein (CipA), which serves as a scaffolding protein for the complex produced. This attachment occurs through specific interactions between cohesin modules of CipA and dockerin modules in enzymes. The present work aims to construct celulosomes in vitro with the structural protein CipA, a xylanase called Xyn10D and a cellulose called CelJ from C.thermocellum. A mini-scafoldin was constructed from modules derived from CipA containing two cohesion modules. This was cloned and expressed in Escherichia coli. The other two genes were cloned under the control of the alcohol oxidase 1 promoter (AOX1) in the vector pPIC9 and integrated into the genome of the methylotrophic yeast Pichia pastoris GS115. Purification of each protein is being carried out. Further studies regarding enzymatic activity of the cellulosome is going to be evaluated. The cellulosome built in vitro and composed of mini-CipA, CelJ and Xyn10D, can be very interesting for application in industrial processes involving the degradation of plant biomass.

Keywords: cellulosome, CipA, Clostridium thermocellum, cohesin, dockerin, yeast

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Cristina Schreiner, Romeo Ciobanu, Marius Pislaru

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This paper aims to build a system based on fuzzy models that can be implemented in the assessment of ecological systems, to determine appropriate methods of action for reducing adverse effects on environmental and implicit the population. The model proposed provides new perspective for environmental assessment, and it can be used as a practical instrument for decision-making.

Keywords: ecosystem model, environmental security, fuzzy logic, sustainability of habitable regions

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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Authors: William Albeiro Alvarez, Gloria Patricia Jaramillo, Ivan Reinaldo Sarmiento

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Understanding the behavior of individuals and the different human factors that influence the choice when faced with a complex system such as transportation is one of the most complicated aspects of measuring in the components that constitute the modeling of route choice due to that various behaviors and driving mode directly or indirectly affect the choice. During the last two decades, with the development of information and communications technologies, new data collection techniques have emerged such as GPS, geolocation with mobile phones, apps for choosing the route between origin and destination, individual service transport applications among others, where an interest has been generated to improve discrete choice models when considering the incorporation of these developments as well as psychological factors that affect decision making. This paper implements a discrete choice model that proposes and estimates a hybrid model that integrates route choice models and latent variables based on the observation on the route of a sample of public taxi drivers from the city of Medellín, Colombia in relation to its behavior, personality, socioeconomic characteristics, and driving mode. The set of choice options includes the routes generated by the individual service transport applications versus the driver's choice. The hybrid model consists of measurement equations that relate latent variables with measurement indicators and utilities with choice indicators along with structural equations that link the observable characteristics of drivers with latent variables and explanatory variables with utilities.

Keywords: behavior choice model, human factors, hybrid model, real time data

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Authors: Mahsa Mousavi, Hamid Reza Pourshaghaghi, Mohammad Tahghighi, Henk Corporaal

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Recently, Statistic Random-Access Memory-based (SRAM-based) Field-Programmable Gate Arrays (FPGAs) are widely used in aeronautics and space systems where high dependability is demanded and considered as a mandatory requirement. Since design’s circuit is stored in configuration memory in SRAM-based FPGAs; they are very sensitive to Single Event Upsets (SEUs). In addition, the adverse effects of SEUs on the electronics used in space are much higher than in the Earth. Thus, developing fault tolerant techniques play crucial roles for the use of SRAM-based FPGAs in space. However, fault tolerance techniques introduce additional penalties in system parameters, e.g., area, power, performance and design time. In this paper, an accurate estimation of configuration memory vulnerability to SEUs is proposed for approximate-tolerant applications. This vulnerability estimation is highly required for compromising between the overhead introduced by fault tolerance techniques and system robustness. In this paper, we study applications in which the exact final output value is not necessarily always a concern meaning that some of the SEU-induced changes in output values are negligible. We therefore define and propose Approximate-based Configuration Memory Vulnerability Factor (ACMVF) estimation to avoid overestimating configuration memory vulnerability to SEUs. In this paper, we assess the vulnerability of configuration memory by injecting SEUs in configuration memory bits and comparing the output values of a given circuit in presence of SEUs with expected correct output. In spite of conventional vulnerability factor calculation methods, which accounts any deviations from the expected value as failures, in our proposed method a threshold margin is considered depending on user-case applications. Given the proposed threshold margin in our model, a failure occurs only when the difference between the erroneous output value and the expected output value is more than this margin. The ACMVF is subsequently calculated by acquiring the ratio of failures with respect to the total number of SEU injections. In our paper, a test-bench for emulating SEUs and calculating ACMVF is implemented on Zynq-7000 FPGA platform. This system makes use of the Single Event Mitigation (SEM) IP core to inject SEUs into configuration memory bits of the target design implemented in Zynq-7000 FPGA. Experimental results for 32-bit adder show that, when 1% to 10% deviation from correct output is considered, the counted failures number is reduced 41% to 59% compared with the failures number counted by conventional vulnerability factor calculation. It means that estimation accuracy of the configuration memory vulnerability to SEUs is improved up to 58% in the case that 10% deviation is acceptable in output results. Note that less than 10% deviation in addition result is reasonably tolerable for many applications in approximate computing domain such as Convolutional Neural Network (CNN).

