Search results for: optimized techniques

Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri

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In this study, ¹⁷⁷Lu-DOTATOC was prepared under optimized conditions (radiochemical purity: > 99%, radionuclidic purity: > 99%). The percentage of injected dose per gram (%ID/g) was calculated for organs up to 168 h post injection. Compartmental model was applied to mathematical description of the drug behaviour in tissue at different times. The biodistribution data showed the significant excretion of the radioactivity from the kidneys. The adrenal and pancreas, as major expression sites for somatostatin receptor (SSTR), had significant uptake. A pharmacokinetic model of ¹⁷⁷Lu-DOTATOC was presented by compartmental analysis which demonstrates the behavior of the complex.

Keywords: biodistribution, compartmental modeling, ¹⁷⁷Lu, Octreotide

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Authors: Nader Al-Rashidi, David Greenhalgh

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Mathematical modelling techniques are now being used by health organizations worldwide to help understand the likely impact that intervention strategies treatment options and combinations of these have on the prevalence and incidence of hepatitis C virus (HCV) in the people who inject drugs (PWID) population. In this poster, we develop a deterministic, compartmental mathematical model to approximate the spread of the HCV in a PWID population that has been divided into two groups by time since onset of injection. The model assumes that after injection needles adopt the most infectious state of their previous state or that of the PWID who last injected with them. Using analytical techniques, we find that the model behaviour is determined by the basic reproductive number R₀, where R₀ = 1 is a critical threshold separating two different outcomes. The disease-free equilibrium is globally stable if R₀ ≤ 1 and unstable if R₀ > 1. Additionally, we make some simulations where have confirmed that the model tends to this endemic equilibrium value with realistic parameter values giving an HCV prevalence.

Keywords: hepatitis C, people who inject drugs, HCV, PWID

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Authors: Yasaman Esfandiari

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Mechanical engineering has always dealt with amplification of the input power in power trains. One of the ways to achieve this goal is to use gears to change the amplitude and direction of the torque and the speed. However, the gears should be optimally designed to best achieve these objectives. In this study, helical gear systems are optimized to achieve maximum power. Material selection, space restriction, available facilities for manufacturing, the probability of tooth breakage, and tooth wear are taken into account and governing equations are derived. Finally, a Matlab code was generated to solve the optimization problem and the results are verified.

Keywords: design, gears, Matlab, optimization

Procedia PDF Downloads 240

Authors: Walid S. Alfuhaid, Saud A. Alghamdi, John M. Watkins, M. Edwin Sawan

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Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.

Keywords: decentralized, optimal control, output, singular perturb

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Authors: K. Majumdar, S. Datta

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Electricity is recognized as fundamental to industrialization and improving the quality of life of the people. Harnessing the immense untapped hydropower potential in Tripura region opens avenues for growth and provides an opportunity to improve the well-being of the people of the region, while making substantial contribution to the national economy. Gumti hydro power plant generates power to mitigate the crisis of power in Tripura, India. The first unit of hydro power plant (5 MW) was commissioned in June 1976 & another two units of 5 MW was commissioned simultaneously. But out of 15 MW capacity at present only 8-9 MW power is produced from Gumti hydro power plant during rainy season. But during lean season the production reduces to 0.5 MW due to shortage of water. Now, it is essential to implement some mitigation measures so that the further atrocities can be prevented and originality will be possible to restore. The decision making ability of the Analytic Hierarchy Process (AHP) and Concordance Analysis Techniques (CAT) are utilized to identify the better decision or solution to the present problem. Some related attributes are identified by the method of surveying within the experts and the available reports and literatures. Similar criteria are removed and ultimately seven relevant ones are identified. All the attributes are compared with each other and rated accordingly to their importance over the other with the help of Pair wise Comparison Matrix. In the present investigation different mitigation measures are identified and compared to find the best suitable alternative which can solve the present uncertainties involving the existence of the Gumti Hydro Power Plant.

