Search results for: information and communication technologies

Authors: Ratri Werdiningtyas, Yongping Wei, Andrew Western

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The status quo of social-ecological systems is the results of not only natural processes but also the accumulated consequence of policies applied in the past. Often water management objectives are challenging and are only achieved to a limited degree on the ground. In choosing water management approaches, it is important to account for current conditions and important differences due to varied histories. Since the mid-nineteenth century, Victorian water management has evolved through a series of policy regime shifts. The main goal of this research to explore and identify the stages of the evolution of the water policy instruments as practiced in Victoria from 1890-2016. This comparative historical analysis has identified four stages in Victorian policy instrument development. In the first stage, the creation of policy instruments aimed to match the demand and supply of the resource (reserve condition). The second stage begins after natural system alone failed to balance supply and demand. The focus of the policy instrument shifted to an authority perspective in this stage. Later, the increasing number of actors interested in water led to another change in policy instrument. The third stage focused on the significant role of information from different relevant actors. The fourth and current stage is the most advanced, in that it involved the creation of a policy instrument for synergizing the previous three focal factors: reserve, authority, and information. When considering policy in other jurisdiction, these findings suggest that a key priority should be to reflect on the jurisdictions current position among these four evolutionary stages and try to make improve progressively rather than directly adopting approaches from elsewhere without understanding the current position.

Keywords: policy instrument, policy transformation, socio-ecolgical system, water management

Procedia PDF Downloads 141

Authors: Kwadwo Yeboah

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Background and Aims: The adoption of International Accounting Standards (IAS) is considered to be one of the most significant developments in the accounting profession. The adoption of IAS aims to improve financial reporting quality by ensuring that financial information is transparent and comparable across borders. However, there is a lack of research on the impact of IAS on financial reporting quality in emerging economies. This study aims to fill this gap by evaluating the impact of IAS on financial reporting quality in emerging economies. Methods: This study uses a sample of firms from emerging economies that have adopted IAS. The sample includes firms from different sectors and industries. The financial reporting quality of these firms is measured using financial ratios, such as earnings quality, financial leverage, and liquidity. The data is analyzed using a regression model that controls for firm-specific factors, such as size and profitability. Results: The results show that the adoption of IAS has a positive impact on financial reporting quality in emerging economies. Specifically, firms that adopt IAS exhibit higher earnings quality and lower financial leverage compared to firms that do not adopt IAS. Additionally, the adoption of IAS has a positive impact on liquidity, suggesting that firms that adopt IAS have better access to financing. Conclusions: The findings of this study suggest that the adoption of IAS has a positive impact on financial reporting quality in emerging economies. The results indicate that IAS adoption can improve transparency and comparability of financial information, which can enhance the ability of investors to make informed investment decisions. The study contributes to the literature by providing evidence of the impact of IAS adoption in emerging economies. The findings of this study have implications for policymakers and regulators in emerging economies, as they can use this evidence to support the adoption of IAS and improve financial reporting quality in their respective countries.

Keywords: accounting, international, standards, finance

Procedia PDF Downloads 77

Authors: F. Q. Shao, W. Q. Wang, Y. Yin, T. P. Yu, D. B. Zou, J. M. Ouyang

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The Radiation Pressure Acceleration (RPA) mechanism is very promising in laser-driven ion acceleration because of high laser-ion energy conversion efficiency. Although some experiments have shown the characteristics of RPA, the energy of ions is quite limited. The ion energy obtained in experiments is only several MeV/u, which is much lower than theoretical prediction. One possible limiting factor is the transverse instability incited in the RPA process. The transverse instability is basically considered as the Rayleigh-Taylor (RT) instability, which is a kind of interfacial instability and occurs when a light fluid pushes against a heavy fluid. Multi-dimensional particle-in-cell (PIC) simulations show that the onset of transverse instability will destroy the acceleration process and broaden the energy spectrum of fast ions during the RPA dominant ion acceleration processes. The evidence of the RT instability driven by radiation pressure has been observed in a laser-foil interaction experiment in a typical RPA regime, and the dominant scale of RT instability is close to the laser wavelength. The development of transverse instability in the radiation-pressure-acceleration dominant laser-foil interaction is numerically examined by two-dimensional particle-in-cell simulations. When a laser interacts with a foil with modulated surface, the internal instability is quickly incited and it develops. The linear growth and saturation of the transverse instability are observed, and the growth rate is numerically diagnosed. In order to optimize interaction parameters, a method of information entropy is put forward to describe the chaotic degree of the transverse instability. With moderate modulation, the transverse instability shows a low chaotic degree and a quasi-monoenergetic proton beam is produced.