Keywords: fault tolerance, FPGA, single event upset, approximate computing

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Authors: Francisco Dos Santos, Diogo Fonseca-Pereira, Sílvia Arroz-Madeira, Henrique Veiga-Fernandes

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Haematopoiesis is a developmental process that generates all blood cell lineages in health and disease. This relies on quiescent haematopoietic stem cells (HSCs) that are able to differentiate, self renew and expand upon physiological demand. HSCs have great interest in regenerative medicine, including haematological malignancies, immunodeficiencies and metabolic disorders. However, the limited yield from existing HSC sources drives the global need for reliable techniques to expand harvested HSCs at high quality and sufficient quantities. With the extensive use of cord blood progenitors for clinical applications, there is a demand for a safe and efficient expansion protocol that is able to overcome the limitations of the cord blood as a source of HSC. StemCell2MAXTM developed a technology that enhances the survival, proliferation and transplantation efficiency of HSC, leading the way to a more widespread use of HSC for research and clinical purposes. StemCell2MAXTM MIX is a solution that improves HSC expansion up to 20x, while preserving stemness, when compared to state-of-the-art. In a recent study by a leading cord blood bank, StemCell2MAX MIX was shown to support a selective 100-fold expansion of CD34+ Hematopoietic Stem and Progenitor Cells (when compared to a 10-fold expansion of Total Nucleated Cells), while maintaining their multipotent differentiative potential as assessed by CFU assays. The technology developed by StemCell2MAXTM opens new horizons for the usage of expanded hematopoietic progenitors for both research purposes (including quality and functional assays in Cord Blood Banks) and clinical applications.

Keywords: cord blood, expansion, hematopoietic stem cell, transplantation

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Authors: Kedar Hardikar, Joe Varghese

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Conductive adhesives have found wide-ranging applications in electronics industry ranging from fixing a defective conductor on printed circuit board (PCB) attaching an electronic component in an assembly to protecting electronics components by the formation of “Faraday Cage.” The reliability requirements for the conductive adhesive vary widely depending on the application and expected product lifetime. While the conductive adhesive is required to maintain the structural integrity, the electrical performance of the associated sub-assembly can be affected by the degradation of conductive adhesive. The degradation of the adhesive is dependent upon the highly varied use case. The conventional approach to assess the reliability of the sub-assembly involves subjecting it to the standard environmental test conditions such as high-temperature high humidity, thermal cycling, high-temperature exposure to name a few. In order to enable projection of test data and observed failures to predict field performance, systematic development of an acceleration factor between the test conditions and field conditions is crucial. Common acceleration factor models such as Arrhenius model are based on rate kinetics and typically rely on an assumption of linear degradation in time for a given condition and test duration. The application of interest in this work involves conductive adhesive used in an electronic circuit of a capacitive sensor. The degradation of conductive adhesive in high temperature and humidity environment is quantified by the capacitance values. Under such conditions, the use of established models such as Hallberg-Peck model or Eyring Model to predict time to failure in the field typically relies on linear degradation rate. In this particular case, it is seen that the degradation is nonlinear in time and exhibits a square root t dependence. It is also shown that for the mechanism of interest, the presence of moisture is essential, and the dominant mechanism driving the degradation is the diffusion of moisture. In this work, a framework is developed to incorporate nonlinear degradation of the conductive adhesive for the development of an acceleration factor. This method can be extended to applications where nonlinearity in degradation rate can be adequately characterized in tests. It is shown that depending on the expected product lifetime, the use of conventional linear degradation approach can overestimate or underestimate the field performance. This work provides guidelines for suitability of linear degradation approximation for such varied applications

Keywords: conductive adhesives, nonlinear degradation, physics of failure, acceleration factor model.

