Search results for: network diagnostic tool

Authors: Ailing Yang, Penghan Song, Aihua Cai

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The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods.

Keywords: maneuvering target, state estimation, Kalman filter, LSTM, self-attention

Procedia PDF Downloads 177

Authors: Arthi Ganapathy, Arithra Banerjee, Saroj Kaler

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Abdominal aorta is the sole purveyor of all organs in the abdomen. Anomalies of its main trunk or its branches are to be meticulously observed as it effects the perfusion of an organ. Varying patterns of the testicular artery is one of them. The origin and course of testicular arteries have to be identified carefully during various surgical procedures like renal transplant, intra abdominal surgeries and even in orthopedic surgery like spine surgery. With the advent of new intra-abdominal therapeutic and diagnostic techniques, the anatomy of testicular arteries has assumed much more significance. Though the variations of the testicular vein are well documented, the variations of the testicular artery are not so frequent in incidence. We report a case of the bilateral aberrant origin of the testicular artery from polar renal arteries. We also discuss its developmental basis. Such anomalies if left unnoticed will lead to serious intraoperative complications during procedures on retroperitoneal organs. Any damage to testicular arteries will compromise the function of the gonads.

Keywords: cadaver, gonadal, renal, surgery

Procedia PDF Downloads 225

Authors: Mohd Faridz Ahmad, Muhammad Amir Asyraf Rosli

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Aerobic dance has becoming a popular mode of exercise especially among women due to its fun nature. With a catchy music background and joyful dance steps, aerobic dancers would be able to have fun while sweating out. Depending on its level of aggressiveness, aerobic may also improve and maintain cardiorespiratory fitness other than being a great tool for weight loss. This study intends to prove that aerobic dance activity can bring the same, if not better impacts on health than other types of cardiovascular exercise such as jogging and cycling. The objective of this study was to evaluate and identify the effect of six weeks aerobic dance on cardiovascular fitness and weight loss among women. This study, which was held in Seremban Fit Challenge, used a quasi-experimental design. The subjects selected include a total of 14 women (n = 14) with age (32.4 years old ± 9.1), weight (65.93 kg ± 11.24) and height (165.36 ± 3.46) who joined the Seremban Fit Challenge Season 13. The subjects were asked to join an aerobic dance class with duration of one hour for six weeks in a row. As for the outcome, cardiovascular fitness was measured with a 1-mile run test while any changes on weight was measured using the weighing scale. The result showed that there was a significant difference between pre and post-test for cardiovascular fitness when p = 0.02 < 0.05 and weight loss when p = 0.00 < 0.05. In conclusion, a six-week long aerobic dance program would have a positive effect on cardiovascular fitness and weight. Therefore, aerobic dance may be used as an alternative tool for people who wish to lead a healthy lifestyle in a fun way.

Keywords: aerobic dance, cardiovascular fitness, weight loss, 1-mile run test

Procedia PDF Downloads 547

Authors: O. Abdelkhalek, A. Naimi, M. Rami, M. N. Tandjaoui, A. Kechich

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This paper deals with the active and reactive power flow analysis inside the unified power quality conditioner (UPQC) during several cases. The UPQC is a combination of shunt and series active power filter (APF). It is one of the best solutions towards the mitigation of voltage sags and swells problems on distribution network. This analysis can provide the helpful information to well understanding the interaction between the series filter, the shunt filter, the DC bus link and electrical network. The mathematical analysis is based on active and reactive power flow through the shunt and series active power filter. Wherein series APF can absorb or deliver the active power to mitigate a swell or sage voltage where in the both cases it absorbs a small reactive power quantity whereas the shunt active power absorbs or releases the active power for stabilizing the storage capacitor’s voltage as well as the power factor correction. The voltage sag and voltage swell are usually interpreted through the DC bus voltage curves. These two phenomena are introduced in this paper with a new interpretation based on the active and reactive power flow analysis inside the UPQC. For simplifying this study, a linear load is supposed in this digital simulation. The simulation results are carried out to confirm the analysis done.

Keywords: UPQC, Power flow analysis, shunt filter, series filter.

