Search results for: gaussian selection operator

Authors: Kabil Boukhari

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In the context of information retrieval, the selection of the most relevant words is a very important step. In fact, the text cleaning allows keeping only the most representative words for a better use. In this paper, we propose a library for the purpose text preprocessing within an implemented application to facilitate this task. This study has two purposes. The first, is to present the related work of the various steps involved in text preprocessing, presenting the segmentation, stemming and lemmatization algorithms that could be efficient in the rest of study. The second, is to implement a developed tool for text preprocessing in French and English. This library accepts unstructured text as input and provides the preprocessed text as output, based on a set of rules and on a base of stop words for both languages. The proposed library has been made on different corpora and gave an interesting result.

Keywords: text preprocessing, segmentation, knowledge extraction, normalization, text generation, information retrieval

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Authors: Viola Hubačová Pirová

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The assessment of psychomotor development allows us to identify children with motor delays, helps us to monitor progress in time and prepare suitable intervention programs. The foundation of psychomotor development lies in pre-school age and is crucial for child´s further cognitive and social development. Many assessment tools of psychomotor development have been developed over the years. Some of them are easy screening tools; others are more complex and sophisticated. The purpose of this review is to describe the history of psychomotor assessment, specify preschool children´s psychomotor evaluation and review eight psychomotor development assessment tools for preschool children (Denver II., DEMOST-PRE, TGMD -2/3, BOT-2, MABC-2, PDMS-2, KTK, MOT 4-6). The selection of test depends on purpose and context in which is the assessment planned.

Keywords: assessment of psychomotor development, preschool children, psychomotor development, review of assessment tools

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Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

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Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

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Authors: Rabbia Tariq, Hannan Sajjad, Mehreen Sirshar

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Design patterns are widely used to make the process of development easier as they greatly help the developers to develop the software. Different design patterns have been introduced till now but the behavior of same design pattern may differ in different domains that can lead to the wrong selection of the design pattern. The paper aims to discover the design patterns that suits best with respect to their domain thereby helping the developers to choose an effective design pattern. It presents the comprehensive analysis of design patterns based on different methodologies that include simulation, case study and comparison of various algorithms. Due to the difference of the domain the methodology used in one domain may be inapplicable to the other domain. The paper draws a conclusion based on strength and limitation of each design pattern in their respective domain.

Keywords: design patterns, evaluation, quality assurance, software domains

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Authors: Iman A. Saad, Loay E. George

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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

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Authors: Steven D. P Moore

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A novel method referred to asKýklos(Ky) dimensional geometry is proposed as an entity specific core geometric dimensional measurement system. Ky geometric measures can constructscaled multi-dimensionalmodels using regular and irregular sets in IRn. This entity specific-derived geometric measurement system shares similar fractal methods in which a ‘fractal transformation operator’ is applied to a set S to produce a union of N copies. The Kýklos’ inputs use 1D geometry as a core measure. One-dimensional inputs include the radius interval of a circle/sphere or the semiminor/semimajor axes intervals of an ellipse or spheroid. These geometric inputs have finite values that can be measured by SI distance units. The outputs for each interval are divided and subdivided 1D subcomponents with a union equal to the interval geometry/length. Setting a limit of subdivision iterations creates a finite value for each 1Dsubcomponent. The uniqueness of this method is captured by allowing the simplest 1D inputs to define entity specific subclass geometric core measurements that can also be used to derive length measures. Current methodologies for celestial based measurement of time, as defined within SI units, fits within this methodology, thus combining spatial and temporal features into geometric core measures. The novel Ky method discussed here offers geometric measures to construct scaled multi-dimensional structures, even models. Ky classes proposed for consideration include celestial even subatomic. The application of this offers incredible possibilities, for example, geometric architecture that can represent scaled celestial models that incorporates planets (spheroids) and celestial motion (elliptical orbits).