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Authors: Olaide O. Wahab, Lukman O. Olasunkanmi, Krishna K. Govender, Penny P. Govender

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The economic and environmental challenges associated with azo disperse dyes applications are due to poor aqueous solubility and low degradation tendency which stems from low chemical reactivity. Poor aqueous solubility property of this group of dyes necessitates the use of dispersing agents which increase operational costs and also release toxic chemical components into the environment, while their low degradation tendency is due to the high stability of the azo functional group (-N=N-) in their chemical structures. To address these problems, this study investigated theoretically the effects of some polar substituents on the aqueous solubility and reactivity properties of disperse yellow (DY) 119 dye with a view to theoretically develop new azo disperse dyes with improved solubility in water and higher degradation tendency in the environment using DMol³ computational code. All calculations were carried out using the Becke and Perdew version of Volsko-Wilk-Nusair (VWN-BP) level of density functional theory in conjunction with double numerical basis set containing polarization function (DNP). The aqueous solubility determination was achieved with conductor-like screening model for realistic solvation (COSMO-RS) in conjunction with known empirical solubility model, while the reactivity was predicted using frontier molecular orbital calculations. Most of the new derivatives studied showed evidence of higher aqueous solubility and degradation tendency compared to the parent dye. We conclude that these derivatives are promising alternative dyes for more economic and environmental benign dyeing practice and therefore recommend them for synthesis.

Keywords: aqueous solubility, azo disperse dye, degradation, disperse yellow 119, DMol³, reactivity

Procedia PDF Downloads 207

Authors: Avishek Chanda, Nam Kyeun Kim, Debes Bhattacharyya

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The use of renewable substitutes in various semi-structural and structural applications has experienced an increase since the last few decades. Sandwich panels have been used for many decades, although research on understanding the effects of the core structures on the panels’ fire-reaction properties is limited. The current work investigates the fire-performance of a corrugated sandwich panel made from renewable, biodegradable, and sustainable material, plywood. The bench-scale fire testing apparatus, cone-calorimeter, was employed to evaluate the required fire-reaction properties of the sandwich core in a panel configuration, with three corrugated layers glued together with face-sheets under a heat irradiance of 50 kW/m². The study helped in documenting a unique heat release trend associated with the fire performance of the 3-layered corrugated sandwich panels and in understanding the structural stability of the samples in the event of a fire. Furthermore, the total peak heat release rate was observed to be around 421 kW/m², which is significantly low compared to many polymeric materials in the literature. The total smoke production was also perceived to be very limited compared to other structural materials, and the total heat release was also nominal. The time to ignition of 21.7 s further outlined the advantages of using the plywood component since polymeric composites, even with flame-retardant additives, tend to ignite faster. Overall, the corrugated plywood sandwich panels had significant fire-reaction properties and could have important structural applications. The possible use of structural panels made from bio-degradable material opens a new avenue for the use of similar structures in sandwich panel preparation.

Keywords: corrugated sandwich panel, fire-reaction properties, plywood, renewable material

Procedia PDF Downloads 158

Authors: B. Vinod, L. J. Sudev

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Natural fibers as reinforcement in polymer matrix material are gaining lot of attention in recent years. Natural fibers like jute, sisal, coir, hemp, banana etc. have attracted substantial importance as a potential structural material because of its attractive features along with its good mechanical properties. Cryogenic applications of natural fiber reinforced polymer composites are gaining importance. These materials need to possess good mechanical and physical properties at cryogenic temperatures to meet the high requirements by the cryogenic engineering applications. The objective of this work is to investigate the mechanical behavior of hybrid hemp/jute fibers reinforced epoxy composite material at liquid nitrogen temperature. Hybrid hemp/jute fibers reinforced polymer composite is prepared by hand lay-up method and test specimens are cut according to ASTM standards. These test specimens are dipped in liquid nitrogen for different time durations. The tensile properties, flexural properties and impact strength of the specimen are tested immediately after the specimens are removed from liquid nitrogen container. The experimental results indicate that the cryogenic treatment of the polymer composite has a significant effect on the mechanical properties of this material. The tensile properties and flexural properties of the hybrid hemp/jute fibers epoxy composite at liquid nitrogen temperature is higher than at room temperature. The impact strength of the material decreased after subjecting it to liquid nitrogen temperature.