Procedia PDF Downloads 572

Authors: Vethathirri Ramanujam Srinivasan, S. M. Shiva Nagendra

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Air quality management in urban areas is a serious concern in both developed and developing countries. In this regard, more number of air quality monitoring stations are planned to mitigate air pollution in urban areas. In India, Central Pollution Control Board has set up 574 air quality monitoring stations across the country and proposed to set up another 500 stations in the next few years. The number of monitoring stations for each city has been decided based on population data. The setting up of ambient air quality monitoring stations and their operation and maintenance are highly expensive. Therefore, there is a need to optimize monitoring networks for air quality management. The present paper discusses the various methods such as Indian Standards (IS) method, US EPA method and European Union (EU) method to arrive at the minimum number of air quality monitoring stations. In addition, optimization of rain-gauge method and Inverse Distance Weighted (IDW) method using Geographical Information System (GIS) are also explored in the present work for the design of air quality network in Chennai city. In summary, additionally 18 stations are required for Chennai city, and the potential monitoring locations with their corresponding land use patterns are ranked and identified from the 1km x 1km sized grids.

Keywords: air quality monitoring network, inverse distance weighted method, population based method, spatial variation

Procedia PDF Downloads 189

Authors: Lu Zhao, Nadir Farhi, Zoi Christoforou, Nadia Haddadou

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The safety test of deploying intelligent connected vehicles (ICVs) on the road network is a critical challenge. Road traffic network simulation can be used to test the functionality of ICVs, which is not only time-saving and less energy-consuming but also can create scenarios with car collisions. However, the relationship between different human driver behaviors and the car-collision occurrences has been not understood clearly; meanwhile, the procedure of car-collisions generation in the traffic numerical simulators is not fully integrated. In this paper, we propose an approach to identify specific driver profiles from real driven data; then, we replicate them in numerical traffic simulations with the purpose of generating inter-vehicular collisions. We proposed three profiles: (i) 'aggressive': short time-headway, (ii) 'inattentive': long reaction time, and (iii) 'normal' with intermediate values of reaction time and time-headway. These three driver profiles are extracted from the NGSIM dataset and simulated using the intelligent driver model (IDM), with an extension of reaction time. At last, the generation of inter-vehicular collisions is performed by varying the percentages of different profiles.

Keywords: vehicular collisions, human driving behavior, traffic modeling, car-following models, microscopic traffic simulation

Procedia PDF Downloads 171

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

Procedia PDF Downloads 259

Authors: B. Varaprasad, C. Srinivasa Rao

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In the manufacturing sector, hard turning has emerged as vital machining process for cutting hardened steels. Besides many advantages of hard turning operation, one has to implement to achieve close tolerances in terms of surface finish, high product quality, reduced machining time, low operating cost and environmentally friendly characteristics. In the present study, three-dimensional CAE (Computer Aided Engineering) based simulation of  hard turning by using commercial software DEFORM 3D has been compared to experimental results of  stresses, temperatures and tool forces in machining of AISI D3 steel using mixed Ceramic inserts (CC6050). In the present analysis, orthogonal cutting models are proposed, considering several processing parameters such as cutting speed, feed, and depth of cut. An exhaustive friction modeling at the tool-work interfaces is carried out. Work material flow around the cutting edge is carefully modeled with adaptive re-meshing simulation capability. In process simulations, feed rate and cutting speed are constant (i.e.,. 0.075 mm/rev and 155 m/min), and analysis is focused on stresses, forces, and temperatures during machining. Close agreement is observed between CAE simulation and experimental values.

Keywords: hard turning, computer aided engineering, computational machining, finite element method

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Authors: Noman Ahmed, Fariha Tahseen

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Since several decades, unplanned urbanization and rapid growth of informal settlements have evolved and increased in size and number. Large cities such as Karachi have been impacted with sprawl and rising share of unplanned settlements where poor communities reside. Threats of eviction, deteriorating law and order situation, lack of essential amenities and infrastructure, extortion and bullying from local and non-local musclemen and feeble response of government agencies towards their development needs are some predicaments. Non-governmental organizations (NGOs) have caused important interventions in such locations. Appraisal of the community-based mapping as a tool in supporting the development work in less privileged areas in Karachi has been the objective of this research. The Orangi Pilot Project (OPP), under the leadership of its slain director Perween Rahman had a significant role to play in developing and extending this approach in low income locations in Karachi and beyond. The paper investigates the application of mapping in the process of peri urban land invasion causing rapid transformation of traditional settlements in Karachi. Mixed methodology components comprising literature review, archival research, and unstructured interviews with key informants and case studies have been used.

