Search results for: gravitational search algorithm

Authors: Amor Jnifene, Cedric Cocaud

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One of the most constraining problems facing the development of autonomous vehicles is the limitations of current technologies. Guidance and navigation controllers need to be faster and more robust. Communication data links need to be more reliable and secure. For an Unmanned Aerial Vehicles (UAV) to be useful, and fully autonomous, one important feature that needs to be an integral part of the navigation system is autonomous trajectory planning. The work discussed in this paper presents a method for on-line trajectory planning for UAV’s. This method takes into account various constraints of different types including specific vectors of approach close to target points, multiple objectives, and other constraints related to speed, altitude, and obstacle avoidance. The trajectory produced by the proposed method ensures a smooth transition between different segments, satisfies the minimum curvature imposed by the dynamics of the UAV, and finds the optimum velocity based on available atmospheric conditions. Given a set of objective points and waypoints a skeleton of the trajectory is constructed first by linking all waypoints with straight segments based on the order in which they are encountered in the path. Secondly, vectors of approach (VoA) are assigned to objective waypoints and their preceding transitional waypoint if any. Thirdly, the straight segments are replaced by 3D curvilinear trajectories taking into account the aircraft dynamics. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircrafts, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers. In summary, this work presents a method for on-line 3D trajectory generation (TG) of Unmanned Aerial Vehicles (UAVs). The method takes as inputs a series of waypoints and an optional vector of approach for each of the waypoints. Using a dynamic model based on the performance equations of fixed wing aircraft, the TG computes a set of 3D parametric curves establishing a course between every pair of waypoints, and assembling these sets of curves to construct a complete trajectory. The algorithm ensures geometric continuity at each connection point between two sets of curves. The geometry of the trajectory is optimized according to the dynamic characteristics of the aircraft such that the result translates into a series of dynamically feasible maneuvers.

Keywords: trajectory planning, unmanned autonomous air vehicle, vector of approach, waypoints

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Authors: Radhia Toujani, Jalel Akaichi

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Social Networks generally present a hierarchy of communities. To determine these communities and the relationship between them, detection algorithms should be applied. Most of the existing algorithms, proposed for hierarchical communities identification, are based on either agglomerative clustering or divisive clustering. In this paper, we present a hybrid hierarchical clustering approach for community detection based on both bottom-up and bottom-down clustering. Obviously, our approach provides more relevant community structure than hierarchical method which considers only divisive or agglomerative clustering to identify communities. Moreover, we performed some comparative experiments to enhance the quality of the clustering results and to show the effectiveness of our algorithm.

Keywords: agglomerative hierarchical clustering, community structure, divisive hierarchical clustering, hybrid hierarchical clustering, opinion mining, social network, social network analysis

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Authors: Kolade Olawande Owoeye, George R. S. Weir

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The widespread of terrorism and extremism activities on the internet has become a major threat to the government and national securities due to their potential dangers which have necessitated the need for intelligence gathering via web and real-time monitoring of potential websites for extremist activities. However, the manual classification for such contents is practically difficult or time-consuming. In response to this challenge, an automated classification system called composite technique was developed. This is a computational framework that explores the combination of both semantics and syntactic features of textual contents of a web. We implemented the framework on a set of extremist webpages dataset that has been subjected to the manual classification process. Therein, we developed a classification model on the data using J48 decision algorithm, this is to generate a measure of how well each page can be classified into their appropriate classes. The classification result obtained from our method when compared with other states of arts, indicated a 96% success rate in classifying overall webpages when matched against the manual classification.

Keywords: extremist, web pages, classification, semantics, posit

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Goran Begović

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In recent years, many researchers are focusing on non-intrusive measuring methods when it comes to human biosignals. These methods provide solutions for everyday use, whether it’s health monitoring or finessing the workout routine. One of the biggest issues with these solutions is that the sensors’ accuracy is highly variable due to many factors, such as ambiental light, skin color diversity, etc. That is why we wanted to explore different outcomes under those kinds of circumstances in order to find the most optimal algorithm(s) for extracting heart rate (HR) information. The optimization of such algorithms can benefit the wider, cheaper, and safer application of home health monitoring, without having to visit medical professionals as often when it comes to observing heart irregularities. In this study, we explored the accuracy of infrared (IR), red, and green LED sensorics in a controlled environment and compared the results with a medically accurate ECG monitoring device.

