Search results for: integrated waste management system

Authors: Amir Hossein Daei Sorkhabi, Bita Khazini

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In this paper the intelligent control of full automatic car wash using a programmable logic controller (PLC) has been investigated and designed to do all steps of carwashing. The Intelligent control of full automatic carwash has the ability to identify and profile the geometrical dimensions of the vehicle chassis. Vehicle dimension identification is an important point in this control system to adjust the washing brushes position and time duration. The study also tries to design a control set for simulating and building the automatic carwash. The main purpose of the simulation is to develop criteria for designing and building this type of carwash in actual size to overcome challenges of automation. The results of this research indicate that the proposed method in process control not only increases productivity, speed, accuracy and safety but also reduce the time and cost of washing based on dynamic model of the vehicle. A laboratory prototype based on an advanced intelligent control has been built to study the validity of the design and simulation which it’s appropriate performance confirms the validity of this study.

Keywords: Automatic Carwash, Dimension, PLC.

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Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method as a Web-App is developed for auto-generated data replication to provide a twin of the targeted data structure. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi", has been developed. A special login form has been developed with a special instance of the data validation; this verification process secures the web application from its early stages. The system has been tested and validated, and up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database, WebAppShield.

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Authors: S. M. Anowarul Haque, Md. Asiful Islam

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Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: Load forecasting, artificial neural network, particle swarm optimization.

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: Intrusion detection system, decision tree, support vector machine, feature selection.

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Authors: Gunther Reinhart, Marwan Radi

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Since the 1940s, many promising telepresence research results have been obtained. However, telepresence technology still has not reached industrial usage. As human intelligence is necessary for successful execution of most manual assembly tasks, the ability of the human is hindered in some cases, such as the assembly of heavy parts of small/medium lots or prototypes. In such a case of manual assembly, the help of industrial robots is mandatory. The telepresence technology can be considered as a solution for performing assembly tasks, where the human intelligence and haptic sense are needed to identify and minimize the errors during an assembly process and a robot is needed to carry heavy parts. In this paper, preliminary steps to integrate the telepresence technology into industrial robot systems are introduced. The system described here combines both, the human haptic sense and the industrial robot capability to perform a manual assembly task remotely using a force feedback joystick. Mapping between the joystick-s Degrees of Freedom (DOF) and the robot-s ones are introduced. Simulation and experimental results are shown and future work is discussed.

Keywords: Assembly, Force Feedback, Industrial Robot, Teleassembly, Telepresence.

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Authors: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing in urban streets is one of the most suitable options for solving the traffic problems and environment pollutions in the cities of the country. Unlike its acceptable outcomes, there are problems concerning the necessity to pay by the mass. Regarding the fact that public response in order to succeed in this strategy is so influential, studying their response and behavior to get the feedback and improve the strategies is of great importance. In this study, a questionnaire was used to examine the public reactions to the traffic congestion pricing schemes at the center of Tehran metropolis and the factors involved in people’s decision making in accepting or rejecting the congestion pricing schemes were assessed based on the data obtained from the questionnaire as well as the international experiences. Then, by analyzing and comparing the schemes, guidelines to reduce public objections to them are discussed. The results of reviewing and evaluating the public reactions show that all the pros and cons must be considered to guarantee the success of these projects. Consequently, with targeted public education and consciousness-raising advertisements, prior to initiating a scheme and ensuring the mechanism of the implementation after the start of the project, the initial opposition is reduced and, with the gradual emergence of the real and tangible benefits of its implementation, users’ satisfaction will increase.

Keywords: Demand management, international experiences, traffic congestion pricing, public acceptance, public objection.

