Search results for: feed forward network

Authors: Aymen Sekhri, Emmanuel Kwabena Frimpong, Bolaji Mubarak Ayeyemi, Aleksi Hirvonen, Matias Hirvonen, Tedros Tesfay Andemichael

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Fixation identification, which involves isolating and identifying fixations and saccades in eye-tracking protocols, is an important aspect of eye-movement data processing that can have a big impact on higher-level analyses. However, fixation identification techniques are frequently discussed informally and rarely compared in any meaningful way. With two state-of-the-art algorithms, we will implement fixation detection and analysis in this work. The velocity threshold fixation algorithm is the first algorithm, and it identifies fixation based on a threshold value. For eye movement detection, the second approach is U'n' Eye, a deep neural network algorithm. The goal of this project is to analyze and visualize eye-tracking data from an eye gaze dataset that has been provided. The data was collected in a scenario in which individuals were shown photos and asked whether or not they recognized them. The results of the two-fixation detection approach are contrasted and visualized in this paper.

Keywords: human-computer interaction, eye-tracking, CNN, fixations, saccades

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Authors: Sallama Resen, Celal Öztürk

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Distance estimation between tow nodes has wide scope of surveillance and tracking applications. This paper suggests a Bluetooth Low Energy (BLE) technology as a media for transceiver and receiver signal in small indoor areas. As an example, BLE communication technologies used in child safety domains. Local network is designed to detect child position in indoor school area consisting Mobile Beacons (MB), Access Points (AP) and Smart Phones (SP) where MBs stuck in children’s shoes as wearable sensors. This paper presents a technique that can detect mobile beacons’ position and help finding children’s location within dynamic environment. By means of bluetooth beacons that are attached to child’s shoes, the distance between the MB and teachers SP is estimated with an accuracy of less than one meter. From the simulation results, it is shown that high accuracy of position coordinates are achieved for multi-mobile beacons in different environments.

Keywords: bluetooth low energy, child safety, mobile beacons, received signal strength

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Authors: Meet Patel, Darshan Patel, Nilay Shah

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Excess growth of wind-based renewable energy sources is required to identify the optimal location and damping capacity of doubly fed induction-generator-based (DFIG) wind farms while it penetrates into the transmission network. In this analysis, various ratings of DFIG wind farms are penetrated into the Single Machine Infinite Bus (SMIB ) at a different distance of the transmission line. On the basis of detailed examinations, a prime position is evaluated to maximize the stability of overall systems. A damping controller is designed at an optimum location to mitigate the small oscillations. The proposed model was validated using eigenvalue analysis, calculation of the participation factor, and time-domain simulation.

Keywords: DFIG, small signal stability, eigenvalues, time domain simulation

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Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

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Authors: Dimitrios Triantakonstantis, Demetris Stathakis

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Urban areas have been expanded throughout the globe. Monitoring and modeling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modeling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: artificial neural networks, CORINE, urban atlas, urban growth prediction

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Authors: Corentin Jankowiak, Aggelos Zacharopoulos, Caterina Brandoni

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In a context of increasing stress put on the electricity network by the decarbonization of many sectors, energy storage is likely to be the key mitigating element, by acting as a buffer between production and demand. In particular, the highest potential for storage is when connected closer to the loads. Yet, low voltage storage struggles to penetrate the market at a large scale due to the novelty and complexity of the solution, and the competitive advantage of fossil fuel-based technologies regarding regulations. Strong and reliable numerical simulations are required to show the benefits of storage located near loads and promote its development. The present study was restrained from excluding aggregated control of storage: it is assumed that the storage units operate independently to one another without exchanging information – as is currently mostly the case. A computationally light battery model is presented in detail and validated by direct comparison with a domestic battery operating in real conditions. This model is then used to develop Peak-Shaving (PS) control strategies as it is the decentralized service from which beneficial impacts are most likely to emerge. The aggregation of flatter, peak- shaved consumption profiles is likely to lead to flatter and arbitraged profile at higher voltage layers. Furthermore, voltage fluctuations can be expected to decrease if spikes of individual consumption are reduced. The crucial part to achieve PS lies in the charging pattern: peaks depend on the switching on and off of appliances in the dwelling by the occupants and are therefore impossible to predict accurately. A performant PS strategy must, therefore, include a smart charge recovery algorithm that can ensure enough energy is present in the battery in case it is needed without generating new peaks by charging the unit. Three categories of PS algorithms are introduced in detail. First, using a constant threshold or power rate for charge recovery, followed by algorithms using the State Of Charge (SOC) as a decision variable. Finally, using a load forecast – of which the impact of the accuracy is discussed – to generate PS. A performance metrics was defined in order to quantitatively evaluate their operating regarding peak reduction, total energy consumption, and self-consumption of domestic photovoltaic generation. The algorithms were tested on load profiles with a 1-minute granularity over a 1-year period, and their performance was assessed regarding these metrics. The results show that constant charging threshold or power are far from optimal: a certain value is not likely to fit the variability of a residential profile. As could be expected, forecast-based algorithms show the highest performance. However, these depend on the accuracy of the forecast. On the other hand, SOC based algorithms also present satisfying performance, making them a strong alternative when the reliable forecast is not available.