Keywords: data science, ECG, heart rate, holter monitor, LED sensors

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Authors: Merzak Siham, Benguerine Zohra, Si Tayeb Fatima, Bouzian Chaimaa Affaf, Jou Siham, Belkessam Nafissa

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Introduction: Medicinal plants, particularly spices, are essential for pharmacological research due to their health benefits. This study focuses on Curcuma longa, a spice recognized for its therapeutic properties. Materials and Methods: This study is based on a thorough search conducted on Google Scholar, PubMed, and ScienceDirect. From an initial selection of 25 articles, five were chosen to extract relevant information on Curcuma longa. Results and Discussions: Clinical studies have indicated that curcumin is well tolerated at doses up to 12 g/day. Its anti-rheumatic efficacy was compared to phenylbutazone in 18 individuals. Each participant received a daily dose of either 1200 mg of curcumin or 300 mg of phenylbutazone for 2 weeks. Curcumin was well tolerated at this dose and demonstrated activity comparable to phenylbutazone. Additionally, a study on 62 patients showed that curcumin sustainably relieved symptoms without toxicity. Its effects included reduced itching, lesions, and pain. In ten volunteers, administering 500 mg of curcumin for seven days resulted in a 33% decrease in lipid peroxidation, a 29% increase in HDL cholesterol, and a 12% decrease in total cholesterol. It is important to note that curcumin is a potent, selective inhibitor of phosphorylase kinase, an increased marker in psoriasis. Conclusion: Curcumin is promising as a future drug for various diseases, but its bioavailability must be improved through techniques such as nano encapsulation. Additionally, exploring chemical derivatives of curcumin could lead to more potent and targeted molecules.

Keywords: turmeric, spice, medicinal plants, pharmacological activities.

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Authors: Rayah Asiri, Anna Robinson-Barella, Adam Todd, Andy Husband

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Introduction: A high prevalence of diabetes and diabetes-related complications in ethnic minority communities is of significant concern. Several studies have indicated low adherence rates to antidiabetic medications in ethnic minorities. Poor adherence to antidiabetic medications leads to a higher risk of complications and mortality. This review aims to explore the barriers to and facilitators of adherence to antidiabetic medication among ethnic minority groups in high-income countries. Methods: A comprehensive search of MEDLINE, Embase, CINAHL, and PsycINFO databases for qualitative studies exploring the barriers to or facilitators of adherence to antidiabetic medication in ethnic minority groups were conducted from database inception to March 2022 (PROSPERO CRD42022320681). A quality assessment of the studies was conducted using the Critical Appraisal Skills Programme (CASP) tool. Key concepts and themes from relevant studies were synthesised using a meta-ethnographic approach. Result: A total of 18 studies were included in the review, and three major themes were developed: 1) cultural underpinnings, 2) communication and building relationships, and 3) managing diabetes during holidays. Conclusion: Multiple barriers and facilitators of adherence to antidiabetic medication among ethnic minority people in high-income countries have been identified. A medication adherence intervention focusing on identified barriers to adherence to antidiabetic medication in ethnic minorities may help in improving diabetes outcomes in these groups.

Keywords: medication adherence, diabetes, ethnic minority, barriers, facilitators

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Authors: Anubhav Shrivastava, Lakshya Bhat, Shivarudraswamy

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Distributed Generation is the need of the hour. With current advancements in the DG technology, there are some major issues that need to be tackled in order to make this method of generation of energy more efficient and feasible. Among other problems, the control in voltage is the major issue that needs to be addressed. This paper focuses on control of voltage using reactive power control of DGs with the help of fuzzy logic. The membership functions have been defined accordingly and the control of the system is achieved. Finally, with the help of simulation results in Matlab, the control of voltage within the tolerance limit set (+/- 5%) is achieved. The voltage waveform graphs for the IEEE 14 bus system are obtained by using simple algorithm with MATLAB and then with fuzzy logic for 14 bus system. The goal of this project was to control the voltage within limits by controlling the reactive power of the DG using fuzzy logic.