Keywords: squatters (katchi abadis), land grabbing, community empowerment, housing rights, mapping, infrastructure development

Procedia PDF Downloads 315

Authors: Tomas Berhanu Bekele

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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.

Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression

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Authors: Libo Jiang, Huan Li, Rongling Wu

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Ordinary differentiation equations (ODE) have proven to be powerful for reconstructing precise and informative gene regulatory networks (GRNs) from dynamic gene expression data. However, joint modeling and analysis of all genes, essential for the systematical characterization of genetic interactions, are challenging due to high dimensionality and a complex pattern of genetic regulation including activation, repression, and antitermination. Here, we address these challenges by unifying variable selection and game theory through ODE. Each gene within a GRN is co-expressed with its partner genes in a way like a game of multiple players, each of which tends to choose an optimal strategy to maximize its “fitness” across the whole network. Based on this unifying theory, we designed and conducted a real experiment to infer salt tolerance-related GRNs for Euphrates poplar, a hero tree that can grow in the saline desert. The pattern and magnitude of interactions between several hub genes within these GRNs were found to determine the capacity of Euphrates poplar to resist to saline stress.

Keywords: gene regulatory network, ordinary differential equation, game theory, LASSO, saline resistance

Procedia PDF Downloads 639

Authors: Rakesh Namdeti

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Toxic dyes found in industrial effluent must be treated before being disposed of due to their harmful impact on human health and aquatic life. Thus, Musa acuminata (Banana Leaves) was employed in the role of a biosorbent in this work to get rid of methylene blue derived from a synthetic solution. The effects of five process parameters, such as temperature, pH, biosorbent dosage, and initial methylene blue concentration, using a central composite design (CCD), and the percentage of dye clearance were investigated. The response was modelled using a quadratic model based on the CCD. The analysis of variance revealed the most influential element on experimental design response (ANOVA). The temperature of 44.30C, pH of 7.1, biosorbent dose of 0.3 g, starting methylene blue concentration of 48.4 mg/L, and 84.26 percent dye removal were the best conditions for Musa acuminata (Banana leave powder). At these ideal conditions, the experimental percentage of biosorption was 76.93. The link between the estimated results of the developed ANN model and the experimental results defined the success of ANN modeling. As a result, the study's experimental results were found to be quite close to the model's predicted outcomes.

Keywords: Musa acuminata, central composite design, methylene blue, artificial neural network

Procedia PDF Downloads 76

Authors: Rituparna Nath, Shawn J. Marshall

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Glaciers are one of the main sensitive climatic indicators, as they respond strongly to small climatic shifts. We develop a flow line model of glacier dynamics to simulate the past and future extent of glaciers in the Canadian Rocky Mountains, with the aim of coupling this model within larger scale regional climate models of glacier response to climate change. This paper will focus on glacier-climate modeling and reconstructions of glacier volume from the Little Ice Age (LIA) to present for Athabasca Glacier, Alberta, Canada. Glacier thickness, volume and mass change will be constructed using flow line modelling and examination of different climate scenarios that are able to give good reconstructions of LIA ice extent. With the availability of SPOT 5 imagery, Digital elevation models and GIS Arc Hydro tool, ice catchment properties-glacier width and LIA moraines have been extracted using automated procedures. Simulation of glacier mass change will inform estimates of meltwater run off over the historical period and model calibration from the LIA reconstruction will aid in future projections of the effects of climate change on glacier recession. Furthermore, the model developed will be effective for further future studies with ensembles of glaciers.

Keywords: flow line modeling, Athabasca Glacier, glacier mass balance, Remote Sensing, Arc hydro tool, little ice age

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Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

Procedia PDF Downloads 114

Authors: A. Moualdia, D. J. Boudana, O. Bouchhida, A. Medjber

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Wind energy has many advantages, it does not pollute and it is an inexhaustible source. However, the cost of this energy is still too high to compete with traditional fossil fuels, especially on sites less windy. The performance of a wind turbine depends on three parameters: the power of wind, the power curve of the turbine and the generator's ability to respond to wind fluctuations. This paper presents a control chain conversion based on a double-fed asynchronous machine and flow-oriented. The supply system comprises of two identical converters, one connected to the rotor and the other one connected to the network via a filter. The architecture of the device is up by three commands are necessary for the operation of the turbine control extraction of maximum power of the wind to control itself (MPPT) control of the rotor side converter controlling the electromagnetic torque and stator reactive power and control of the grid side converter by controlling the DC bus voltage and active power and reactive power exchanged with the network. The proposed control has been validated in both modes of operation of the three-bladed wind 7.5 kW, using Matlab/Simulink. The results of simulation control technology study provide good dynamic performance and static.

