Search results for: reduced order macro models

Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

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The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

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Authors: Iram Batool, Aamer Saeed, Irfan Zia Qureshi, Ayesha Razzaq, Saima Kalsoom

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Heterocyclic compounds analogues and their derivatives have attracted strong interest in medicinal chemistry due to their biological and pharmacological properties. A series of new thiazolopyrimidine carboxylates were conveniently synthesized by one-pot three-component reaction of ethyl acetoacetate, 2-aminothiazole and benzaldehyde substituted with electron-donating and electron-withdrawing groups in order to find some more potent antidiabetic and antibacterial drugs. The structures of synthesized compounds were characterized by elemental analysis, IR, 1H NMR, 13C NMR spectroscopy. An in vitro antidiabetic effect was evaluated in adult male BALB/c mice and antibacterial activities were tested against Micrococcus luteus, Salmonella typhimurium, Bacillus subtilis, Bordetella bronchiseptica and Escherichia coli. Some of the tested compounds proved to possess good to excellent activities more than the reference drugs. An in silico molecular docking was also performed on synthesized compounds. The current study is expected to provide useful insights into the design of antidiabetic and antibacterial drugs and understanding the mechanism by which such drugs interact with RNA and diabetes target and exert their biochemical action.

Keywords: antidiabetic, antibacterial, MOE docking, thiazolopyrimidine

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Authors: Kingkan Pongsiri

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This paper aims to study the role and activities of the participants and the impact of activities created in the local area in order to sustainably develop the local areas. This study applied both qualitative and quantitative approaches presented in descriptive style; the data was collected via survey, observation and in-depth interviews with samples. The results illustrated five sorts of roles of participants of the Cicada Walking-street and four types of creative activities; recreation based, art based, cultural based, and live events. Integration of local characteristics, arts and cultures were presented creatively and interestingly. Participants are various. The roles of the participants found in the Cicada Market are group of the property and area management, entrepreneurs, leisure (entertaining persons), local people, and tourists. The good impacts on local communities are those in terms of economy, environmental friendly and local arts and cultures promoting. On the other hand, the traffic congestion, waste and the increasing of energy consumption are negative impacts from area development.

Keywords: creative tourism activity, destination development, sustainable development, walking street

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Authors: Eszter Repasi, Akos Koller

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Our genetic information determines our look, physiology, sports performance and all our features. Maximizing the performances of athletes have adopted a science-based approach to the nutritional support. Nowadays genetics studies have blended with nutritional sciences, and a dynamically evolving, new research field have appeared. Nutritional genomics is needed to be used by nutritional experts. This is a recent field of nutritional science, which can provide a solution to reach the best sport performance using correlations between the athlete’s genome, nutritions, molecules, included human microbiome (links between food, microbiome and epigenetics), nutrigenomics and nutrigenetics. Nutritional genomics has a tremendous potential to change the future of dietary guidelines and personal recommendations. Experts need to use new technology to get information about the athletes, like nutritional genomics profile (included the determination of the oral and gut microbiome and DNA coded reaction for food components), which can modify the preparation term and sports performance. The influence of nutrients on the genes expression is called Nutrigenomics. The heterogeneous response of gene variants to nutrients, dietary components is called Nutrigenetics. The human microbiome plays a critical role in the state of health and well-being, and there are more links between food or nutrition and the human microbiome composition, which can develop diseases and epigenetic changes as well. A nutritional genomics-based profile of athletes can be the best technic for a dietitian to make a unique sports nutrition diet plan. Using functional food and the right food components can be effected on health state, thus sports performance. Scientists need to determine the best response, due to the effect of nutrients on health, through altering genome promote metabolites and result changes in physiology. Nutritional biochemistry explains why polymorphisms in genes for the absorption, circulation, or metabolism of essential nutrients (such as n-3 polyunsaturated fatty acids or epigallocatechin-3-gallate), would affect the efficacy of that nutrient. Controlled nutritional deficiencies and failures, prevented the change of health state or a newly discovered food intolerance are observed by a proper medical team, can support better sports performance. It is important that the dietetics profession informed on gene-diet interactions, that may be leading to optimal health, reduced risk of injury or disease. A special medical application for documentation and monitoring of data of health state and risk factors can uphold and warn the medical team for an early action and help to be able to do a proper health service in time. This model can set up a personalized nutrition advice from the status control, through the recovery, to the monitoring. But more studies are needed to understand the mechanisms and to be able to change the composition of the microbiome, environmental and genetic risk factors in cases of athletes.