Keywords: decentralised control, domestic integrated batteries, electricity network performance, peak-shaving algorithm

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Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

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Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: big data, machine learning, ontology model, urban data model

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Authors: Patrizia Poscic, Sanja Candrlic, Danijela Jaksic

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The University of Rijeka, Department of Informatics participated in the Stand4Info project, co-financed by the European Union, with the main idea of an alignment of study programs with occupational and qualifications standards in the field of Informatics. A brief overview of our research methodology, goals and deliverables is shown. Our main research and project objectives were: a) development of occupational standards, qualification standards and study programs based on the Croatian Qualifications Framework (CROQF), b) higher education quality improvement in the field of information and communication sciences, c) increasing the employability of students of information and communication technology (ICT) and science, and d) continuously improving competencies of teachers in accordance with the principles of CROQF. CROQF is a reform instrument in the Republic of Croatia for regulating the system of qualifications at all levels through qualifications standards based on learning outcomes and following the needs of the labor market, individuals and society. The central elements of CROQF are learning outcomes - competences acquired by the individual through the learning process and proved afterward. The place of each acquired qualification is set by the level of the learning outcomes belonging to that qualification. The placement of qualifications at respective levels allows the comparison and linking of different qualifications, as well as linking of Croatian qualifications' levels to the levels of the European Qualifications Framework and the levels of the Qualifications framework of the European Higher Education Area. This research has made 3 proposals of occupational standards for undergraduate study level (System Analyst, Developer, ICT Operations Manager), and 2 for graduate (master) level (System Architect, Business Architect). For each occupational standard employers have provided a list of key tasks and associated competencies necessary to perform them. A set of competencies required for each particular job in the workplace was defined and each set of competencies as described in more details by its individual competencies. Based on sets of competencies from occupational standards, sets of learning outcomes were defined and competencies from the occupational standard were linked with learning outcomes. For each learning outcome, as well as for the set of learning outcomes, it was necessary to specify verification method, material, and human resources. The task of the project was to suggest revision and improvement of the existing study programs. It was necessary to analyze existing programs and determine how they meet and fulfill defined learning outcomes. This way, one could see: a) which learning outcomes from the qualifications standards are covered by existing courses, b) which learning outcomes have yet to be covered, c) are they covered by mandatory or elective courses, and d) are some courses unnecessary or redundant. Overall, the main research results are: a) completed proposals of qualification and occupational standards in the field of ICT, b) revised curricula of undergraduate and master study programs in ICT, c) sustainable partnership and association stakeholders network, d) knowledge network - informing the public and stakeholders (teachers, students, and employers) about the importance of CROQF establishment, and e) teachers educated in innovative methods of teaching.

Keywords: study program, qualification standard, occupational standard, higher education, informatics and computer science

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Authors: Moumita Chanda, Md. Fazlul Karim Patwary

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Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

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Authors: B. Madhevan, R. Sakkaravarthi, R. Diya

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The number and variety of mobile robot applications are increasing day by day, both in an industry and in our daily lives. First developed as a tool, nowadays mobile robots can be integrated as an entity in Internet-accessible resources. The present work is organized around four potential resources such as cloud computing, Internet of things, Big data analysis and Co-simulation. Further, the focus relies on integrating, analyzing and discussing the need for integrating Internet-accessible resources and the challenges deriving from such integration, and how these issues have been tackled. Hence, the research work investigates the concepts of the Internet-accessible resources from the aspect of the autonomous mobile robots with an overview of the performances of the currently available database systems. IaR is a world-wide network of interconnected objects, can be considered an evolutionary process in mobile robots. IaR constitutes an integral part of future Internet with data analysis, consisting of both physical and virtual things.