Keywords: information entropy, radiation pressure acceleration, Rayleigh-Taylor instability, transverse instability

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Authors: Bencherif Kada

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In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

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Authors: Sheetal Sharma

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Runoff,decreasing water levels and recharge in urban areas have been a complex issue now a days pointing defective urban design and increasing demography as cause. Very less has been discussed or analysed for water sensitive Urban Master Plans or local area plans. Land use planning deals with land transformation from natural areas into developed ones, which lead to changes in natural environment. Elaborated knowledge of relationship between the existing patterns of land use-land cover and recharge with respect to prevailing soil below is less as compared to speed of development. The parameters of incompatibility between urban functions and the functions of the natural environment are becoming various. Changes in land patterns due to built up, pavements, roads and similar land cover affects surface water flow seriously. It also changes permeability and absorption characteristics of the soil. Urban planners need to know natural processes along with modern means and best technologies available,as there is a huge gap between basic knowledge of natural processes and its requirement for balanced development planning leading to minimum impact on water recharge. The present paper analyzes the variations in land use land cover and their impacts on surface flows and sub-surface recharge in study area. The methodology adopted was to analyse the changes in land use and land cover using GIS and Civil 3d auto cad. The variations were used in  computer modeling using Storm-water Management Model to find out the runoff for various soil groups and resulting recharge observing water levels in POW data for last 40 years of the study area. Results were anlayzed again to find best correlations for sustainable recharge in urban areas.

Keywords: geology, runoff, urban planning, land use-land cover

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Authors: Halima Adel Halim Shnishah, David Mulvaney

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Applying traditional symmetric cryptography algorithms while computing encryption and decryption provides immunity to secret keys against different attacks. One of the popular techniques generating automated secret keys is evolutionary computing by using Eureqa API tool, which got attention in 2013. In this paper, we are generating automated secret keys for image encryption and decryption using Eureqa API (tool which is used in evolutionary computing technique). Eureqa API models pseudo-random input data obtained from a suitable source to generate secret keys. The validation of generated secret keys is investigated by performing various statistical tests (histogram, chi-square, correlation of two adjacent pixels, correlation between original and encrypted images, entropy and key sensitivity). Experimental results obtained from methods including histogram analysis, correlation coefficient, entropy and key sensitivity, show that the proposed image encryption algorithms are secure and reliable, with the potential to be adapted for secure image communication applications.

Keywords: image encryption algorithms, Eureqa, statistical measurements, automated key generation

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Authors: Chandan Deep Singh

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In present days, companies are facing the rapid competition in terms of customer requirements to be satisfied, new technologies to be integrated into future products, new safety regulations to be followed, new computer-based tools to be introduced into design activities that becomes more scientific. In today’s highly competitive market, survival focuses on various factors such as quality, innovation, adherence to standards, and rapid response as the basis for competitive advantage. For competitive advantage, companies have to produce various competencies: for improving the capability of suppliers and for strengthening the process of integrating technology. For more competitiveness, organizations should operate in a strategy driven way and have a strategic architecture for developing core competencies. Traditional ways to take such experience and develop competencies tend to take a lot of time and they are expensive. A new learning environment, which is built around a gaming engine, supports the development of competences in specific subject areas. Technology competencies have a significant role in firm innovation and competitiveness; they interact with the competitive environment. Technological competencies vary according to the type of competitive environment, thus enhancing firm innovativeness. Technological competency is gained through extensive experimentation and learning in its research, development and employment in manufacturing. This is a review paper based on competency and strategic success of automobile industry. The aim here is to study strategy formulation and competency tools in the industry. This work is a review of literature related to competency and strategy in automobile industry. This study involves review of 34 papers related to competency and strategy.