Keywords: concordance analysis techniques, analytic hierarchy process, hydro power

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Authors: Ying Ying Liu, Austin Cooke, Parimala Thulasiraman

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Internet of Things (IoT) has attracted a recent spark in research on Internet of Vehicles (IoV). In this paper, we focus on one research area in IoV: preserving location privacy of vehicle data. We discuss existing location privacy preserving techniques and provide a scheme for evaluating these techniques under IoV traffic condition. We propose a different strategy in applying Differential Privacy using k-d tree data structure to preserve location privacy and experiment on real world Gowalla data set. We show that our strategy produces differentially private data, good preservation of utility by achieving similar regression accuracy to the original dataset on an LSTM (Long Term Short Term Memory) neural network traffic predictor.

Keywords: differential privacy, internet of things, internet of vehicles, location privacy, privacy preservation scheme

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Authors: Sakshi Gupta, Seema Joshi

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Thiosemicarbazones (TSCs) have garnered significant attention in coordination chemistry due to their versatile coordination modes and pharmacological properties. Mixed ligand complexes of TSCs represent a promising area of research, offering enhanced antimicrobial activities compared to their parent compounds. This review provides an overview of the synthesis, characterization, and antimicrobial properties of mixed ligand complexes incorporating thiosemicarbazones. The synthesis of mixed ligand complexes typically involves the reaction of a metal salt with TSC ligands and additional ligands, such as nitrogen- or oxygen-based ligands. Various transition metals, including copper, nickel, and cobalt, have been employed to form mixed ligand complexes with TSCs. Characterization techniques such as spectroscopy, X-ray crystallography, and elemental analysis are commonly utilized to confirm the structures of these complexes. One of the key advantages of mixed ligand complexes is their enhanced antimicrobial activity compared to pure TSC compounds. The synergistic effect between the TSC ligands and additional ligands contributes to increased efficacy, possibly through improved metal-ligand interactions or enhanced membrane permeability. Furthermore, mixed ligand complexes offer the potential for selective targeting of microbial species while minimizing toxicity to mammalian cells. This selectivity arises from the specific interactions between the metal center, TSC ligands, and biological targets within microbial cells. Such targeted antimicrobial activity is crucial for developing effective treatments with minimal side effects. Moreover, the versatility of mixed ligand complexes allows for the design of tailored antimicrobial agents with optimized properties. By varying the metal ion, TSC ligands, and additional ligands, researchers can fine-tune the physicochemical properties and biological activities of these complexes. This tunability opens avenues for the development of novel antimicrobial agents with improved efficacy and reduced resistance. In conclusion, mixed ligand complexes of thiosemicarbazones represent a promising class of compounds with potent antimicrobial activities. Further research in this field holds great potential for the development of novel therapeutic agents to combat microbial infections effectively.

Keywords: metal complex, thiosemicarbazones, mixed ligand, selective targeting, antimicrobial activity

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Authors: Suleiman Obeidat, Nabeel Mandahawi

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In this work, the packaging process for a move is improved. The customers of this move need their household stuff to be moved from their current house to the new one with minimum damage, in an organized manner, on time and with the minimum cost. Our goal was to improve the process between 10% and 20% time efficiency, 90% reduction in damaged parts and an acceptable improvement in the cost of the total move process. The expected ROI was 833%. Many improvement techniques have been used in terms of the way the boxes are prepared, their preparation cost, packing the goods, labeling them and moving them to a place for moving out. DMAIC technique is used in this work: SIPOC diagram, value stream map of “As Is” process, Root Cause Analysis, Maps of “Future State” and “Ideal State” and an Improvement Plan. A value of ROI=624% is obtained which is lower than the expected value of 833%. The work explains the techniques of improvement and the deficiencies in the old process.

Keywords: packaging, lean tools, six sigma, DMAIC methodology, SIPOC

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

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Authors: Ebenezer Obaloluwa Olaniyi

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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Omar Alhamad, Waleed Eid

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Reinforced concrete is a concrete lined with steel so that the materials work together in the resistance forces. Reinforcement rods or mesh are used for tensile, shear, and sometimes intense pressure in a concrete structure. Reinforced concrete is subject to many natural problems or industrial errors. The result of these problems is that it reduces the efficiency of the reinforced concrete or its usefulness. Some of these problems are cracks, earthquakes, high temperatures or fires, as well as corrosion of reinforced iron inside reinforced concrete. There are also factors of ancient buildings or monuments that require some techniques to preserve them. This research presents some general information about reinforced concrete, the pros and cons of reinforced concrete, and then presents a series of literary studies of some of the late published researches on the subject of reinforced concrete and how to preserve it, propose solutions or treatments for the treatment of reinforced concrete problems, raise efficiency and quality for a longer period. These studies have provided advanced and modern methods and techniques in the field of reinforced concrete.