Keywords: internet-accessible resources, cloud computing, big data analysis, internet of things, mobile robot

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Authors: Tanu Aneja, Harsha Malaviya

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Capturing pose information in cricket shots poses several challenges, such as low-resolution videos, noisy data, and joint occlusions caused by the nature of the shots. In response to these challenges, we propose a CondDGConv-based framework specifically for cricket shot prediction. By analyzing the spatial-temporal relationships in batsman shot sequences from an annotated 2D cricket dataset, our model achieves a 97% accuracy in predicting shot types. This performance is made possible by conditioning the graph network on batsman 2D poses, allowing for precise prediction of shot outcomes based on pose dynamics. Our approach highlights the potential for enhancing shot prediction in cricket analytics, offering a robust solution for overcoming pose-related challenges in sports analysis.

Keywords: action recognition, cricket. sports video analytics, computer vision, graph convolutional networks

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Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

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In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

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Authors: Latifat Afolake Ogunfolabo, Hakeem Babafemi Ogunfolabo

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The gastrointestinal tract is densely populated with micro-organism which closely and intensively interacts with the host and ingested feed. Food borne infections are some of the major international challenges that lead to high mortality and also, antimicrobial resistance, which has been classified as a serious threat by World Health Organization. Samples of slaughtered cattle and goats intestines were collected and standard culture methods were used for bacteria isolation and identification. Minimum inhibitory concentration of commonly used antibiotic using modification of the disk diffusion method was carried out on isolates. The samples cultured were all positive to Pseudomonas aeruginosa (95% and 90%), Escherichia coli (85%), Salmonella typhi (70% and 60%), Staphylococcus aureus (75%and 100%), Micrococcus luteus (55% and35%), Bacillus macerans (60% and 5%), Bacillus cereus (25% and 20%), Clostridium perfringens (20% and 5%), Micrococcus varians (20% and 5%), Bacillus subtilis (25% and 5%), Streptococcus faecalis (40% and 25%) and Streptococcus faecium (15% and 10%) in goat and cattle respectively. Also, Proteus mirabilis (40%), Micrococcus luteus (35%), Proteus vulgaris (30%), Klebsiella aerogenes(15%) were isolated from cattle. The total coliform (13.55 x10⁵cfu/gm ± 1.77) and (20.30 x10⁵cfu/gm ± 1.27) counts were significantly higher than the total bacteria count (8.3 x10⁵cfu/gm ± 1.41) and (16.60 x10⁵cfu/gm ±0.49) for goat and cattle respectively. Selected Bacteria count of isolates showed that Staphylococcus aureus had the highest significant value (6.9 x10⁵cfu/gm ± 0.57) and (16.80 x10⁵cfu/gm ± 0.57) Escherichia coli (4.60 x10⁵cfu/gm ± 0.42) and (7.05 x10⁵cfu/gm ± 0.64) while the lowest significant value was obtained in Salmonella/Shigella (1.7 x10⁵cfu/gm ± 0.00) and (1.5 x10⁵cfu/gm ± 0.00) for goat and cattle respectively. Susceptibility of bacteria isolated from slaughtered goat and cattle intestine to commonly used antibiotics showed that the highest statistical significant value for zone of inhibition for goat was obtained for Ciprofloxacin (30.00 ± 2.25, 23.75 ± 2.49, 17.17 ± 1.40) followed by Augmentin (28.33 ± 1.22, 21. 83 ± 2.44, 16.67 ± 1.49), Erythromycin (27.75 ±1.48, 20.25 ± 1.29, 16.67 ± 1.26) while the lowest values were obtained for Ofloxacin (27.17 ± 1.89, 21.42 ± 2.19, 16.83 ± 1.26) respectively and values obtained for cattle are Ciprofloxacin (30.64 ± 1.6, 25.79 ± 1.76, 8.07 ± 11.49) followed by Augmentin (28.29 ± 1.33, 22.64 ± 1.82, 17.43 ± 1.55) Ofloxacin (26.57 ± 2.02, 20.79 ± 2.75, 16.21 ± 1.19) while the lowest values were obtained for Erythromycin (26.64 ± 1.49, 20.29 ± 1.49, 16.29 ± 1.33) at different dilution factor (10⁻¹, 10⁻², 10⁻³) respectively. The isolates from goat and cattle were all susceptible to Augmentin at the three different dilution factors. Some goat isolates are intermediate to Ciprofloxacin and Erythromycin at 10⁻² and 10⁻³, while resistance to Ciprofloxacin at 10⁻³ dilution factor. Ciprofloxacin and Ofloxacin at the dilution factors of 10⁻³ and 10⁻¹ for some cattle isolate and resistance were observed for Ofloxacin and Erythromycin at dilution of 10⁻³. These results indicate the susceptibilities and the antimicrobial resistance to commonly used antibiotic.