Keywords: Kyklos, geometry, measurement, celestial, dimension

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Authors: Rishabh Sharma

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The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system

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Authors: Kamalpreet Kaur, Harjit Pal Singh, Vikas Khullar

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In Wireless Sensor Network (WSN), the main limitation is generally inimitable energy consumption during processing of the sensor nodes. Cluster head (CH) election is one of the main issues that can reduce the energy consumption. Therefore, discovering energy saving routing protocol is the focused area for research. In this paper, fuzzy-based energy aware routing protocol is presented, which enhances the stability and network lifetime of the network. Fuzzy logic ensures the well-organized selection of CH by taking four linguistic variables that are concentration, energy, centrality, and distance to base station (BS). The results show that the proposed protocol shows better results in requisites of stability and throughput of the network.

Keywords: ERA, fuzzy logic, network model, WSN

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Authors: Semra Sirin Kiris

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Nonlinear dynamic analysis is permitted to be used for structures without any restrictions. The important issue is the selection of the design earthquake to conduct the analyses since quite different response may be obtained using ground motion records at the same general area even resulting from the same earthquake. In seismic design codes, the method requires scaling earthquake records based on site response spectrum to a specified hazard level. Many researches have indicated that this limitation about selection can cause a large scatter in response and other charecteristics of ground motion obtained in different manner may demonstrate better correlation with peak seismic response. For this reason influence of eleven different ground motion parameters on the peak displacement of reinforced concrete systems is examined in this paper. From conducting 7020 nonlinear time history analyses for single degree of freedom systems, the most effective earthquake parameters are given for the range of the initial periods and strength ratios of the structures. In this study, a hysteresis model for reinforced concrete called Q-hyst is used not taken into account strength and stiffness degradation. The post-yielding to elastic stiffness ratio is considered as 0.15. The range of initial period, T is from 0.1s to 0.9s with 0.1s time interval and three different strength ratios for structures are used. The magnitude of 260 earthquake records selected is higher than earthquake magnitude, M=6. The earthquake parameters related to the energy content, duration or peak values of ground motion records are PGA(Peak Ground Acceleration), PGV (Peak Ground Velocity), PGD (Peak Ground Displacement), MIV (Maximum Increamental Velocity), EPA(Effective Peak Acceleration), EPV (Effective Peak Velocity), teff (Effective Duration), A95 (Arias Intensity-based Parameter), SPGA (Significant Peak Ground Acceleration), ID (Damage Factor) and Sa (Spectral Response Spectrum).Observing the correlation coefficients between the ground motion parameters and the peak displacement of structures, different earthquake parameters play role in peak displacement demand related to the ranges formed by the different periods and the strength ratio of a reinforced concrete systems. The influence of the Sa tends to decrease for the high values of strength ratio and T=0.3s-0.6s. The ID and PGD is not evaluated as a measure of earthquake effect since high correlation with displacement demand is not observed. The influence of the A95 is high for T=0.1 but low related to the higher values of T and strength ratio. The correlation of PGA, EPA and SPGA shows the highest correlation for T=0.1s but their effectiveness decreases with high T. Considering all range of structural parameters, the MIV is the most effective parameter.

Keywords: earthquake parameters, earthquake resistant design, nonlinear analysis, reinforced concrete

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Authors: Agostinho Antunes

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The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: comparative genomics, adaptive evolution, bioinformatics, phylogenetics, genome mining

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Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: S. Ghasemi, K. Khorasani

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In this paper, the problem of fault detection and isolation in the attitude control subsystem of spacecraft formation flying is considered. In order to design the fault detection method, an extended Kalman filter is utilized which is a nonlinear stochastic state estimation method. Three fault detection architectures, namely, centralized, decentralized, and semi-decentralized are designed based on the extended Kalman filters. Moreover, the residual generation and threshold selection techniques are proposed for these architectures.

Keywords: component, formation flight of satellites, extended Kalman filter, fault detection and isolation, actuator fault

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Authors: Mojtaba Ghodsi, Hamidreza Ziaifar, Morteza Mohammadzaheri, Payam Soltani

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In this paper, the performance of a medium power (25 kW/25 kHz) hybrid inverter with a reactive transformer is investigated. To analyze the sensitivity of the inverster, the RSM technique is employed to manifest the effective factors in the inverter to minimize current passing through the Insulated Bipolar Gate Transistors (IGBTs) (current stress). It is revealed that the ratio of the axillary inductor to the effective inductance of resonant inverter (N), is the most effective parameter to minimize the current stress in this type of inverter. In practice, proper selection of N mitigates the current stress over IGBTs by five times. This reduction is very helpful to keep the IGBTs at normal temperatures.

