Search results for: applied computing

Authors: Tareg Omar Mansour, Khaled Omar Elhaji

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Model solutions of pentanol in the salt water of various concentrations were subjected to electrochemical oxidation using a dimensionally stable anode (DSA) and a platinised titanium cathode. The removal of pentanol was analysed over time using gas chromatography (GC) and by monitoring the total organic carbon (TOC) concentration of the reaction mixture. It was found that the removal of pentanol occurred more efficiently at higher salinities and higher applied electrical current values. When using a salt concentration of 20,000 ppm and an applied current of 100 mA there was a decrease in concentration of pentanol of 15 %. When the salt concentration and applied current were increased to 58,000 ppm and 500 mA respectively, the decrease in concentration was improved to 64 %.

Keywords: dimensionally stable anode (DSA), total organic hydrocarbon (TOC), gas chromatography mass spectrometry (GCMS), electrochemical oxidation

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Authors: Anastasia Rita Widiarti, Agus Harjoko, Marsono, Sri Hartati

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This paper presents the results of a study to test whether the Javanese character manuscript image preprocessing model that have been more widely applied, can also be applied to segment of the Batak characters manuscripts. The treatment process begins by converting the input image into a binary image. After the binary image is cleaned of noise, then the segmentation lines using projection profile is conducted. If unclear histogram projection is found, then the smoothing process before production indexes line segments is conducted. For each line image which has been produced, then the segmentation scripts in the line is applied, with regard of the connectivity between pixels which making up the letters that there is no characters are truncated. From the results of manuscript preprocessing system prototype testing, it is obtained the information about the system truth percentage value on pieces of Pustaka Batak Podani Ma AjiMamisinon manuscript ranged from 65% to 87.68% with a confidence level of 95%. The value indicates the truth percentage shown the initial processing model in Javanese characters manuscript image can be applied also to the image of the Batak characters manuscript.

Keywords: connected component, preprocessing, manuscript image, projection profiles

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Authors: A. Amar

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The angular distributions of the nuclear systems under consideration have been analyzed in the framework of the optical model (OM), where the real part was taken in the crystal model form. A crystal model (CM) has been applied to deuteron elastically scattered by ⁶,⁷Li and ⁹Be. A crystal model (CM) + distorted-wave Born approximation (DWBA) + dynamic polarization potential (DPP) potential has been applied to deuteron elastically scattered by ⁶,⁷Li and 9Be. Also, a crystal model has been applied to ⁶Li elastically scattered by ¹⁶O and ²⁸Sn in addition to the ⁷Li+⁷Li system and the ¹²C(alpha,⁸Be) ⁸Be reaction. The continuum-discretized coupled-channels (CDCC) method has been applied to the ⁷Li+⁷Li system and agreement between the crystal model and the continuum-discretized coupled-channels (CDCC) method has been observed. In general, the models succeeded in reproducing the differential cross sections at the full angular range and for all the energies under consideration.

Keywords: optical model (OM), crystal model (CM), distorted-wave born approximation (DWBA), dynamic polarization potential (DPP), the continuum-discretized coupled-channels (CDCC) method, and deuteron elastically scattered by ⁶, ⁷Li and ⁹Be

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Authors: Payman Tajalli, Steven Segal

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Applied ethics is an area of ethics which is looked upon most favorably as the most appropriate and useful for educational purposes; after all if ethics finds no application would any investment of time, effort and finance by the educational institutions be warranted? The current approaches to ethics in business and management often entail appealing to various types of moral theories and to this end almost every major philosophical approach has been enlisted. In this paper, we look at ethics through the philosophy of Emmanuel Levinas to argue that since ethics is ‘first philosophy’ it can neither be rule-based nor rule-governed, not something that can be worked out first and then applied to a given situation, hence the overwhelming emphasis on ‘applied ethics’ as a field of study in business and management education is unjustified. True ethics is not applied ethics. This assertion does not mean that teaching ethical theories and philosophies need to be abandoned rather it is the acceptance of the fact that an increase in cognitive awareness of such theories and ethical models and frameworks, or the mastering of techniques and procedures for ethical decision making, will not affect the desired ethical transformation in our students. Levinas himself argued for an ethics without a foundation, not one that required us to go ‘beyond good and evil’ as Nietzsche contended, rather an ethics which necessitates going ‘before good and evil'. Such an ethics does not provide us with a set of methods or techniques or a decision tree that enable us determine the rightness of an action and what we ought to do, rather it is about a way of being, an ethical posture or approach one takes in the inter-subjective relationship with the other that holds the promise of ethical conduct. Ethics in this Levinasian sense then is one of infinite and unconditional responsibility for the other person in relationship, an ethics which is not subject to negotiation, calculation or reciprocity, and as such it could neither be applied nor taught through conventional pedagogy with its focus on knowledge transfer from the teacher to student, and to this end Levinas offers a non-maieutic, non-conventional approach to pedagogy. The paper concludes that from a Levinasian perspective on ethics and education, we may need to guide our students to move away from the clear and objective professionalism of the management and applied ethics towards the murky individual spiritualism. For Levinas, this is ‘the Copernican revolution’ in ethics.