Keywords: gene-diet interaction, multidisciplinary team, microbiome, diet plan

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Authors: Thandie Veronicah Sima, Moatlhodi Wiseman Letshwenyo

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Discharge of wastewater is one of the major sources of phosphorus entering streams, lakes and other water bodies causing undesired environmental problem such as eutrophication. This condition not only puts the ecosystem at risk but also causes severe economic damages. Stringent laws have been developed globally by different bodies to control the level of phosphorus concentrations into receiving environments. In order to satisfy the constraints, a high degree of tertiary treatment or at least a significant reduction of phosphorus concentration is obligatory. This comprehensive review summarizes phosphorus removal technologies, from the most commonly used conventional technologies such as chemical precipitation through metal addition, membrane filtration, reverse osmosis and enhanced biological phosphorus removal using activated sludge system to passive systems such as constructed wetlands and filtration systems. Trends, perspectives and scientific procedures conducted by different researchers have been presented. This review critically evaluates the advantages and limitations behind each of the technologies. Enhancement of passive systems using reactive media such as industrial wastes to provide additional uptake through adsorption or precipitation is also discussed in this article.

Keywords: adsorption, chemical precipitation, enhanced biological phosphorus removal, phosphorus removal

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Authors: Amel Benatallah, Michel Marie, Faical Ghozlane

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Bluetongue (BT) is a major concern of veterinary services and a real threat to the sheep population. Epidemiological situation of blue tongue has revealed that in 2000, the serotype 2 (BTV2) was isolated and identified. The vector of BTV has affected 10 provinces out of 48 provinces in the country. As a result, 28 outbreaks were reported with 191 cases including 29 deaths. In 2006, the vector of the FCO has still hit Algeria, but this time with another serotype, the BTV 1. The latter was responsible for the resurgence of the disease in 11 provinces (29 outbreaks with 265 reported cases and 36 deaths).The same serotype (BTV1) was isolated and identified in 2008 in two provinces (2 outbreaks with 15 cases revealing 5 deaths) , in 2009 in 5 provinces (19 outbreaks with 78 reported cases and 20 deaths). In addition, 2010 and 2011 saw the resurgence of the same serotype (BTV1) respectively in 9 (46 outbreaks with 131 cases including and 25 deaths) and 7 provinces (16 outbreaks with 63 reported cases and 6 deaths). Serological and entomological surveys were conducted in Algeria during the period from 2000 to 2007 in order to identify the different BTV strains of existing FCO in Algeria in addition to vector Culicoides Imicola and to study the ecology of this vector to limit its movement in the country.

Keywords: blue tongue, serotype, vectors, culicoides imicola, BTV, FCO

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Authors: Mohsen Goodarzi, George Berghorn

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Despite the rapid growth in the number of green building and community development projects, the long-term performance of these projects has not yet been sufficiently evaluated from the users’ points of view. This is partially due to the lack of post-occupancy evaluation tools available for this type of project. In this study, a post-construction evaluation model is developed to evaluate the relationship between the perceived performance and satisfaction of residents in LEED-certified residential buildings and communities. To develop this evaluation model, a primary five-factor model was developed based on the existing models and residential satisfaction theories. Each factor of the model included several measures that were adopted from LEED certification systems such as LEED-BD+C New Construction, LEED-BD+C Multifamily Midrise, LEED-ND, as well as the UC Berkeley’s Center for the Built Environment survey tool. The model included four predictor variables (factors), including perceived building performance (8 measures), perceived infrastructure performance (9 measures), perceived neighborhood design (6 measures), and perceived economic performance (4 measures), and one dependent variable (factor), which was residential satisfaction (6 measures). An online survey was then conducted to collect the data from the residents of LEED-certified residential communities (n=192) and the validity of the model was tested through Confirmatory Factor Analysis (CFA). After modifying the CFA model, 26 measures, out of the initial 33 measures, were retained to enter into a Structural Equation Model (SEM) and to find the relationships between the perceived buildings performance, infrastructure performance, neighborhood design, economic performance and residential Satisfaction. The results of the SEM showed that the perceived building performance was the most influential factor in determining residential satisfaction in LEED-certified communities, followed by the perceived neighborhood design. On the other hand, perceived infrastructure performance and perceived economic performance did not show any significant relationship with residential satisfaction in these communities. This study can benefit green building researchers by providing a model for the evaluation of the long-term performance of these projects. It can also provide opportunities for green building practitioners to determine priorities for future residential development projects.