Keywords: antibiotic susceptibility, bacteria, cattle, goat, identification

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Authors: Gobinathan Devathasan, Kezia Devathasan

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Objective: To improve the current modified Broca-Wernicke-Lichtheim-Kussmaul speech schema and provide insight into autism. Methods: We reviewed the pertinent literature. Current findings, involving Brodmann areas 22, 46, 9,44,45,6,4 are based on neuropathology and functional MRI studies. However, in primary autism, there is no lucid explanation and changes described, whether neuropathology or functional MRI, appear consequential. Findings: We forward an enhanced model which may explain the enigma related to autism. Vowel output is subcortical and does need cortical representation whereas consonant speech is cortical in origin. Left lateralization is needed to commence the circuitry spin as our life have evolved with L-amino acids and left spin of electrons. A fundamental species difference is we are capable of three syllable-consonants and bi-syllable expression whereas cetaceans and songbirds are confined to single or dual consonants. The 4 key sites for speech are superior auditory cortex, Broca’s two areas, and the supplementary motor cortex. Using the Argand’s diagram and Reimann’s projection, we theorize that the Euclidean three dimensional synaptic neuronal circuits of speech are quantized to coherent waves, and then decoherence takes place at area 6 (spherical representation). In this quantum state complex, 3-consonant languages are instantaneously integrated and multiple languages can be learned, verbalized and differentiated. Conclusion: We postulate that evolutionary human speech is elevated to quantum interaction unlike cetaceans and birds to achieve the three consonants/bi-syllable speech. In classical primary autism, the sudden speech switches off and on noted in several cases could now be explained not by any anatomical lesion but failure of coherence. Area 6 projects directly into prefrontal saccadic area (8); and this further explains the second primary feature in autism: lack of eye contact. The third feature which is repetitive finger gestures, located adjacent to the speech/motor areas, are actual attempts to communicate with the autistic child akin to sign language for the deaf.

Keywords: quantum neuronal paradigm, cetaceans and human speech, autism and rapid magnetic stimulation, coherence and decoherence of speech

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Authors: Lata Shakya, Toshio Otsuki, Saori Imoto, Bijaya Krishna Shrestha, Umesh Bahadur Malla

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2015 Gorkha Nepal earthquake have damaged the human settlements in 14 districts of Nepal. Historic core areas of three principal cities namely Kathmandu, Lalitpur and Bhaktapur including numerous traditional ‘newari’ settlements in the peripheral areas have been either collapsed or severely damaged. Despite Government of Nepal and (international) non-government organisations’ attempt towards disaster risk management through the preparation of policies and guidelines and implementation of community-based activities, the recent ‘Gorkha’ earthquake has demonstrated the inadequate preparedness, poor implementation of a legal instrument, resource constraints, and managerial weakness. However, the social capital through community based institutions, self-help attitude, and community bond has helped a lot not only in rescue and relief operation but also in a post-disaster temporary shelter living thereby exhibiting the resilient power of the local community. Conducting a detailed case study of ‘Kaminani’ community with 42 houses at ward no. 16 of Bhaktapur municipality, this paper analyses the local community’s response and activities on the Gorkha earthquake in rescue and relief operation as well as in post disaster work. Leadership, the existence of internal/external aid, physical and human support are also analyzed. Social resource and networking are also explained through critical review of the existing community organisation and their activities. The research methodology includes literature review, field survey, and interview with community leaders and residents based on a semi-structured questionnaire. The study reveals that community carried their recovery process in four different phases: (i) management of emergency evacuation, (ii) constructing community owed temporary shelter for individuals, (iii) demolishing upper floors of the damaged houses, and (iv) planning for collaborative housing reconstruction. As territorial based organization, religion based agency and aim based institution exist in the survey area from pre-disaster time, it can be assumed that the community activists including leaders are well experienced to create aim-based group and manage teamwork to deal with various issues and problems collaboratively. Physical and human support including partial financial aid from external source as a result of community leader’s personal networking is extended to the community members. Thus, human/social resource and personal/social network play a crucial role in the recovery process. And to build such social capital, community should have potential from pre-disaster time.