Keywords: business ethics, ethics education, Levinas, maieutic teaching, ethics without foundation

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Authors: Rohit T. P., Sahil Athrij, Sasi Gopalan

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Currently, the content entertainment industry is dominated by mobile devices. As the trends slowly shift towards Augmented/Virtual Reality applications the computational demands on these devices are increasing exponentially and we are already reaching the limits of hardware optimizations. This paper proposes a software solution to this problem. By leveraging the capabilities of cloud computing we can offload the work from mobile devices to dedicated rendering servers that are way more powerful. But this introduces the problem of latency. This paper introduces a protocol that can achieve high-performance low latency Augmented/Virtual Reality experience. There are two parts to the protocol, 1) In-flight compression The main cause of latency in the system is the time required to transmit the camera frame from client to server. The round trip time is directly proportional to the amount of data transmitted. This can therefore be reduced by compressing the frames before sending. Using some standard compression algorithms like JPEG can result in minor size reduction only. Since the images to be compressed are consecutive camera frames there won't be a lot of changes between two consecutive images. So inter-frame compression is preferred. Inter-frame compression can be implemented efficiently using WebGL but the implementation of WebGL limits the precision of floating point numbers to 16bit in most devices. This can introduce noise to the image due to rounding errors, which will add up eventually. This can be solved using an improved interframe compression algorithm. The algorithm detects changes between frames and reuses unchanged pixels from the previous frame. This eliminates the need for floating point subtraction thereby cutting down on noise. The change detection is also improved drastically by taking the weighted average difference of pixels instead of the absolute difference. The kernel weights for this comparison can be fine-tuned to match the type of image to be compressed. 2) Dynamic Load distribution Conventional cloud computing architectures work by offloading as much work as possible to the servers, but this approach can cause a hit on bandwidth and server costs. The most optimal solution is obtained when the device utilizes 100% of its resources and the rest is done by the server. The protocol balances the load between the server and the client by doing a fraction of the computing on the device depending on the power of the device and network conditions. The protocol will be responsible for dynamically partitioning the tasks. Special flags will be used to communicate the workload fraction between the client and the server and will be updated in a constant interval of time ( or frames ). The whole of the protocol is designed so that it can be client agnostic. Flags are available to the client for resetting the frame, indicating latency, switching mode, etc. The server can react to client-side changes on the fly and adapt accordingly by switching to different pipelines. The server is designed to effectively spread the load and thereby scale horizontally. This is achieved by isolating client connections into different processes.

Keywords: 2D kernelling, augmented reality, cloud computing, dynamic load distribution, immersive experience, mobile computing, motion tracking, protocols, real-time systems, web-based augmented reality application

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Authors: Roseline Oghogho Osaseri, Osaseri E. I.

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Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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Authors: Namrata D. Hiremath, Mahalaxmi Bhille, P. G. Sunitha Hiremath

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Computer systems play an integral role in all facets of the engineering profession. This calls for an understanding of the processor-level components of computer systems, their design and operation, and their impact on the overall performance of the systems. Systems users are always in need of faster, more powerful, yet cheaper computer systems. The focus of Computer Science engineering graduates is inclined towards software oriented base. To be an efficient programmer there is a need to understand the role of hardware architecture towards the same. It is essential for the students of Computer Science and Engineering to know the basic building blocks of any computing device and how the digital principles can be used to build them. Hence two courses Digital Electronics of 3 credits, which is associated with lab of 1.5 credits and Computer Organization of 5 credits, were introduced at the sophomore level. Activity was introduced with the objective to teach the hardware concepts to the students of Computer science engineering through structured lab. The students were asked to design and implement a component of a computing device using MultiSim simulation tool and build the same using hardware components. The experience of the activity helped the students to understand the real time applications of the SSI and MSI components. The impact of the activity was evaluated and the performance was measured. The paper explains the achievement of the ABET outcomes a, c and k.

