Search results for: Accident risks estimation

Authors: Abdul Jamil Nazari, Shigeo Honma

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This paper evaluates and compares the effect of fractional flow curves on the heavy oil and light oil recoveries in a petroleum reservoir. Fingering of flowing water is one of the serious problems of the oil displacement by water and another problem is the estimation of the amount of recover oil from a petroleum reservoir. To address these problems, the fractional flow of heavy oil and light oil are investigated. The fractional flow approach treats the multi-phases flow rate as a total mixed fluid and then describes the individual phases as fractional of the total flow. Laboratory experiments are implemented for two different types of oils, heavy oil, and light oil, to experimentally obtain relative permeability and fractional flow curves. Application of the light oil fractional curve, which exhibits a regular S-shape, to the water flooding method showed that a large amount of mobile oil in the reservoir is displaced by water injection. In contrast, the fractional flow curve of heavy oil does not display an S-shape because of its high viscosity. Although the advance of the injected waterfront is faster than in light oil reservoirs, a significant amount of mobile oil remains behind the waterfront.

Keywords: Fractional flow curve, oil recovery, relative permeability, water fingering.

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Authors: Nader Nabhani, Amir Tofighi

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Nanotechnology is the science of creating, using and manipulating objects which have at least one dimension in range of 0.1 to 100 nanometers. In other words, nanotechnology is reconstructing a substance using its individual atoms and arranging them in a way that is desirable for our purpose. The main reason that nanotechnology has been attracting attentions is the unique properties that objects show when they are formed at nano-scale. These differing characteristics that nano-scale materials show compared to their nature-existing form is both useful in creating high quality products and dangerous when being in contact with body or spread in environment. In order to control and lower the risk of such nano-scale particles, the main following three topics should be considered: 1) First of all, these materials would cause long term diseases that may show their effects on body years after being penetrated in human organs and since this science has become recently developed in industrial scale not enough information is available about their hazards on body. 2) The second is that these particles can easily spread out in environment and remain in air, soil or water for very long time, besides their high ability to penetrate body skin and causing new kinds of diseases. 3) The third one is that to protect body and environment against the danger of these particles, the protective barriers must be finer than these small objects and such defenses are hard to accomplish. This paper will review, discuss and assess the risks that human and environment face as this new science develops at a high rate.

Keywords: Nanotechnology, risk assessment, environment.

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Authors: J. Bertrandt, A. Kłos, R. Waszkowski, T. Nowicki, R. Pytlak, E. Stęzycka, A. Gazdzinska

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 The aim of the work was estimation of copper intake with the daily food rations used for alimentation of students of military high schools and soldiers doing compulsory military service in the Polish Army. An average planned copper content in daily food rations used for alimentation of students and soldiers amounted to 2.49±0.35 mg, and 2.44±0.25 mg respectively. The copper content in the daily food ration given for consumption to students amounted from 1.81±0.14 mg to 2.58±0.44 mg while daily food rations served to soldiers delivered from 2.06±0.45 mg to 2.13±0.33 mg. The copper content in the rations planned for students and soldiers alimentation was within the limits of the norms obligatory in Poland. Daily food rations given for consumption, except rations served for students, were within the limits of the recommended norms, but food rations really eaten by examined men didn’t cover the requirements for copper.

Keywords: Copper, daily food ration, military service.

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Authors: Debasis Sarkar

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Building Information Modeling (BIM) is a holistic documentation process for operational visualization, design coordination, estimation and project scheduling. BIM software defines objects parametrically and it is a tool for virtual reality. Primary advantage of implementing BIM is the visual coordination of the building structure and systems such as Mechanical, Electrical and Plumbing (MEP) and it also identifies the possible conflicts between the building systems. This paper is an attempt to develop a risk based BIM model which would highlight the primary advantages of application of BIM pertaining to urban infrastructure transportation project. It has been observed that about 40% of the Architecture, Engineering and Construction (AEC) companies use BIM but primarily for their outsourced projects. Also, 65% of the respondents agree that BIM would be used quiet strongly for future construction projects in India. The 3D models developed with Revit 2015 software would reduce co-ordination problems amongst the architects, structural engineers, contractors and building service providers (MEP). Integration of risk management along with BIM would provide enhanced co-ordination, collaboration and high probability of successful completion of the complex infrastructure transportation project within stipulated time and cost frame.