Keywords: liquid nitrogen temperature, polymer composite, tensile properties, flexural properties

Procedia PDF Downloads 405

Authors: Biki Sarmah, Priyanko Raj Mudiar

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In the modern world of remotely interactive virtual reality-based learning and teaching, including professional skill-building training and acquisition practices, as well as data acquisition and robotic systems, the revolutionary application or implementation of field-programmable neurostimulator aids and first-hand interactive sensitisation techniques into 3D holographic audio-visual platforms have been a coveted dream of many scholars, professionals, scientists, and students. Integration of 'kinaesthetic vibrotactile haptic perception' along with an actuated step magnitude contact profiloscopy in augmented reality-based learning platforms and professional training can be implemented by using an extremely calculated and well-coordinated image telemetry including remote data mining and control technique. A real-time, computer-aided (PLC-SCADA) field calibration based algorithm must be designed for the purpose. But most importantly, in order to actually realise, as well as to 'interact' with some 3D holographic models displayed over a remote screen using remote laser image telemetry and control, all spatio-physical parameters like cardinal alignment, gyroscopic compensation, as well as surface profile and thermal compositions, must be implemented using zero-order type 1 actuators (or transducers) because they provide zero hystereses, zero backlashes, low deadtime as well as providing a linear, absolutely controllable, intrinsically observable and smooth performance with the least amount of error compensation while ensuring the best ergonomic comfort ever possible for the users.

Keywords: haptic feedback, kinaesthetic vibrotactile 3D design, medical simulation training, piezo diaphragm based actuator

Procedia PDF Downloads 169

Authors: Ashima Sharma, Tapan K. Chaudhuri

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Human Serum Albumin (HSA) is one of the most demanded therapeutic protein with immense biotechnological applications. The current source of HSA is human blood plasma. Blood is a limited and an unsafe source as it possesses the risk of contamination by various blood derived pathogens. This issue led to exploitation of various hosts with the aim to obtain an alternative source for the production of the rHSA. But, till now no host has been proven to be effective commercially for rHSA production because of their respective limitations. Thus, there exists an indispensable need to promote non-animal derived rHSA production. Of all the host systems, Escherichia coli is one of the most convenient hosts which has contributed in the production of more than 30% of the FDA approved recombinant pharmaceuticals. E. coli grows rapidly and its culture reaches high cell density using inexpensive and simple substrates. The fermentation batch turnaround number for E. coli culture is 300 per year, which is far greater than any of the host systems available. Therefore, E. coli derived recombinant products have more economical potential as fermentation processes are cheaper compared to the other expression hosts available. Despite of all the mentioned advantages, E. coli had not been successfully adopted as a host for rHSA production. The major bottleneck in exploiting E. coli as a host for rHSA production was aggregation i.e. majority of the expressed recombinant protein was forming inclusion bodies (more than 90% of the total expressed rHSA) in the E. coli cytosol. Recovery of functional rHSA form inclusion body is not preferred because it is tedious, time consuming, laborious and expensive. Because of this limitation, E. coli host system was neglected for rHSA production for last few decades. Considering the advantages of E. coli as a host, the present work has targeted E. coli as an alternate host for rHSA production through resolving the major issue of inclusion body formation associated with it. In the present study, we have developed a novel and innovative method for enhanced soluble and functional production of rHSA in E.coli (~60% of the total expressed rHSA in the soluble fraction) through modulation of the cellular growth, folding and environmental parameters, thereby leading to significantly improved and enhanced -expression levels as well as the functional and soluble proportion of the total expressed rHSA in the cytosolic fraction of the host. Therefore, in the present case we have filled in the gap in the literature, by exploiting the most well studied host system Escherichia coli which is of low cost, fast growing, scalable and ‘yet neglected’, for the enhancement of functional production of HSA- one of the most crucial biomolecule for clinical and biotechnological applications.