Keywords: green building, residential satisfaction, perceived performance, confirmatory factor analysis, structural equation modeling

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Authors: L. Salomon, P. Sklenar

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The Andes hold the highest plant species diversity in the world. How this occurred is one of the most intriguing questions in studies addressing the origin and patterning of plant diversity worldwide. Recently, the explosive adaptive radiations found in high Andean groups have been pointed as triggers to this spectacular diversity. The Andes is the species-richest area for the biggest genus from the Asteraceae family: Senecio. There, the genus presents an incredible diversity of species, striking growth form variation, and large niche span. Even when some studies tried to disentangle the evolutionary story for some Andean species in Senecio, they obtained partially resolved and low supported phylogenies, as expected for recently radiated groups. The high-throughput sequencing (HTS) approaches have proved to be a powerful tool answering phylogenetic questions in those groups whose evolutionary stories are recent and traditional techniques like Sanger sequencing are not informative enough. Although these tools have been used to understand the evolution of an increasing number of Andean groups, nowadays, their scope has not been applied for Senecio. This project aims to contribute to a better knowledge of the mechanisms shaping the hyper diversity of Senecio in the Andean region, using HTS focusing on Senecio ser. Culcitium (Asteraceae), recently recircumscribed. Firstly, reconstructing a highly resolved and supported phylogeny, and after assessing the role of allopatric differentiation, hybridization, and genome duplication in the diversification of the group. Using the Hyb-Seq approach, combining target enrichment using Asteraceae COS loci baits and genome skimming, more than 100 new accessions were generated. HybPhyloMaker and HybPiper pipelines were used for the phylogenetic analyses, and another pipeline in development (Paralogue Wizard) was used to deal with paralogues. RAxML was used to generate gene trees and Astral for species tree reconstruction. Phyparts were used to explore as first step of gene tree discordance along the clades. Fully resolved with moderated supported trees were obtained, showing Senecio ser. Culcitium as monophyletic. Within the group, some species formed well-supported clades with morphologically related species, while some species would not have exclusive ancestry, in concordance with previous studies using amplified fragment length polymorphism (AFLP) showing geographical differentiation. Discordance between gene trees was detected. Paralogues were detected for many loci, indicating possible genome duplications; ploidy level estimation using flow cytometry will be carried out during the next months in order to identify the role of this process in the diversification of the group. Likewise, TreeSetViz package for Mesquite, hierarchical likelihood ratio congruence test using Concaterpillar, and Procrustean Approach to Cophylogeny (PACo), will be used to evaluate the congruence among different inheritance patterns. In order to evaluate the influence of hybridization and Incomplete Lineage Sorting (ILS) in each resultant clade from the phylogeny, Joly et al.'s 2009 method in a coalescent scenario and Paterson’s D-statistic will be performed. Even when the main discordance sources between gene trees were not explored in detail yet, the data show that at least to some degree, processes such as genome duplication, hybridization, and/or ILS could be involved in the evolution of the group.

Keywords: adaptive radiations, Andes, genome duplication, hybridization, Senecio

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Authors: Amirah Azzeri, Fatiha H. Shabaruddin, Scott A. McDonald, Rosmawati Mohamed, Maznah Dahlui