Keywords: Building information modeling (BIM), infrastructure transportation, project risk management, underground metro rail.

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Authors: Nasser M. Amaitik, Nabil A. Alfagi

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The world-s largest Pre-stressed Concrete Cylinder Pipe (PCCP) water supply project had a series of pipe failures which occurred between 1999 and 2001. This has led the Man-Made River Authority (MMRA), the authority in charge of the implementation and operation of the project, to setup a rehabilitation plan for the conveyance system while maintaining the uninterrupted flow of water to consumers. At the same time, MMRA recognized the need for a long term management tool that would facilitate repair and maintenance decisions and enable taking the appropriate preventive measures through continuous monitoring and estimation of the remaining life of each pipe. This management tool is known as the Pipe Risk Management System (PRMS) and now in operation at MMRA. Both the rehabilitation plan and the PRMS require the availability of complete and accurate pipe construction and manufacturing data This paper describes a systematic approach of data collection, analysis, evaluation and correction for the construction and manufacturing data files of phase I pipes which are the platform for the PRMS database and any other related decision support system.

Keywords: Asbuilt, History, IMD, MMRA, PDBMS & PRMS

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Authors: Sajjad Farashi

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Neurons in the nervous system communicate with each other by producing electrical signals called spikes. To investigate the physiological function of nervous system it is essential to study the activity of neurons by detecting and sorting spikes in the recorded signal. In this paper a method is proposed for considering the spike sorting problem which is based on the nonlinear modeling of spikes using exponential autoregressive model. The genetic algorithm is utilized for model parameter estimation. In this regard some selected model coefficients are used as features for sorting purposes. For optimal selection of model coefficients, self-organizing feature map is used. The results show that modeling of spikes with nonlinear autoregressive model outperforms its linear counterpart. Also the extracted features based on the coefficients of exponential autoregressive model are better than wavelet based extracted features and get more compact and well-separated clusters. In the case of spikes different in small-scale structures where principal component analysis fails to get separated clouds in the feature space, the proposed method can obtain well-separated cluster which removes the necessity of applying complex classifiers.

Keywords: Exponential autoregressive model, Neural data, spike sorting, time series modeling.

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Authors: Rishabh Garg

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Traditionally, business parties build trust with a centralized operating mechanism, such as payment by letter of credit. However, the increase in cyber-attacks and malicious hacking has jeopardized business operations and finance practices. Emerging markets, due to their high banking risks and the large presence of digital financing, are looking for technology that enables transparency and traceability of any transaction in trade, finance or supply chain management. Blockchain systems, in the absence of any central authority, enable transactions across the globe with the help of decentralized applications. DApps consist of a front-end, a blockchain back-end, and middleware, that is, the code that connects the two. The front-end can be a sophisticated web app or mobile app, which is used to implement the functions/methods on the smart contract. Web apps can employ technologies such as HTML, CSS, React and Express. In this wake, fintech and blockchain products are popping up in brokerages, digital wallets, exchanges, post-trade clearance, settlement, middleware, infrastructure and base protocols. The present paper provides a technology driven solution, financial inclusion and innovative working paradigm for business and finance.

Keywords: Authentication, blockchain, channel, cryptography, DApps, data portability, Decentralized Public Key Infrastructure, Ethereum, hash function, Hashgraph, Privilege creep, Proof of Work algorithm, revocation, storage variables, Zero Knowledge Proof.

