Search results for: hidden layer
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2901

Search results for: hidden layer

1521 Towards Accurate Velocity Profile Models in Turbulent Open-Channel Flows: Improved Eddy Viscosity Formulation

Authors: W. Meron Mebrahtu, R. Absi

Abstract:

Velocity distribution in turbulent open-channel flows is organized in a complex manner. This is due to the large spatial and temporal variability of fluid motion resulting from the free-surface turbulent flow condition. This phenomenon is complicated further due to the complex geometry of channels and the presence of solids transported. Thus, several efforts were made to understand the phenomenon and obtain accurate mathematical models that are suitable for engineering applications. However, predictions are inaccurate because oversimplified assumptions are involved in modeling this complex phenomenon. Therefore, the aim of this work is to study velocity distribution profiles and obtain simple, more accurate, and predictive mathematical models. Particular focus will be made on the acceptable simplification of the general transport equations and an accurate representation of eddy viscosity. Wide rectangular open-channel seems suitable to begin the study; other assumptions are smooth-wall, and sediment-free flow under steady and uniform flow conditions. These assumptions will allow examining the effect of the bottom wall and the free surface only, which is a necessary step before dealing with more complex flow scenarios. For this flow condition, two ordinary differential equations are obtained for velocity profiles; from the Reynolds-averaged Navier-Stokes (RANS) equation and equilibrium consideration between turbulent kinetic energy (TKE) production and dissipation. Then different analytic models for eddy viscosity, TKE, and mixing length were assessed. Computation results for velocity profiles were compared to experimental data for different flow conditions and the well-known linear, log, and log-wake laws. Results show that the model based on the RANS equation provides more accurate velocity profiles. In the viscous sublayer and buffer layer, the method based on Prandtl’s eddy viscosity model and Van Driest mixing length give a more precise result. For the log layer and outer region, a mixing length equation derived from Von Karman’s similarity hypothesis provides the best agreement with measured data except near the free surface where an additional correction based on a damping function for eddy viscosity is used. This method allows more accurate velocity profiles with the same value of the damping coefficient that is valid under different flow conditions. This work continues with investigating narrow channels, complex geometries, and the effect of solids transported in sewers.

Keywords: accuracy, eddy viscosity, sewers, velocity profile

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1520 Fight against Money Laundering with Optical Character Recognition

Authors: Saikiran Subbagari, Avinash Malladhi

Abstract:

Anti Money Laundering (AML) regulations are designed to prevent money laundering and terrorist financing activities worldwide. Financial institutions around the world are legally obligated to identify, assess and mitigate the risks associated with money laundering and report any suspicious transactions to governing authorities. With increasing volumes of data to analyze, financial institutions seek to automate their AML processes. In the rise of financial crimes, optical character recognition (OCR), in combination with machine learning (ML) algorithms, serves as a crucial tool for automating AML processes by extracting the data from documents and identifying suspicious transactions. In this paper, we examine the utilization of OCR for AML and delve into various OCR techniques employed in AML processes. These techniques encompass template-based, feature-based, neural network-based, natural language processing (NLP), hidden markov models (HMMs), conditional random fields (CRFs), binarizations, pattern matching and stroke width transform (SWT). We evaluate each technique, discussing their strengths and constraints. Also, we emphasize on how OCR can improve the accuracy of customer identity verification by comparing the extracted text with the office of foreign assets control (OFAC) watchlist. We will also discuss how OCR helps to overcome language barriers in AML compliance. We also address the implementation challenges that OCR-based AML systems may face and offer recommendations for financial institutions based on the data from previous research studies, which illustrate the effectiveness of OCR-based AML.

Keywords: anti-money laundering, compliance, financial crimes, fraud detection, machine learning, optical character recognition

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1519 The Effect of Nanofiber Web on Thermal Conductivity, Air and Water Vapor Permeability

Authors: Ilkay Ozsev Yuksek, Nuray Ucar, Zeynep Esma Soygur, Yasemin Kucuk

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In this study, composite fabrics with polyacrylonitrile electrospun nanofiber deposited onto quilted polyester fabric have been produced in order to control the isolation properties such as water vapor permeability, air permeability and thermal conductivity. Different nanofiber webs were manufactured by changing polymer concentration from 10% to 16% and by changing the deposition time from 1 to 3 hours. Presence of nanofiber layer on the quilted fabric results to an increase of an isolation, i.e., a decrease of the moisture vapor transport rates at 20%, decrease of thermal conductivity at 15% and a decrease of air permeability values at 50%.