Keywords: manufacturing competency, strategic success, competitiveness, strategy formulation

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Authors: Svetlana Gudkova

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The Internet of Things experiences a rapid growth bringing inevitable changes into many spheres of human activities. As the Internet has changed the social and business landscape, IoT as its extension, can bring much more profound changes in economic value creation and competitiveness of the economies. It has been already recognized as the next industrial revolution. However, the development of IoT is in a great extent stimulated by the entrepreneurial activity. To expand and reach its full potential it requires proactive entrepreneurs, who explore the potential and create innovative ideas pushing the boundaries of IoT technologies' application further. The goal of the research is to analyze, how entrepreneurs utilize the opportunities created by IoT and how do they stimulate the development of IoT through discovering of new ways of generating economic value and creating opportunities, which attract other entrepreneurs. The qualitative research methods have been applied to prepare the case studies. Entrepreneurs are recognized as an engine of economic growth. They introduce innovative products and services into the market through the creation of a new combination of the existing resources and utilizing new knowledge. Entrepreneurs not only create economic value but what is more important, they challenge the existing business models and invent new ways of value creation. Through identification and exploitation of entrepreneurial opportunities, they create new opportunities for other entrepreneurs. It makes the industry more attractive to other profit/innovation-driven start-ups. IoT creates numerous opportunities for entrepreneurs in the different industries. Smart cities, healthcare, manufacturing, retail, agriculture, smart vehicles and smart buildings benefit a lot from IoT-based breakthrough innovations introduced by entrepreneurs. They reinvented successfully the business models and created new entrepreneurial opportunities for other start-ups to introduce next innovations.

Keywords: entrepreneurship, internet of things, breakthrough innovations, start-ups

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Authors: Tarnveer Kaur

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Amino acids, as fundamental structural units of peptides and proteins, have an important role in biological systems by affecting solubility, denaturation, and activity of biomolecules. A study of these effects on thermophysical properties of model compounds in the presence of electrolytes solutions provides information about solute-solvent and solute-solute interactions on biomolecules. Ionic liquids (ILs) as organic electrolytes and green solvents are composed of an organic cation and an inorganic anion, which are liquid at ambient conditions. In the past decade, extensive investigations showed that the use of ILs as reaction media for processes involving biologically relevant compounds is promising in view of their successful application in kinetic resolution, biocatalysis, biosynthesis, separation, and purification processes. The scope of this information is valuable to explore the interactions of amino acids in ILs. To reach this purpose, apparent molar volumes of glycine/L-alanine in aqueous solutions of 1-butyl-3-methylimidazolium bromide/chloride were determined from precise density measurements at temperatures T = (288.15-318.15) K and at atmospheric pressure. Positive values for all the studied amino acids indicate the dominance of hydrophilic-ionic interactions between amino acids and Ionic liquids. The effect of temperature on volumetric properties of glycine/L-alanine in solutions has been determined from the partial molar expansibility and second-order partial molar expansibility. Further, volumetric interaction parameters and hydration number have been calculated, which have been interpreted in terms of possible solute-solvent interactions.

Keywords: ILs, amino acids, volumetric properties, hydration numbers

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Authors: Lovemore Motsi

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The rapid pace of technological innovation, along with a global fascination with the internet, continues to result in a dominating call to integrate internet technologies in institutions of learning. However, the pressing question remains – how can online in-service training for teachers, support quality and success in professional development programmers. The aim of this study was to examine an integrated model that extended the Unified Theory of Acceptance and Use of Technology (UTAUT) with additional constructs – including attitude and behaviour intention – adopted from the Theory of Planned Behaviour (TPB) to answer the question. Data was collected from secondary school teachers at 10 selected schools in the Tshwane South district by means of the Statistical Package for Social Scientists (SPSS v 23.0), and the collected data was analysed quantitatively. The findings are congruent with model testing under conditions of volitional usage behaviour. In this regard, the role of facilitating condition variables is insignificant as a determinant of usage behaviour. Social norm variables also proved to be a weak determinant of behavioural intentions. Findings demonstrate that effort expectancy is the key determinant of online INSET usage. Based on these findings, the variable social influence and facilitating conditions are important factors in ensuring the acceptance of online INSET among teachers in selected secondary schools in the Tshwane South district.