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Authors: L. N. Corîci, A. E. Frissen, D -J. Van Zoelen, I. F. Eggen, F. Peter, C. M. Davidescu, C. G. Boeriu

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Two commercial proteases from Bacillus licheniformis (Alcalase 2.4 L FG and Alcalase 2.5 L, Type DX) were screened for the production of Z-Ala-Phe-NH2 in batch reaction. Alcalase 2.4 L FG was the most efficient enzyme for the C-terminal amidation of Z-Ala-Phe-OMe using ammonium carbamate as ammonium source. Immobilization of protease has been achieved by the sol-gel method, using dimethyldimethoxysilane (DMDMOS) and tetramethoxysilane (TMOS) as precursors (unpublished results). In batch production, about 95% of Z-Ala-Phe-NH2 was obtained at 30°C after 24 hours of incubation. Reproducibility of different batches of commercial Alcalase 2.4 L FG preparations was also investigated by evaluating the amidation activity and the entrapment yields in the case of immobilization. A packed-bed reactor (0.68 cm ID, 15.0 cm long) was operated successfully for the continuous synthesis of peptide amides. The immobilized enzyme retained the initial activity over 10 cycles of repeated use in continuous reactor at ambient temperature. At 0.75 mL/min flow rate of the substrate mixture, the total conversion of Z-Ala-Phe-OMe was achieved after 5 hours of substrate recycling. The product contained about 90% peptide amide and 10% hydrolysis byproduct.

Keywords: packed-bed reactor, peptide amide, protease, sol-gel immobilization.

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Authors: Adi A. Maaita, Hamza A. A. Al_Sewadi

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One of the crucial parameters of digital cryptographic systems is the selection of the keys used and their distribution. The randomness of the keys has a strong impact on the system’s security strength being difficult to be predicted, guessed, reproduced, or discovered by a cryptanalyst. Therefore, adequate key randomness generation is still sought for the benefit of stronger cryptosystems. This paper suggests an algorithm designed to generate and test pseudo random number sequences intended for cryptographic applications. This algorithm is based on mathematically manipulating a publically agreed upon information between sender and receiver over a public channel. This information is used as a seed for performing some mathematical functions in order to generate a sequence of pseudorandom numbers that will be used for encryption/decryption purposes. This manipulation involves permutations and substitutions that fulfill Shannon’s principle of “confusion and diffusion”. ASCII code characters were utilized in the generation process instead of using bit strings initially, which adds more flexibility in testing different seed values. Finally, the obtained results would indicate sound difficulty of guessing keys by attackers.

Keywords: Cryptosystems, Information Security agreement, Key distribution, Random numbers.

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Authors: Pil Woo Heo, In Sub Park

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Flows in a microchannel are laminar, which means that mixing depends on only inter-diffusion. A micromixer plays an important role in obtaining fast diagnosis results in the fields of m-TAS (total analysis system), Bio-MEMS and LOC (lab-on-a-chip).

In this paper, we propose a new active mixer with vertical flow placement via a series of inlets for micromixing. This has two inlets on the same axis, one of which is located before the other. The sample input by the first inlet flows into the down-position, while the other sample by the second inlet flows into the up-position. In the experiment, the samples were located vertically in up-down positions in a micro chamber. PZT was attached below a chamber, and ultrasonic waves were radiated in the down to up direction towards the samples in the micro chamber in order to accelerate the mixing. The mixing process was measured by the change of color in a micro chamber using phenolphthalein and NaOH. The results of the experiment showed that the samples in the microchamber were efficiently mixed and that our new active mixer was superior to the horizontal type of active mixers in view of the grey levels and the standard deviation.

Keywords: Active mixer, vertical flow placement, microchannel, bio-MEMS, LOC.

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Authors: Loke Kean Koay, Mani Maran Ratnam

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A mechanically-resonant torsional spring scanner was developed in a recent study. Various methods were developed to improve the angular displacement of the scanner while maintaining the scanner frequency. However the effects of rotor magnet radial position on scanner characteristics were not well investigated. In this study, the relationships between the magnet position and the scanner characteristics such as natural frequency, angular displacement and stress level were studied. A finite element model was created and an average deviation of 3.18% was found between the simulation and experimental results, qualifying the simulation results as a guide for further investigations. Three magnet positions on the transverse oscillating suspended plate were investigated by finite element analysis (FEA) and one of the positions were selected as the design position. The magnet position with the longest distance from the twist axis of mirror was selected since it attains minimum stress level, while exceeding the minimum critical flicker frequency and delivering the targeted angular displacement to the scanner.

Keywords: Computer-aided design, design optimization, torsional scanner.

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: Gradient image, segmentation and extract, mean-shift algorithm, dictionary learning.