Keywords: digital, computer organization, ABET, structured enquiry, course activity

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Authors: H. Katkhuda

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A time domain approach is used in this paper to identify unknown dynamic forces applied on two dimensional frames using the measured dynamic structural responses for a sub-structure in the two dimensional frame. In this paper a sub-structure finite element model with short length of measurement from only three or four accelerometers is required, and an iterative least-square algorithm is used to identify the unknown dynamic force applied on the structure. Validity of the method is demonstrated with numerical examples using noise-free and noise-contaminated structural responses. Both harmonic and impulsive forces are studied. The results show that the proposed approach can identify unknown dynamic forces within very limited iterations with high accuracy and shows its robustness even noise- polluted dynamic response measurements are utilized.

Keywords: dynamic force identification, dynamic responses, sub-structure, time domain

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

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Authors: Pablo Kubo, Cassio Paiva, Adelino Ferreira

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The main objective of this research study is to present the results of the influence of shock absorber condition, from a truck front suspension, on the vertical dynamic load applied on the pavement. For the measurements, it has been used a durability test track located in Brazil. The shock absorber conditions were new, used and failed with a constant load of 6 tons on the front suspension, the maximum allowed load for front axle according to Brazilian legislation. By applying relative damage concept, it is possible to conclude that the variation on the shock absorber conditions will significantly affect the load applied on the pavement. Although, it is recommended to repeat the same methodology in order to analyze the influence on the variation of the quarter car model variants.

Keywords: damage, shock absorber, vertical dynamic load, absorber

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Authors: Dipanshu Sur, Ratnabali Chakravorty

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Background: Striae result from rapid expansion of the underlying tissue, e.g. during puberty, pregnancy or rapid weight gain. Prior data indicate that the incidence of stretch marks in Indian women is 77%.The hormonal and genetic factors are associated with their appearance. Recently that has been found skin extensibility, elasticity and rupture were strongly influenced by the water content of dermis and epidermis cells. Objective: The objectives were to assess the effects of topical treatments applied during pregnancy on the later development of stretch marks. Materials and methods: An open, prospective, randomized study was done on 120 pregnant women in whom skin elasticity and hydration as well as striae presence or apparition were measured at baseline and periodically until delivery. Patients were randomly assigned to application in wet skin cream, or in dry skin conditions. Results: The average basal hydration was 42 ±13 IU and the final was 46 ± 6 IU (P = 0.0325; 95% CI: -7.66 to -0.34), which difference was statistically significant. By measuring the moisture in the control region (forearm) a basal reading of 40 ± 9 IU and end of study of 38 ± 6; (p = 0.1547; 95% CI: -0.77 to 4.77) and this difference was considered to be not statistically significant. It was observed that at the end of the study, 55% women without ridges; mild ridges 5%; 36% moderate, and 4%, severe ridges. The proportion of women without grooves was 54% when the cream was applied studied wet skin and 45% when the cream was applied on dry skin. Conclusion: It was shown that cream under study increased hydration and elasticity of abdominal skin consequently in all subjects. This effect is more significant (54%) when the cream is applied to damp skin.

Keywords: striae gravidarum, skin moisturizer, skin hydration, skin elasticity

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Authors: Mechlouch Ridha Fethi

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This paper presents a recent mathematical model in political sciences concerning democracy. The model is represented by a logarithmic equation linking the Relative Index of Democracy (RID) to Participation Ratio (PR). Firstly the meanings of the different parameters of the model were presented; and the variation curve of the RID according to PR with different critical areas was discussed. Secondly, the model was applied to a virtual group where we show that the model can be applied depending on the gender. Thirdly, it was observed that the model can be extended to different language models of democracy and that little use to assess the state of democracy for some International organizations like UNO.