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Objective: A scaled-up treatment cascade with direct-acting antiviral (DAA) therapy is necessary to achieve global WHO targets for hepatitis C virus (HCV) elimination in Malaysia. Recently, limited access to Sofosbuvir/Daclatasvir (SOF/DAC) is available through compulsory licensing, with future access to Sofosbuvir/Velpatasvir (SOF/VEL) expected through voluntary licensing due to recent agreements. SOF/VEL has superior clinical outcomes, particularly for cirrhotic stages, but has higher drug acquisition costs compared to SOF/DAC. It has been proposed that a stratified treatment cascade might be the most cost-efficient approach for Malaysia whereby all HCV patients are treated with SOF/DAC except for patients with cirrhosis who are treated with SOF/VEL. This study aimed to conduct a five-year budget impact analysis from the provider perspective of the proposed stratified treatment cascade for HCV treatment in Malaysia. Method: A disease progression model that was developed based on model-predicted HCV epidemiology data in Malaysia was used for the analysis, where all HCV patients in scenario A were treated with SOF/DAC for all disease stages while in scenario B, SOF/DAC was used only for non-cirrhotic patients and SOF/VEL was used for the cirrhotic patients. The model projections estimated the annual numbers of patients in care and the numbers of patients to be initiated on DAA treatment nationally. Healthcare costs associated with DAA therapy and disease stage monitoring was included to estimate the downstream cost implications. For scenario B, the estimated treatment uptake of SOF/VEL for cirrhotic patients were 25%, 50%, 75%, 100% and 100% for 2018, 2019, 2020, 2021 and 2022 respectively. Healthcare costs were estimated based on standard clinical pathways for DAA treatment described in recent guidelines. All costs were reported in US dollars (conversion rate US$1=RM4.09, the price year 2018). Scenario analysis was conducted for 5% and 10% reduction of SOF/VEL acquisition cost anticipated from the competitive market pricing of generic DAA in Malaysia. Results: The stratified treatment cascade with SOF/VEL in Scenario B was found to be cost-saving compared to Scenario A. A substantial portion of the cost reduction was due to the costs associated with DAA therapy which resulted in USD 40 thousand (year 1) to USD 443 thousand (year 5) savings annually, with cumulative savings of USD 1.1 million after 5 years. Cost reductions for disease stage monitoring were seen in year three onwards which resulted in cumulative savings of USD 1.1 thousand. Scenario analysis estimated cumulative savings of USD 1.24 to USD 1.35 million when the acquisition cost of SOF/VEL was reduced. Conclusion: A stratified treatment cascade with SOF/VEL was expected to be cost-saving and can results in a budget impact reduction in overall healthcare expenditure in Malaysia compared to treatment with SOF/DAC. The better clinical efficacy with SOF/VEL is expected to halt patients’ HCV disease progression and may reduce downstream costs of treating advanced disease stages. The findings of this analysis may be useful to inform healthcare policies for HCV treatment in Malaysia.

Keywords: Malaysia, direct acting antiviral, compulsory licensing, voluntary licensing

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Authors: Shahab Hasani Nasab, Aran Aeini, Navid Kermanshahi

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In order to reduce road building costs and reduce environmental damage, recycled materials can be used instead of mineral materials in the production of asphalt mixtures. Today, in most parts of the world, cold recycled asphalt with bitumen emulsion, has acceptable results. However, Cold Recycled Asphalt have some deficiency such as stripping, thermal cracking, and rutting. This requires the addition of additives to reduce this deficiency of recycled pavement with emulsified asphalt. In this research, nano-alumina and emulsified asphalt were used to modify the properties of recycled asphalt mixtures according to the technical specifications and the operation of cold recycling. Marshall test methods, dynamic creep test, and resiliency modulus test has been used to obtain the nano-alumina’s effects on asphalt mixture properties. The results show that the addition of nano-alumina would reduce the Marshall stability in samples but increases the rutting resistance. The resiliency modulus increases significantly with this additive.

Keywords: cold asphalt, cold recycling, nano-alumina, dynamic creep, bitumen emulsion

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Authors: H. K. V. Narayan

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This study was conducted at Tata Memorial Hospital (TMH), Mumbai, India. The study was to evaluate the impact of adapting Smart Card (SC) for clinical and business transactions in order to reduce Lead times and to enforce business rules of the hospital. The objective for implementing the Smart Card was to improve the patient perception of quality in terms of structures process and outcomes and also to improve the productivity of the Institution. The Smart Card was implemented in phases from 2011 and integrated with the Hospital Information System (HIS/EMR). The implementation was a learning curve for all the stake holders as software obviated the need to use hardcopies of transactions. The acceptability to the stake holders was challenge in change management. The study assessed the impact 3 years into the implementation and the observed trends have suggested that it has decreased the lead times for services and increased the no of transactions and thereby the productivity. Patients who used to complain of multiple queues and cumbersome transactions now compliment the administration for effective use of Information and Communication Technology.