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Authors: K. Bommanna Raja, M.Madheswaran, K.Thyagarajah

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A higher order spline interpolated contour obtained with up-sampling of homogenously distributed coordinates for segmentation of kidney region in different classes of ultrasound kidney images has been developed and presented in this paper. The performance of the proposed method is measured and compared with modified snake model contour, Markov random field contour and expert outlined contour. The validation of the method is made in correspondence with expert outlined contour using maximum coordinate distance, Hausdorff distance and mean radial distance metrics. The results obtained reveal that proposed scheme provides optimum contour that agrees well with expert outlined contour. Moreover this technique helps to preserve the pixels-of-interest which in specific defines the functional characteristic of kidney. This explores various possibilities in implementing computer-aided diagnosis system exclusively for US kidney images.

Keywords: Ultrasound Kidney Image – Kidney Segmentation –Active Contour – Markov Random Field – Higher Order SplineInterpolation

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Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

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Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: Ecosystem, business model, personal data, preventive healthcare.

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Authors: Yizhen Zhao, Adam S. Z. Belloum, Gonc¸alo Maia da Costa, Zhiming Zhao

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Machine learning has evolved from an area of academic research to a real-world applied field. This change comes with challenges, gaps and differences exist between common practices in academic environments and the ones in production environments. Following continuous integration, development and delivery practices in software engineering, similar trends have happened in machine learning (ML) systems, called MLOps. In this paper we propose a framework that helps to streamline and introduce best practices that facilitate the ML lifecycle in an industrial setting. This framework can be used as a template that can be customized to implement various machine learning experiments. The proposed framework is modular and can be recomposed to be adapted to various use cases (e.g. data versioning, remote training on Cloud). The framework inherits practices from DevOps and introduces other practices that are unique to the machine learning system (e.g.data versioning). Our MLOps practices automate the entire machine learning lifecycle, bridge the gap between development and operation.

Keywords: Cloud computing, continuous development, data versioning, DevOps, industrial setting, MLOps, machine learning.

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Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

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Several meteorological parameters were used for the  prediction of monthly average daily global solar radiation on  horizontal using recurrent neural networks (RNNs). Climatological  data and measures, mainly air temperature, humidity, sunshine  duration, and wind speed between 1995 and 2007 were used to design  and validate a feed forward and recurrent neural network based  prediction systems. In this paper we present our reference system  based on a feed-forward multilayer perceptron (MLP) as well as the  proposed approach based on an RNN model. The obtained results  were promising and comparable to those obtained by other existing  empirical and neural models. The experimental results showed the  advantage of RNNs over simple MLPs when we deal with time series  solar radiation predictions based on daily climatological data.

Keywords: Recurrent Neural Networks, Global Solar Radiation, Multi-layer perceptron, gradient, Root Mean Square Error.

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Authors: Insung Jung, lockjo Koo, Gi-Nam Wang

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The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.

Keywords: Neural network, U-healthcare, prediction, timeseries, computer aided prediction.

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Authors: D. Vijayakumar, R. K. Nema

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Over Current Relays (OCRs) and Directional Over Current Relays (DOCRs) are widely used for the radial protection and ring sub transmission protection systems and for distribution systems. All previous work formulates the DOCR coordination problem either as a Non-Linear Programming (NLP) for TDS and Ip or as a Linear Programming (LP) for TDS using recently a social behavior (Particle Swarm Optimization techniques) introduced to the work. In this paper, a Modified Particle Swarm Optimization (MPSO) technique is discussed for the optimal settings of DOCRs in power systems as a Non-Linear Programming problem for finding Ip values of the relays and for finding the TDS setting as a linear programming problem. The calculation of the Time Dial Setting (TDS) and the pickup current (Ip) setting of the relays is the core of the coordination study. PSO technique is considered as realistic and powerful solution schemes to obtain the global or quasi global optimum in optimization problem.

Keywords: Directional over current relays, Optimization techniques, Particle swarm optimization, Power system protection.