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Authors: Vasco A. P. Cadavez, Fernando C. Monteiro

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The objective of this study was to develop and compare alternative prediction equations of lean meat proportion (LMP) of lamb carcasses. Forty (40) male lambs, 22 of Churra Galega Bragançana Portuguese local breed and 18 of Suffolk breed were used. Lambs were slaughtered, and carcasses weighed approximately 30 min later in order to obtain hot carcass weight (HCW). After cooling at 4º C for 24-h a set of seventeen carcass measurements was recorded. The left side of carcasses was dissected into muscle, subcutaneous fat, inter-muscular fat, bone, and remainder (major blood vessels, ligaments, tendons, and thick connective tissue sheets associated with muscles), and the LMP was evaluated as the dissected muscle percentage. Prediction equations of LMP were developed, and fitting quality was evaluated through the coefficient of determination of estimation (R2 e) and standard error of estimate (SEE). Models validation was performed by k-fold crossvalidation and the coefficient of determination of prediction (R2 p) and standard error of prediction (SEP) were computed. The BT2 measurement was the best single predictor and accounted for 37.8% of the LMP variation with a SEP of 2.30%. The prediction of LMP of lamb carcasses can be based simple models, using as predictors the HCW and one fat thickness measurement.

Keywords: Bootstrap, Carcass, Lambs, Lean meat

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Authors: Cheewaphongphan P., Garivait S., Pongpullponsak A., Patumsawad S.

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Thailand is one of the world-s leaders of rice producers and exporters. Farmers have to increase the rice cultivation frequency for serving the national increasing of export-s demand. It leads to an elimination of rice residues by open burning which is the quickest and costless management method. The open burning of rice residue is one of the major causes of air pollutants and greenhouse gas (GHG) emission. Under ASEAN agreement on trans-boundary haze, Thailand set the master plan to mitigate air pollutant emission from open burning of agricultural residues. In this master plan, residues incorporation is promoted as alternative management method to open burning. However, the assessment of both options in term of GHG emission in order to investigate their contribution to long-term global warming is still scarce or inexistent. In this study, a method on rice residues assessment was first developed in order to estimate and compare GHG emissions from rice cultivation under rice residues open burning and the case with incorporation of the same amount of rice residues, using 2006 IPCC guidelines for emission estimation and Life Cycle Analysis technique. The emission from rice cultivation in different preparing area practice was also discussed.

Keywords: Greenhouse gases, Incorporation, Rice cultivation, Rice field residue, Rice residue management

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Authors: Sina Fadaie, Seyed Abolhassan Naeini

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Coastal embankments play an important role in coastal structures by reducing the effect of the wave forces and controlling the movement of sediments. Many coastal areas are underlain by weak and compressible soils. Estimation of during construction settlement of coastal embankments is highly important in design and safety control of embankments and appurtenant structures. Accordingly, selecting and establishing of an appropriate model with a reasonable level of complication is one of the challenges for engineers. Although there are advanced models in the literature regarding design of embankments, there is not enough information on the prediction of their associated settlement, particularly in coastal areas having considerable soft soils. Marine engineering study in Iran is important due to the existence of two important coastal areas located in the northern and southern parts of the country. In the present study, the validity of Terzaghi’s consolidation theory has been investigated. In addition, the settlement of these coastal embankments during construction is predicted by using special methods in PLAXIS software by the help of appropriate boundary conditions and soil layers. The results indicate that, for the existing soil condition at the site, some parameters are important to be considered in analysis. Consequently, a model is introduced to estimate the settlement of the embankments in such geotechnical conditions.

Keywords: Consolidation, coastal embankments, settlement, numerical methods, finite elements method.

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Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model.

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Authors: Reinaldo Biscaro, Luciano R. Ferreira, Leonardo C. Biscaro, Raphael C. Biscaro, Isabela S. Vasconcelos, Laura C. R. Ferreira, Cristiano M. Galhardi, Erica P. Baciuk