Keywords: analytical analysis, hybrid resonant inverter, reactive transformer, response surface method

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Authors: Vilas Warudkar, Dinkar Janghel, Siraj Ahmed

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Rapid development experienced by India requires huge amount of energy. Actual supply capacity additions have been consistently lower than the targets set by the government. According to World Bank 40% of residences are without electricity. In 12th five year plan 30 GW grid interactive renewable capacity is planned in which 17 GW is Wind, 10 GW is from solar and 2.1 GW from small hydro project, and rest is compensated by bio gas. Renewable energy (RE) and energy efficiency (EE) meet not only the environmental and energy security objectives, but also can play a crucial role in reducing chronic power shortages. In remote areas or areas with a weak grid, wind energy can be used for charging batteries or can be combined with a diesel engine to save fuel whenever wind is available. India according to IEC 61400-1 belongs to class IV Wind Condition; it is not possible to set up wind turbine in large scale at every place. So, the best choice is to go for small scale wind turbine at lower height which will have good annual energy production (AEP). Based on the wind characteristic available at MANIT Bhopal, rotor for small scale wind turbine is designed. Various Aero foil data is reviewed for selection of airfoil in the Blade Profile. Airfoil suited of Low wind conditions i.e. at low Reynold’s number is selected based on Coefficient of Lift, Drag and angle of attack. For designing of the rotor blade, standard Blade Element Momentum (BEM) Theory is implanted. Performance of the Blade is estimated using BEM theory in which axial induction factor and angular induction factor is optimized using iterative technique. Rotor performance is estimated for particular designed blade specifically for low wind Conditions. Power production of rotor is determined at different wind speeds for particular pitch angle of the blade. At pitch 15o and velocity 5 m/sec gives good cut in speed of 2 m/sec and power produced is around 350 Watts. Tip speed of the Blade is considered as 6.5 for which Coefficient of Performance of the rotor is calculated 0.35, which is good acceptable value for Small scale Wind turbine. Simple Load Model (SLM, IEC 61400-2) is also discussed to improve the structural strength of the rotor. In SLM, Edge wise Moment and Flap Wise moment is considered which cause bending stress at the root of the blade. Various Load case mentioned in the IEC 61400-2 is calculated and checked for the partial safety factor of the wind turbine blade.

Keywords: annual energy production, Blade Element Momentum Theory, low wind Conditions, selection of airfoil

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Authors: Vasile Caunii, Andreea D. Serban, Mihaela Ivancia

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The paper presents a new approach in terms of the circular economy of technologies for feeding and aeration of accumulations and water basins for fish farming and aquaculture. Because fish is and will be one of the main foods on the planet, the use of bio-eco-technologies is a priority for all producers. The technologies proposed in the paper want to reduce by a substantial percentage the costs of operation of ponds and water accumulation, using non-polluting technologies with minimal impact on the environment. The paper proposes two innovative, intelligent systems, fully automated that use a common platform, completely eco-friendly. One system is intended to aerate the water of the fish pond, and the second is intended to feed the fish by dispersing an optimal amount of fodder, depending on population size, age and habits. Both systems use a floating platform, regenerative energy sources, are equipped with intelligent and innovative systems, and in addition to fully automated operation, significantly reduce the costs of aerating water accumulations (natural or artificial) and feeding fish. The intelligent system used for feeding, in addition, to reduce operating costs, optimizes the amount of food, thus preventing water pollution and the development of bacteria, microorganisms. The advantages of the systems are: increasing the yield of fish production, these are green installations, with zero pollutant emissions, can be arranged anywhere on the water surface, depending on the user's needs, can operate autonomously or remotely controlled, if there is a component failure, the system provides the operator with accurate data on the issue, significantly reducing maintenance costs, transmit data about the water physical and chemical parameters.