Keywords: smart card, high availability of health care information, reduction in potential medical errors due to elimination of transcription errors, reduction in no of queues, increased transactions, augmentation of revenue

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Authors: Si Mon Kueh, Tom J. Kazmierski

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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

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Authors: Brwa Abdulrahman Abubaker

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Recently, there has been a lot of interest in the difficult task of applying reinforcement learning to autonomous mobile robots. Conventional reinforcement learning (TRL) techniques have many drawbacks, such as lengthy computation times, intricate control frameworks, a great deal of trial and error searching, and sluggish convergence. In this paper, a modified Spiking Neural Network (SNN) is used to offer a distinct method for autonomous mobile robot learning and control in unexpected surroundings. As a learning algorithm, the suggested model combines dopamine modulation with spike-timing-dependent plasticity (STDP). In order to create more computationally efficient, biologically inspired control systems that are adaptable to changing settings, this work uses the effective and physiologically credible Izhikevich neuron model. This study is primarily focused on creating an algorithm for target tracking in the presence of obstacles. Results show that the SNN trained with three obstacles yielded an impressive 96% success rate for our proposal, with collisions happening in about 4% of the 214 simulated seconds.

Keywords: spiking neural network, spike-timing-dependent plasticity, dopamine modulation, reinforcement learning

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Authors: Madhawa Basnayaka, Jouni Paltakari

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Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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Authors: Prayas Sharma

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This paper proposed a generalized class of estimators, an exponential class of estimators based on the adaption of Sharma and Singh (2015) and Solanki and Singh (2013), and a simple difference estimator for estimating unknown population mean in the case of Poisson distributed population in simple random sampling without replacement. The expressions for mean square errors of the proposed classes of estimators are derived from the first order of approximation. It is shown that the adapted version of Solanki and Singh (2013), the exponential class of estimator, is always more efficient than the usual estimator, ratio, product, exponential ratio, and exponential product type estimators and equally efficient to simple difference estimator. Moreover, the adapted version of Sharma and Singh's (2015) estimator is always more efficient than all the estimators available in the literature. In addition, theoretical findings are supported by an empirical study to show the superiority of the constructed estimators over others with an application to earthquake data of Turkey.

Keywords: auxiliary attribute, point bi-serial, mean square error, simple random sampling, Poisson distribution

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Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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Authors: Amanda R. R. Oliveira, Caio F. F. C. Cunha, Juan C. L. Junior, Amorim H. P. Junior

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Children deaths are traumatic events that most often can be prevented. The technology of prevention and intervention in cases of infant deaths is available at low cost and with solid evidence and favorable results, however, with low access cover. Weight is one of the main factors related to death in the neonatal period, so the newborns of low birth weight are a population at high risk of death in the neonatal period, especially early neonatal period. This paper describes the development of a model based in neural network analysis to predict the mortality risk rating in the early neonatal period for newborns of low birth weight to identify the individuals of this population with increased risk of death. The neural network applied was trained with a set of newborns data obtained from Brazilian health system. The resulting network presented great success rate in identifying newborns with high chances of death, which demonstrates the potential for using this tool in an integrated manner to the health system, in order to direct specific actions for improving prognosis of newborns.

Keywords: low birth weight, neonatal death risk, neural network, newborn

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Authors: Hassiba Bougueria, Nesrine Benarous, Souheyla Chetioui