Keywords: Gorkha Nepal earthquake, local community, recovery process, social resource, social network

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Authors: Petros Gkotsis, Anastasios Zouboulis, Manasis Mitrakas, Dimitrios Zamboulis, E. Peleka

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The most serious drawback in wastewater treatment using membrane bioreactors (MBRs) is membrane fouling which gradually leads to membrane permeability decrease and efficiency deterioration. This work is part of a research project that aims to develop an integrated methodology for membrane fouling control, using specific chemicals which will enhance the coagulation and flocculation of compounds responsible for fouling, hence reducing biofilm formation on the membrane surface and limiting the fouling rate acting as a pre-treatment step. For this purpose, a pilot-scale plant with fully automatic operation achieved by means of programmable logic controller (PLC) has been constructed and tested. The experimental set-up consists of four units: wastewater feed unit, bioreactor, membrane (side-stream) filtration unit and permeate collection unit. Synthetic wastewater was fed as the substrate for the activated sludge. The dissolved oxygen (DO) concentration of the aerobic tank was maintained in the range of 2-3 mg/L during the entire operation by using an aerator below the membrane module. The membranes were operated at a flux of 18 LMH while membrane relaxation steps of 1 min were performed every 10 min. Both commercial and composite coagulants are added in different concentrations in the pilot-scale plant and their effect on the overall performance of the ΜΒR system is presented. Membrane fouling was assessed in terms of TMP, membrane permeability, sludge filterability tests, total resistance and the unified modified fouling index (UMFI). Preliminary tests showed that particular attention should be paid to the addition of the coagulant solution, indicating that pipe flocculation effectively increases hydraulic retention time and leads to voluminous sludge flocs. The most serious drawback in wastewater treatment using MBRs is membrane fouling, which gradually leads to membrane permeability decrease and efficiency deterioration. This results in increased treatment cost, due to high energy consumption and the need for frequent membrane cleaning and replacement. Due to the widespread application of MBR technology over the past few years, it becomes clear that the development of a methodology to mitigate membrane fouling is of paramount importance. The present work aims to develop an integrated technique for membrane fouling control in MBR systems and, thus, contribute to sustainable wastewater treatment.

Keywords: coagulation, membrane bioreactor, membrane fouling, pilot plant

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Authors: Nadia Chagtmi, Nejla Rejab, Noureddine Boulejfen

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This paper presents a calibration approach based on artificial neural networks (ANN) to determine the envelop signal (I+jQ) of a six-port based receiver (SPR). The memory effects called also dynamic behavior and the nonlinearity brought by diode based power detector have been taken into consideration by the ANN. Experimental set-up has been performed to validate the efficiency of this method. The efficiency of this approach has been confirmed by the obtained results in terms of waveforms. Moreover, the obtained error vector magnitude (EVM) and the mean absolute error (MAE) have been calculated in order to confirm and to test the ANN’s performance to achieve I/Q recovery using the output voltage detected by the power based detector. The baseband signal has been recovered using ANN with EVMs no higher than 1 % and an MAE no higher than 17, 26 for the SPR excited different type of signals such QAM (quadrature amplitude modulation) and LTE (Long Term Evolution).

Keywords: six-port based receiver; calibration, nonlinearity, memory effect, artificial neural network

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Authors: A. P. Mikhailovich, V. V. Fomin, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Woody vegetation among the upper limit of its habitat is a sensitive indicator of biota reaction to regional climate changes. Quantitative assessment of temporal and spatial changes in the distribution of trees and plant biocenoses calls for the development of new modeling approaches based upon selected data from measurements on the ground level and ultra-resolution aerial photography. Statistical models were developed for the study area located in the Polar Urals. These models allow obtaining probabilistic estimates for placing Siberian Larch trees into one of the three age intervals, namely 1-10, 11-40 and over 40 years, based on the Weilbull distribution of the maximum horizontal crown projection. Authors developed the distribution map for larch trees with crown diameters exceeding twenty centimeters by deciphering aerial photographs made by a UAV from an altitude equal to fifty meters. The total number of larches was equal to 88608, forming the following distribution row across the abovementioned intervals: 16980, 51740, and 19889 trees. The results demonstrate that two processes can be observed in the course of recent decades: first is the intensive forestation of previously barren or lightly wooded fragments of the study area located within the patches of wood, woodlands, and sparse stand, and second, expansion into mountain tundra. The current expansion of the Siberian Larch in the region replaced the depopulation process that occurred in the course of the Little Ice Age from the late 13ᵗʰ to the end of the 20ᵗʰ century. Using data from field measurements of Siberian larch specimen biometric parameters (including height, diameter at root collar and at 1.3 meters, and maximum projection of the crown in two orthogonal directions) and data on tree ages obtained at nine circular test sites, authors developed a model for artificial neural network including two layers with three and two neurons, respectively. The model allows quantitative assessment of a specimen's age based on height and maximum crone projection values. Tree height and crown diameters can be quantitatively assessed using data from aerial photographs and lidar scans. The resulting model can be used to assess the age of all Siberian larch trees. The proposed approach, after validation, can be applied to assessing the age of other tree species growing near the upper tree boundaries in other mountainous regions. This research was collaboratively funded by the Russian Ministry for Science and Education (project No. FEUG-2023-0002) and Russian Science Foundation (project No. 24-24-00235) in the field of data modeling on the basis of artificial neural network.