Keywords: nanofiber/fabric composites, electrospinning, isolation, thermal conductivity, moisture vapor transport, air permeability

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1518 Comparison of Various Policies under Different Maintenance Strategies on a Multi-Component System

Authors: Demet Ozgur-Unluakin, Busenur Turkali, Ayse Karacaorenli

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Maintenance strategies can be classified into two types, which are reactive and proactive, with respect to the time of the failure and maintenance. If the maintenance activity is done after a breakdown, it is called reactive maintenance. On the other hand, proactive maintenance, which is further divided as preventive and predictive, focuses on maintaining components before a failure occurs to prevent expensive halts. Recently, the number of interacting components in a system has increased rapidly and therefore, the structure of the systems have become more complex. This situation has made it difficult to provide the right maintenance decisions. Herewith, determining effective decisions has played a significant role. In multi-component systems, many methodologies and strategies can be applied when a component or a system has already broken down or when it is desired to identify and avoid proactively defects that could lead to future failure. This study focuses on the comparison of various maintenance strategies on a multi-component dynamic system. Components in the system are hidden, although there exists partial observability to the decision maker and they deteriorate in time. Several predefined policies under corrective, preventive and predictive maintenance strategies are considered to minimize the total maintenance cost in a planning horizon. The policies are simulated via Dynamic Bayesian Networks on a multi-component system with different policy parameters and cost scenarios, and their performances are evaluated. Results show that when the difference between the corrective and proactive maintenance cost is low, none of the proactive maintenance policies is significantly better than the corrective maintenance. However, when the difference is increased, at least one policy parameter for each proactive maintenance strategy gives significantly lower cost than the corrective maintenance.

Keywords: decision making, dynamic Bayesian networks, maintenance, multi-component systems, reliability

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1517 The Effect of Gender and Resources on Entrepreneurial Activity

Authors: Frederick Nyakudya

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In this paper, we examine the relationship between human capital, personal wealth and social capital to explain the differential start-up rates between female and male entrepreneurs. Since our dependent variable is dichotomous, we examine the determinants of these using a maximum likelihood logit estimator. We used the Global Entrepreneurship Monitor database covering the period 2006 to 2009 with 421 usable cases drawn from drawn from the Lower Layer Super Output Areas in the East Midlands in the United Kingdom. we found evidence that indicates that a female positively moderate the positive relationships between indicators of human capital, personal wealth and social capital with start-up activity. The findings have implications for programs, policies, and practices to encourage more females to engage in start-up activity.

Keywords: entrepreneurship, star-up, gender, GEM

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1516 Development of Perovskite Quantum Dots Light Emitting Diode by Dual-Source Evaporation

Authors: Antoine Dumont, Weiji Hong, Zheng-Hong Lu

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Light emitting diodes (LEDs) are steadily becoming the new standard for luminescent display devices because of their energy efficiency and relatively low cost, and the purity of the light they emit. Our research focuses on the optical properties of the lead halide perovskite CsPbBr₃ and its family that is showing steadily improving performances in LEDs and solar cells. The objective of this work is to investigate CsPbBr₃ as an emitting layer made by physical vapor deposition instead of the usual solution-processed perovskites, for use in LEDs. The deposition in vacuum eliminates any risk of contaminants as well as the necessity for the use of chemical ligands in the synthesis of quantum dots. Initial results show the versatility of the dual-source evaporation method, which allowed us to create different phases in bulk form by altering the mole ratio or deposition rate of CsBr and PbBr₂. The distinct phases Cs₄PbBr₆, CsPbBr₃ and CsPb₂Br₅ – confirmed through XPS (x-ray photoelectron spectroscopy) and X-ray diffraction analysis – have different optical properties and morphologies that can be used for specific applications in optoelectronics. We are particularly focused on the blue shift expected from quantum dots (QDs) and the stability of the perovskite in this form. We already obtained proof of the formation of QDs through our dual source evaporation method with electron microscope imaging and photoluminescence testing, which we understand is a first in the community. We also incorporated the QDs in an LED structure to test the electroluminescence and the effect on performance and have already observed a significant wavelength shift. The goal is to reach 480nm after shifting from the original 528nm bulk emission. The hole transport layer (HTL) material onto which the CsPbBr₃ is evaporated is a critical part of this study as the surface energy interaction dictates the behaviour of the QD growth. A thorough study to determine the optimal HTL is in progress. A strong blue shift for a typically green emitting material like CsPbBr₃ would eliminate the necessity of using blue emitting Cl-based perovskite compounds and could prove to be more stable in a QD structure. The final aim is to make a perovskite QD LED with strong blue luminescence, fabricated through a dual-source evaporation technique that could be scalable to industry level, making this device a viable and cost-effective alternative to current commercial LEDs.