Keywords: enhanced functional production of rHSA in E. coli, recombinant human serum albumin, recombinant protein expression, recombinant protein processing

Procedia PDF Downloads 348

Authors: Rajat Dhawan, Hitendra K. Malik

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Electronegative plasmas comprising electrons, positive ions, and negative ions are advantageous for their expanding applications in industries. In plasma cleaning, plasma etching, and plasma deposition process, electronegative plasmas are preferred because of relatively less potential developed on the surface of the material under investigation. Also, the presence of negative ions avoid the irregularity in etching shapes and also enhance the material working during the fabrication process. The interaction of metallic conducting surface with plasma becomes mandatory to understand these applications. A metallic conducting probe immersed in a plasma results in the formation of a thin layer of charged species around the probe called as a sheath. The density of the ions embedded on the surface of the material and the sheath thickness are the important parameters for the surface-plasma interaction. Sheath thickness will give rise to the information of affected plasma region due to conducting surface/probe. The knowledge of the density of ions in the sheath region is advantageous in plasma nitriding, and their temperature is equally important as it strongly influences the thickness of the modified layer during surface plasma interaction. In the present work, we considered a negatively biased metallic probe immersed in a warm electronegative plasma. For this system, we adopted the continuity equation and momentum transfer equation for both the positive and negative ions, whereas electrons are described by Boltzmann distribution. Finally, we use the Poisson’s equation. Here, we assumed the spherical geometry for small probe radius. Poisson’s equation reveals the behaviour of potential surrounding a conducting metallic probe along with the use of the continuity and momentum transfer equations, with the help of proper boundary conditions. In turn, it gives rise to the information about the density profile of charged species and most importantly the thickness of the sheath. By keeping in mind, the well-known Bohm-Sheath criterion, all calculations are done. We found that positive ion density decreases with an increase in positive ion temperature, whereas it increases with the higher temperature of the negative ions. Positive ion density decreases as we move away from the center of the probe and is found to show a discontinuity at a particular distance from the center of the probe. The distance where discontinuity occurs is designated as sheath edge, i.e., the point where sheath ends. These results are beneficial for industrial applications, as the density of ions embedded on material surface is strongly affected by the temperature of plasma species. It has a drastic influence on the surface properties, i.e., the hardness, corrosion resistance, etc. of the materials.

Keywords: electronegative plasmas, plasma surface interaction positive ion density, sheath thickness

Procedia PDF Downloads 135

Authors: Ahmed A. Alghamdi

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Single-walled carbon nanotubes (SWCNTs) are an outstanding material for applications in thermoelectric power generation, nanoelectronics, electrochemical energy storage, photovoltaics, and light emission. They are ultra-lightweight and possess electrical as well as thermal conductivity, flexibility, and mechanical strength. SWCNT is applicable in water treatment, brine desalination, removal of heavy metal ions associated with pollutants, and oil-water separation. Carbon nanotube (CNT) is believed to tackle the trade-off issue between permeability, selectivity, and fouling issues in membrane filtration applications. Studying these CNT structures, as well as their interconnection in nanotechnology, assists in finding the precise position to be placed for water desalination. Reverse osmosis (RO) has been used globally for desalination, resulting in purified water. Thin film composite (TFC) membranes were utilized in the RO process for desalination. The sheet thickness increases the salt rejection and decreases the water flux when CNT is utilized as a support layer to this membrane. Thus, through a temperature-induced phase separation technique (TIPS), axially aligned SWCNT (AASWCNT) is fabricated, and its use enhances the salt rejection and water flux at short reaction times with a modified procedure. An evaluation was conducted and analogized with prior works in the literature, which exhibited that the prepared TFC membrane showed a better outcome.