Keywords: D.F.I.G, variable wind speed, hypersynchrone, energy quality, hyposynchrone

Procedia PDF Downloads 367

Authors: Isaac Kofi Mensah

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E-government has been adopted and used by many governments/countries around the world including Ghana to provide citizens and businesses with more accurate, real-time, and high quality services and information. The objective of this paper is to present an overview of the Government of Ghana’s (GoG) adoption and implement of e-government and its usage by the Ministries, Departments and its agencies (MDAs) as well as other public sector institutions to deliver efficient public service to the general public i.e. citizens, business etc. Government implementation of e-government focused on facilitating effective delivery of government service to the public and ultimately to provide efficient government-wide electronic means of sharing information and knowledge through a network infrastructure developed to connect all major towns and cities, Ministries, Departments and Agencies and other public sector organizations in Ghana. One aim for the Government of Ghana use of ICT in public administration is to improve productivity in government administration and service by facilitating the exchange of information to enable better interaction and coordination of work among MDAs, citizens and private businesses. The study was prepared using secondary sources of data from government policy documents, national and international published reports, journal articles, and web sources. This study indicates that through the e-government initiative, currently citizens and businesses can access and pay for services such as renewal of driving license, business registration, payment of taxes, acquisition of marriage and birth certificates as well as application for passport through the GoG electronic service (eservice) and electronic payment (epay) portal. Further, this study shows that there is an enormous commitment from GoG to adopt and implement e-government as a tool not only to transform the business of government but also to bring efficiency in public services delivered by the MDAs. To ascertain this, a further study need to be carried out to determine if the use of e-government has brought about the anticipated improvements and efficiency in service delivery of MDAs and other state institutions in Ghana.

Keywords: electronic government, electronic services, electronic pay, MDAs

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Authors: Ashagrie Getnet Flattie

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Line-of-sight (LOS) information, data rates, good quality, and flexible network service are limited by the fact that, for the duration of any given connection, they experience severe variation in signal strength due to fading and path loss. Wireless system faces major challenges in achieving wide coverage and capacity without affecting the system performance and to access data everywhere, all the time. In this paper, the cell coverage and edge rate of different Multiple-input multiple-output (MIMO) schemes in 20 MHz Long Term Evolution (LTE) system under Unmanned Air Vehicles (UAV) platform are investigated. After some background on the enormous potential of UAV, MIMO, and LTE in wireless links, the paper highlights the presented system model which attempts to realize the various benefits of MIMO being incorporated into UAV platform. The performances of the three MIMO LTE schemes are compared with the performance of 4x4 MIMO LTE in UAV scheme carried out to evaluate the improvement in cell radius, BER, and data throughput of the system in different morphology. The results show that significant performance gains such as bit error rate (BER), data rate, and coverage can be achieved by using the presented scenario.