Keywords: material physics, perovskite, light emitting diode, quantum dots, high vacuum deposition, thin film processing

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1515 PsyVBot: Chatbot for Accurate Depression Diagnosis using Long Short-Term Memory and NLP

Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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1514 NSBS: Design of a Network Storage Backup System

Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

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The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

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1513 Study of Ion Density Distribution and Sheath Thickness in Warm Electronegative Plasma

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

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1512 Coding of RMAC and Its Theoretical and Simulation-Based Performance Comparison with SMAC

Authors: Hamida Qumber Ali, Waseem Muhammad Arain, Shama Siddiqui, Sayeed Ghani

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We present an implementing of RMAC in TinyOS 1.x. RMAC is a cross layer and Duty-cycle MAC protocols that was proposed to provide energy efficient transmission services for wireless sensor networks. The protocol has a unique and efficient packet transmission scheduling mechanism that enables it to overcome delivery latency and overcome traffic congestion. Design details and implementation challenges are divulged. Experiments are conducted to show the correctness of our implementation with numerous assumptions. Simulations are performed to compare the performance of RMAC and SMAC. Our results show that RMAC outperforms SMAC in energy efficiency and delay.

Keywords: MAC protocol, performance, RMAC, wireless sensor networks

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1511 The Cultural Persona of Artificial Intelligence: An Analysis of Anthropological Challenges to Public Communication

Authors: Abhivardhan, Ritu Agarwal

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The role of entrepreneurial ethics is connected with materializing the core components of human life, and the flexible and gullible attributions dominate the materialization of human lifestyle and outreach in the age of the internet and globalization. One of the key bi-products of the age of information – Artificial Intelligence has become a relevant mechanism to materialize and understand human empathy and originality via various algorithmic policing methodologies with specific intricacies. Since it has a special connection with ethnocentrism – it has the potential to influence the approach of international law and politics owed to the rise of and approach towards perception and communication via populism in progressive and third world countries. The paper argues about the cultural persona of artificial intelligence, and its ontological resemblance in human life is connected with the ethnocentric treatment of cyberspace, with an analysis of the influence of the ethics of entrepreneurship in international politics. The paper further provides an analysis of fake news and misinformation as the sub-strata of communication strategies involving populism determined as a communication strategy and about the legal case of constitutional redemption in recent legislative developments in Europe, the U.S, and Asia with reference to certain important strategies, policy documentation, declarations, and legal instruments. The paper concludes that the capillaries of the anthropomorphic developments of cultural perception via towards artificial intelligence have a hidden and unstable connection with the common approach of entrepreneurial ethics, which influences populism to disrupt the peaceful order of international politics via some minor backlashes in the technological, legal and social realm of human life. Suggestions with the conclusion are hereby provided.

Keywords: ethnocentrism, perception politics, populism, international law, slacktivism, artificial intelligence ethics, enculturation

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1510 Polymeric Composites with Synergetic Carbon and Layered Metallic Compounds for Supercapacitor Application

Authors: Anukul K. Thakur, Ram Bilash Choudhary, Mandira Majumder

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In this technologically driven world, it is requisite to develop better, faster and smaller electronic devices for various applications to keep pace with fast developing modern life. In addition, it is also required to develop sustainable and clean sources of energy in this era where the environment is being threatened by pollution and its severe consequences. Supercapacitor has gained tremendous attention in the recent years because of its various attractive properties such as it is essentially maintenance-free, high specific power, high power density, excellent pulse charge/discharge characteristics, exhibiting a long cycle-life, require a very simple charging circuit and safe operation. Binary and ternary composites of conducting polymers with carbon and other layered transition metal dichalcogenides have shown tremendous progress in the last few decades. Compared with bulk conducting polymer, these days conducting polymers have gained more attention because of their high electrical conductivity, large surface area, short length for the ion transport and superior electrochemical activity. These properties make them very suitable for several energy storage applications. On the other hand, carbon materials have also been studied intensively, owing to its rich specific surface area, very light weight, excellent chemical-mechanical property and a wide range of the operating temperature. These have been extensively employed in the fabrication of carbon-based energy storage devices and also as an electrode material in supercapacitors. Incorporation of carbon materials into the polymers increases the electrical conductivity of the polymeric composite so formed due to high electrical conductivity, high surface area and interconnectivity of the carbon. Further, polymeric composites based on layered transition metal dichalcogenides such as molybdenum disulfide (MoS2) are also considered important because they are thin indirect band gap semiconductors with a band gap around 1.2 to 1.9eV. Amongst the various 2D materials, MoS2 has received much attention because of its unique structure consisting of a graphene-like hexagonal arrangement of Mo and S atoms stacked layer by layer to give S-Mo-S sandwiches with weak Van-der-Waal forces between them. It shows higher intrinsic fast ionic conductivity than oxides and higher theoretical capacitance than the graphite.