Keywords: reinforced concrete, treatment, concrete, corrosion, seismic, cracks

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Authors: Antonio D. Lee, Steven X. Jiang

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A variety of techniques and methods are available to evaluate cognitive performance in Urban Search and Rescue (USAR) applications. However, traditional cognitive performance evaluation techniques typically incorporate either the conscious or systematic aspect, failing to take into consideration the subconscious or intuitive aspect. This leads to incomplete measures and produces ineffective designs. In order to fill the gaps in past research, this study developed a theoretical framework to facilitate the integration of situation awareness (SA) and intuitive pattern recognition (IPR) to enhance the cognitive performance representation in USAR applications. This framework provides guidance to integrate both SA and IPR in order to evaluate the cognitive performance of the USAR responders. The application of this framework will help improve the system design.

Keywords: cognitive performance, intuitive pattern recognition, situation awareness, urban search and rescue

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Authors: Y. C. Khoo, W. T. Lai

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The single orifice hydraulic flat spray nozzle was evaluated with two global imaging techniques to characterize various aspects of the resulting spray. The two techniques were high resolution flow visualization and Particle Image Velocimetry (PIV). A CCD camera with 29 million pixels was used to capture shadowgraph images to realize ligament formation and collapse as well as droplet interaction. Quantitative analysis was performed to give the sizing information of the droplets and ligaments. This camera was then applied with a PIV system to evaluate the overall velocity field of the spray, from nozzle exit to droplet discharge. PIV images were further post-processed to determine the inclusion angle of the spray. The results from those investigations provided significant quantitative understanding of the spray structure. Based on the quantitative results, detailed understanding of the spray behavior was achieved.

Keywords: spray, flow visualization, PIV, shadowgraph, quantitative sizing, velocity field

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Authors: Kais Siala, Mohamed Kharrat, Mohamed Abid

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Exposure therapies encourage patients to gradually begin facing their painful memories of the trauma in order to reduce fear and anxiety. In this context, virtual reality techniques are widely used for treatment of different kinds of phobia. The particular case of fear of death phobia (thanataphobia) is addressed in this paper. For this purpose, we propose to make a simulation of Near Death Experience (NDE) using augmented reality techniques. We propose in particular to simulate the Out-of-Body experience (OBE) which is the first step of a Near-Death-Experience (NDE). In this paper, we present technical aspects of this simulation as well as short-term impact in terms of physiological measures. The non-linear Poincéré plot is used to describe the difference in Heart Rate Variability between In-Body and Out-Of-Body conditions.

Keywords: Out-of-Body simulation, physiological measure, augmented reality, phobia psychotherapy, HRV, Poincaré plot

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Authors: M. S. Abd El-Sadek, M. A. Omar, Gharib M. Taha