Keywords: unified theory of acceptance and use of technology (UTAUT), teacher professional development, secondary schools, online INSET

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Authors: Erwan Negre, Ewan J. O'Connor, Juha Toivonen

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The need for CO2 monitoring technologies grows simultaneously with the worldwide concerns regarding environmental challenges. To that purpose, we developed a compact coherent all-fiber ranged-resolved Differential Absorption Lidar (RR-DIAL). It has been designed along a tunable 2x1fiber optic switch set to a frequency of 1 Hz between two Distributed FeedBack (DFB) lasers emitting in the continuous-wave mode at 1571.41 nm (absorption line of CO2) and 1571.25 nm (CO2 absorption-free line), with linewidth and tuning range of respectively 1 MHz and 3 nm over operating wavelength. A three stages amplification through Erbium and Erbium-Ytterbium doped fibers coupled to a Radio Frequency (RF) driven Acousto-Optic Modulator (AOM) generates 100 ns pulses at a repetition rate from 10 to 30 kHz with a peak power up to 2.5 kW and a spatial resolution of 15 m, allowing fast and highly resolved CO2 profiles. The same afocal collection system is used for the output of the laser source and the backscattered light which is then directed to a circulator before being mixed with the local oscillator for heterodyne detection. Packaged in an easily transportable box which also includes a server and a Field Programmable Gate Array (FPGA) card for on-line data processing and storing, our setup allows an effective and quick deployment for versatile in-situ analysis, whether it be vertical atmospheric monitoring, large field mapping or sequestration site continuous oversight. Setup operation and results from initial field measurements will be discussed.

Keywords: CO2 profiles, coherent DIAL, in-situ atmospheric sensing, near infrared fiber source

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Authors: Ivana Cabarkapa, Zorica Tomicic, Olivera Duragic

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Antimicrobial resistance represents one of the major challenges facing humanity in the last decades. Increasing antibiotic-resistant pathogens indicates the need for the development of alternative antibacterial drugs and new treatment strategies. One of the innovative emerging treatments in overcoming multidrug-resistant pathogens certainly represents the inhibition anti-quorum sensing system. For most of the food-borne pathogens, the expression of the virulence depends on their capability communication with other members of the population by means of quorum sensing (QS). QS represents a specific way of bacterial intercellular communication, which enabled owing to their ability to detect and to respond to cell population density by gene regulation. QS mechanisms are responsible for controls the pathogenesis, virulence luminescence, motility, sporulation and biofilm formation of many organisms by regulating gene expression. Therefore, research in this field is being an attractive target for the development of new natural antibacterial agents. Anti-QS compounds are known to have the ability to prohibit bacterial pathogenicity. Considering the importance of quorum sensing during bacterial pathogenesis, this research has been focused on evaluation anti - QS properties of four essential oils (EOs) Origanum heracleoticum, Origanum vulgare, Thymus vulgare, and Thymus serpyllum, using biomonitor strain of Chromobacterium violaceum CV026. Tests conducted on Luria Bertani agar supplemented with N hexanol DL homoserine lacton (HHL) 10µl/50ml of agar. The anti-QS potential of the EOs was assayed in a range of concentrations of 200 – 0.39 µl/ml using the disc diffusion method. EOs of Th. vulgaris and T. serpyllum were exhibited anti-QS activity indicated by a non- pigmented ring with a dilution-dependent manner. The lowest dilution of EOs T. vulgaris and T. serpyllum in which they exhibited visually detectable inhibition of violacein synthesis was 6.25 µl/ml for both tested EOs. EOs of O. heracleoticum and O. vulgare were displayed different active principles, i.e., antimicrobial activity indicated by the inner clear ring and anti-QS activity indicated by the outer non-pigmented ring, in a concentration-dependent manner. The lowest dilution of EOs of O. heracleoticum and O. vulgare in which exhibited visually detectable inhibition of violacein synthesis was 1.56 and 3.25 µl/ml, respectively. Considering that, the main constituents of the tested EOs represented by monoterpenes (carvacrol, thymol, γ-terpinene, and p-cymene), anti - QS properties of tested EOs can be mainly attributed to their activity. In particular, from the scientific literature, carvacrol and thymol show a sub-inhibitory effect against foodborne pathogens. Previous studies indicated that sub-lethal concentrations of carvacrol reduced the mobility of bacteria due to the ability of interference using QS mechanism between the bacterial cells, and thereby reducing the ability of biofilm formation The precise mechanism by which carvacrol inhibits biofilm formation is still not fully understood. Our results indicated that EOs displayed different active principles, i.e., antimicrobial activity indicated by the inner clear ring and anti-QS activity indicated by an outer non- pigmented ring with visually detectable inhibition of violacein. Preliminary results suggest that EOs represent a promising alternative for effective control of the emergence and spread of resistant pathogens.