Keywords: supercapacitor, layered transition-metal dichalcogenide, conducting polymer, ternary, carbon

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1509 Modeling of Anode Catalyst against CO in Fuel Cell Using Material Informatics

Authors: M. Khorshed Alam, H. Takaba

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The catalytic properties of metal usually change by intermixturing with another metal in polymer electrolyte fuel cells. Pt-Ru alloy is one of the much-talked used alloy to enhance the CO oxidation. In this work, we have investigated the CO coverage on the Pt2Ru3 nanoparticle with different atomic conformation of Pt and Ru using a combination of material informatics with computational chemistry. Density functional theory (DFT) calculations used to describe the adsorption strength of CO and H with different conformation of Pt Ru ratio in the Pt2Ru3 slab surface. Then through the Monte Carlo (MC) simulations we examined the segregation behaviour of Pt as a function of surface atom ratio, subsurface atom ratio, particle size of the Pt2Ru3 nanoparticle. We have constructed a regression equation so as to reproduce the results of DFT only from the structural descriptors. Descriptors were selected for the regression equation; xa-b indicates the number of bonds between targeted atom a and neighboring atom b in the same layer (a,b = Pt or Ru). Terms of xa-H2 and xa-CO represent the number of atoms a binding H2 and CO molecules, respectively. xa-S is the number of atom a on the surface. xa-b- is the number of bonds between atom a and neighboring atom b located outside the layer. The surface segregation in the alloying nanoparticles is influenced by their component elements, composition, crystal lattice, shape, size, nature of the adsorbents and its pressure, temperature etc. Simulations were performed on different size (2.0 nm, 3.0 nm) of nanoparticle that were mixing of Pt and Ru atoms in different conformation considering of temperature range 333K. In addition to the Pt2Ru3 alloy we also considered pure Pt and Ru nanoparticle to make comparison of surface coverage by adsorbates (H2, CO). Hence, we assumed the pure and Pt-Ru alloy nanoparticles have an fcc crystal structures as well as a cubo-octahedron shape, which is bounded by (111) and (100) facets. Simulations were performed up to 50 million MC steps. From the results of MC, in the presence of gases (H2, CO), the surfaces are occupied by the gas molecules. In the equilibrium structure the coverage of H and CO as a function of the nature of surface atoms. In the initial structure, the Pt/Ru ratios on the surfaces for different cluster sizes were in range of 0.50 - 0.95. MC simulation was employed when the partial pressure of H2 (PH2) and CO (PCO) were 70 kPa and 100-500 ppm, respectively. The Pt/Ru ratios decrease as the increase in the CO concentration, without little exception only for small nanoparticle. The adsorption strength of CO on the Ru site is higher than the Pt site that would be one of the reason for decreasing the Pt/Ru ratio on the surface. Therefore, our study identifies that controlling the nanoparticle size, composition, conformation of alloying atoms, concentration and chemical potential of adsorbates have impact on the steadiness of nanoparticle alloys which ultimately and also overall catalytic performance during the operations.

Keywords: anode catalysts, fuel cells, material informatics, Monte Carlo

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1508 Electrochemical Synthesis and Morphostructural Study of the Cuprite Thin Film

Authors: M. El Hajji, A. Hallaoui, L. Bazzi, A. Benlhachemi, Lh. Bazzi, M. Hilali, O. Jbara, A. Tara, B. Bakiz

Abstract:

The cathodic electro deposition of the cuprite Cu2O by chrono potentiometry is performed on two types of electrodes "titanium and stainless steel", in a basic medium containing the precursor of copper. The plot produced vs SCE, shows the formation of a brown layer on the electrode surface. The chrono potentiometric recording made between - 0.2 and - 1 mA/cm2, has allowed us to have a deposit having different morphologies and structural orientation obtained as a function of the variation of many parameters. The morphology, the size of crystals, and the phase of the deposits produced were studied by conventional techniques of analysis of the solid, particularly the X-ray diffraction (XRD), scanning electron microscopy analysis (SEM) and quantitative chemical analysis (EDS). The results will be presented and discussed, they show that the majority of deposits are pure and uniform.