Keywords: treeline, dynamic, climate, modeling

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Authors: Hamad Almebayedh, Chuxia Lin, Yu wang

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The environmental impact assessment (EIA) must be improved, assessed, and quality checked for human and environmental health and safety. Soil contamination is expanding, and sites and soil remediation activities proceeding around the word which simplifies the answer “quality soil characterization” will lead to “quality EIA” to illuminate the contamination level and extent and reveal the unknown for the way forward to remediate, countifying, containing, minimizing and eliminating the environmental damage. Spatial interpolation methods play a significant role in decision making, planning remediation strategies, environmental management, and risk assessment, as it provides essential elements towards site characterization, which need to be informed into the EIA. The Innovative 3D soil mapping and soil characterization technology presented in this research paper reveal the unknown information and the extent of the contaminated soil in specific and enhance soil characterization information in general which will be reflected in improving the information provided in developing the EIA related to specific sites. The foremost aims of this research paper are to present novel 3D mapping technology to quality and cost-effectively characterize and estimate the distribution of key soil characteristics in contaminated sites and develop Innovative process/procedure “assessment measures” for EIA quality and assessment. The contaminated site and field investigation was conducted by innovative 3D mapping technology to characterize the composition of petroleum hydrocarbons contaminated soils in a decommissioned oilfield waste pit in Kuwait. The results show the depth and extent of the contamination, which has been interred into a developed assessment process and procedure for the EIA quality review checklist to enhance the EIA and drive remediation and risk assessment strategies. We have concluded that to minimize the possible adverse environmental impacts on the investigated site in Kuwait, the soil-capping approach may be sufficient and may represent a cost-effective management option as the environmental risk from the contaminated soils is considered to be relatively low. This research paper adopts a multi-method approach involving reviewing the existing literature related to the research area, case studies, and computer simulation.

Keywords: quality EIA, spatial interpolation, soil characterization, contaminated site

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Authors: Abdullah Alshehab

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Governments worldwide are intensely focused on digitizing public transactions to establish reliable e-government services. The advent of new digital technologies and ongoing advancements in ICT have profoundly transformed business operations. Citizen engagement and participation in e-government services are crucial for the system's success. However, it is essential to measure and enhance citizen satisfaction levels to effectively evaluate and improve these systems. Citizen satisfaction is a key criterion that allows government institutions to assess the quality of their services. There is a strong connection between information quality, service quality, and system quality, all of which directly impact user satisfaction. Additionally, both system quality and information quality have indirect effects on citizen satisfaction. A causal map, which is a network diagram representing causes and effects, can illustrate these relationships. According to the literature, the main factors influencing citizen satisfaction are trust, reliability, citizen support, convenience, and transparency. This paper investigates the causal relationships among these factors and identifies any interrelatedness between them.

Keywords: e-government services, e-satisfaction, citizen satisfaction, causal map.

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Authors: Anne Öman

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Today in Sweden and in other countries, a variety of digital artefacts, such as laptops, tablets, interactive whiteboards, are being used at all school levels. From an educational perspective, digital artefacts challenge traditional teaching because they provide a range of modes for expression and communication and are not limited to the traditional medium of paper. Digital technologies offer new opportunities for representations and physical interactions with objects, which put forward the role of the body in interaction and learning. From a multimodal perspective the emphasis is on the use of multiple semiotic resources for meaning- making and the study presented here has examined the differential use of semiotic resources by pupils interacting in a digitally designed task in a primary school context. The instances analyzed in this paper come from a case study where the learning task was to create an advertising film in a film-software. The study in focus involves the analysis of a single case with the emphasis on the examination of the classroom setting. The research design used in this paper was based on a micro ethnographic perspective and the empirical material was collected through video recordings of small-group work in order to explore pupils’ communication within the group activity. The designed task described here allowed students to build, share, collaborate upon and publish the redesigned products. The analysis illustrates the variety of communicative modes such as body position, gestures, visualizations, speech and the interaction between these modes and the representations made by the pupils. The findings pointed out the importance of embodied communication during the small- group processes from a learning perspective as well as a pedagogical understanding of pupils’ representations, which were similar from a cultural literacy perspective. These findings open up for discussions with further implications for the school practice concerning the small- group processes as well as the redesigned products. Wider, the findings could point out how multimodal interactions shape the learning experience in the meaning-making processes taking into account that language in a globalized society is more than reading and writing skills.