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Introduction: The present study had the objective to present the profile of workers with shoulder disorders related to labor lawsuits in Brazil. The study analyzed the association between the worker’s health and the actions performed by the companies related to injured professional. The research method performed a retrospective, cross-sectional and quantitative database analysis. The documents of labor lawsuits with shoulder injury registered at the Regional Labor Court in the 15^th region (Campinas - São Paulo) were submitted to the medical examination and evaluated during the period from 2012 until 2015. The data collected were age, gender, onset of symptoms, length of service, current occupation, type of shoulder injury, referred complaints, type of acromion, associated or related diseases, company actions as CAT (workplace accident communication), compliance of NR7 by the organization (Environmental Risk Prevention Program - PPRA and Medical Coordination Program in Occupational Health - PCMSO). Results: From the 93 workers evaluated, there was a prevalence of men (58.1%), with a mean age of 42.6 y-o, and 54.8% were included in the age group 35-49 years. Regarding the length of work time in the company, 66.7% have worked for more than 5 years. There was an association between gender and current occupational status (p < 0.005), with predominance of women in household occupation (13 vs. 2) and predominance of unemployed men in job search situation (24 vs. 10) and reintegrated to work by judicial decision (8 vs. 2). There was also a correlation between pain and functional limitation (p < 0.01). There was a positive association of PPRA with the complaint of functional limitation and negative association with pain (p < 0.04). There was also a correlation between the sedentary lifestyle and the presence of PCMSO and PPRA (p < 0.04), and the absence of CAT in the companies (p < 0.001). It was concluded that the appearance or aggravation of osseous and articular shoulder pathologies in workers who have undertaken labor law suits seem to be associated with individual habits or inadequate labor practices. These data can help preventing the occurrence of these lesions by implementing local health promotion policies at work.

Keywords: Work-related accidents, cross-sectional study, shoulder lesions, labor lawsuits.

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Authors: Lida Haghnegahdar, Ezzatollah Asgharizadeh

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Value engineering is an efficacious contraption for administrators to make up their minds. Value perusals proffer the gaffers a suitable instrument to decrease the expenditures of the life span, quality amelioration, structural improvement, curtailment of the construction schedule, longevity prolongation or a merging of the aforementioned cases. Subjecting organizers to pressures on one hand and their accountability towards their pertinent fields together with inherent risks and ambiguities of other options on the other hand set some comptrollers in a dilemma utilization of risk management and the value engineering in projects manipulation with regard to complexities of implementing projects can be wielded as a contraption to identify and efface each item which wreaks unnecessary expenses and time squandering sans inflicting any damages upon the essential project applications. Of course It should be noted that implementation of risk management and value engineering with regard to the betterment of efficiency and functions may lead to the project implementation timing elongation. Here time revamping does not refer to time diminishing in the whole cases. his article deals with risk and value engineering conceptualizations at first. The germane reverberations effectuated due to its execution in Iran Khodro Corporation are regarded together with the joint features and amalgamation of the aforesaid entia; hence the proposed blueprint is submitted to be taken advantage of in engineering and industrial projects including Iran Khodro Corporation.

Keywords: Management, risk engineering, value engineering, project manipulation, Iran Khodro.

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Authors: Zhengkun Guo, Yanbin Li, Wenqing Wang, Bo Zou

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Active radar and sonar systems often report Doppler measurements in addition to the position measurements such as range and bearing. The tracker can perform better by making full use of the Doppler measurements. However, due to the high nonlinearity of the Doppler measurements with respect to the target state in the Cartesian coordinate systems, those measurements are not always fully exploited. This paper mainly focuses on dealing with the Doppler measurements as well as the position measurements in Polar coordinates. The Statically Fused Converted Position and Doppler Measurements Kalman Filter (SF-CMKF) with additive debiased measurement conversion has been presented. However, the exact compensation for the bias of the measurement conversion are multiplicative and depend on the statistics of the cosine of the angle measurement errors. As a result, the consistency and performance of the SF-CMKF may be suboptimal in the large angle error situations. In this paper, the multiplicative unbiased position and Doppler measurement conversion for two-dimensional (Polar-to-Cartesian) tracking are derived, and the SF-CMKF is improved by using those conversion. Monte Carlo simulations are presented to demonstrate the statistic consistency of the multiplicative unbiased conversion and the superior performance of the modified SF-CMKF (SF-UCMKF).

Keywords: Measurement conversion, Doppler, Kalman filter, estimation, tracking.