Keywords: anti-quorum sensing activity, Chromobacterium violaceum, essential oils, violacein

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Anees Raza, Liu Chunyan

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Renewable energy technologies are need of the time and are already making the big impact in the climatic outlook of the world. Biogas technology is one of those, and it has a lot of benefits for its users. It is cost effective because it is produced from the raw material which is available free of cost to the livestock farmers. Bio-slurry, a by-product of biogas, is being used as fertilizer for the crops production and increasing soil fertility. There are many other household benefits of technology. Research paper discusses the benefits of biogas as perceived by the biogas users as well as non-users of Tehsil Jhang. Data were collected from 60 respondents (30 users and 30 non-users) selected purposively through validated and pre-tested interview schedule from the respondents. Collected data were analyzed by using Statistical Package for Social Sciences (SPSS). Household benefits like ‘makes cooking easy,’ ‘Less breathing issues for working women in kitchens’ and ‘Use of bio-slurry as organic fertilizer’ had the highly significant relationship between them with t-values of 3.24, 4.39 and 2.80 respectively. Responses of the respondents about environmental benefits of biogas technology showed that ‘less air pollution’ had a significant relationship between them while ‘less temperature rise up than due to the burning of wood /dung’ had the non-significant relationship in the responses of interviewed respondents. It was clear from the research that biogas users were becoming influential in convincing non-users to adopt this technology due to its noticeable benefits. Research area where people were depending on wood to be used as fire fuel could be helped in reduction of cutting of trees which will help in controlling deforestation and saving the environment.People should be encouraged in using of biogas technology through providing them subsidies and low mark up loans.

Keywords: biogas technology, deforestation, environmental benefits, renewable energy

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Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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Authors: Tamar Khardziani, Violeta Berikashvili, Amrosi Chkuaseli, Vladimir Elisashvili

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The main objectives of this proposal are to develop low-cost, innovative, and competitive technologies for the production of mycelial biomass of medicinal mushrooms as a natural food supplement for poultry. To fulfill this task, industrial strains of Lentinus edodes, Ganoderma lucidum, and Pleurotus ostreatus were used in this study. The solid-state fermentation (SSF) of wheat grains, wheat bran, and soy flour was performed in flasks and bags. Among nine mushroom strains, P. ostreatus 2191 appeared to be the most productive in protein biomass accumulation in the SSF of wheat bran. All mushrooms produced exopolysaccharide with the highest yield of 5-8 mg/mL depending on fungal strain and growth substrate. Supplementation of medium with 1% glycerol and 2-4% peptone favored mushroom growth and protein accumulation. Among inorganic nitrogen sources, KNO₃ also provided high biomass and protein production. The SSF of all growth substrates was accompanied by the secretion of cellulase and xylanase activities. The highest CMCase activity (12-13 U/g) was revealed in the cultivation of P. ostreatus 2191 using wheat bran as a growth substrate and ammonium sulfate or yeast extract as a nitrogen source, whereas the highest xylanase activity was detected in the fermentation of soy flour supplemented with peptone. Acknowledgments: This work was supported by the Shota Rustaveli National Science Foundation of Georgia (Grant number STEM-22-2077).

Keywords: mushrooms, plant raw materials, fermentation, biomass protein, cellulase

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Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: Tommi Mahlamaki, Mika Ojala

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Digitalization is changing our lives in many ways. As consumers, we are accustomed using different online interactive sales systems. However, while many online selling sites offer systems that have evolved from simple selling functions, the change has not been as rapid in business-to-business (B2B) markets. This is because many B2B companies rely on personal sales and personal communication. The main objective of this research is to clarify perceptions towards digital interactive sales systems and, more specifically, sales configurators. It also aims to identify trends towards the use of sales configurators. To reach these objectives, an online questionnaire was created that targets Finnish B2B distributors who are, by definition, part of B2B markets. The questionnaire was sent to 340 distributors, and it was returned by 150 respondents. The results showed that 82% of respondents had heard about sales configurators, and 64% had used them. The results also showed that 48% of respondents felt that the use of sales configurators would increase in the future, while only 2% felt they would be used less. The future use of sales configurators was not seen as affecting the level of personal sales. In light of the results, we recommend that B2B companies create marketing strategies that integrate and complement traditional sales processes with digital interactive systems.