Keywords: communicative learning, interactive learning environments, pedagogical issues, primary school education

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Authors: Hayder Shanbara, Felicite Ruddock, William Atherton, Ali Al-Rifaie

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In highways construction, Hot Mix Asphalt (HMA) is used predominantly as a paving material from many years. Around 90 percent of the world road network is laid by flexible pavements. However, there are some restrictions on paving hot mix asphalt such as immoderate greenhouse gas emission, rainy season difficulties, fuel and energy consumption and cost. Therefore, Cold Bitumen Emulsion Mixture (CBEM) is considered an alternative mix to the HMA. CBEM is the popular type of Cold Mix Asphalt (CMA). It is unheated emulsion, aggregate and filler mixtures, which can be prepared and mixed at ambient temperature. This research presents a simple and more practicable design procedure of CBEM and discusses limitations of this design. CBEM is a mixture of bitumen emulsion and aggregates that mixed and produced at ambient temperature. It is relatively easy to produce, but the design procedure that provided by Asphalt Institute (Manual Series 14 (1989)) pose some issues in its practical application.

Keywords: cold bitumen, emulsion mixture, design procedure, pavement

Procedia PDF Downloads 252

Authors: Mohammad Shams Esfand Abadi, Mohammad Ranjbar, Reza Ebrahimpour

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This work presents the distributed processing solution problem in a diffusion network based on the adapt then combine (ATC) and combine then adapt (CTA)selective partial update normalized least mean squares (SPU-NLMS) algorithms. Also, we extend this approach to dynamic selection affine projection algorithm (DS-APA) and ATC-DS-APA and CTA-DS-APA are established. The purpose of ATC-SPU-NLMS and CTA-SPU-NLMS algorithm is to reduce the computational complexity by updating the selected blocks of weight coefficients at every iteration. In CTA-DS-APA and ATC-DS-APA, the number of the input vectors is selected dynamically. Diffusion cooperation strategies have been shown to provide good performance based on these algorithms. The good performance of introduced algorithm is illustrated with various experimental results.

Keywords: selective partial update, affine projection, dynamic selection, diffusion, adaptive distributed networks

Procedia PDF Downloads 709

Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

Procedia PDF Downloads 283

Authors: Minh Quang Le, Dane Taylor

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Convection is a well-studied topic in fluid dynamics, yet it is less understood in the context of networks flows. Here, we incorporate techniques from topological data analysis (namely, persistent homology) to automate the detection and characterization of convective/cyclic/chiral flows over networks, particularly those that arise for irreversible Markov chains (MCs). As two applications, we study convection cycles arising under the PageRank algorithm, and we investigate chiral edges flows for a stochastic model of a bi-monomer's configuration dynamics. Our experiments highlight how system parameters---e.g., the teleportation rate for PageRank and the transition rates of external and internal state changes for a monomer---can act as homology regularizers of convection, which we summarize with persistence barcodes and homological bifurcation diagrams. Our approach establishes a new connection between the study of convection cycles and homology, the branch of mathematics that formally studies cycles, which has diverse potential applications throughout the sciences and engineering.

Keywords: homology, persistent homolgy, markov chains, convection cycles, filtration

Procedia PDF Downloads 139

Authors: Ander Pomposo

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Purpose: The aim of this study was to investigate the impact that dialogue has on the relationship between shared leadership and innovative behavior and the importance of dialogue in innovation. This study wants to contribute to the literature by providing theorists and researchers a better understanding of how to move forward in the studies of moderator variables in the relationship between shared leadership and team outcomes such as innovation. Methodology: A systematic review of the literature, originally adopted from the medical sciences but also used in management and leadership studies, was conducted to synthesize research in a systematic, transparent and reproducible manner. A final sample of 48 empirical studies was scientifically synthesized. Findings: Shared leadership gives a better solution to team management challenges and goes beyond the classical, hierarchical, or vertical leadership models based on the individual leader approach. One of the outcomes that emerge from shared leadership is team innovative behavior. To intensify the relationship between shared leadership and team innovative behavior, and understand when is more effective, the moderating effects of other variables in this relationship should be examined. This synthesis of the empirical studies revealed that dialogue is a moderator variable that has an impact on the relationship between shared leadership and team innovative behavior when leadership is understood as a relational process. Dialogue is an activity between at least two speech partners trying to fulfill a collective goal and is a way of living open to people and ideas through interaction. Dialogue is productive when team members engage relationally with one another. When this happens, participants are more likely to take responsibility for the tasks they are involved and for the relationships they have with others. In this relational engagement, participants are likely to establish high-quality connections with a high degree of generativity. This study suggests that organizations should facilitate the dialogue of team members in shared leadership which has a positive impact on innovation and offers a more adaptive framework for the leadership that is needed in teams working in complex work tasks. These results uncover the necessity of more research on the role that dialogue plays in contributing to important organizational outcomes such as innovation. Case studies describing both best practices and obstacles of dialogue in team innovative behavior are necessary to gain a more detailed insight into the field. It will be interesting to see how all these fields of research evolve and are implemented in dialogue practices in the organizations that use team-based structures to deal with uncertainty, fast-changing environments, globalization and increasingly complex work.