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Authors: K. N. Penna, J. P. English

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The destruction of the Juukan Gorge rock shelters in 2020 has catalysed impetus within Australian society for a significant change in engagement with Indigenous Peoples, and the approach to Indigenous cultural heritage, both within the Pilbara region and more broadly across Australia. Culture-based and people-centred approaches are inherent to inclusive sustainable development and Free, Prior, Informed Consent, outcomes encouraged by international and local recommendations on the human rights and cultural heritage preservation of Indigenous peoples. In this paper, we present an interpretive model of an evolved process for mining project development, incorporating culture-based and people-centred approaches, based on the Theory U system change method. The evolved process advocates a change in organisational mindset and culture, and a comprehensive understanding of Indigenous Peoples’ culture and values, as the foundations for increasing their influence and achieving mutually beneficial developments.

Keywords: Indigenous Engagement, mining industry, culture-based approach, people-centred approach, Theory U.

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Authors: Tulika Bhattacharjee, A. K.Chakraborty

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Due to the deregulation of the Electric Supply Industry and the resulting emergence of electricity market, the volumes of power purchases are on the rise all over the world. In a bid to meet the customer-s demand in a reliable and yet economic manner, utilities purchase power from the energy market over and above its own production. This paper aims at developing an optimal power purchase model with two objectives viz economy and environment ,taking various functional operating constraints such as branch flow limits, load bus voltage magnitudes limits, unit capacity constraints and security constraints into consideration.The price of purchased power being an uncertain variable is modeled using fuzzy logic. DEMO (Differential Evolution For Multi-objective Optimization) is used to obtain the pareto-optimal solution set of the multi-objective problem formulated. Fuzzy set theory has been employed to extract the best compromise non-dominated solution. The results obtained on IEEE 30 bus system are presented and compared with that of NSGAII.

Keywords: Deregulation, Differential Evolution, Multi objective Optimization, Pareto Optimal Set, Optimal Power Flow

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Authors: Ameni Mokni, Hatem Mhiri, Georges Le Palec, Philippe Bournot

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Numerical study of a plane jet occurring in a vertical heated channel is carried out. The aim is to explore the influence of the forced flow, issued from a flat nozzle located in the entry section of a channel, on the up-going fluid along the channel walls. The Reynolds number based on the nozzle width and the jet velocity ranges between 3 103 and 2.104; whereas, the Grashof number based on the channel length and the wall temperature difference is 2.57 1010. Computations are established for a symmetrically heated channel and various nozzle positions. The system of governing equations is solved with a finite volumes method. The obtained results show that the jet-wall interactions activate the heat transfer, the position variation modifies the heat transfer especially for low Reynolds numbers: the heat transfer is enhanced for the adjacent wall; however it is decreased for the opposite one. The numerical velocity and temperature fields are post-processed to compute the quantities of engineering interest such as the induced mass flow rate, and the Nusselt number along the plates.

Keywords: Channel, Heat flux, Jet, Mixed convection.

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Authors: S. M. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

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One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: Spoken Dialog System, Spoken Language Understanding, Web Semantic, Name Entity Recognition.

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Authors: Chiung-ying Lee, Chia-hua Chang

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In July 1, 2007, Taiwan Stock Exchange (TWSE) on market observation post system (MOPS) adds a new "Financial reference database" for investors to do investment reference. This database as a warning to public offering companies listed on the public financial information and it original within eight targets. In this paper, this database provided by the indicators for the application of company financial crisis early warning model verify that the database provided by the indicator forecast for the financial crisis, whether or not companies have a high accuracy rate as opposed to domestic and foreign scholars have positive results. There is use of Logistic Regression Model application of the financial early warning model, in which no joined back-conditions is the first model, joined it in is the second model, has been taken occurred in the financial crisis of companies to research samples and then business took place before the financial crisis point with T-1 and T-2 sample data to do positive analysis. The results show that this database provided the debt ratio and net per share for the best forecast variables.

Keywords: Financial reference database, Financial early warning model, Logistic Regression.