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Authors: Ashly Joseph

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Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies.

Keywords: Machine Learning, Natural Learning Processing, Denial-of-Service attacks, Sentiment Analysis, Cloud computing.

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Authors: Nurhani Kasuan, Zakariah Yusuf, Mohd Nasir Taib, Mohd Hezri Fazalul Rahiman, Nazurah Tajuddin, Mohd Azri Abdul Aziz

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This paper presents a hybrid fuzzy-PD plus PID (HFPP) controller and its application to steam distillation process for essential oil extraction system. Steam temperature is one of the most significant parameters that can influence the composition of essential oil yield. Due to parameter variations and changes in operation conditions during distillation, a robust steam temperature controller becomes nontrivial to avoid the degradation of essential oil quality. Initially, the PRBS input is triggered to the system and output of steam temperature is modeled using ARX model structure. The parameter estimation and tuning method is adopted by simulation using HFPP controller scheme. The effectiveness and robustness of proposed controller technique is validated by real time implementation to the system. The performance of HFPP using 25 and 49 fuzzy rules is compared. The experimental result demonstrates the proposed HFPP using 49 fuzzy rules achieves a better, consistent and robust controller compared to PID when considering the test on tracking the set point and the effects due to disturbance.

Keywords: Fuzzy Logic controller, steam temperature, steam distillation, real time control.

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Authors: Mária Hudáková, Mária Lusková

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This report is focused on widening the theoretical knowledge as well as controlling practical application from the risk management point of view, regarding to dynamic business changes that have occurred in Slovakia which recently has been considered to be an environment full of risk and uncertainty. The idea of the report is the proposal of the controlling operation model in the course of risk management process in an enterprise operating in Slovakia, by which the controller is able to identify early risk factors in suggested major areas of the business management upon appropriate business information integration, consecutive control and prognoses and to prepare in time full-value documents in order to suggest measures for reduction thereof. Dealing with risk factors, that can quickly limit the growth potential of the enterprise, is an essential part of managerial activities on each level. This is the reason why mutual unofficial, ergo collegial cooperation of individual departments is necessary for controlling application from the business risk management point of view. An important part of the report is elaborated survey of the most important risk factors existing in major management areas of enterprises operating in Slovakia. The outcome of the performed survey is a catalogue of the most important enterprise risk factors. The catalogue serves for better understanding risk factors affecting the Slovak enterprises, their importance and evaluation.

Keywords: Controlling, information system, risks management, risk factor, crisis of enterprise.

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Authors: Mahmoud Saeidi, Ali Nazemipour

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In this paper, we propose a novel adaptive spatiotemporal filter that utilizes image sequences in order to remove noise. The consecutive frames include: current, previous and next noisy frames. The filter proposed in this paper is based upon the weighted averaging pixels intensity and noise variance in image sequences. It utilizes the Appropriate Number of Consecutive Frames (ANCF) based on the noisy pixels intensity among the frames. The number of consecutive frames is adaptively calculated for each region in image and its value may change from one region to another region depending on the pixels intensity within the region. The weights are determined by a well-defined mathematical criterion, which is adaptive to the feature of spatiotemporal pixels of the consecutive frames. It is experimentally shown that the proposed filter can preserve image structures and edges under motion while suppressing noise, and thus can be effectively used in image sequences filtering. In addition, the AWA filter using ANCF is particularly well suited for filtering sequences that contain segments with abruptly changing scene content due to, for example, rapid zooming and changes in the view of the camera.

Keywords: Appropriate Number of Consecutive Frames, Adaptive Weighted Averaging, Motion Estimation, Noise Variance, Motion Compensation

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Authors: Hadi Veisi, Mansour Jamzad

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In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation are evaluated and compared. In training and evaluation, each image block is assigned to a network based on its complexity value. Best-SNR is another alternative in selecting compressor network for image blocks in evolution phase which chooses one of the trained networks such that results best SNR in compressing the input image block. In our evaluations, best results are obtained when overlapping the blocks is allowed and choosing the networks in compressor is based on the Best-SNR. In this case, the results demonstrate superiority of this method comparing with previous similar works and JPEG standard coding.