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Azo dyes are one of the most widely used compounds in organic chemistry, primarily due to their relatively simple preparation methods. They have therefore been widely used, in particular as colorants for textiles, printing inks, cosmetics, and food additives. In addition to their use as dyes, azo compounds have attracted much attention from chemists as their potential applications are important in coordination chemistry, metal-organic frameworks (MOF) structures, COF (covalent-organic frameworks), and catalysis. Moreover, they have found many applications in different fields, such as nonlinear optics, optical storage, photoluminescence, and magnetism. The compound bis{(E)-1-[(2,4,6-tribromophenyl)diazenyl]naphthalen-2-olato}copper(II) dimethyl sulfoxide monosolvate, the CuII atom is tetracoordinate with a square-planar geometry, surrounded by two bidentate (E)-1-[(2,4,6-tribromophenyl)diazenyl]naphthalene-2-olate ligands via two N atoms and two O atoms. The O-Cu-O angles and N-Cu-N are of the order of 177.90(16)° and 177.8(2)°, respectively. The distances Cu-O and Cu- N are 1.892(4) Å and 1.976(4) Å, respectively. The cohesion of the crystal is ensured by hydrogen bonds of the C—H…O type and by π=π staking interactions [centroid–centroid distance = 3.679(4)Å]. The DMSO solvent molecule is disordered at two positions with occupancy rates of 0.70 and 0.30.

Keywords: azo dyes, DRX, structural characterization, biological activity

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

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Authors: Khaled M. Youssef, Sara I. Ahmed

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In this study, artifacts-free bulk nanocrystalline pure aluminum alloy samples were prepared through mechanical milling under ultra-high purity argon and at both liquid nitrogen and room temperatures. The nanostructure evolution during milling was examined using X-ray diffraction and transmission electron microscope techniques. The in-situ consolidated samples after milling exhibited an average grain size of 18 nm. The tensile properties of this novel material are reported in comparison with coarse-grained aluminum alloys. The 0.2% offset yield strength of the nanocrystalline aluminum was found to be 340 MPa. This value is at least one order of magnitude higher than that of the coarse-grained aluminum alloy. In addition to this extraordinarily high strength, the nanocrystalline aluminum showed a significant tensile ductility, with 6% uniform elongation and 11% elongation-to-failure. The transmission electron microscope observations in this study provide evidence of deformation twinning in the plastically deformed nanocrystalline aluminum. These results highlight a change of the deformation mechanism from a typical dislocation slip to twinning deformation induced by partial dislocation activities.

Keywords: nanocrystalline, aluminum, strength, ductility

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Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

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Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

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Authors: Ail Akbar Emamverdian, Neriman Özada, Atabak Rahimzadeh Ilkhchi, Zahra Emamverdian

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The reverse shoulder prosthesis is an innovative procedure design to treat of (GH) joint problems with severe rotator cuff deficiency. The original reverse shoulder prosthesis was invented by France surgery in1985 and has been in clinical use in the United States in 2004. These prostheses consist of baseplate that attached to the glenoid, in order to hold a spherical component, and humeral part consist of polyethylene insert which is flat. This prosthesis is the ‘reverse’ configuration. The indications for the reverse prosthesis are: (1) treating failed hemi arthroplasty with irrecoverable rotator cuff tears, (2) relief of painful arthritis associated with cuff tear arthropathy, (3) instauration after tumor resection, (4) pseudo paralysis because of irrecoverable rotator cuff tears (5) some fractures of the shoulder which reverse shoulder prostheses is only the option for treatment. This prosthesis resulting in relief of pain and decreasing the range of motion in above indications. However, this prosthesis and its applications such as notching of the scapula, dislocation of the prosthesis parts and acromial stress fractures. In this article the reverse shoulder prostheses, indication has been reviewed. This study can make clear aspect of reverse shoulder prosthesis that can help to find some solution in future.

Keywords: prostheses, complications, reverse shoulder prosthesis, indications

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Authors: Moohyun Lee, Soojung Hur, Yongwan Park

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In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

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Authors: Manuel Iretzberger

Abstract:

This paper aims to uncover the ideological aspects in the political thought of Carl Schmitt, who is enjoying an ever-increasing popularity in various academic fields, following in the wake of rising interest in questions of sovereignty and legitimacy. Given Schmitt’s biography, i.e. his role as the ‘Crown Jurist of the Third Reich’ (Gurian), an extraordinarily thorough examination is necessary; however, instead of merely ‘deconstructing’ his works, certain ontological truths he might have attained, shall be taken seriously. To this end, his notions of politics and the state of exception are scrutinized, which are indeed considered intriguing, yet prove to be enigmatic and impalpable at the core when read closely. In order to explain this conjuncture, both Schmitt’s philosophy of history and his ‘secret discussion’ (Agamben) with Walter Benjamin are depicted. As it turns out – it is argued – his concept of the Political has to be conceived of as embedded in a much broader context: In a post-transcendental, immanent age, he regards traditional modes of representation as no longer feasible and clings to authoritarianism as a surrogate – his Catholicism plays a decisive role here, forcing him to inject normatively biased assumptions into his political writings. Seeing Schmitt perform ‘rearguard action’ not only serves to disarm his work of most of its menacing aura, it also allows drawing conclusions about ways of legitimatizing democratic rule in modern times, as the paper tries to outline in its last section.