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Authors: Arafat A. A. Shabaneh

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Harsh environments require developed detection by an optical communication system to ensure a high level of security and safety. Fiber Bragg gratings (FBGs) are emerging sensing instruments that respond to variations in strain and temperature by varying wavelengths. In this study, a cascaded uniform FBG is designed as a strain sensor for 6 km length at 1550 nm wavelength with 30 °C temperature by analyzing dynamic strain and wavelength shifts. The FBG is placed in a small segment of an optical fiber that reflects light with a specific wavelength and passes on the remaining wavelengths. Consequently, periodic alteration occurs in the refractive index in the fiber core. The alteration in the modal index of the fiber is produced by strain effects on a Bragg wavelength. When the developed sensor is exposed to the strain (0.01) of the cascaded uniform FBG, the wavelength shifts by 0.0000144383 μm. The sensing accuracy of the developed sensor is 0.0012. Simulation results show the reliability and effectiveness of the strain monitoring sensor for remote sensing application.

Keywords: Remote sensing, cascaded fiber Bragg grating, strain sensor, wavelength shift.

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Authors: S.Jerald Jeba Kumar, M.Madheswaran

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The structure of retinal vessels is a prominent feature, that reveals information on the state of disease that are reflected in the form of measurable abnormalities in thickness and colour. Vascular structures of retina, for implementation of clinical diabetic retinopathy decision making system is presented in this paper. Retinal Vascular structure is with thin blood vessel, whose accuracy is highly dependent upon the vessel segmentation. In this paper the blood vessel thickness is automatically detected using preprocessing techniques and vessel segmentation algorithm. First the capture image is binarized to get the blood vessel structure clearly, then it is skeletonised to get the overall structure of all the terminal and branching nodes of the blood vessels. By identifying the terminal node and the branching points automatically, the main and branching blood vessel thickness is estimated. Results are presented and compared with those provided by clinical classification on 50 vessels collected from Bejan Singh Eye hospital..

Keywords: Diabetic retinopathy, Binarization, SegmentationClinical Decision Support Systems.

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Authors: Marcell S. A. Martins, Benedito S. R. Neto, Gerson L. Serejo, Carlos G. R. Santos

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Indoor positioning systems use sensors such as Bluetooth, ZigBee, and Wi-Fi, as well as cameras for image capture, which can be fixed or mobile. These computer vision-based positioning approaches are low-cost to implement, mainly when it uses a mobile camera. The present study aims to create a design of a fiducial marker for a low-cost indoor localization system. The marker is tape-shaped to perform a continuous reading employing two detection algorithms, one for greater distances and another for smaller distances. Therefore, the location service is always operational, even with variations in capture distance. A minimal localization and reading algorithm was implemented for the proposed marker design, aiming to validate it. The accuracy tests consider readings varying the capture distance between [0.5, 10] meters, comparing the proposed marker with others. The tests showed that the proposed marker has a broader capture range than the ArUco and QRCode, maintaining the same size. Therefore, reducing the visual pollution and maximizing the tracking since the ambient can be covered entirely.

Keywords: Multiscale recognition, indoor localization, tape-shaped marker, Fiducial Marker.

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Authors: Mazliham Mohd Su'ud, Pierre Loonis, Idris Abu Seman

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This paper deals with the extraction of information from the experts to automatically identify and recognize Ganoderma infection in oil palm stem using tomography images. Expert-s knowledge are used as rules in a Fuzzy Inference Systems to classify each individual patterns observed in he tomography image. The classification is done by defining membership functions which assigned a set of three possible hypotheses : Ganoderma infection (G), non Ganoderma infection (N) or intact stem tissue (I) to every abnormalities pattern found in the tomography image. A complete comparison between Mamdani and Sugeno style,triangular, trapezoids and mixed triangular-trapezoids membership functions and different methods of aggregation and defuzzification is also presented and analyzed to select suitable Fuzzy Inference System methods to perform the above mentioned task. The results showed that seven out of 30 initial possible combination of available Fuzzy Inference methods in MATLAB Fuzzy Toolbox were observed giving result close to the experts estimation.