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In recent years, photocatalytic degradation of various kinds of organic and inorganic pollutants using semiconductor powders as photocatalysts has been extensively studied. Owing to its relatively high photocatalytic activity, biological and chemical stability, low cost, nonpoisonous and long stable life, Tin oxide materials have been widely used as catalysts in chemical reactions, including synthesis of vinyl ketone, oxidation of methanol and so on. Tin oxide (SnO₂), with a rutile-type crystalline structure, is an n-type wide band gap (3.6 eV) semiconductor that presents a proper combination of chemical, electronic and optical properties that make it advantageous in several applications. In the present work, SnO₂ nanoparticles were synthesized at room temperature by the sol-gel process and thermohydrolysis of SnCl₂ in isopropanol by controlling the crystallite size through calculations. The synthesized nanoparticles were identified by using XRD analysis, TEM, FT-IR, and Uv-Visible spectroscopic techniques. The crystalline structure and grain size of the synthesized samples were analyzed by X-Ray diffraction analysis (XRD) and the XRD patterns confirmed the presence of tetragonal phase SnO₂. In this study, Methylene blue degradation was tested by using SnO₂ nanoparticles (at different calculations temperatures) as a photocatalyst under sunlight as a source of irradiation. The results showed that the highest percentage of degradation of Methylene blue dye was obtained by using SnO₂ photocatalyst at calculations temperature 800 ᵒC. The operational parameters were investigated to be optimized to the best conditions which result in complete removal of organic pollutants from aqueous solution. It was found that the degradation of dyes depends on several parameters such as irradiation time, initial dye concentration, the dose of the catalyst and the presence of metals such as silver as a dopant and its concentration. Percent degradation was increased with irradiation time. The degradation efficiency decreased as the initial concentration of the dye increased. The degradation efficiency increased as the dose of the catalyst increased to a certain level and by further increasing the SnO₂ photocatalyst dose, the degradation efficiency is decreased. The best degradation efficiency on which obtained from pure SnO₂ compared with SnO₂ which doped by different percentage of Ag.

Keywords: SnO₂ nanoparticles, a sol-gel method, photocatalytic applications, methylene blue, degradation efficiency

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Authors: N. Azadi-Tinat, H. Oraizi

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Design of compact UWB multilayered microstrip filter with E-shape resonator is presented, which provides wide stopband up to 20 GHz and arbitrary impedance matching. The design procedure is developed based on the method of least squares and theory of N-coupled transmission lines. The dimensions of designed filter are about 11 mm × 11 mm and the three E-shape resonators are placed among four dielectric layers. The average insertion loss in the passband is less than 1 dB and in the stopband is about 30 dB up to 20 GHz. Its group delay in the UWB region is about 0.5 ns. The performance of the optimized filter design perfectly agrees with the microwave simulation softwares.

Keywords: method of least square, multilayer microstrip filter, n-coupled transmission lines, ultra-wideband

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Authors: Serhat Tuzun, Tufan Demirel

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Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

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Authors: Nadia Bachir (Dahmani), Fatima Zohra Otmani

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Due to its interesting optoelectronic properties, methylammonium perovskite CH3NH3PbI3 is used as the active layer in the development of several solar cells. In this work, the hybrid (organic-inorganic) cell with the architecture FTO/pedotpss/CH3NH3PbI3/pcdtbt/Al is simulated using the Organic and Hybrid Material Nano Simulation Tool (OghmaNano). We studied the influence of certain parameters, such as thickness, on the characteristics of the solar cell. The effect of the device temperature was also investigated. The photovoltaic characteristic curves, such as current-voltage (j-V), are presented in this work. The optimized final parameters are Voc = 0.947 V, FF = 0.8034%, and PCE = 23.16%.

Keywords: OghmaNano software, hybrid perovskite cell, CH3NH3PbI3, conversion efficiency

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Authors: M. Douak, Z. Aouachria

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The aim of our study is to project an optimized wind turbine of Darrieus type. This type of wind turbine is characterized by a low starting torque in comparison with the Savonius rotor allowing them to operate for a period greater than wind speed. This led us to reconsider the Darrieus rotor to optimize a design which will increase its starting torque. The study of a system of monitoring and control of the angle of attack of blade profile, which allows an auto start to wind speeds as low as possible is presented for the straight blade of Darrieus turbine. The study continues to extend to other configurations namely those of parabolic type.