Keywords: Benjamin, history, immanence, Schmitt, sovereignty

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Authors: N. O. Muniz, F. A. Vechietti, L. Treccani, K. Rezwan, Luis Alberto dos Santos

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Developing new technologies in the manufacture of biomaterials is a major challenge for researchers in the tissue engineering area. Many in vitro and in vivo studies have revealed the significance of the porous structure of the biomaterials on the promotion of bone ingrowth. The use of Rapid Prototyping in the manufacture of ceramics in the biomedical area has increased in recent years and few studies are conducted on obtaining alumina pieces. The aim of this work was the study of alumina pieces obtained by 3D printing and uniaxial dry pressing (DP) in order to evaluate porosity achieved by this two different techniques. Also, the influence of the powder drying process was determined. The row alumina powders were drying by freeze drying and oven. Apparent porosity, apparent density, retraction after thermal treatment were evaluated. The porosity values obtained by DP, regardless of method of drying powders, were much lower than those obtained by RP as expected. And for the prototyped samples, the method of powder drying significantly influenced porosities, reached 48% for drying oven versus 65% for freeze-drying. Therefore, the method of 3D printing, using different powder drying, allows a better control over the porosity.

Keywords: rapid prototyping, freeze-drying, porosity, alumina

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Authors: Shazwanis Shukri

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The Mediterranean Sea, at the crossroads of three continents has always been the focus of pan-European and worldwide attention. Over the past decade, the Mediterranean Sea has become a hotbed for irregular migration particularly from the African continent toward the Europe. Among the major transit routes in the Mediterranean Sea include the Strait of Gibraltar, Canary Island and island of Lampedusa. In recent years, Mediterranean Sea has witnessed significant numbers of accidents and shipwrecks involving the irregular migrants and refugees trying to reach Europe via the sea. The shipwrecks and traffickers exploitation of migrants draw most of the attention particularly for the European Union (EU). This incident has been a wakeup call for the EU and become the top political agenda in the EU policy to tackle irregular migration and human smuggling at sea. EU has repeatedly addressed irregular migration as one of the threats the EU and its citizens may be confronted with and therefore immediate measures are crucial to tackle the crisis. In light of this, various initiatives have been adopted by the EU to strengthen external border control and restrict access to irregular migrants, notably through the enforcement of Frontex and Eunavfor Med. This paper analyses current development of counter-migration operations by the EU in response to migration crisis in the Mediterranean Sea. The analysis is threefold. First, this study examines the patterns and trends of irregular migration’s movements from recent perspective. Second, this study concentrates on the evolution of the EU operations that are in place in the Mediterranean Sea, notably by Frontex and Eunavfor Med to curb the influx of irregular migrants to the European countries, including, among others, Greece and Italy. Third, this study investigates the EU approaches to fight against the proliferation of human trafficking networks at sea. This study is essential to determine the roles of the EU in tackling migration crisis and human trafficking in the Mediterranean Sea and the effectiveness of their counter-migration operations to reduce the number of irregular migrants travelling via the sea. Elite interviews and document analysis were used as a methodology in this study. The study discovers that the EU operations have successfully contributed to reduce the numbers of irregular migrant’s arrival to Europe. The study also shows that the operations were effective to disrupt smugglers business models particularly from Libya. This study provides essential understanding about the roles of the EU not limited to tackle the migration crisis and disrupt trafficking networks, but also pledged to prevent further loss of lives at sea.