Keywords: cathodic electrodeposition, cuprite Cu2O, XRD, SEM, EDS analysis

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1507 Mechanical Properties of Kenaf Reinforced Composite with Different Fiber Orientation

Authors: Y. C. Ching, K. H. Chong

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The increasing of environmental awareness has led to grow interest in the expansion of materials with eco-friendly attributes. In this study, a 3 ply sandwich layer of kenaf fiber reinforced unsaturated polyester with various fiber orientations was developed. The effect of the fiber orientation on mechanical and thermal stability properties of polyester was studied. Unsaturated polyester as a face sheets and kenaf fibers as a core was fabricated with combination of hand lay-up process and cold compression method. Tested result parameters like tensile, flexural, impact strength, melting point, and crystallization point were compared and recorded based on different fiber orientation. The failure mechanism and property changes associated with directional change of fiber to polyester composite were discussed.

Keywords: kenaf fiber, polyester, tensile, thermal stability

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1506 A Prevalence of Phonological Disorder in Children with Specific Language Impairment

Authors: Etim, Victoria Enefiok, Dada, Oluseyi Akintunde, Bassey Okon

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Phonological disorder is a serious and disturbing issue to many parents and teachers. Efforts towards resolving the problem have been undermined by other specific disabilities which were hidden to many regular and special education teachers. It is against this background that this study was motivated to provide data on the prevalence of phonological disorders in children with specific language impairment (CWSLI) as the first step towards critical intervention. The study was a survey of 15 CWSLI from St. Louise Inclusive schools, Ikot Ekpene in Akwa Ibom State of Nigeria. Phonological Processes Diagnostic Scale (PPDS) with 17 short sentences, which cut across the five phonological processes that were examined, were validated by experts in test measurement, phonology and special education. The respondents were made to read the sentences with emphasis on the targeted sounds. Their utterances were recorded and analyzed in the language laboratory using Praat Software. Data were also collected through friendly interactions at different times from the clients. The theory of generative phonology was adopted for the descriptive analysis of the phonological processes. Data collected were analyzed using simple percentage and composite bar chart for better understanding of the result. The study found out that CWSLI exhibited the five phonological processes under investigation. It was revealed that 66.7%, 80%, 73.3%, 80%, and 86.7% of the respondents have severe deficit in fricative stopping, velar fronting, liquid gliding, final consonant deletion and cluster reduction, respectively. It was therefore recommended that a nationwide survey should be carried out to have national statistics of CWSLI with phonological deficits and develop intervention strategies for effective therapy to remediate the disorder.

Keywords: language disorders, phonology, phonological processes, specific language impairment

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1505 Effect of Underwater Antiquities as a Hidden Competitive Advantage of Hotels on Their Financial Performance: An Exploratory Study

Authors: Iman Shawky, Mohamed Elsayed

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Every hotel works in the hospitality market tends to have its own merit and character in its products marketing in order to maintain both its brand's identity and image among guests. According to the growth of global competition in the hospitality industry; the concept of competitive advantage is becoming increasingly important in hotels' marketing world as it examines reasons for outweighing hotels in their dimensions of strategic and marketing plans. In fact, Egypt is the land of appeared and submerged secrets as a result of its ancient civilization ongoing explorations. Although underwater antiquities represent ambiguous treasures, they have auspicious future in it, particularly in Alexandria. The study aims at examining to what extent underwater antiquities represent a competitive advantage of four and five-star hotels in Alexandria. For achieving this aim, an exploratory study conducted by currying out the investigation and comparison of the closest and most popular landmarks mentioned on both hotels' official websites and on common used reservations' websites. In addition to that, two different questionnaire forms designed; one for both revenue and sales and marketing hotels' managers while the other for their guests. The results indicate that both official hotels' websites and the most common used reservations' websites totally ignore mentioning underwater antiquities as attractive landmarks surrounding Alexandria hotels. Furthermore, most managers expect that underwater antiquities can furnish distinguished competitive advantage to their hotels. Also, they can help exceeding guests' expectations during their accommodation as long as they included on both official hotels' and reservations' websites as the most surrounding famous landmarks. Moreover, most managers foresee that high awareness of underwater antiquities can enhance the guests' accommodation frequencies and improve the financial performance of their hotels.