Keywords: distributed generation, fuzzy logic, matlab, newton raphson, IEEE 14 bus, voltage regulation, radial network

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Authors: Raida Zouari, Iness Ahriz, Rafik Zayani, Ali Dziri, Ridha Bouallegue

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This paper proposes a room level indoor localization algorithm based on the use Multi-Layer Neural Network (MLNN) classifiers and one versus one strategy. Seven parameters of the Channel Impulse Response (CIR) were used and Gram-Shmidt Orthogonalization was performed to study the relevance of the extracted parameters. Simulation results show that when relevant CIR parameters are used as position fingerprint and when optimal MLNN architecture is selected good room level localization score can be achieved. The current study showed also that some of the CIR parameters are not correlated to the location and can decrease the localization performance of the system.

Keywords: mobile indoor localization, multi-layer neural network (MLNN), channel impulse response (CIR), Gram-Shmidt orthogonalization

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Authors: Nadia Akkari

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This paper presents the analysis and simulation of the control of double star induction motor, using direct torque control (DTC) based on RST regulator. The DTC is an excellent solution for general- purpose induction drives in very wide range the short sampling time required by the TC schemes makes them suited to a very fast torque and flux controlled drives as well the simplicity of the control algorithm. DTC is inherently a motion sensorless control method. The RST regulator can improve the double star induction motor performance in terms of overshoot, rapidity, cancellation of disturbance, and capacity to maintain a high level of performance. Simulation results indicate that the proposed regulator has better performance responses. The implementation of the DTC applied to a double star induction motor based on RST regulator is validated with simulated results.

Keywords: Direct Torque Control (DTC), Double Star Induction Motor (DSIM), RST Regulator

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Authors: Vijay Kr. Yadav, Nilam Rathi

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Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.

Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy

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Authors: David Koren, Vojko Kilar

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The modern energy-efficient houses are often founded on a thermal insulation (TI) layer placed under the building’s RC foundation slab. The purpose of the paper is to identify the potential problems of the buildings founded on TI layer from the seismic point of view. The two main goals of the study were to assess the seismic behavior of such buildings, and to search for the critical structural parameters affecting the response of the superstructure as well as of the extruded polystyrene (XPS) layer. As a test building a multi-storeyed RC frame structure with and without the XPS layer under the foundation slab has been investigated utilizing nonlinear dynamic (time-history) and static (pushover) analyses. The structural response has been investigated with reference to the following performance parameters: i) Building’s lateral roof displacements, ii) Edge compressive and shear strains of the XPS, iii) Horizontal accelerations of the superstructure, iv) Plastic hinge patterns of the superstructure, v) Part of the foundation in compression, and vi) Deformations of the underlying soil and vertical displacements of the foundation slab (i.e. identifying the potential uplift). The results have shown that in the case of higher and stiff structures lying on firm soil the use of XPS under the foundation slab might induce amplified structural peak responses compared to the building models without XPS under the foundation slab. The analysis has revealed that the superstructure as well as the XPS response is substantially affected by the stiffness of the foundation slab.

Keywords: extruded polystyrene (XPS), foundation on thermal insulation, energy-efficient buildings, nonlinear seismic analysis, seismic response, soil–structure interaction

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Authors: E. A. Krasikov

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Dependence of the materials properties on neutron irradiation intensity (flux) is a key problem while usage data of the accelerated materials irradiation in test reactors for forecasting of their capacity for work in realistic (practical) circumstances of operation. Investigations of the reactor pressure vessel steel radiation degradation dependence on fast neutron fluence (embrittlement kinetics) at low flux reveal the instability in the form of the scatter of the experimental data and wave-like sections of embrittlement kinetics appearance. Disclosure of the steel degradation oscillating is a sign of the steel structure cyclic self-recovery transformation as it take place in self-organization processes. This assumption has received support through the discovery of the similar ‘anomalous’ data in scientific publications and by means of own additional experiments. Data obtained stimulate looking-for ways to management of the structural steel radiation stability (for example, by means of nano - structure modification for radiation defects annihilation intensification) for creation of the intelligent self-recovering material. Expected results: - radiation degradation theory and mechanisms development, - more adequate models of the radiation embrittlement elaboration, - surveillance specimen programs improvement, - methods and facility development for usage data of the accelerated materials irradiation for forecasting of their capacity for work in realistic (practical) circumstances of operation, - search of the ways for creating of the radiation stable self-recovery intelligent materials.