Keywords: digitalization, interactive systems, marketing, sales process

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Authors: Mohd Said Nurumal, Sarah Sheikh Abdul Karim

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Information regarding out of hospital cardiac arrest incidence include outcome in Malaysia is limited and fragmented. This study aims to identify incidence and adherence to protocol of out of hospital cardiac arrest and also to explore the issues faced by the pre-hospital personnel in regards managing cardiac arrest victim in Kuala Lumpur, Malaysia. A mixed method approach combining the qualitative and quantitative study design was used. The 285 pre-hospital care data sheet of out of hospital cardiac arrest during the year of 2011 were examined by using checklists for identify the incidence and adherence to protocol. Nine semi-structured interviews and two focus group discussions were performed. For the incidence based on the overall out of hospital cardiac arrest cases that occurred in 2011 (n=285), the survival rates were 16.8%. For adherence to protocol, only 89 (41.8%) of the cases adhered to the given protocol and 124 did not adhere to such protocol. The qualitative information provided insight about the issues related to out of hospital cardiac arrest in every aspect. All the relevant qualitative data were merged into few categories relating issues that could affect the management of out of hospital cardiac arrest performed by pre-hospital care team. One of the essential elements in the out of hospital cardiac arrest handling by pre-hospital care is to ensure increase of survival rates and excellent outcomes by adhering to given protocols based on international standard benchmarks. Measures are needed to strengthen the quick activation of the pre-hospital care service, prompt bystander cardiopulmonary resuscitation, early defibrillation and timely advanced cardiac life support and also to tackle all the issues highlighted in qualitative results.

Keywords: pre-hospital care, out of hospital cardiac arrest, incidence, protocol, mixed method research

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Authors: Adel Ahmadi Hosseini, Fatemeh Tavanaei, Alessandro Navarra, Ferri Hassani

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Mining engineering, as a part of geoscience, must address modern concerns. Traditional mining methods incorporate drill and blast technologies, which are followed by different issues, including excessive noise, vibration, air pollution, and safety hazards. Over the past two decades, mining engineers have sought alternative solutions to move from drill and blast to continuous methods to prevent such issues and improve sustainability in mining. Among the suggested methods, microwave treatment has shown promising results by creating micro/macro cracks in the rock structure prior to the operations. This research utilizes an energy-based analysis methodology to evaluate the efficiency of the microwave treatment in improving mining operations. The data analysis shows that increasing the input microwave energy dosage intensifies the rock damage. However, this approach can decrease the energy efficiency of the method by more than 50% in some cases. In this study, rock samples were treated with three power levels (3 kW, 7 kW, and 12 kW) and two energy dosages (20 kWh/t and 50 kWh/t), resulting in six conditions. To evaluate the impact of microwave treatment on the geomechanical behavior of the rocks, Unconfined Compressive Strength (UCS) tests were conducted on the microwave-treated samples, yielding stress-strain curves. Using the stress-strain curves, the effect of the different powers and energy dosages of microwaves are discussed. This research shows the potential of using microwave treatment to lead the industry to more sustainable mining.

Keywords: microwave treatment, microwave energy dosage, sustainable mining, rock fragmentation

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Authors: Waheeda Jabbar, Ali Gul, Rida Noor, Sania Kurd, Saba Gulzar

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Hundreds of miners die from mining accidents each year due to poisonous gases found underground mining areas. This paper proposed an idea to protect the precious lives of mining workers. A supervising system is designed which is based on ZigBee wireless technique along with the smart protective helmets to detect real-time surveillance and it gives early warnings on presence of different poisonous gases in order to save mineworkers from any danger caused by these poisonous gases. A wireless sensor network is established using ZigBee wireless technique by integrating sensors on the helmet, apart from this helmet have embedded heartbeat sensor to detect the pulse rate and be aware of the physical or mental strength of a mineworker to increase the potential safety. Radio frequency identification (RFID) technology is used to find the location of workers. A ZigBee based base station is set-upped to control the communication. The idea is implemented and results are verified through experiment.