Keywords: democracy, mathematic, modelization, quantification

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Authors: Ophir Nave

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In our research, we present the concept of singularly perturbed vector field (SPVF) method, and its application to thermal explosion of diesel spray combustion. Given a system of governing equations, which consist of hidden Multi-scale variables, the SPVF method transfer and decompose such system to fast and slow singularly perturbed subsystems (SPS). The SPVF method enables us to understand the complex system, and simplify the calculations. Later powerful analytical, numerical and asymptotic methods (e.g method of integral (invariant) manifold (MIM), the homotopy analysis method (HAM) etc.) can be applied to each subsystem. We compare the results obtained by the methods of integral invariant manifold and SPVF apply to spray droplets combustion model. The research deals with the development of an innovative method for extracting fast and slow variables in physical mathematical models. The method that we developed called singular perturbed vector field. This method based on a numerical algorithm applied to global quasi linearization applied to given physical model. The SPVF method applied successfully to combustion processes. Our results were compared to experimentally results. The SPVF is a general numerical and asymptotical method that reveals the hierarchy (multi-scale system) of a given system.

Keywords: polydisperse spray, model reduction, asymptotic analysis, multi-scale systems

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Authors: Lukasz Grzegorz Broda, Taiwo Oseni, Andrew Stranieri, Rodrigo Marino, Ronelle Welton, Mark Yates

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The oral health of residents in aged care centres in Australia is poor, contributing to infections, hospital admissions, and increased suffering. Although the use of electric toothbrushes has been deployed in many centres, smartbrushes that record and transmit information about brushing patterns and duration are not routinely deployed. Yet, the use of smartbrushes for aged care residents promises better oral care. Thus, a study aimed at investigating the appropriateness and suitability of a smartbrush for aged care residents is currently underway. Due to the peculiarity of the aged care setting, the incorporation of smartbrushes into residents’ care does require careful planning and design considerations. This paper describes an initial design process undertaken through the use of an actor to understand the important elements to be incorporated whilst installing a smartbrush for use in aged care settings. The design covers the configuration settings of the brush and app, including ergonomic factors related to brush and smartphone placement. A design science approach led to an installation re-design and a revised protocol for the planned study, the ultimate aim being to design installations to enhance perceived usefulness, ease of use, and attitudes towards the incorporation of smartbrushes for improving oral health care for aged care residents.

Keywords: smartbrush, applied computing, life and medical sciences, health informatics

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Authors: Sérgio Afonso Mulema, Andrés Carrión García, Vicente Ernesto

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This paper analyses the effect of fertilizer (organic and inorganic) in the growth of tilapia. An experiment was implemented in the Aquapesca Company of Mozambique; there were considered four different treatments. Each type of fertilizer was applied in two of these treatments; a feed was supplied to the third treatment, and the fourth was taken as control. The weight and length of the tilapia were used as the growth parameters, and to measure the water quality, the physical-chemical parameters were registered. The results show that the weight and length were different for tilapias cultivated in different treatments. These differences were evidenced mainly by organic and feed treatments, where there was the largest and smallest value of these parameters, respectively. In order to prove that these differences were caused only by applied treatment without interference for the aquatic environment, a Fisher discriminant analysis was applied, which confirmed that the treatments were exposed to the same environment condition.

Keywords: fertilizer, tilapia, growth, statistical methods

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Authors: João Madureira, Ricardo Lagido, Inês Sousa, Fraunhofer Portugal

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Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU.

Keywords: inertial measurement unit (IMU), global positioning system (GPS), smartphone, surfing performance

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Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

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Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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Authors: M. Abir Hossain, M. Shahjada Tarafder

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This paper deals with the analysis of potential flow past two-dimensional body by discretizing the body into panels where the Laplace equation was applied to each panel. The Laplace equation was solved at each panel by applying the boundary conditions. The boundary condition was applied at each panel to mathematically formulate the problem and then convert the problem into a computer-solvable problem. Kutta condition was applied at both the leading and trailing edges to see whether the condition is satisfied or not. Another approach that is applied for the analysis is Vortex Lattice Method (VLM). A vortex ring is considered at each control point. Using the Biot-Savart Law the strength at each control point is calculated and hence the pressure differentials are measured. For the comparison of the analytic result with the experimental result, different NACA section hydrofoil is used. The analytic result of NACA 0012 and NACA 0015 are compared with the experimental result of Abbott and Doenhoff and found significant conformity with the achieved result.