Keywords: degradation, radiation, steel, wave-like kinetics

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Authors: Qing K. Zhu

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Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

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This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: machine learning, medical diagnosis, meningitis detection, pediatric research

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Authors: Andrey Yatsun, Andrei Malchikov

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Exoskeletons are used to support and compensate for the load on the human musculoskeletal system. Elastomers are an important component of exoskeletons, providing additional support and compensating for the load. The algorithm of the active elastomer tension system provides the required auxiliary force depending on the angle of rotation and the tilt speed of the operator's torso. Feedback for the drive is provided by a force sensor integrated into the attachment of the exoskeleton vest. The use of direct force measurement ensures the required accuracy in all settings of the man-machine system. Non-adjustable elastic elements make it difficult to move without load, tilt forward and walk. A strategy for the organization of the auxiliary forces management system is proposed based on the allocation of 4 operating modes of the human-machine system.

Keywords: soft exoskeleton, mathematical modeling, pre-tension elastomer, human-machine interaction

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Authors: M. G. Shilina

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The prospects for political and economic development of the Eurasian space are currently discussed at both governmental and expert levels. New concepts actively proposed by the Eurasian governments require the analysis and search for effective implementation options. In the paper, an attempt to identify effective solutions to the problems surrounding the current economic integration of the Eurasian states is given on the basis of an interdisciplinary, comprehensive, structured analysis. The phenomenon is considered through the prism of the international law, world economy and politics, combined with the study of existing intergovernmental practice. The modeling method was taken as the basis for the research and is supplemented by legal and empirical methods. The detailed multi-level model of practical construction the 'Great Eurasia' (the GE) concept is proposed, the option for building a phased interaction in Eurasia is given through the prism of construction by the Eurasian Economic Union (the EAEU) as the main tool. The Shanghai Cooperation Organization (the SCO) is seen as the most promising element of the model. The SCO is capable of streamlining the formation of the GE and determine the transformation of Eurasia into a common economic space. Effective development of the economic integration between Eurasian states on the framework of the SCO is optimal. The SCO+ could be used as a platform for integration-integration processes formation. The creation of stable financial ties could become the basis for the possible formation of an expanded transregional integration platform. The paper concludes that the implementation of the proposed model could entail a gradual economic rapprochement of Eurasia and beyond.

Keywords: economic integration, The Eurasian Economic Union, The European Union, The Shanghai Cooperation Organization, the silk road economic belt

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Authors: Nazanin Ahmadi Daryakenari

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Background: Diabetes significantly influences the risk of heart failure. The interplay between distinct types of diabetes, heart failure, and their distribution across various age groups remains an area of active exploration. This study endeavors to scrutinize the age group distribution in publications addressing Type 1 and Type 2 diabetes and heart failure on PubMed while also examining the evolving publication trends. Methods: We leveraged E-utilities and RegEx to search and extract publication data from PubMed using various mesh terms. Subsequently, we conducted descriptive statistics and t-tests to discern the differences between the two diabetes types and the distribution across age groups. Finally, we analyzed the temporal trends of publications concerning both types of diabetes and heart failure. Results: Our findings revealed a divergence in the age group distribution between Type 1 and Type 2 diabetes within heart failure publications. Publications discussing Type 2 diabetes and heart failure were more predominant among older age groups, whereas those addressing Type 1 diabetes and heart failure displayed a more balanced distribution across all age groups. The t-test revealed no significant difference in the means between the two diabetes types. However, the number of publications exploring the relationship between Type 2 diabetes and heart failure has seen a steady increase over time, suggesting an escalating interest in this area. Conclusion: The dissection of publication patterns on PubMed uncovers a pronounced association between Type 2 diabetes and heart failure within older age groups. This highlights the critical need to comprehend the distinct age group differences when examining diabetes and heart failure to inform and refine targeted prevention and treatment strategies.