Keywords: LTE, MIMO, path loss, UAV

Procedia PDF Downloads 279

Authors: Mohamed Hendawy Mousa, Warda Youssef Mohamed Morsy

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Background: Sepsis is a major cause of mortality and morbidity in trauma patients. Body mass index as an indicator of nutritional status was reported as a predictor of injury pattern and complications among critically ill injured patients. Aim: The aim of this study is to investigate the relationship between body mass index and the development of sepsis, systemic inflammatory response syndrome among adult trauma patients at emergency hospital - Cairo University. Research design: Descriptive correlational research design was utilized in the current study. Research questions: Q1. What is the body mass index profile of adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, Q2. What is the frequency of systemic inflammatory response syndrome and sepsis among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, and Q3. What is the relationship between the development of sepsis, systemic inflammatory response syndrome and body mass index among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?. Sample: A purposive sample of 52 adult male and female trauma patients with revised trauma score 10 to 12. Setting: The Emergency Hospital affiliated to Cairo University. Tools: Four tools were utilized to collect data pertinent to the study: Socio demographic and medical data tool, Systemic inflammatory response syndrome assessment tool, Revised Trauma Score tool, and Sequential organ failure assessment tool. Results: The current study revealed that, (61.5 %) of the studied subjects had normal body mass index, (25 %) were overweight, and (13.5 %) were underweight. 84.6% of the studied subjects had systemic inflammatory response syndrome and 92.3% were suffering from mild sepsis. No significant statistical relationship was found between body mass index and occurrence of Systemic inflammatory response syndrome (2= 2.89 & P = 0.23). However, Sequential organ failure assessment scores were affected significantly by body mass index was found mean of initial and last Sequential organ failure assessment score for underweight, normal and obese where t= 7.24 at p = 0.000, t= 16.49 at p = 0.000 and t= 9.80 at p = 0.000 respectively. Conclusion: Underweight trauma patients showed significantly higher rate of developing sepsis as compared to patients with normal body weight and obese. Recommendations: based on finding of this study the following are recommended: replication of the study on a larger probability sample from different geographical locations in Egypt; Carrying out of further studies in order to assess the other risk factors influencing trauma outcome and incidence of its complications; Establishment of standardized guidelines for managing underweight traumatized patients with sepsis.

Keywords: body mass index, sepsis, systemic inflammatory response syndrome, adult trauma

Procedia PDF Downloads 250

Authors: Galih Mediana

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Boarding school can helps students to turn all good qualities into habits. The process of forming one's personality can be done in various ways. In addition to gaining general knowledge at school during learning hours, teachers can instill values in students which can be done while in the dormitory when the learning process has ended. This shows the important role that must be played by boarding school’s teachers. Transformational leadership and a culture of innovation are things that can instill innovative behavior in teachers. This study aims to determine the effect of perceptions of transformational leadership and a culture of innovation on innovative work behavior among Islamic boarding school teachers. Respondents in this study amounted to 70 teachers. To measure transformational leadership, a modified measuring tool is used, namely the Multifactor Leadership Questionnaire (MLQ) by Bass (1985). To measure innovative work behavior, a measurement tool based on dimensions from Janssen (2000) is used. The innovation culture in this study will be measured using the innovation culture factor from Dobni (2008). This study uses multiple regression analysis to test the hypothesis. The results of this study indicate that there is an influence of perceptions of transformational leadership and innovation culture factors on innovative work behavior in Islamic boarding school’s teachers by 57.7%.

Keywords: transformational leadership, innovative work behavior, innovation culture, boarding school, teacher

Procedia PDF Downloads 108

Authors: Afzal Hussain, Mohammad A. Altamimi, Syed Sarim Imam, Mudassar Shahid, Osamah Abdulrahman Alnemer

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Exhaustive application of sulfamethoxazole (SUX) became as a global threat for human health due to water contamination through diverse sources. The addressed combined application of Hansen solubility (HSPiP software) parameters and Quality by Design tool for developing various green nanoemulsions. HSPiP program assisted to screen suitable excipients based on Hansen solubility parameters and experimental solubility data. Various green nanoemulsions were prepared and characterized for globular size, size distribution, zeta potential, and removal efficiency. Design Expert (DoE) software further helped to identify critical factors responsible to have direct impact on percent removal efficiency, size, and viscosity. Morphological investigation was visualized under transmission electron microscopy (TEM). Finally, the treated was studied to negate the presence of the tested drug employing ICP-OES (inductively coupled plasma optical emission microscopy) technique and HPLC (high performance liquid chromatography). Results showed that HSPiP predicted biocompatible lipid, safe surfactant (lecithin), and propylene glycol (PG). Experimental solubility of the drug in the predicted excipients were quite convincing and vindicated. Various green nanoemulsions were fabricated, and these were evaluated for in vitro findings. Globular size (100-300 nm), PDI (0.1-0.5), zeta potential (~ 25 mV), and removal efficiency (%RE = 70-98%) were found to be in acceptable range for deciding input factors with level in DoE. Experimental design tool assisted to identify the most critical variables controlling %RE and optimized content of nanoemulsion under set constraints. Dispersion time was varied from 5-30 min. Finally, ICP-OES and HPLC techniques corroborated the absence of SUX in the treated water. Thus, the strategy is simple, economic, selective, and efficient.