Keywords: dialogue, innovation, leadership, shared leadership, team innovative behavior

Procedia PDF Downloads 183

Authors: Jasraj Meena, Malay Kumar, Manu Vardhan

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Cloud computing is a new technology in industry and academia. The technology has grown and matured in last half decade and proven their significant role in changing environment of IT infrastructure where cloud services and resources are offered over the network. Cloud technology enables users to use services and resources without being concerned about the technical implications of technology. There are substantial research work has been performed for the usage of cloud computing in educational institutes and majority of them provides cloud services over high-end blade servers or other high-end CPUs. However, this paper proposes a new stack called “CiCKAStack” which provide cloud services over unutilized computing resources, named as commodity computers. “CiCKAStack” provides IaaS and PaaS using underlying commodity computers. This will not only increasing the utilization of existing computing resources but also provide organize file system, on demand computing resource and design and development environment.

Keywords: commodity computers, cloud-computing, KVM, CloudStack, AppScale

Procedia PDF Downloads 274

Authors: Emad A. Mohammed

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Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

Procedia PDF Downloads 147

Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

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Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

Procedia PDF Downloads 232

Authors: S. Fares, K. Mellakh, A. Hmouri

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The StorMer project aims to set up a network of researchers to study traditional hydraulic rainwater harvesting systems in the Mediterranean basin, a region suffering from the major impacts of climate change and limited natural water resources. The arid and semi-arid Mediterranean basin has a long history of pioneering water management practices. The region has developed various ancient traditional water management systems, such as cisterns and qanats, to sustainably manage water resources under historical conditions of scarcity. Therefore, the StorMer project brings together Spain, France, Italy, Greece, Jordan and Morocco to explore traditional rainwater harvesting practices and systems in the Mediterranean region and to develop accurate modeling to simulate the performance and sustainability of these technologies under present-day climatic conditions. The ultimate goal of this project was to resuscitate and valorize these practices in the context of contemporary challenges. This project was intended to establish a Mediterranean network to serve as a basis for a more ambitious project. The ultimate objective was to analyze traditional hydraulic systems and create a prototype hydraulic ecosystem using a coupled environmental approach and traditional and ancient know-how, with the aim of reinterpreting them in the light of current techniques. The combination of ‘traditional’ and ‘modern knowledge/techniques’ is expected to lead to proposals for innovative hydraulic systems. The pandemic initially slowed our progress, but in the end it forced us to carry out the fieldwork in Morocco and Saudi Arabia, and so restart the project. With the participation of colleagues from chronologically distant fields (archaeology, sociology), we are now prepared to share our observations and propose the next steps. This interdisciplinary approach should give us a global vision of the project's objectives and challenges. A diachronic approach is needed to tackle the question of the long-term adaptation of societies in a Mediterranean context that has experienced several periods of water stress. The next stage of the StorMer project is the implementation of pilots in non-urbanized regions. These pilots will test the implementation of traditional systems and will be maintained and evaluated in terms of effectiveness, cost and acceptance. Based on these experiences, larger projects will be proposed and could provide information for regional water management policies. One of the most important lessons learned from this project is the highly social nature of managing traditional rainwater harvesting systems. Unlike modern, centralized water infrastructures, these systems often require the involvement of communities, which assume ownership and responsibility for them. This kind of community engagement leads to greater maintenance and, therefore, sustainability of the systems. Knowledge of the socio-cultural characteristics of these communities means that the systems can be adapted to the needs of each location, ensuring greater acceptance and efficiency.

Keywords: oasis, rainfall harvesting, arid regions, Mediterranean

Procedia PDF Downloads 43