Keywords: Adaptive image compression, Image complexity, Multi-layer perceptron neural network, JPEG Standard, PSNR.

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Authors: S. Areerachakul

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Nowadays, several techniques such as; Fuzzy Inference System (FIS) and Neural Network (NN) are employed for developing of the predictive models to estimate parameters of water quality. The main objective of this study is to compare between the predictive ability of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model and Artificial Neural Network (ANN) model to estimate the Biochemical Oxygen Demand (BOD) on data from 11 sampling sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2004-2011. The five parameters of water quality namely Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen (NO3N), and Total Coliform bacteria (T-coliform) are used as the input of the models. These water quality indices affect the biochemical oxygen demand. The experimental results indicate that the ANN model provides a higher correlation coefficient (R=0.73) and a lower root mean square error (RMSE=4.53) than the corresponding ANFIS model.

Keywords: adaptive neuro-fuzzy inference system, artificial neural network, biochemical oxygen demand, surface water.

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Authors: Hoda Zolfagharnejad, Behnam Kamkar, Omid Abdi

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Crop coefficient (Kc) is an important factor contributing to estimation of evapotranspiration, and is also used to determine the irrigation schedule. This study investigated and determined the monthly Kc of winter wheat (Triticum aestivum L.) using five vegetation indices (VIs): Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), Soil Adjusted Vegetation Index (SAVI), Infrared Percentage Vegetation Index (IPVI), and Ratio Vegetation Index (RVI) of four basins in Golestan province, Iran. 14 Landsat-8 images according to crop growth stage were used to estimate monthly Kc of wheat. VIs were calculated based on infrared and near infrared bands of Landsat 8 images using Geographical Information System (GIS) software. The best VIs were chosen after establishing a regression relationship among these VIs with FAO Kc and Kc that was modified for the study area by the previous research based on R² and Root Mean Square Error (RMSE). The result showed that local modified SAVI with R²= 0.767 and RMSE= 0.174 was the best index to produce monthly wheat Kc maps.

Keywords: Crop coefficient, remote sensing, vegetation indices, wheat.

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Authors: Kasra Afsahi, Maryam Soheilifar, S. Hossein Hosseini

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Background: There is growing evidence that Cerebral Vascular Accident (CVA) can be a consequence of COVID-19 infection. Understanding novel treatment approaches is important in optimizing patient outcomes. Case: This case explores the use of Virtual Reality (VR) in the treatment of a 23-year-old COVID-positive female presenting with left hemiparesis in August 2020. Imaging showed right globus pallidus, thalamus, and internal capsule ischemic stroke. Conventional rehabilitation was started two weeks later, with VR included. This game-based VR technology developed for stroke patients was based on upper extremity exercises and functions for stroke. Physical examination showed left hemiparesis with muscle strength 3/5 in the upper extremity and 4/5 in the lower extremity. The range of motion of the shoulder was 90-100 degrees. The speech exam showed a mild decrease in fluency. Mild lower lip dynamic asymmetry was seen. Babinski was positive on the left. Gait speed was decreased (75 steps per minute). Intervention: Our game-based VR system was developed based on upper extremity physiotherapy exercises for post-stroke patients to increase the active, voluntary movement of the upper extremity joints and improve the function. The conventional program was initiated with active exercises, shoulder sanding for joint ROMs, walking shoulder, shoulder wheel, and combination movements of the shoulder, elbow, and wrist joints, alternative flexion-extension, pronation-supination movements, Pegboard and Purdo pegboard exercises. Also, fine movements included smart gloves, biofeedback, finger ladder, and writing. The difficulty of the game increased at each stage of the practice with progress in patient performances. Outcome: After 6 weeks of treatment, gait and speech were normal and upper extremity strength was improved to near normal status. No adverse effects were noted. Conclusion: This case suggests that VR is a useful tool in the treatment of a patient with COVID-19 related CVA. The safety of developed instruments for such cases provides approaches to improve the therapeutic outcomes and prognosis as well as increased satisfaction rate among patients.