Keywords: Type 1 diabetes, Type 2 diabetes, heart failure, age groups, publication patterns, PubMed

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Authors: Shivani Singh, Shantanu Nakhare, Kalyani Nair, Rohan Shetty

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As social networking is growing at a rapid pace today it is vital that we work on improving its management. Research has shown that the content present in online social networks may have significant influence on impressionable minds. If such platforms are misused, it will lead to negative consequences. Detecting insults or inappropriate messages continues to be one of the most challenging aspects of Online Social Networks (OSNs) today. We address this problem through a Machine Learning Based Soft Text Classifier approach using Support Vector Machine algorithm. The proposed system acts as a screening mechanism the alerts the user about such messages. The messages are classified according to their subject matter and each comment is labeled for the presence of profanity and insults.

Keywords: machine learning, online social networks, soft text classifier, support vector machine

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Authors: Guilherme Ribeiro, Alexandre Oliveira, Antonio Ferreira, Shyam Visweswaran, Gregory Cooper

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Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

Keywords: approach instance-based, area under the ROC curve, patient-specific decision path, clinical predictions

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Authors: Aadita Chaudhury

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Since at least the early 2000s, DNA profiling has achieved a preeminent status in forensic investigations into criminal acts. While the criminal justice system has a long history of using forensic evidence and testing them through establish technoscientific means, the primacy of DNA in establishing 'truth' or reconstructing a series of events is unparalleled in the history of forensic science. This paper seeks to elucidate the ways in which DNA profiling has become the most authoritative instrument of 'truth' in criminal investigations, and how it is used in the legal process to ascertain culpability, create the notion of infallible evidence, and advance the search for justice. It is argued that DNA profiling has created a paradigm shift in how the legal system and the general public understands crime and culpability, but not without limitations. There are indications that even trace amounts of DNA evidence can point to causal links in a criminal investigation, however, there still remains many rooms to create confusion and doubt from empirical evidence within the narrative of crimes. Many of the shortcomings of DNA-based forensic investigations are explored and evaluated with regards to claims of the authority of biological evidence and implications for the public understanding of the elusive concepts of truth and justice in the present era. Public misinformation about the forensic analysis processes could produce doubt or faith in the judgements rooted in them, depending on other variables presented at the trial. A positivist understanding of forensic science that is shared by the majority of the population does not take into consideration that DNA evidence is far from definitive, and can be used to support any theories of culpability, to create doubt and to deflect blame.

Keywords: DNA profiling, epistemology of forensic science, philosophy of forensic science, sociology of scientific knowledge

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Authors: Mariam Bibi, Rubab Mehboob, Mehreen Sirshar

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Satisfying the customer requirements is the ultimate goal of producing or developing any product. The quality of the product is decided on the bases of the level of customer satisfaction. There are different techniques which have been reported during the survey which enhance the quality of the product through software defect prediction and by locating the missing software requirements. Some mining techniques were proposed to assess the individual performance indicators in collaborative environment to reduce errors at individual level. The basic intention is to produce a product with zero or few defects thereby producing a best product quality wise. In the analysis of survey the techniques like Genetic algorithm, artificial neural network, classification and clustering techniques and decision tree are studied. After analysis it has been discovered that these techniques contributed much to the improvement and enhancement of the quality of the product.