Keywords: Arduino, gas sensor (MQ7), RFID, wireless ZigBee

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Authors: Bencherif Kada

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In forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects, and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction and area of an object, etc.) and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants and bare soils. Texture attributes seem to provide no useful information while spatial attributes of shape, compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, biodiversity, shrublands

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Authors: Farbod Behnaminia, Saeed Samet

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The COVID-19 pandemic has paralyzed many lives until a vaccine was available, which caused the so-called “new normal.” According to the World Health Organization (WHO), COVID-19 is an infectious disease. It can cause significant illness or death in anyone. Governments and health officials tried to impose rules and regulations to avoid and slow down transmission. Therefore, software engineers worldwide developed applications to trace and track patients’ movements and notify others, mainly using Bluetooth. In this way, everyone could be informed whether they come in close contact with someone who has COVID-19 and takes proper safety precautions. Because most of the applications use technologies that can potentially reveal the user’s identity and location, researchers have debated privacy preservation and how to improve user privacy during such pandemics. Thanks to Distributed Ledger Technology (DLT), there have been some proposed methods to develop privacy-preserving Patient Tracking Systems in the last two years. As an instance of the DLT, Blockchain is like a decentralized peer-to-peer database that maintains a record of transactions. Transactions are immutable, transparent, and anonymous in this system. We conducted a comprehensive evaluation of the literature by looking for papers in the relevant field and dividing them into pre- and post-pandemic systems. Additionally, we discussed the many uses of blockchain technology in pandemic control. We found that two major obstacles facing blockchain implementation across many healthcare systems are scalability and privacy. The Polkadot platform is presented, along with a review of its efficacy in tackling current concerns. A more scalable healthcare system is achievable in the near future using Polkadot as well as a much more privacy-preserving environment.

Keywords: blockchain, electronic record management, EHR, privacy-preserving, patient tracking, COVID-19, trust and confidence, Polkadot

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Authors: Vida Dones-Jimenez

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The main purpose of this study is to determine the preschool teachers’ technology and 21st-century skills and its relation to teachers’ performance. The participants were 94 preschool teachers and 59 school administrators from the CDAPS member schools. The data were collected by using 21st Century Skill, developed by ISSA (2009), Technology Skills of Teachers Survey (2013) and Teacher Performance Evaluation Criteria and Descriptors (200) was modified by the current researcher to suit the needs of her study and was administered personally by her. The surveys were designed to measure the participants’ 21st-century skills, technology skills and teaching performance. The result of the study indicates that the majority of the preschool teachers are the college graduate. Most of them are in the teaching profession for 0 to 10 years. It also indicated that the majority of the school administrators are masters’ degree holder. The preschool teachers are outstanding in their teaching performance as rated by the school administrators. The preschool teachers are skillful in using technology, and they are very skillful in executing the 21st-century skills in teaching. It was further determined that no significant difference between preschool teachers 21st-century skill in regards to educational attainment same as with the number of years in teaching, likewise with their technology skills. Furthermore, the study has shown that there is a very weak relationship between technology and 21st-century skills of preschool teachers, a weak relationship between technology skills and teaching performance and a very weak relationship between 21st-century skills and teaching performance were also established. The study recommends that the preschool teachers should be encouraged to enroll in master degree programs. School administrators should support the implementation of newly adopted technologies and support faculty members at various levels of use and experience. It is also recommended that regular review of the professional development plan be undertaken to upgrade 21st-century teaching and learning skills of preschool teachers.

Keywords: preschool teacher, teaching performance, technology, 21st century skills

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Authors: Wenbo Wang, Yi-Fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state-of-the-art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study introduces a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive, and authoritative data; 2) developing a search function to automatically select relevant, new, and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graphs in Wikidata to dynamically augment the representations of claims and references without introducing too much noise, II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: fact checking, claim verification, deep learning, natural language processing

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Authors: Kazuaki Shiraishi, Narumitsu Asai, Tsukasa Kitahara, Sosuke Mieno, Takaharu Kameoka

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The purpose of this research is to facilitate productivity advances in agriculture. To accomplish this, we developed an automatic three-dimensional (3D) recording system for growth of field crops that consists of a number of inexpensive modules: a very low-cost stereo camera, a couple of ZigBee wireless modules, a Raspberry Pi single-board computer, and a third generation (3G) wireless communication module. Our system uses an inexpensive Web stereo camera in order to keep total costs low. However, inexpensive video cameras record low-resolution images that are very noisy. Accordingly, in order to resolve these problems, we adopted a deep learning method. Based on the results of extended period of time operation test conducted without the use of an external power supply, we found that by using Super-Resolution Convolutional Neural Network method, our system could achieve a balance between the competing goals of low-cost and superior performance. Our experimental results showed the effectiveness of our system.