Keywords: Kutta condition, Law of Biot-Savart, pressure differentials, potential flow, vortex lattice method

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Authors: Suwimol Apapol, Punrapha Praditpong

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The objectives of the study were to find out the frequencies of figures of speech in fragrance advertising captions as well as the types of figures of speech most commonly applied in captions. The relation between figures of speech and fragrance was also examined in order to analyze how figures of speech were used to represent fragrance. Thirty-five fragrance advertisements were randomly selected from the Internet. Content analysis was applied in order to consider the relation between figures of speech and fragrance. The results showed that figures of speech were found in almost every fragrance advertisement except one advertisement of several Goods service. Thirty-four fragrance advertising captions used at least one kind of figure of speech. Metaphor was most frequently found and also most frequently applied in fragrance advertising captions, followed by alliteration, rhyme, simile and personification, and hyperbole respectively which is in harmony with the research hypotheses as well.

Keywords: advertising captions, captions on internet, consumer purchasing decision, e-commerce

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Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

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Authors: Tan Zhang, Zhongjian Wang, Jack Xin, Zhiwen Zhang

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We aim to efficiently compute the spreading speeds of reaction-diffusion-advection (RDA) fronts in divergence-free random flows under the Kolmogorov-Petrovsky-Piskunov (KPP) nonlinearity. We study a stochastic interacting particle method (IPM) for the reduced principal eigenvalue (Lyapunov exponent) problem of an associated linear advection-diffusion operator with spatially random coefficients. The Fourier representation of the random advection field and the Feynman-Kac (FK) formula of the principal eigenvalue (Lyapunov exponent) form the foundation of our method implemented as a genetic evolution algorithm. The particles undergo advection-diffusion and mutation/selection through a fitness function originated in the FK semigroup. We analyze the convergence of the algorithm based on operator splitting and present numerical results on representative flows such as 2D cellular flow and 3D Arnold-Beltrami-Childress (ABC) flow under random perturbations. The 2D examples serve as a consistency check with semi-Lagrangian computation. The 3D results demonstrate that IPM, being mesh-free and self-adaptive, is simple to implement and efficient for computing front spreading speeds in the advection-dominated regime for high-dimensional random flows on unbounded domains where no truncation is needed.

Keywords: KPP front speeds, random flows, Feynman-Kac semigroups, interacting particle method, convergence analysis

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Authors: Kwangmin Joo

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Automatic detection of lumbar vertebrae and classification method is proposed for evaluating the degree of disc narrowing. Prior to classification, deep learning based segmentation is applied to detect individual lumbar vertebra. M-net is applied to segment five lumbar vertebrae and fine-tuning segmentation is employed to improve the accuracy of segmentation. Using the features extracted from previous step, clustering technique, k-means clustering, is applied to estimate the degree of disc space narrowing under four grade scoring system. As preliminary study, techniques proposed in this research could help building an automatic scoring system to diagnose the severity of disc narrowing from X-ray images.

Keywords: Disc space narrowing, Degenerative disc disorders, Deep learning based segmentation, Clustering technique

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Authors: Vladimir Kulyukin, Tanwir Zaman, Sarat Kiran Andhavarapu

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Research on nutrition label use identifies four factors that impede comprehension and retention of nutrition information by consumers: label’s location on the package, presentation of information within the label, label’s surface size, and surrounding visual clutter. In this paper, a system is presented that makes nutrition label use more effective for nutrition information comprehension and retention. The system’s front end is a smartphone application. The system’s back end is a four node Linux cluster for image recognition and data storage. Image frames captured on the smartphone are sent to the back end for skewed or aligned barcode recognition. When barcodes are recognized, corresponding nutrition labels are retrieved from a cloud database and presented to the user on the smartphone’s touchscreen. Each displayed nutrition label is positioned centrally on the touchscreen with no surrounding visual clutter. Wikipedia links to important nutrition terms are embedded to improve comprehension and retention of nutrition information. Standard touch gestures (e.g., zoom in/out) available on mainstream smartphones are used to manipulate the label’s surface size. The nutrition label database currently includes 200,000 nutrition labels compiled from public web sites by a custom crawler. Stress test experiments with the node cluster are presented. Implications for proactive nutrition management and food policy are discussed.