Keywords: bio-eco-technologies, economy, environment, fish

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Authors: Ahmed Elsebaay, Maged A. Abu Adma, Mahmoud Ramadan

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This study presents a technique clarifying the effect of ambient air temperature and loads power factor changing from standard values on electric generator power rating. The study introduces an optimized technique for selecting the correct electric generator power rating for certain application and operating site ambient temperature. The de-rating factors due to the previous effects will be calculated to be applied on a generator to select its power rating accurately to avoid unsafe operation and save its lifetime. The information in this paper provides a simple, accurate, and general method for synchronous generator selection and eliminates common errors.

Keywords: ambient temperature, de-rating factor, electric generator, power factor

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Authors: Sophie Oakes-Rogers, Di Bailey, Karen Slade

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Female offenders are a uniquely vulnerable group, who are at high risk of suicide. Whilst the prevention of self-harm and suicide remains a key global priority, we need to better understand the relationship between these challenging behaviours that constitute a pressing problem, particularly in environments designed to prioritise safety and security. Method choice is unlikely to be random, and is instead influenced by a range of cultural, social, psychological and environmental factors, which change over time and between countries. A key aspect of self-harm and suicide in women receiving forensic care is the lack of free access to methods. At a time where self-harm and suicide rates continue to rise internationally, understanding the role of these influencing factors and the impact of current suicide prevention strategies on the use of near-lethal methods is crucial. This poster presentation will present findings from 25 interviews and 3 focus groups, which enlisted a Participatory Action Research approach to explore the differences between self-harming and suicidal behavior. A key element of this research was using the lived experiences of women receiving forensic care from one forensic pathway in the UK, and the staffs who care for them, to discuss the role of near-lethal self-harm (NLSH). The findings and suggestions from the lived accounts of the women and staff will inform a draft assessment tool, which better assesses the risk of suicide based on the lethality of methods. This tool will be the first of its kind, which specifically captures the needs of women receiving forensic services. Preliminary findings indicate women engage in NLSH for two key reasons and is determined by their history of self-harm. Women who have a history of superficial non-life threatening self-harm appear to engage in NLSH in response to a significant life event such as family bereavement or sentencing. For these women, suicide appears to be a realistic option to overcome their distress. This, however, differs from women who appear to have a lifetime history of NLSH, who engage in such behavior in a bid to overcome the grief and shame associated with historical abuse. NLSH in these women reflects a lifetime of suicidality and indicates they pose the greatest risk of completed suicide. Findings also indicate differences in method selection between forensic provisions. Restriction of means appears to play a role in method selection, and findings suggest it causes method substitution. Implications will be discussed relating to the screening of female forensic patients and improvements to the current suicide prevention strategies.

Keywords: forensic mental health, method substitution, restriction of means, suicide

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Authors: Kateryna Zharan, Jan C. Bongaerts

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Mining operations are energy intensive, and the share of energy costs in total costs is often quoted in the range of 40 %. Saving on energy costs is, therefore, a key element of any mine operator. With the improving reliability and security of renewable energy (RE) sources, and requirements to reduce carbon dioxide emissions, perspectives for using RE in mining operations emerge. These aspects are stimulating the mining companies to search for ways to substitute fossil energy with RE. Hereby, the main purpose of this study is to present the survey research assessment in matter of finding out the key issues related to the integration of RE into mining activities, based on the mining and renewable energy experts’ opinion. The purpose of the paper is to present the outcomes of a survey conducted among mining and renewable energy experts about the feasibility of RE in mining operations. The survey research has been developed taking into consideration the following categories: first of all, the mining and renewable energy experts were chosen based on the specific criteria. Secondly, they were offered a questionnaire to gather their knowledge and opinions on incentives for mining operators to turn to RE, barriers and challenges to be expected, environmental effects, appropriate business models and the overall impact of RE on mining operations. The outcomes of the survey allow for the identification of factors which favor and disfavor decision-making on the use of RE in mining operations. It concludes with a set of recommendations for further study. One of them relates to a deeper analysis of benefits for mining operators when using RE, and another one suggests that appropriate business models considering economic and environmental issues need to be studied and developed. The results of the paper will be used for developing a hybrid optimized model which might be adopted at mines according to their operation processes as well as economic and environmental perspectives.