Keywords: data mining, defect prediction, missing requirements, software quality

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Authors: Nazih Ramadan, Manal Mohy-Eldine, Amani Hanoon, Alaa Shehab

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Background and Aims: The study of fingerprints is widely used in providing a clue regarding identity. Age and gender identification from fingerprints is an important step in forensic anthropology in order to minimize the list of suspects search. The aim of this study was to determine finger ridge density and patterns among Egyptians, and to estimate age and gender using ridge densities. Materials and Methods: This study was conducted on 177 randomly-selected healthy Egyptian subjects (90 males and 87 females). They were divided into three age groups; Group (a): from 6-< 12 years, group (b) from 12-< 18 years and group (c) ≥ 18 years. Bilateral digital prints, from every subject, were obtained by the inking procedure. Ridge count per 25 mm² was determined together with assessment of ridge pattern type. Statistical analysis was done with references to different age and sex groups. Results: There was a statistical significant difference in ridge density between the different age groups; where younger ages had significantly higher ridge density than older ages. Females proved to have significantly higher ridge density than males. Also, there was a statistically significant negative correlation between age and ridge density. Ulnar loops were the most frequent pattern among Egyptians then whorls then arches then radial loops. Finally, different regression models were constructed to estimate age and gender from fingerprints ridge density. Conclusion: fingerprint ridge density can be used to identify both age and sex of subjects. Further studies are recommended on different populations, larger samples or using different methods of fingerprint recording and finger ridge counting.

Keywords: age, sex identification, Egyptian population, fingerprints, ridge density

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Authors: Mahdi Zolfaghari, Seyed Hossein Hosseinian, Hossein Askarian Abyaneh, Mehrdad Abedi

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This paper presents a virtual active power filter (VAPF) using vehicle to grid (V2G) technology to maintain power quality requirements. The optimal discrete operation of the power converter of electric vehicle (EV) is based on recognizing desired switching states using the model predictive control (MPC) algorithm. A fast dynamic response, lower total harmonic distortion (THD) and good reference tracking performance are realized through the presented control strategy. The simulation results using MATLAB/Simulink validate the effectiveness of the scheme in improving power quality as well as good dynamic response in power transferring capability.

Keywords: electric vehicle, model predictive control, power quality, V2G technology, virtual active power filter

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Authors: Abu Afree Andalib, M. Mezbah Uddin, M. Rafiur Rahman, M. Abir Hossain, Rajia Sultana Kamol

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This paper deals with the analysis of flow past the marine turbine blade which is designed by using the blade element theory and momentum theory for the purpose of using in the field of renewable energy. The designed blade is analyzed for various parameters using FSI module of Ansys. Computational Fluid Dynamics is used for the study of fluid flow past the blade and other fluidic phenomena such as lift, drag, pressure differentials, energy dissipation in water. Finite Element Analysis (FEA) module of Ansys was used to analyze the structural parameter such as stress and stress density, localization point, deflection, force propagation. Fine mesh is considered in every case for more accuracy in the result according to computational machine power. The relevance of design, search and optimization with respect to complex fluid flow and structural modeling is considered and analyzed. The relevancy of design and optimization with respect to complex fluid for minimum drag force using Ansys Adjoint Solver module is analyzed as well. The graphical comparison of the above-mentioned parameter using CFD and FEA and subsequently FSI technique is illustrated and found the significant conformity between both the results.

Keywords: blade element theory, computational fluid dynamics, finite element analysis, fluid-structure interaction, momentum theory

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Authors: Elena Krelja Kurelović, Jasminka Tomljanović, Vlatka Davidović

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The development of web technologies and mobile devices makes creating, accessing, using and sharing information or communicating with each other simpler every day. However, while the amount of information constantly increasing it is becoming harder to effectively organize and find quality information despite the availability of web search engines, filtering and indexing tools. Although digital technologies have overall positive impact on students’ lives, frequent use of these technologies and digital media enriched with dynamic hypertext and hypermedia content, as well as multitasking, distractions caused by notifications, calls or messages; can decrease the attention span, make thinking, memorizing and learning more difficult, which can lead to stress and mental exhaustion. This is referred to as “information overload”, “information glut” or “information anxiety”. Objective of this study is to determine whether students show signs of information overload and to identify the possible predictors. Research was conducted using a questionnaire developed for the purpose of this study. The results show that students frequently use technology (computers, gadgets and digital media), while they show moderate level of information literacy. They have sometimes experienced symptoms of information overload. According to the statistical analysis, higher frequency of technology use and lower level of information literacy are correlated with larger information overload. The multiple regression analysis has confirmed that the combination of these two independent variables has statistically significant predictive capacity for information overload. Therefore, the information science teachers should pay attention to improving the level of students’ information literacy and educate them about the risks of excessive technology use.