Keywords: European union, frontex, irregular migration, Mediterranean sea

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Authors: J. Andrade-Garda, A. Anguera, J. Ares-Casal, M. Hidalgo-Lorenzo, J.-A. Lara, D. Lizcano, S. Suárez-Garaboa

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In the current constantly changing economic context, collaborative networks allow partners to undertake projects that would not be possible if attempted by them individually. These projects usually involve the performance of a group of tasks (named roles) that have to be distributed among the partners. Thus, an allocation/matching problem arises that will be referred to as Role-Partner Allocation problem. In real life this situation is addressed by negotiation between partners in order to reach ad hoc agreements. Besides taking a long time and being hard work, both historical evidence and economic analysis show that such approach is not recommended. Instead, the allocation process should be automated by means of a centralized matching scheme. However, as a preliminary step to start the search for such a matching mechanism (or even the development of a new one), the problem and its core components must be specified. To this end, this paper establishes (i) the definition of the problem and its constraints, (ii) the key features of the involved elements (i.e., roles and partners); and (iii) how to create preference lists both for roles and partners. Only this way it will be possible to conduct subsequent methodological research on the solution method.     

Keywords: collaborative network, matching, partner, preference list, role

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Authors: Uwalomwa Uwuigbe, Olubukola Ranti Uwuigbe, Jinadu Olugbenga, Otekunrin Adegbola

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Corporate reporting has evolved over the years resulting from criticisms of the precedent by shareholders, stakeholders and other relevant financial institutions. Integrated reporting has become a globalized corporate reporting style, with its adoption around the world occurring rapidly to bring about an improvement in the quality of corporate reporting. While some countries have swiftly clinched into reporting in an integrated manner, others have not. In addition, there are ample research that has been conducted on the benefits of adopting integrated reporting, however, the same is not true in developing economies like Nigeria. Hence, this study basically examined the factors determining the adoption of integrated reporting in Nigeria. One hundred (100) copies of questionnaire was administered to financial managers of 20 selected listed companies in the Nigeria stock exchange market. The data obtained was analysed using the Spearman Rank Order Correlation via the Statistical Package for Social Science. This study observed that there is a significant relationship between the social pressures of isomorphic changes and integrated reporting adoption in Nigeria. The study recommends the need for an enforcement mechanism to be put in place while considering the adoption of integrated reporting in Nigeria, enforcement mechanisms should put into consideration the investors demand, the level of economic development, and the degree of corporate social responsibility.

Keywords: corporate social responsibility, isomorphic, integrated reporting, Nigeria, sustainability

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Authors: Mcjerry A. Bekoe, Emile Uwamahoro

Abstract:

Social media has become the order of the day, in particular among the youth. It is widely used both formally and informally in the university communities with varied definitions both in the academic circles and in the public domain. In simple terms, it is a media upon which social interactions are carried. In this work social media denote mobile phones, and web-base applications use by students and institutions to construct, partake, and distribute both existing and new information in a digital setting through internet communication. The basic aim of conducting this study was to analyze the perception of students and faculty members Beijing Normal University on social media use in the academic setting and to contribute to the understanding of how university students use social media, the advantages and disadvantages of social media in education. The study was qualitative and employed open-ended interview questions developed to seek students’ perception of the effects of social media and administered based on purposive sampling. Document analysis was also done because of triangulation to ensure validity and reliability. The results show there are positive and negative impacts of social media use depending on how one uses it. Social media have the capability to become a priceless asset to aid their educational communication.

Keywords: academics, high education, interactions, social media

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Authors: Ivana Bulog

Abstract:

Decision making is a vital part of the business world and any other field of human endeavor. Which way a business organization will take, and where that way will lead it, depends on broad range of decisions made by managers in the managerial structure. Strategic decisions are of the greatest importance for organizational success. Although much empirical research has been done trying to describe and explain its nature and effectiveness, knowledge about strategic decision making is still incomplete. This paper explores the nature of strategic decision making in particular setting - in Croatian companies. The main focus of this research is on the style that decision makers on strategic management level are following when making decisions of life importance for their companies. Two main decision making style that explain the way decision maker collects and processes available information and performs all the activities in strategic decision making process were empirical tested: rational and intuitive one. Besides analyzing their existence on strategic management level in Croatian companies, their effectiveness is analyzed as well. Results showed that decision makers at strategic management level are following both styles somewhat equally in order to function effectively, and that intuitive style is more effective when considering decisions outcomes.

Keywords: decision making style, decision making effectiveness, strategic decisions, management sciences

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