Keywords: quality by design, sulfamethoxazole, green nanoemulsion, water treatment, icp-oes, hansen program (hspip software

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Authors: Bilgehan Gültekin, Tuba Gültekin

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Peace diplomacy is the most important international tool to keep peace all over the world. The study titled “peace diplomacy for international relations” is consist of three part. In the first part, peace diplomacy is going to be introduced as a tool of peace communication and peace management. And, in this part, peace communication will be explained by international communication perspective. In the second part of the study,public relations events and communication campaigns will be developed originally for peace diplomacy. In this part, it is aimed original public communication dialogue management tools for peace diplomacy. the aim of the final part of the study, is to produce original public communication model for international relations. The model includes peace modules, peace management projects, original dialogue procedures and protocols, dialogue education, dialogue management strategies, peace actors, communication models, peace team management and public diplomacy steps. The creative part of the study aims to develop a model used for international relations for all countries. Creative Peace Diplomacy Model will be developed in the case of Turkey-Turkey-France and Turkey-Greece relations. So, communication and public relations events and campaigns are going to be developed as original for only this study.

Keywords: peace diplomacy, public communication model, dialogue management, international relations

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Authors: Yating Yang, Xue Zhang, Chengli Zhao

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Technology capability refers to the comprehensive ability that influences all factors of technological development. Among them, researchers’ resources serve as the foundation and driving force for technology capability, representing a significant manifestation of a country/region's technological capability. Therefore, the cross-border transfer behavior of researchers to some extent reflects changes in technological capability between countries/regions, providing a unique research perspective for technological capability assessment. This paper proposes a technological capability assessment model based on personnel transfer networks, which consists of a researchers' transfer network model and a country/region role evolution model. It evaluates the changes in a country/region's technological capability roles from the perspective of researcher transfers and conducts an analysis using artificial intelligence as a case study based on literature data. The study reveals that the United States, China, and the European Union are core nodes, and identifies the role evolution characteristics of several major countries/regions.

Keywords: transfer network, technological capability assessment, central-peripheral structure, role evolution

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Authors: Dana Hisham Mohamed Abdrabo

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The paper examines the effect of Drama works on the Egyptian public opinion regarding the religion of Judaism, Israel as a state and the Jew's image to Egyptian Muslims. The paper examines the role of Media and in particular, Dramas on achieving interreligious dialogue between Judaism and Islam and its role in making peace between the Egyptian Muslims -and Arabs in general- on the one hand, and the Jew on the other hand, and the implications of this on the relationship between Arab countries and Israel as a state. The research uses the Survey method with Egyptian Muslims as a main sample for the research to examine such effect. Dramas have a role in presenting the Jew, Judaism, and Israel as a state and as a political system in various ways. The paper is related to multidisciplinary fields; it is related to political sciences, political sociology, communication, social change, and cognitive sociology fields. The research adds a new analytical study for a new tool for the peacemaking process in the Middle East region through adopting an interdisciplinary approach which is needed in the studies aim to achieve stability and peace in the Middle East region and its neighboring countries.

Keywords: dramas tool, Egyptian public opinion, interreligious dialogue, Israel & Egyptian relations , Judaism

Procedia PDF Downloads 209

Authors: Md. Shaheen Shah, Abdelsalam Abugharara, Dipesh Maharjan, Syed Imtiaz, Stephen Butt

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Drilling performance is an essential goal in petroleum and mining industry. Drilling rate of penetration (ROP), which is inversely proportional to the mechanical specific energy (MSE) is influenced by numerous factors among which are the applied parameter: torque (T), weight on bit (WOB), fluid flow rate, revolution per minute (rpm), rock related parameters: rock type, rock homogeneousness, rock anisotropy orientation, and mechanical parameters: bit type, configuration of the bottom hole assembly (BHA). This paper is focused on studying the drilling performance by implementing a passive vibration assisted rotary drilling tool (pVARD) as part of the BHA through using different bit types: coring bit, roller cone bit, and PDC bit and various rock types: rock-like material, granite, sandstone, etc. The results of this study aim to produce a pVARD index for optimal drilling performance considering the recommendations of the pVARD’s spring compression tests and stress-strain analysis of rock samples conducted prior to drilling experiments, analyzing the cutting size distribution, and evaluating the applied drilling parameters as a function of WOB. These results are compared with those obtained from drilling without pVARD, which represents the typical rigid BHA of the conventional drilling.