Keywords: Fuzzy Inference Systems, Tomography analysis, Modelizationof expert's information, Ganoderma Infection pattern recognition

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Authors: Rajkishore Nayak, Tarun Panwar, Majo George, Irfan Ulhaq, Soumik Parida

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Factors related to the growth of fashion and textile manufacturing in the Sub-Saharan African (SSA) countries are analyzed in this paper. Important factors associated with the growth of fashion and textile manufacturing in the SSA countries are being identified, underlined, and evaluated in this study. This research performed a SWOT analysis of the garment industries in the SSA region by exploring into various literature in the garment manufacturing and export data. SSA countries need to grow a lot in the fashion and textile manufacturing and export to come in par with the developments in the sector globally. Unlike the developing countries such as Vietnam and Bangladesh, the total export to the US, the EU and other parts of the world has declined. On the other hand, the total supply of fashion and textiles to the domestic market has been in rise. However, the local communities still need to rely on other countries to meet their demand. Import of cheaper clothes from countries like Bangladesh China and Vietnam is one of the main challenges local manufacturers are facing as it is very difficult to be competitive in pricing.

Keywords: Sub-Saharan Africa, apparel industry, sustainable fashion, developing countries, fashion, textiles.

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Authors: Ehi E. Aimiuwu

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As of 2017, many online learning professionals, institutions, and journals are still wondering how instructors can keep student engaged in the online learning environment to facilitate active learning effectively. The purpose of this qualitative single-case and narrative research is to explore whether online professors understand their role as mentors and facilitators of students’ academic success by keeping students engaged in active learning based on personalized experience in the field. Data collection tools that were used in the study included an NVivo 12 Plus qualitative software, an interview protocol, a digital audiotape, an observation sheet, and a transcription. Seven online professors in the United States from LinkedIn and residencies were interviewed for this study. Eleven online teaching techniques from previous research were used as the study framework. Data analysis process, member checking, and key themes were used to achieve saturation. About 85.7% of professors agreed on rubric as the preferred online grading technique. About 57.1% agreed on professors logging in daily, students logging in about 2-5 times weekly, knowing students to increase accountability, email as preferred communication tool, and computer access for adequate online learning. About 42.9% agreed on syllabus for clear class expectations, participation to show what has been learned, and energizing students for creativity.

Keywords: Class facilitation, class management, online teaching, online education, pedagogy.

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Authors: Loralee P. Potter, Peter J. Schubert

Abstract:

Solid-state hydrogen storage using catalytically-modified porous silicon can be rapidly charged at moderate pressures (8 bar) without exothermic runaway. Discharge requires temperatures of approximately 110oC, so for larger storage vessels a means is required for thermal energy to penetrate bulk storage media. This can be realized with low-density metal foams, such as Celmet™. This study explores several material and dimensional choices of the metal foam to produce rapid heating of bulk silicon particulates. Experiments run under vacuum and in a pressurized hydrogen environment bracket conditions of empty and full hydrogen storage vessels, respectively. Curve-fitting of the heating profiles at various distances from an external heat source is used to derive both a time delay and a characteristic time constant. System performance metrics of a hydrogen storage subsystem are derived from the experimental results. A techno-economic analysis of the silicon and metal foam provides comparison with other methods of storing hydrogen for mobile and portable applications. 

Keywords: conduction, convection, kinetics, fuel cell

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Authors: H. Mukhtar, N. M. Noor, R. Nasir, D. F. Mohshim

Abstract:

The main aim of this work is to develop a model of hydrogen sulfide (H2S) separation from natural gas by using membrane separation technology. The model is developed by incorporating three diffusion mechanisms which are Knudsen, viscous and surface diffusion towards membrane selectivity and permeability. The findings from the simulation result shows that the permeability of the gas is dependent toward the pore size of the membrane, operating pressure, operating temperature as well as feed composition. The permeability of methane has the highest value for Poly (1-trimethylsilyl-1-propyne ) PTMSP membrane at pore size of 0.1nm and decreasing toward a minimum peak at pore range 1 to 1.5 nm as pore size increased before it increase again for pore size is greater than 1.5 nm. On the other hand, the permeability of hydrogen sulfide is found to increase almost proportionally with the increase of membrane pore size. Generally, the increase of pressure will increase the permeability of gas since more driving force is provided to the system while increasing of temperature would decrease the permeability due to the surface diffusion drop off effect. A corroboration of the simulation result also showed a good agreement with the experimental data.

Keywords: Hydrogen Sulfide, Methane, Inorganic Membrane, Organic Membrane, Pore Model

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