Keywords: Darrieus turbine, pitch angle, self stating, wind energy

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Authors: Ahmed Ali Torad

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Background: Breast feeding maintains the maternal fetal immunological link, favours the transmission of immune-competence from the mother to her infant and is considered an important contributory factor to the neo natal immune defense system. Purpose: This study was conducted to investigate the effect of relaxation techniques on immunological properties of breast milk. Subjects and Methods: Thirty breast feeding mothers with a single, mature infant without any complications participated in the study. Subjects will be recruited from outpatient clinic of obstetric department of El Kasr El-Aini university hospital in Cairo. Mothers were randomly divided into two equal groups using coin toss method: Group (A) (relaxation training group) (experimental group): It will be composed of 15 women who received relaxation training program in addition to breast feeding and nutritional advices and Group (B) (control group): It will be composed of 15 women who received breast feeding and nutritional advices only. Results: The results showed that mean mother’s age was 28.4 ± 3.68 and 28.07 ± 4.09 for group A and B respectively, there were statistically significant differences between pre and post values regarding cortisol level, IgA level, leucocyte count and infant’s weight and height and there is only statistically significant differences between both groups regarding post values of all immunological variables (cortisol – IgA – leucocyte count). Conclusion: We could conclude that there is a statistically significant effect of relaxation techniques on immunological properties of breast milk.

Keywords: relaxation, breast, milk, immunology, lactation

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Authors: M. Doumi, A. Miloudi, A. G. Aissaoui, K. Tahir, C. Belfedal, S. Tahir

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The studies on the photovoltaic system are extensively increasing because of a large, secure, essentially exhaustible and broadly available resource as a future energy supply. However, the output power induced in the photovoltaic modules is influenced by an intensity of solar cell radiation, temperature of the solar cells and so on. Therefore, to maximize the efficiency of the photovoltaic system, it is necessary to track the maximum power point of the PV array, for this Maximum Power Point Tracking (MPPT) technique is used. Some MPPT techniques are available in that perturbation and observation (P&O) and Fuzzy logic controller (FLC). The fuzzy control method has been compared with perturb and observe (P&O) method as one of the most widely conventional method used in this area. Both techniques have been analyzed and simulated. MPPT using fuzzy logic shows superior performance and more reliable control with respect to the P&O technique for this application.

Keywords: photovoltaic system, MPPT, perturb and observe, fuzzy logic

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Authors: Ambachew Simreteab Gebremedhn

Abstract:

Context: The paper explores the use of synchronous reference frame theory (SRFT) and instantaneous reactive power theory (IRPT) based control of Unified Power Quality Conditioner (UPQC) for improving power quality in distribution systems. Research Aim: To investigate the performance of different control configurations of UPQC using SRFT and IRPT for mitigating power quality issues in distribution systems. Methodology: The study compares three control techniques (SRFT-IRPT, SRFT-SRFT, IRPT-IRPT) implemented in series and shunt active filters of UPQC. Data is collected under various control algorithms to analyze UPQC performance. Findings: Results indicate the effectiveness of SRFT and IRPT based control techniques in addressing power quality problems such as voltage sags, swells, unbalance, harmonics, and current harmonics in distribution systems. Theoretical Importance: The study provides insights into the application of SRFT and IRPT in improving power quality, specifically in mitigating unbalanced voltage sags, where conventional methods fall short. Data Collection: Data is collected under various control algorithms using simulation in MATLAB Simulink and real-time operation executed with experimental results obtained using RT-LAB. Analysis Procedures: Performance analysis of UPQC under different control algorithms is conducted to evaluate the effectiveness of SRFT and IRPT based control techniques in mitigating power quality issues. Questions Addressed: How do SRFT and IRPT based control techniques compare in improving power quality in distribution systems? What is the impact of using different control configurations on the performance of UPQC? Conclusion: The study demonstrates the efficacy of SRFT and IRPT based control of UPQC in mitigating power quality issues in distribution systems, highlighting their potential for enhancing voltage and current quality.

Keywords: power quality, UPQC, shunt active filter, series active filter, non-linear load, RT-LAB, MATLAB

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Authors: Eman I. Raslan, Haitham S. Hamza, Reda A. El-Khoribi

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Fiber-Wireless (FiWi) networks are a promising candidate for future broadband access networks. These networks combine the optical network as the back end where different passive optical network (PON) technologies are realized and the wireless network as the front end where different wireless technologies are adopted, e.g. LTE, WiMAX, Wi-Fi, and Wireless Mesh Networks (WMNs). The convergence of both optical and wireless technologies requires designing architectures with robust efficient and effective bandwidth allocation schemes. Different bandwidth allocation algorithms have been proposed in FiWi networks aiming to enhance the different segments of FiWi networks including wireless and optical subnetworks. In this survey, we focus on the differentiating between the different bandwidth allocation algorithms according to their enhancement segment of FiWi networks. We classify these techniques into wireless, optical and Hybrid bandwidth allocation techniques.