Keywords: COVID-19, stroke, virtual reality, rehabilitation.

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Authors: Andrew Jester, Ross Lee, Pritpal Singh

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As the world transitions to a more sustainable energy economy, the deployment of energy storage technologies is expected to increase to develop a more resilient grid system. However, current technologies are associated with various environmental and safety issues throughout their entire lifecycle; therefore, a new battery technology is desirable for grid applications to curtail these risks. Biological cells, such as human neurons and electrocytes in the electric eel, can serve as a more sustainable design template for a new bio-inspired (i.e., biomimetic) battery. Within biological cells, an electrochemical gradient across the cell membrane forms the membrane potential, which serves as the driving force for ion transport into/out of the cell akin to the charging/discharging of a battery cell. This work serves as the first step for developing such a biomimetic battery cell, starting with the fabrication and characterization of ion-selective membranes to facilitate ion transport through the cell. Performance characteristics (e.g., cell voltage, power density, specific energy, roundtrip efficiency) for the cell under investigation are compared to incumbent battery technologies and biological cells to assess the readiness level for this emerging technology. Using a Na+-Form Nafion-117 membrane, the cell in this work successfully demonstrated behavior like human neurons; these findings will inform how cell components can be re-engineered to enhance device performance.

Keywords: Battery, biomimetic, electrocytes, human neurons, ion-selective membranes, membrane potential.

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Authors: Hui-Jae You, Sun-Tae Chung, Souhwan Jung

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SAD (Sum of Absolute Difference) algorithm is heavily used in motion estimation which is computationally highly demanding process in motion picture encoding. To enhance the performance of motion picture encoding on a VLIW processor, an efficient implementation of SAD algorithm on the VLIW processor is essential. SAD algorithm is programmed as a nested loop with a conditional branch. In VLIW processors, loop is usually optimized by software pipelining, but researches on optimal scheduling of software pipelining for nested loops, especially nested loops with conditional branches are rare. In this paper, we propose an optimal scheduling and implementation of SAD algorithm with conditional branch on a VLIW DSP processor. The proposed optimal scheduling first transforms the nested loop with conditional branch into a single loop with conditional branch with consideration of full utilization of ILP capability of the VLIW processor and realization of earlier escape from the loop. Next, the proposed optimal scheduling applies a modulo scheduling technique developed for single loop. Based on this optimal scheduling strategy, optimal implementation of SAD algorithm on TMS320C67x, a VLIW DSP is presented. Through experiments on TMS320C6713 DSK, it is shown that H.263 encoder with the proposed SAD implementation performs better than other H.263 encoder with other SAD implementations, and that the code size of the optimal SAD implementation is small enough to be appropriate for embedded environments.

Keywords: Optimal implementation, SAD algorithm, VLIW, TMS320C6713.

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Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

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Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: Hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection.

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Authors: Ilker Kalkan, Saruhan Kartal

Abstract:

Reinforced concrete (RC) beams rarely undergo lateral-torsional buckling (LTB), since these beams possess large lateral bending and torsional rigidities owing to their stocky cross-sections, unlike steel beams. However, the problem of LTB is becoming more and more pronounced in the last decades as the span lengths of concrete beams increase and the cross-sections become more slender with the use of pre-stressed concrete. The buckling moment of a beam mainly depends on its lateral bending rigidity and torsional rigidity. The nonhomogeneous and elastic-inelastic nature of RC complicates estimation of the buckling moments of concrete beams. Furthermore, the lateral bending and torsional rigidities of RC beams and the buckling moments are affected from different forms of concrete cracking, including flexural, torsional and restrained shrinkage cracking. The present study pertains to the effects of concrete cracking on the torsional rigidities of RC beams prone to elastic LTB. A series of tests on rather slender RC beams indicated that torsional cracking does not initiate until buckling in elastic LTB, while flexural cracking associated with lateral bending takes place even at the initial stages of loading. Hence, the present study clearly indicated that the un-cracked torsional rigidity needs to be used for estimating the buckling moments of RC beams liable to elastic LTB.