Keywords: competitive advantage, financial performance, hotels' websites, underwater antiquities

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1504 Malignant Idiopathic Intracranial Hypertension Revealed a Hidden Primary Spinal Leptomeningeal Medulloblastoma

Authors: Naim Izet Kajtazi

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Context: Frequently, the cause of raised intracranial pressure remains unresolved and rarely is related to spinal tumors, moreover less to spinal medulloblastoma without primary brain focus. Process: An 18-year-old woman had a 3-month history of headaches and impaired vision. Neurological examination revealed bilateral sixth cranial nerve palsies with bilateral papilloedema of grade III. No focal brain or spine lesion was found on imaging. Consecutive lumbar punctures showed high opening pressure and subsequent increasing protein level. The meningeal biopsy was negative. At one point, she developed an increasing headache, vomiting and back pain. Spine MRI showed diffuse nodular leptomeningeal enhancement with the largest nodule at T6–T7. Malignant cells were detected in cerebrospinal fluid. She underwent laminectomy with excisional biopsy, and pathology showed medulloblastoma WHO grade IV. Outcome: She was treated with chemotherapy and craniospinal irradiation and made a good recovery. Relevance: Primary spinal leptomeningeal medulloblastoma is extremely rare, especially without primary brain focus, but may cause increased intracranial pressure, even in the early microscopic phases, and it should be considered in the differential diagnosis if conventional and aggressive treatment of idiopathic intracranial hypertension fails. We assume that arachnoiditis from tumor seeding caused increased intracranial pressure. Appropriate neurosurgical intervention and surgical biopsy are mandated if a suspicious lesion is detected. Consider proper rescreening of the whole neuroaxis in refractory cases of intracranial hypertension.

Keywords: CNS infection, IIH, headache, primary spinal leptomeningeal medulloblastoma

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1503 Application of Scoring Rubrics by Lecturers towards Objective Assessment of Essay Questions in the Department of Social Science Education, University of Calabar, Nigeria

Authors: Donald B. Enu, Clement O. Ukpor, Abigail E. Okon

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Unreliable scoring of students’ performance by lecturers short-chains students’ assessment in terms of underequipping the school authority with facts as intended by society through the curriculum hence, the learners, the school and the society are cheated because the usefulness of testing is defeated. This study, therefore, examined lecturers’ scoring objectivity of essay items in the Department of Social Science Education, University of Calabar, Nigeria. Specifically, it assessed lecturers’ perception of the relevance of scoring rubrics and its level of application. Data were collected from all the 36 lecturers in the Department (28 members and 8 non-members adjourned to the department), through a 20-item questionnaire and checklist instruments. A case-study design was adopted. Descriptive statistics of frequency counts, weighted means, standard deviations, and percentages were used to analyze data gathered. A mean score of 2.5 and or 60 percent and above formed the acceptance or significant level in decision taking. It was found that lecturers perceived the use of scoring rubrics as a relevant practice to ensure fairness and reliable treatment of examiners scripts particularly in marking essay items and that there is a moderately high level of adherence to the application of scoring rubrics. It was also observed that some criteria necessary for the scoring objectivity of essay items were not fully put in place in the department. It was recommended strongly that students’ identities be hidden while marking and that pre-determined marking scheme should be prepared centrally and strictly adhered to during marking and recording of scores. Conference marking should be enforced in the department.

Keywords: essay items, objective scoring, scorers reliability, scoring rubrics

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1502 Simulation of Carbon Nanotubes/GaAs Hybrid PV Using AMPS-1D

Authors: Nima E. Gorji

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The performance and characteristics of a hybrid heterojunction single-walled carbon nanotube and GaAs solar cell is modelled and numerically simulated using AMPS-1D device simulation tool. The device physics and performance parameters with different junction parameters are analysed. The results suggest that the open-circuit voltage changes very slightly by changing the work function, acceptor and donor density while the other electrical parameters reach to an optimum value. Increasing the concentration of a discrete defect density in the absorber layer decreases the electrical parameters. The current-voltage characteristics, quantum efficiency, band gap and thickness variation of the photovoltaic response will be quantitatively considered.

Keywords: carbon nanotube, GaAs, hybrid solar cell, AMPS-1D modelling

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1501 Performance Evaluation of Distributed and Co-Located MIMO LTE Physical Layer Using Wireless Open-Access Research Platform

Authors: Ishak Suleiman, Ahmad Kamsani Samingan, Yeoh Chun Yeow, Abdul Aziz Bin Abdul Rahman

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In this paper, we evaluate the benefits of distributed 4x4 MIMO LTE downlink systems compared to that of the co-located 4x4 MIMO LTE downlink system. The performance evaluation was carried out experimentally by using Wireless Open-Access Research Platform (WARP), where the comparison between the 4x4 MIMO LTE transmission downlink system in distributed and co-located techniques was examined. The measured Error Vector Magnitude (EVM) results showed that the distributed technique achieved better system performance compared to the co-located arrangement.