Keywords: information overload, computers, mobile devices, digital media, information literacy, students

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Authors: Sajidullah Khan, Najeeb Ullah, Wang Yin Chai, Chai Soo See

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In this paper, we propose an approach to remove impulse and Poisson noise from X-ray images. Many filters have been used for impulse noise removal from color and gray scale images with their own strengths and weaknesses but X-ray images contain Poisson noise and unfortunately there is no intelligent filter which can detect impulse and Poisson noise from X-ray images. Our proposed filter uses the upgraded layer discrimination approach to detect both Impulse and Poisson noise corrupted pixels in X-ray images and then restores only those detected pixels with a simple efficient and reliable one line equation. Our Proposed algorithms are very effective and much more efficient than all existing filters used only for Impulse noise removal. The proposed method uses a new powerful and efficient noise detection method to determine whether the pixel under observation is corrupted or noise free. Results from computer simulations are used to demonstrate pleasing performance of our proposed method.

Keywords: X-ray image de-noising, impulse noise, poisson noise, PRWF

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Authors: Busiswa Madikazi

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This systematic mapping study explores the underrepresentation of women's contributions to farming in the Global South within the development of Information and Communication Technologies (ICT)-based extension methods. Despite women farmers constituting 70% of the agricultural labour force, their productivity is hindered by various constraints, including illiteracy, household commitments, and limited access to credit and markets. A systematic mapping approach was employed with the aim of identifying evidence gaps in existing ICT extension for women farmers. The data collection protocol follows a structured approach, incorporating key criteria for inclusion, exclusion, search strategy, and coding and the PICO strategy (Population, Intervention, Comparator, and Outcome). The results yielded 119 articles that qualified for inclusion. The findings highlight that mobile phone apps (WhatsApp) and radio/television programming are the primary extension methods employed while integrating ICT with training, field visits, and demonstrations are underutilized. Notably, the study emphasizes the inadequate attention to critical issues such as food security, gender equality, and attracting youth to farming within ICT extension efforts. These findings indicate a significant policy and practice gap, neglecting community-driven approaches that cater to women's specific needs and enhance their agricultural production. Map highlights the importance of refocusing ICT extension efforts to address women farmers’ unique challenges, thereby contributing to their empowerment and improving agricultural practices.

Keywords: agricultural extension, ICT, women farmers, smallholders

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Authors: Cholpassorn Sitthiwarongchai

Abstract:

The purposes of this paper were to search for the uniqueness of community products from Bang Khonthi District, Samut Songkram Province, Thailand and to create a proper brand for the community products. Four important questions were asked to identify the uniqueness of the community products. The first question: What is the brand of coconut sugar that community wants to imply? The answer was 100 percent authentic coconut sugar. The second question: What is the nature of this product? The answer was that it is a natural product without any harmful chemical. The third question is: Who are the target customers? The answer was that homemakers and tourists are target customers. The fourth question: What is the brand guarantee to customers? The answer was that the brand guarantees that the product is 100 percent natural process with a high quality and it is a community production. The findings revealed that in terms of product, customers rated quality and package as the two most important factors. In terms of price, customers rated lower price and a visible label as the two most important factors. In terms of place, customer rated layout and the cleanliness of the place as the two most important factors. In terms of promotion, customer rated public relations and brochure at the store as the most important factors. From the group discussion, the local community agreed that the brand for the community coconut sugar of Salapi community should be a picture of a green coconut tree and yellow color background. This brand implies the strength of community and authentic of the high quality natural product.

Keywords: coconut sugar, community brand, Samut Songkram, natural product

Procedia PDF Downloads 397

Authors: Zin Mar Lwin

Abstract:

Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods.

Keywords: BCI, EEG, ICA, SVM

Procedia PDF Downloads 279