Keywords: 3D plant data, automatic recording, stereo camera, deep learning, image processing

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Authors: Komal Fizza

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Irrational and non-judicious use of antibiotics pave the way for an upsurge in antibiotic resistance, diminished effectiveness of different therapeutic regimens and as well as impounding effect on disease management leading to further morbidities. In the backdrop of this the current research is aimed to assess whether antimicrobial prescribing is in accordance with the Infectious Disease Society of America Guidelines in hospitalized patients at Shifa International Hospital, Islamabad, Pakistan. Shifa International Hospital, Islamabad is a 500 bed hospital. With the help of MIS team a form wad developed that gave the information about medical records number, name of the patient, day of start of antibiotic, the day antibiotic is supposed to be stopped and as well as the diagnosis of the patient. A ward pharmacist was employed to generate this report on a daily basis. The therapeutic regiment was reviewed by the pharmacist by monitoring the clinical progress, laboratory report and diagnosis. On the basis of this information, pharmacist made suggestions and forwarded to the hospital doctors responsible for prescribing antibiotics. If desired, changes were made regularly. In the current research our main focus was to implement this action and therefore, started monitoring patients who were on antibiotic regimens for more than 10-15 days. We took this initiative since November, 2013. At the start of the program a maximum 19 patients/day were reported to be on antibiotic regimen for more than 10-15 days. After the implementation of the initiative, the number of patients was decreased to fifteen patients per day in December, further decreased to 7 in the month of January and 9 and 6 in February and March respectively. The average patient census was 350. The current pilot study highlighted the role of pharmacist in initiating antibiotic stewardship programs in hospital settings.

Keywords: stewardship, antibiotics, resistance, clinical process

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Authors: Brahim Bellali, Fatima Bellali

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The integration of information technology systems (ITS) into a company's human resources processes seems to be the appropriate solution to the problem of evolving and adapting its human resources management practices in order to be both more strategic and more efficient in terms of costs and service quality. In this context, the aim of this work is to study the impact of information technology systems (ITS) on the recruitment process. In this study, we targeted candidates who had recruited using IT tools. The target population consists of 34 candidates based in Casablanca, Morocco. In order to collect the data, a questionnaire had to be drawn up. The survey is based on a data sheet and a questionnaire that is divided into several sections to make it more structured and comprehensible. The results show that the majority of respondents say that companies are making greater use of online CV libraries and social networks as digital solutions during the recruitment process. The results also show that 50% of candidates say that the use of digital tools by companies would not slow them down when applying for a job and that these IT tools improve manual recruitment processes, while 44.1% think that they facilitate recruitment without any human intervention. The majority of respondents (52.9%) think that social networks are the digital solutions most often used by recruiters in the sourcing phase. The constraints of digital recruitment encountered are the dehumanization of human resources (44.1%) and the limited interaction during remote interviews (44.1%), which leaves no room for informal exchanges. Digital recruitment can be a highly effective strategy for finding qualified candidates in a variety of fields. Here are a few recommendations for optimizing your digital recruitment process: (1) Use online recruitment platforms: LinkedIn, Twitter, and Facebook ; (2) Use applicant tracking systems (ATS) ; (3) Develop a content marketing strategy.

Keywords: IT systems, recruitment, challenges, constraints

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Authors: Sirilak Areerachakul, Nat Ployong, Supayothin Na Songkla

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This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

Keywords: artificial neural network, classification, students, e-learning

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Authors: Rusudan Kinkladze, Guguli Kurashvili, Ketevan Chitaladze

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Foreign direct investment is a driving force in the development of the interdependent national economies, and the study and analysis of investments is an urgent problem. It is particularly important for transitional economies, such as Georgia, and the study and analysis of investments is an urgent problem. Consequently, the goal of the research is the study and analysis of direct foreign investments in Georgia, and identification and forecasting of modern trends, and covers the period of 2006-2015. The study uses the methods of statistical observation, grouping and analysis, the methods of analytical indicators of time series, trend identification and the predicted values are calculated, as well as various literary and Internet sources relevant to the research. The findings showed that modern investment policy In Georgia is favorable for domestic as well as foreign investors. Georgia is still a net importer of investments. In 2015, the top 10 investing countries was led by Azerbaijan, United Kingdom and Netherlands, and the largest share of FDIs were allocated in the transport and communication sector; the financial sector was the second, followed by the health and social work sector, and the same trend will continue in the future. 

Keywords: foreign direct investments, methods, statistics, analysis

Procedia PDF Downloads 326