Keywords: multiple-input-multiple-output (MIMO), distributed MIMO, co-located MIMO, LTE

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1500 Combined Effect of Vesicular System and Iontophoresis on Skin Permeation Enhancement of an Analgesic Drug

Authors: Jigar N. Shah, Hiral J. Shah, Praful D. Bharadia

Abstract:

The major challenge faced by formulation scientists in transdermal drug delivery system is to overcome the inherent barriers related to skin permeation. The stratum corneum layer of the skin is working as the rate limiting step in transdermal transport and reduce drug permeation through skin. Many approaches have been used to enhance the penetration of drugs through this layer of the skin. The purpose of this study is to investigate the development and evaluation of a combined approach of drug carriers and iontophoresis as a vehicle to improve skin permeation of an analgesic drug. Iontophoresis is a non-invasive technique for transporting charged molecules into and through tissues by a mild electric field. It has been shown to effectively deliver a variety of drugs across the skin to the underlying tissue. In addition to the enhanced continuous transport, iontophoresis allows dose titration by adjusting the electric field, which makes personalized dosing feasible. Drug carrier could modify the physicochemical properties of the encapsulated molecule and offer a means to facilitate the percutaneous delivery of difficult-to-uptake substances. Recently, there are some reports about using liposomes, microemulsions and polymeric nanoparticles as vehicles for iontophoretic drug delivery. Niosomes, the nonionic surfactant-based vesicles that are essentially similar in properties to liposomes have been proposed as an alternative to liposomes. Niosomes are more stable and free from other shortcoming of liposomes. Recently, the transdermal delivery of certain drugs using niosomes has been envisaged and niosomes have proved to be superior transdermal nanocarriers. Proniosomes overcome some of the physical stability related problems of niosomes. The proniosomal structure was liquid crystalline-compact niosomes hybrid which could be converted into niosomes upon hydration. The combined use of drug carriers and iontophoresis could offer many additional benefits. The system was evaluated for Encapsulation Efficiency, vesicle size, zeta potential, Transmission Electron Microscopy (TEM), DSC, in-vitro release, ex-vivo permeation across skin and rate of hydration. The use of proniosomal gel as a vehicle for the transdermal iontophoretic delivery was evaluated in-vitro. The characteristics of the applied electric current, such as density, type, frequency, and on/off interval ratio were observed. The study confirms the synergistic effect of proniosomes and iontophoresis in improving the transdermal permeation profile of selected analgesic drug. It is concluded that proniosomal gel can be used as a vehicle for transdermal iontophoretic drug delivery under suitable electric conditions.

Keywords: iontophoresis, niosomes, permeation enhancement, transdermal delivery

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1499 Robust Noisy Speech Identification Using Frame Classifier Derived Features

Authors: Punnoose A. K.

Abstract:

This paper presents an approach for identifying noisy speech recording using a multi-layer perception (MLP) trained to predict phonemes from acoustic features. Characteristics of the MLP posteriors are explored for clean speech and noisy speech at the frame level. Appropriate density functions are used to fit the softmax probability of the clean and noisy speech. A function that takes into account the ratio of the softmax probability density of noisy speech to clean speech is formulated. These phoneme independent scoring is weighted using a phoneme-specific weightage to make the scoring more robust. Simple thresholding is used to identify the noisy speech recording from the clean speech recordings. The approach is benchmarked on standard databases, with a focus on precision.

Keywords: noisy speech identification, speech pre-processing, noise robustness, feature engineering

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1498 Gender Recognition with Deep Belief Networks

Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

Abstract:

A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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1497 Effect of Base Coarse Layer on Load-Settlement Characteristics of Sandy Subgrade Using Plate Load Test

Authors: A. Nazeri, R. Ziaie Moayed, H. Ghiasinejad

Abstract:

The present research has been performed to investigate the effect of base course application on load-settlement characteristics of sandy subgrade using plate load test. The main parameter investigated in this study was the subgrade reaction coefficient. The model tests were conducted in a 1.35 m long, 1 m wide, and 1 m deep steel test box of Imam Khomeini International University (IKIU Calibration Chamber). The base courses used in this research were in three different thicknesses of 15 cm, 20 cm, and 30 cm. The test results indicated that in the case of using base course over loose sandy subgrade, the values of subgrade reaction coefficient can be increased from 7  to 132 , 224 , and 396  in presence of 15 cm, 20 cm, and 30 cm base course, respectively.