Keywords: carbon dioxide emissions, mining industry, photovoltaic, renewable energy, survey research, wind generation

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Authors: Anastasiia Yu. Timofeeva

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Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: grade point average, orthogonal regression, penalized regression spline, locally weighted regression

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Hamed Jafargholi

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Global warming presents an immense environmental risk, causing detrimental impacts on ecological systems and putting coastal areas at risk. Implementing efficient measures to minimize greenhouse gas emissions and the use of fossil fuels is essential to reducing global warming. Vapor compression heat pumps provide a practical method for harnessing energy from waste heat sources and reducing energy consumption. However, traditional working fluids used in these heat pumps generally contain a significant global warming potential (GWP), which might cause severe greenhouse effects if they are released. The goal of the emphasis on low-GWP (below 150) refrigerants is to further the vapor compression heat pumps. A classification system for vapor compression heat pumps is offered, with different boundaries based on the needed heat temperature and advancements in heat pump technology. A heat pump could be classified as a low temperature heat pump (LTHP), medium temperature heat pump (MTHP), high temperature heat pump (HTHP), or ultra-high temperature heat pump (UHTHP). The HTHP/UHTHP border is 160 °C, the MTHP/HTHP and LTHP/MTHP limits are 100 and 60 °C, respectively. The refrigerant is one of the most important parts of a vapor compression heat pump system. Presently, the main ways to choose a refrigerant are based on ozone depletion potential (ODP) and GWP, with GWP being the lowest possible value and ODP being zero. Pure low-GWP refrigerants, such as natural refrigerants (R718 and R744), hydrocarbons (R290, R600), hydrofluorocarbons (R152a and R161), hydrofluoroolefins (R1234yf, R1234ze(E)), and hydrochlorofluoroolefin (R1233zd(E)), were selected as candidates for vapor compression heat pump systems based on these selection principles. The performance, characteristics, and potential uses of these low-GWP refrigerants in heat pump systems are investigated in this paper. As vapor compression heat pumps with pure low-GWP refrigerants become more common, more and more low-grade heat can be recovered. This means that energy consumption would decrease. The research outputs showed that the refrigerants R718 for UHTHP application, R1233zd(E) for HTHP application, R600, R152a, R161, R1234ze(E) for MTHP, and R744, R290, and R1234yf for LTHP application are appropriate. The selection of an appropriate refrigerant should, in fact, take into consideration two different environmental and thermodynamic points of view. It might be argued that, depending on the situation, a trade-off between these two groups should constantly be considered. The environmental approach is now far stronger than it was previously, according to the European Union regulations. This will promote sustainable energy consumption and social development in addition to assisting in the reduction of greenhouse gas emissions and the management of global warming.

Keywords: vapor compression, global warming potential, heat pumps, greenhouse

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Authors: S. Ping Ho, R. Dahal

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The global economy has drastically changed how firms operate and compete. Although the construction industry is ‘local’ by its nature, the internationalization of the construction industry has become an inevitable reality. As a result of global competition, staying domestic is no longer safe from competition and, on the contrary, to grow and become an MNE (multi-national enterprise) becomes one of the important strategies for a firm to survive in the global competition. For the successful entrance into competing markets, the firms need to re-define their competitive advantages and re-identify the sources of the competitive advantages. A firm’s initiation of internationalization is not necessarily a result of strategic planning but also involves certain idiosyncratic events that pave the path leading to a firm’s internationalization. For example, a local firm’s incidental or unintentional collaboration with an MNE can become the initiating point of its internationalization process. However, because of the intensive competition in today’s global movement, many firms were compelled to initiate their internationalization as a strategic response to the competition. Understandingly stepping in in the process of internationalization and appropriately implementing the strategies (in the process) at different stages lead the construction firms to a successful internationalization journey. This study is carried out to develop a model of the internationalization process, which derives appropriate strategies that the construction firms can implement at each stage. The proposed model integrates two major and complementary views of internationalization and expresses the dynamic process of internationalization in three stages, which are the pre-international (PRE) stage, the foreign direct investment (FDI) stage, and the multi-national enterprise (MNE) stage. The strategies implied in the proposed model are derived, focusing on capability building, market locations, and entry modes based on the resource-based views: value, rareness, imitability, and substitutability (VRIN). With the proposed dynamic process model the potential construction firms which are willing to expand their business market area can be benefitted. Strategies for internationalization, such as core competence strategy, market selection, partner selection, and entry mode strategy, can be derived from the proposed model. The internationalization process is expressed in two different forms. First, we discuss the construction internationalization process, identify the driving factor/s of the process, and explain the strategy formation in the process. Second, we define the stages of internationalization along the process and the corresponding strategies in each stage. The strategies may include how to exploit existing advantages for the competition at the current stage and develop or explore additional advantages appropriate for the next stage. Particularly, the additionally developed advantages will then be accumulated and drive forward the firm’s stage of internationalization, which will further determine the subsequent strategies, and so on and so forth, spiraling up the stages of a higher degree of internationalization. However, the formation of additional strategies for the next stage does not happen automatically, and the strategy evolution is based on the firm’s dynamic capabilities.