Keywords: BHA, drilling performance, MSE, pVARD, rate of penetration, ROP, tensile and shear fractures, unconfined compressive strength

Procedia PDF Downloads 146

Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab

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Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.

Keywords: deep neural network, foot disorder, plantar pressure, support vector machine

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Francisco Toledo-Castillo, Pilar Peiró-Torres, María Josefa Sospedra-Baeza, Sergio Hidalgo-Fuentes

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The communication presented is about tasks that are been developed in the research project “safeRoute”, “Information safety system for professional road driving” (IPT-2012-110-370000). This R&D project was proposed by the consortium formed by Fagor Electronica la SEU 3 and the University of Valencia to the Ministry of Economy and Competitiveness, which approved it inside the INNPACTO subprogramme grants. Through this type of calls, the Ministry promote the innovative capacity of the Spanish companies and turn on the mechanism for competing internationally. With this kind of calls, private investments for technological and industrial development join their R & D resources with public entities to implement innovative project that could have an international exposure. Thus INNPACTO subprogramme promotes the creation of research projects with public-private partnerships that create exploitable final products. The “safeRoute” Project pretends develop a tool to help to make more safety the travels of commercial transport vehicles of goods and passengers. To achieve its objectives, the project is focused in three main lines of research: vehicle safety, the safety of the roads that they are using, and the safety which drivers do their job, their behaviour while they are driving. To improve safety, the project gives information about these three factors to all people that are involved in the safety of the professional transport. These three factors have influence to the occurrence of traffic accidents, thanks to the information provided and treated about these factors, we can achieve a significant reduction in occupational accidents in the transport sector. SafeRoute provide information about routes, vehicles, and driver behaviours, and in this manner pretends provide to transport companies a tool which could result in a safer driving results and could reduce their costs related to traffic accidents of their vehicles, in that way, this tool could help them to be more competitive, and give a more reliable service. This paper will focus mainly on the information about routes that drivers use to travel in their professional work, and how the researchers of this project have catalogued and evaluated these routes, and finally how that information will be provided to users.

Keywords: driver support systems, professional drivers, road safety, safeRoute

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Authors: R. Ramesh, K. K. Shivaraman

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The main aim of this paper is to handle the energy requirement in an efficient manner by merging the advanced digital communication and control technologies for smart grid applications. In order to reduce user home load during peak load hours, utility applies several incentives such as real-time pricing, time of use, demand response for residential customer through smart meter. However, this method provides inconvenience in the sense that user needs to respond manually to prices that vary in real time. To overcome these inconvenience, this paper proposes a convolutional neural network (CNN) with k-means clustering machine learning model which have ability to forecast energy requirement in short term, i.e., hour of the day or day of the week. By integrating our proposed technique with home energy management based on Bluetooth low energy provides predicted value to user for scheduling appliance in advanced. This paper describes detail about CNN configuration and k-means clustering algorithm for short-term energy forecasting.

Keywords: convolutional neural network, fuzzy logic, k-means clustering approach, smart home energy management

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Authors: Maciej Jedrzejczyk, Karolina Marzantowicz

Abstract:

Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.

Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids

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Authors: Dyah Titisari Widyastuti

Abstract:

Rail-station area development that is based on the concept of TOD (Transit Oriented Development) is principally oriented to pedestrian accessibility for daily mobility. The aim of this research is elaborating how far the existing physical elements of a rail-station district could facilitate pedestrian mobility and establish a pedestrian friendly district toward implementation of a TOD concept. This research was conducted through some steps: (i) mapping the rail-station area pedestrian sidewalk and pedestrian network as well as activity nodes and transit nodes, (ii) assessing the level of pedestrian sidewalk connectivity joining trip origin and destination. The research area coverage in this case is limited to walking distance of the rail station (around 500 meters or 10-15 minutes walking). The findings of this research on the current condition of the street and pedestrian sidewalk network and connectivity, show good preference for the foot modal share (more than 50%) is achieved. Nevertheless, it depends on the distance from the trip origin to destination.

Keywords: accessibility of daily mobility, pedestrian-friendly district, rail-station district, transit oriented development

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