Keywords: Lateral stability, post-cracking torsional rigidity, uncracked torsional rigidity, critical moment.

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Authors: Jiann-Ming Wu, Hsiao-Chang Chen, Chun-Chang Wu, Pei-Hsun Hsu

Abstract:

This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.

Keywords: Blind image deconvolution, linear shift-invariant(LSI), linear image degradation model, radial basis functions (rbf), recursive function, annealed Hopfield neural networks.

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Authors: Mat Isa, C. M., Mohd Saman, H., Mohd Nasir, S. R., Jaapar, A.

Abstract:

International market expansion involves a strategic process of market entry decision through which a firm expands its operation from domestic to the international domain. Hence, entry timing choices require the needs to balance the early entry risks and the problems in losing opportunities as a result of late entry into a new market. Questionnaire surveys administered to 115 Malaysian construction firms operating in 51 countries worldwide have resulted in 39.1 percent response rate. Factor analysis was used to determine the most significant factors affecting entry timing choices of the firms to penetrate the international market. A logistic regression analysis used to examine the firms’ entry timing choices, indicates that the model has correctly classified 89.5 per cent of cases as late movers. The findings reveal that the most significant factor influencing the construction firms’ choices as late movers was the firm factor related to the firm’s international experience, resources, competencies and financing capacity. The study also offers valuable information to construction firms with intention to internationalize their businesses.

Keywords: Factors, early movers, entry timing choices, late movers, Logistic Regression Model, Principal Axis Factorial Analysis, Malaysian construction firms.

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Authors: Jamal R. Elbergali

Abstract:

Multiple Input Multiple Output (MIMO) systems are wireless systems with multiple antenna elements at both ends of the link. Wireless communication systems demand high data rate and spectral efficiency with increased reliability. MIMO systems have been popular techniques to achieve these goals because increased data rate is possible through spatial multiplexing scheme and diversity. Spatial Multiplexing (SM) is used to achieve higher possible throughput than diversity. In this paper, we propose a Zero- Forcing (ZF) detection using a combination of Ordered Successive Interference Cancellation (OSIC) and Zero Forcing using Interference Cancellation (ZF-IC). The proposed method used an OSIC based on Signal to Noise Ratio (SNR) ordering to get the estimation of last symbol, then the estimated last symbol is considered to be an input to the ZF-IC. We analyze the Bit Error Rate (BER) performance of the proposed MIMO system over Rayleigh Fading Channel, using Binary Phase Shift Keying (BPSK) modulation scheme. The results show better performance than the previous methods.

Keywords: SNR, BER, BPSK, MIMO, Modulation, Zero forcing (ZF), OSIC, ZF-IC, Spatial Multiplexing (SM).

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Authors: Aïssa Rezzoug

Abstract:

This paper is aimed to bring new elements that demonstrate the tide caused the groundwater to rise in the shoreline band, on which the urban areas occurs, especially in the western coastal cities of the Kingdom of Saudi Arabia like Jeddah. The reason for the last events of Jeddah inundation was the groundwater rise in the city coupled at the same time to a strong precipitation event. This paper will illustrate the tide participation in increasing the groundwater level significantly. It shows that the reason for internal groundwater recharge within the urban area is not only the excess of the water supply coming from surrounding areas, due to the human activity, with lack of sufficient and efficient sewage system, but also due to tide effect. The research study follows a quantitative method to assess groundwater level rise risks through many in-situ measurements and mathematical modelling. The proposed approach highlights groundwater level, in the urban areas of the city on the shoreline band, reaching the high tide level without considering any input from precipitation. Despite the small tide in the Red Sea compared to other oceanic coasts, the groundwater level is considerably enhanced by the tide from the seaside and by the freshwater table from the landside of the city. In these conditions, the groundwater level becomes high in the city and prevents the soil to evacuate quickly enough the surface flow caused by the storm event, as it was observed in the last historical flood catastrophe of Jeddah in 2009.

Keywords: Flood, groundwater rise, Jeddah, tide.

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