Keywords: mobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

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Authors: Stephanie Elizabeth Talder

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Art therapy is a field that is growing exponentially with new groundbreaking discoveries that allow for embodying trauma and mental healing. Applied theatre and performance is a continuously growing and developing field that can help people who are struggling to work through traumatic experiences plaguing their life. By using performance, there is an ability to target sensitive topics in a manner that does not lead to re-traumatization. The use of theatre as a healing agent has been going on for centuries, with clear applications beginning in Greek theatre and tragedy. When working with complex mental illness, issues such as PTSD, anxiety, and depression can be managed and worked through. A central component of drama therapy is the connection to community and self. The ability to connect mind-body to stories as well as to other people allows for healing to occur. There is the opportunity for healing through emotional catharsis and community building. Applied theatre in connection to the medical field can allow for there to be a meaningful impact made on mental health. Though there is still a significant amount of progress to be made within the stigmatization of mental health problems, bringing in a varying option that allows for there to be movement and community building possesses a strong ability to impact people in a positive way.

Keywords: applied theatre, drama therapy, art therapy, performance, theatre

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Authors: Upal Barua

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Crash risk at intersections is a critical safety issue. This paper examines the effectiveness of removing an existing off-set at an intersection by realignment, in reducing crashes. Empirical Bayes method was applied to conduct a before-and-after study to assess the effect of this safety improvement. The Transportation Safety Improvement Program in Austin Transportation Department completed several safety improvement projects at high crash intersections with a view to reducing crashes. One of the common safety improvement techniques applied was the realignment of intersection approaches removing an existing off-set. This paper illustrates how this safety improvement technique is applied at a high crash intersection from inception to completion. This paper also highlights the significant crash reductions achieved from this safety improvement technique applying Empirical Bayes method in a before-and-after study. The result showed that realignment of intersection approaches removing an existing off-set can reduce crashes by 53%. This paper also features the state of the art techniques applied in planning, engineering, designing and construction of this safety improvement, key factors driving the success, and lessons learned in the process.

Keywords: crash risk, intersection, off-set, safety improvement technique, before-and-after study, empirical Bayes method

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Authors: Panprae Bunyapukkna

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This study investigated figures of speech used in fragrance advertising captions on the Internet. The objectives of the study were to find out the frequencies of figures of speech in fragrance advertising captions and the types of figures of speech most commonly applied in captions. The relation between figures of speech and fragrance was also examined in order to analyze how figures of speech were used to represent fragrance. Thirty-five fragrance advertisements were randomly selected from the Internet. Content analysis was applied in order to consider the relation between figures of speech and fragrance. The results showed that figures of speech were found in almost every fragrance advertisement except one advertisement of Lancôme. Thirty-four fragrance advertising captions used at least one kind of figure of speech. Metaphor was most frequently found and also most frequently applied in fragrance advertising captions, followed by alliteration, rhyme, simile and personification, and hyperbole respectively.

Keywords: advertising speech, fragrance advertisements, figures of speech, metaphor

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Authors: Abdul Mannan Akhtar

Abstract:

In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

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Authors: Syarif Hidayat

Abstract:

As millions of people with different backgrounds perform hajj every year in Saudi Arabia, it brings out several problems. Missing people is among many crucial problems need to be encountered. Some people might have had insufficient knowledge of using tracking system equipment. Other might become a victim of an accident, lose consciousness, or even died, prohibiting them to perform certain activity. For those reasons, people could not send proper SOS message. The major contribution of this paper is the application of the diverse alert method in pilgrims tracking system. It offers a simple yet robust solution to send SOS message by pilgrims during Hajj. Knowledge of context aware computing is assumed herein. This study presents four methods that could be utilized by pilgrims to send SOS. The first method is simple mobile application contains only a button. The second method is based on behavior analysis based off GPS location movement anomaly. The third method is by introducing pressing pattern to smartwatch physical button as a panic button. The fourth method is by identifying certain accelerometer pattern recognition as a sign of emergency situations. Presented method in this paper would be an important part of pilgrims tracking system. The discussion provided here includes easy to use design whilst maintaining tracking accuracy, privacy, and security of its users.

Keywords: context aware computing, emergency alert system, GPS, hajj pilgrim tracking, location-based services

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

Abstract:

In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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