Keywords: construction industry, dynamic capabilities, internationalization process, internationalization strategies, strategic management

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Authors: Dmitry Fedoseyev

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The ultimate success of unmanned aerial vehicles (UAVs) depends largely on the effective control of their flight, especially in variable wind conditions. This paper investigates different approaches to selecting the optimal flight level to maximize the range of UAVs. We propose to consider methods based on mathematical models of atmospheric conditions, as well as the use of sensor data and machine learning algorithms to automatically optimize the flight level in real-time. The proposed approaches promise to improve the efficiency and range of UAVs in various wind conditions, which may have significant implications for the application of these systems in various fields, including geodesy, environmental surveillance, and search and rescue operations.

Keywords: drone, UAV, flight trajectory, wind-searching, efficiency

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Authors: C. Recchia, M. Bourel, B. Recchia

Abstract:

Microorganisms (viruses, bacteria, fungi) are responsible for most communicable diseases, threatening human health. For domestic use, chemical agents are often criticized because of their potential dangerousness, and natural solutions are needed. Application of the “dry microfine steam” (DMS) technology was tested on a selection of common pathogens (SARS-CoV-2, enterovirus EV-71, human coronavirus 229E, E. coli, S. aureus, C. albicans), on different innate surfaces, for 5 to 10 seconds. Quantification of the remaining pathogens was performed, and the reduction rates ranged from 99.8% (S. aureus on plastic) to over 99.999%. DMS showed high efficacy in the elimination of common microorganisms and could be seen as a natural alternative to chemical agents to improve domestic hygiene.

Keywords: steam, SARS-CoV-2, bactericidal, virucidal, fungicidal, sterilization

Procedia PDF Downloads 159

Authors: Fadila Mohamed Mahmoud., Derkaoui I., Krimi Z.

Abstract:

Date palm is a plant which presents a very good adaptation to the difficult conditions of the environment in particular to the drought and saline stress even at high temperatures. This adaptation is related on the biology of the plant and to the presence of a microflora endophyte which live inside its tissues. Fifteen endophytics fungi isolated from date palm were tested in vitro in the presence of various NaCl concentrations to select halotolerantes isolates. These same endophytes were tested for their colonizing capacity by the description of the production of secondary metabolites more particularly the enzymes (pectinases, proteases, and phosphorylases), and the production of antibiotics and growth hormones. Significant difference was observed between the isolates with respect to the tests carried out.

Keywords: Date palm, Halotolerantes, endophyte, Secondary metabolites.

Procedia PDF Downloads 514

Authors: Igor Jerkovic

Abstract:

Biodiversity of flora provides many different nectar sources for the bees. Unifloral honeys possess distinctive flavours, mainly derived from their nectar sources (characteristic volatile organic components (VOCs)). Specific or nonspecific VOCs (chemical markers) could be used for unifloral honey characterisation as addition to the melissopalynologycal analysis. The main honey volatiles belong, in general, to three principal categories: terpenes, norisoprenoids, and benzene derivatives. Some of these substances have been described as characteristics of the floral source, and other compounds, like several alcohols, branched aldehydes, and furan derivatives, may be related to the microbial purity of honey processing and storage conditions. Selection of the extraction method for the honey volatiles profiling should consider that heating of the honey produce different artefacts and therefore conventional methods of VOCs isolation (such as hydrodistillation) cannot be applied for the honey. Two-way approach for the isolation of the honey VOCs was applied using headspace solid-phase microextraction (HS-SPME) and ultrasonic solvent extraction (USE). The extracts were analysed by gas chromatography and mass spectrometry (GC-MS). HS-SPME (with the fibers of different polarity such as polydimethylsiloxane/ divinylbenzene (PDMS/DVB) or divinylbenzene/carboxene/ polydimethylsiloxane (DVB/CAR/PDMS)) enabled isolation of high volatile headspace VOCs of the honey samples. Among them, some characteristic or specific compounds can be found such as 3,4-dihydro-3-oxoedulan (in Centaurea cyanus L. honey) or 1H-indole, methyl anthranilate, and cis-jasmone (in Citrus unshiu Marc. honey). USE with different solvents (mainly dichloromethane or the mixture pentane : diethyl ether 1 : 2 v/v) enabled isolation of less volatile and semi-volatile VOCs of the honey samples. Characteristic compounds from C. unshiu honey extracts were caffeine, 1H-indole, 1,3-dihydro-2H-indol-2-one, methyl anthranilate, and phenylacetonitrile. Sometimes, the selection of solvent sequence was useful for more complete profiling such as sequence I: pentane → diethyl ether or sequence II: pentane → pentane/diethyl ether (1:2, v/v) → dichloromethane). The extracts with diethyl ether contained hydroquinone and 4-hydroxybenzoic acid as the major compounds, while (E)-4-(r-1’,t-2’,c-4’-trihydroxy-2’,6’,6’-trimethylcyclo-hexyl)but-3-en-2-one predominated in dichloromethane extracts of Allium ursinum L. honey. With this two-way approach, it was possible to obtain a more detailed insight into the honey volatile and semi-volatile compounds and to minimize the risks of compound discrimination due to their partial extraction that is of significant importance for the complete honey profiling and identification of the chemical biomarkers that can complement the pollen analysis.

Keywords: honey chemical biomarkers, honey volatile compounds profiling, headspace solid-phase microextraction (HS-SPME), ultrasonic solvent extraction (USE)

Procedia PDF Downloads 195

Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: marine genomics, evolutionary bioinformatics, human genome sequencing, genomic analyses

Procedia PDF Downloads 603

Authors: Faten Khanfir, Mohamed Tlili, Ali Medeb Hamrouni, Raki Selmi, M. S. Khalfi, Faten Ben Amor

Abstract:

Introduction: dental implant failure is a major concern for the clinician and the patient. Objectives: The aim of our study is to investigate the way in which 100 Tunisian dentists carried implant treatment for their patients from the early phase of planning and selection of patients to the placement of the implant in order to look for the implant failure factors. Results: significant correlations were found between failure rates > 5 and their corresponding factors as the number of implants placed (p = 0.001<0, 05), smoking (0.046 <0.05), unbalanced diabetes (0.03<0.05), aseptic protocol (= 0.004< 0.05) and the drilling speed (0,002<0.05) Conclusion: It seems that the number of implant placed, smoking, diabetes, aseptic protocol, and the drilling speed may contribute to dental implant failure.

Keywords: failure, implants, survey, risk, osseointegration

Procedia PDF Downloads 175

Authors: Masoumeh Mofarrah, Amir NahanMoghadam

Abstract:

Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise, and improve EOR methods and their application. Recently, Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic, and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization infeasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

Procedia PDF Downloads 484

Authors: Julianto Agung Saputro, Jogiyanto Hartono

Abstract:

Multiple valuation is widely used by investors and practitioners but its accuracy is questionable. Multiple valuation inaccuracies are due to the unreliability of information used in valuation, inaccuracies comparison group selection, and use of individual multiple values. This study investigated the accuracy of valuation to examine factors that can increase the accuracy of the valuation of multiple ratios, that are discretionary accruals, the comparison group, and the composite of multiple valuation. These results indicate that multiple value adjustment method with discretionary accruals provides better accuracy, the industry comparator group method combined with the size and growth of companies also provide better accuracy. Composite of individual multiple valuation gives the best accuracy. If all of these factors combined, the accuracy of valuation of multiple ratios will give the best results.

Keywords: multiple, valuation, composite, accuracy

Procedia PDF Downloads 275