Keywords: single-walled carbon nanotubes, thin film composite, axially aligned swcnt, temperature induced phase separation technique, reverse osmosis

Procedia PDF Downloads 54

Authors: Kumari Kajal, Muthu Kumar Sampath, Hare Ram Singh

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In this context, the formulation and characterization of collagen silver lipid nanoparticles (CSLNs) were studied for their capacity to serve as fillers/matrix materials used in cosmeceutical applications. The CSLNs were prepared following a series of studies, such as X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM) coupled with energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy FT-IR; thermogravimetric analysis (TGA); and differential scanning calorimetry (DSC). The studies confirmed the structural integrity of nanoparticles, their cargo and thermal stability. The biological functionality of CSLNs was studied by carrying out in vitro & in vivo studies. The antibacterial effect, hemocompatibility and anti-inflammatory characteristics of these fibers were systematically investigated. The toxicological assays included oral toxicity in mice and aquatic life tests with the fish Danio rerio model. The morphology of the nanoparticles was confirmed using high-resolution transmission electron microscopy (HR-TEM). The report found that CSLNs had strong antimicrobial effects, unmatched hemocompatibility, and low or absent inflammatory reactions, which makes them perfect candidates for cosmeceutical applications. The toxicological evaluations evinced a good safety record without any significant adverse effects in both murine and Danio rerio models. This research reveals the efficient way of CSLNs to the efficacy and safety of dermaceuticals.

Keywords: collagen silver lipid nanoparticles (CSLNs), cosmeceuticals, antimicrobial activity, hemocompatibility, in vitro assessment, in vivo assessment.

Procedia PDF Downloads 19

Authors: R. Geetha, J. Arunkumar, P. Gopal, D. Loganathan, K. Pavithra, C. Vikashini

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Mobile Number Portability is an attempt to switch over from one network to another network facility for mobile based on applications. This facility is currently not available for mobile handsets. This application is intended to assist the mobile network and its service customers in understanding the criteria; this will serve as a universal set of requirements which must be met by the customers. This application helps the user's network portability. Accessing permission from the network provider to enable services to the user and utilizing the available network signals. It is enabling the user to make a temporary switch over to other network. The main aim of this research work is to adapt multiple networks at the time of no network coverage. It can be accessed at rural and geographical areas. This can be achieved by this mobile application. The application is capable of temporary switch over between various networks. With this application both the service provider and the network user are benefited. The service provider is benefited by charging a minimum cost for utilizing other network. It provides security in terms of password that is unique to avoid unauthorized users and to prevent loss of balance. The goal intended to be attained is a complete utilization of available network at significant situations and to provide feature that satisfy the customer needs. The temporary switch over is done to manage emergency calls when user is in rural or geographical area, where there will be a very low network coverage. Since people find it trend in using Android mobile, this application is designed as an Android applications, which can be freely downloaded and installed from Play store. In the current scenario, the service provider enables the user to change their network without shifting their mobile network. This application affords a clarification for users while they are jammed in a critical situation. This application is designed by using Android 4.2 and SQLite Version3.

Keywords: mobile number, random number, alarm, imei number, call

Procedia PDF Downloads 364

Authors: Bouhafara Djaber, Menail Younes, Mesrafet Farouk, Aissaoui Mohammed Islem

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This article presents results of experimental investigations of the durability of (GFRP) composite exposed to typical environments of marine industries applications,The use of fiber-glass reinforced polyester composites in marine applications such as Hulls of voyage boats and hulls of small vessels for the military navy , this type of composite is becoming attractive because of their reduced weight and improved corrosion resistance. However,a deep understating of oil ageing effect on composite structures is essential to ensure long-term performance and durability. in this work evaluate the effect of oil ageing on absorptıon behavıor and ımpact properties of glass/polyester composites manufactured with two types of fiber fabrics (fibreglass mat and fiberglass woven roving) and isophthalic polyester resin. The specimens obtained from commercial (GFRP) profiles made of unsaturated polyester resin were subjected to immersion in (i) marine oil for boats and (ii) salt water at ambient temperature for up to 1 month. The effects of such exposure conditions on this types of profile we analysed in what concerns their (i) mass change,(ii) mechanical response in impact, namely on the mechanical response – oil immersion caused a higher level of degradation, compared with salt water immersion;fracture surface examination by scanning electron microscopy revealed delamination, fiber debonding and resin crumbling due to oil effect.

Keywords: Marine Engine Oil, Absorption, Polyester, Glass Fibre

Procedia PDF Downloads 85