Keywords: fiber-wireless (FiWi), dynamic bandwidth allocation (DBA), passive optical networks (PON), media access control (MAC)

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Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Shanshan Zhu, Mohammad Nasim

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Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

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Authors: Sandhya Devi A

Abstract:

The protein content of the cranberry squash (protein: 0g) may be increased by extracting protein from the lentils (9 g), which is particularly linked to a lower risk of developing heart disease. Using the technique of alkaline extraction from the lentils flour, protein may be extracted. Alkaline extraction of protein from lentil flour was optimized utilizing response surface approach in order to maximize both protein content and yield. Cranberry squash may be taken if a protein fortification syrup is prepared and processed into the squash.

Keywords: alkaline extraction, cranberry squash, protein fortification, response surface methodology

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Authors: Delia Enyedi

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Throughout film history, the regular return of 3D cinema has been discussed in connection to crises caused by the advent of television or the competition of the Internet. In addition, the three waves of stereoscopic 3D (from 1952 up to 1983) and its current digital version have been blamed for adding a challenging technical distraction to the viewing experience. By discussing the films Dial M for Murder (1954) and Goodbye to Language (2014), the paper aims to analyze the response of recognized auteurs to the use of 3D techniques in filmmaking. For Alfred Hitchcock, the solution to attaining perceptual immersion paradoxically resided in restraining the signature effect of 3D, namely protrusion. In Jean-Luc Godard’s vision, 3D techniques allowed him to explore perceptual absorption by means of depth of field, for which he had long advocated as being central to cinema. Thus, both directors contribute to the foundation of an auteur aesthetic in 3D filmmaking.

Keywords: Alfred Hitchcock, authorship, 3D filmmaking, Jean-Luc Godard, perceptual absorption, perceptual immersion

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Authors: Jonathan Iworiso

Abstract:

Forecasting the equity premium out-of-sample is a major concern to researchers in finance and emerging markets. The quest for a superior model that can forecast the equity premium with significant economic gains has resulted in several controversies on the choice of variables and suitable techniques among scholars. This research focuses mainly on the application of Regression Training (RT) techniques to forecast monthly equity premium out-of-sample recursively with an expanding window method. A broad category of sophisticated regression models involving model complexity was employed. The RT models include Ridge, Forward-Backward (FOBA) Ridge, Least Absolute Shrinkage and Selection Operator (LASSO), Relaxed LASSO, Elastic Net, and Least Angle Regression were trained and used to forecast the equity premium out-of-sample. In this study, the empirical investigation of the RT models demonstrates significant evidence of equity premium predictability both statistically and economically relative to the benchmark historical average, delivering significant utility gains. They seek to provide meaningful economic information on mean-variance portfolio investment for investors who are timing the market to earn future gains at minimal risk. Thus, the forecasting models appeared to guarantee an investor in a market setting who optimally reallocates a monthly portfolio between equities and risk-free treasury bills using equity premium forecasts at minimal risk.

Keywords: regression training, out-of-sample forecasts, expanding window, statistical predictability, economic significance, utility gains

Procedia PDF Downloads 107

Authors: İsmail İnce, Osman Günaydin, Fatma Özer

Abstract:

Stones used in the construction of historical structures are exposed to various direct or indirect atmospheric effects depending on climatic conditions. Building stones deteriorate partially or fully as a result of this exposure. The historic structures are important symbols of any cultural heritage. Therefore, it is important to protect and restore these historical structures. The aim of this study is to determine the weathering conditions at the Kilistra ancient city. It is located in the southwest of the Konya city, Central Anatolia, and was built by carving into pyroclastic rocks during the Byzantine Era. For this purpose, the petrographic and mechanical properties of the pyroclastic rocks were determined. In the assessment of weathering of structures in the ancient city, in-situ non-destructive testing (i.e., Schmidt hardness rebound value, relative humidity measurement) methods were applied.

Keywords: cultural heritage, Kilistra ancient city, non-destructive techniques, weathering

Procedia PDF Downloads 360