Keywords: modulus of subgrade reaction, plate load test, base course, sandy subgrade

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1496 Effect of Coriolis Force on Magnetoconvection in an Anisotropic Porous Medium

Authors: N. F. M. Mokhtar, N. Z. A. Hamid

Abstract:

This paper reports an analytical investigation of the stability and thermal convection in a horizontal anisotropic porous medium in the presence of Coriolis force and magnetic field. The Darcy model is used in the momentum equation and Boussinesq approximation is considered for the density variation of the porous medium. The upper and lower boundaries of the porous medium are assumed to be conducting to temperature perturbation and we used first order Chebyshev polynomial Tau method to solve the resulting eigenvalue problem. Analytical solution is obtained for the case of stationary convection. It is found that the porous layer system becomes unstable when the mechanical anisotropy parameter elevated and increasing the Coriolis force and magnetic field help to stabilize the anisotropy porous medium.

Keywords: anisotropic, Chebyshev tau method, Coriolis force, Magnetic field

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1495 Composition Dependence of Exchange Anisotropy in PtₓMn₁₋ₓ/Co₇₀Fe₃₀ Films

Authors: Sina Ranjbar, Masakiyo Tsunoda, Mikihiko Oogane, Yasuo Ando

Abstract:

We systematically investigated the exchange anisotropy for ferromagnetic Co70Fe30 and antiferromagnetic PtMn bilayer films. We focused on the relevance between the exchange bias and the composition of the Ptₓ Mn₁₋ₓ (14 < x < 22 and 45 < x < 56 at %) films, and we successfully optimized the composition. The crystal structure of the Ptₓ Mn₁₋ₓ films was FCC for 14 < x < 22 at % and FCT for 45 < x < 56 at % after annealing at 370 ◦C for 6 hours. The unidirectional anisotropy constant (Jₖ) for fcc-Pt₁₅Mn₈₅ (20 nm) and fct-Pt₄₈Mn₅₂ (20 nm) prepared under optimum conditions in composition were 0.16 and 0.20 erg/cm², respectively. Both Pt₁₅Mn₈₅ and Pt₄₈Mn₅₂ films showed a larger unidirectional anisotropy constant (Jₖ) than in other reports. They also showed a flatter surface than that of other antiferromagnetic materials. The obtained PtMn films with a large exchange anisotropy and slight roughness are useful as an antiferromagnetic layer in spintronic applications.

Keywords: antiferromagnetic material, PtMn thin film, exchange anisotropy, composition dependence

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1494 High School Transgender Students in Brazil: The Difficulties of Staying in School and the Psychological Implications in a Hostile School Environment

Authors: Aline Giardin, Maria Rosa Chitolina

Abstract:

Our research conducted in 8 different schools in the city of Rio Grande do Sul, Brazil, we can clearly see that, even in modern times, where the search for equality between men and women is already over 60 years of struggle in this world where you show Much more than two genres and in this world that is proving that sex is not just biological, are confronted with sexist and phallocentric situations in our Schools, and among our students. The sample consisted of 503 students with a mean age between 13 and 21 years. 107 students identified themselves as gay, lesbian, bisexual or transgender. The remainder was identified as heterosexual or none at all. Compared to LGBT students, transgender students faced the school's more hostile climates, while non-transgender female students were less likely to experience anti-LGBT victimization. In addition, transgender students experienced more negative experiences at school compared to students whose gender expression adhered to traditional gender norms. Transgender students were more likely to feel insecure at school, with 80.0% of transgender students reporting that they felt insecure at school because of their gender identity. Female students in our research reported lower frequencies of victimization based on sexual orientation and gender identity and were less likely to feel insecure at school. In all indicators of discrimination in school, high school students have outperformed elementary school students and have had fewer resources and supports related to LGBT. High school students reported higher rates of victimization on sexual orientation and gender expression than elementary school students. For example, about one-third (35.5%) of high school students suffered regular physical Very often) based on their sexual orientation, compared to less than a quarter (21.4%) of primary school students. The whole premise here is to perceive the phallocentrism and sexism hidden in our schools. Opposition between the sexes is not reflexive or articulates a biological fact, but a social construction.

Keywords: transgender students, school, psychological implications, discrimination

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1493 A Multilayer Perceptron Neural Network Model Optimized by Genetic Algorithm for Significant Wave Height Prediction

Authors: Luis C. Parra

Abstract:

The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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1492 Self-Supervised Attributed Graph Clustering with Dual Contrastive Loss Constraints

Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

Abstract:

Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

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