Search results for: low-temperature district heating network

Authors: Kulin Dave, Kapil Mohan

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Earthquakes are considered to be the most destructive rapid-onset disasters human beings are exposed to. The amount of loss it brings in is sufficient to take careful considerations for designing of structures and facilities. Seismic Hazard Analysis is one such tool which can be used for earthquake resistant design. Ground Response Analysis is one of the most crucial and decisive steps for seismic hazard analysis. Rapar district of Kutch, Gujarat falls in Zone 5 of earthquake zone map of India and thus has high seismicity because of which it is selected for analysis. In total 8 bore-log data were studied at different locations in and around Rapar district. Different soil engineering properties were analyzed and relevant empirical correlations were used to calculate maximum shear modulus (Gmax) and shear wave velocity (Vs) for the soil layers. The soil was modeled using Pressure-Dependent Modified Kodner Zelasko (MKZ) model and the reference curve used for fitting was Seed and Idriss (1970) for sand and Darendeli (2001) for clay. Both Equivalent linear (EL), as well as Non-linear (NL) ground response analysis, has been carried out with Masing Hysteretic Re/Unloading formulation for comparison. Commercially available DEEPSOIL v. 7.0 software is used for this analysis. In this study an attempt is made to quantify ground response regarding generated acceleration time-history at top of the soil column, Response spectra calculation at 5 % damping and Fourier amplitude spectrum calculation. Moreover, the variation of Peak Ground Acceleration (PGA), Maximum Displacement, Maximum Strain (in %), Maximum Stress Ratio, Mobilized Shear Stress with depth is also calculated. From the study, PGA values estimated in rocky strata are nearly same as bedrock motion and marginal amplification is observed in sandy silt and silty clays by both analyses. The NL analysis gives conservative results of maximum displacement as compared to EL analysis. Maximum strain predicted by both studies is very close to each other. And overall NL analysis is more efficient and realistic because it follows the actual hyperbolic stress-strain relationship, considers stiffness degradation and mobilizes stresses generated due to pore water pressure.

Keywords: DEEPSOIL v 7.0, ground response analysis, pressure-dependent modified Kodner Zelasko model, MKZ model, response spectra, shear wave velocity

Procedia PDF Downloads 136

Authors: Abhishek Jain, Kavish Kejriwal, V. Balaji Rao, Abhigna Chavda

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Increasing environmental and social concerns are forcing companies to take a fresh view of the impact of supply chain operations on environment and society when designing a supply chain. A challenging task in today’s food industry is the distribution of high-quality food items throughout the food supply chain. Improper storage and unwanted transportation are the major hurdles in food supply chain and can be tackled by making dynamic storage facility location decisions with the distribution network. Since food supply chain in India is one of the biggest supply chains in the world, the companies should also consider environmental impact caused by the supply chain. This project proposes a multi-objective optimization model by integrating sustainability in decision-making, on distribution in a food supply chain network (SCN). A Multi-Objective Mixed-Integer Linear Programming (MOMILP) model between overall cost and environmental impact caused by the SCN is formulated for the problem. The goal of MOMILP is to determine the pareto solutions for overall cost and environmental impact caused by the supply chain. This is solved by using GAMS with CPLEX as third party solver. The outcomes of the project are pareto solutions for overall cost and environmental impact, facilities to be operated and the amount to be transferred to each warehouse during the time horizon.

Keywords: multi-objective mixed linear programming, food supply chain network, GAMS, multi-product, multi-period, environment

Procedia PDF Downloads 320

Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

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Authors: Sukhbir Singh

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This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

Procedia PDF Downloads 120

Authors: Go Woon Kwak, Siyoung Jun, Soyun Maeng, Haeyoung Lee

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Entry is an education platform used in South Korea, created to help students learn to program, in which they can learn to code while playing. Using the online version of the entry, teachers can easily assign programming homework to the student and the students can make programs simply by linking programming blocks. However, the programs may be made by others, so that the authors of the programs should be identified. In this paper, as the first step toward author identification of entry programs, we present an artificial neural network based classification approach to identify genders of authors of a program written in an entry. A neural network has been trained from labeled training data that we have collected. Our result in progress, although preliminary, shows that the proposed approach could be feasible to be applied to the online version of entry for gender identification of authors. As future work, we will first use a machine learning technique for age identification of entry programs, which would be the second step toward the author identification.

Keywords: artificial intelligence, author identification, deep neural network, gender identification, machine learning

Procedia PDF Downloads 324

Authors: Siti Aslamyah, Yushinta Fujaya, Okto Rimaldi

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One of the problems faced in the crab hatchery operations is the reliance on the use of natural feed. This study aims to analyze the response of larval development and determine the initial stages crab larvae begin to fully able to accept artificial feeding predigest with the help of probiotic Bacillus sp. The experiment was conducted in June 2014 through July 2014 at the location of the scale backyard hatcheries, Bojo village Mallusettasi sub-district, district Barru. This study was conducted in two stages larval rearing. The first stage is designed in a completely randomized design with 5 treatments and each with 3 repetitions, ie, without the use of artificial feeding; predigest feed given from zoea 1 - megalopa; predigest feed given since zoea 2 - megalopa; predigest feed given from zoea 3 - megalopa; and feed predigest given since zoea 4 - megalopa. The second stage of the two treatments, i.e. comparing artificial feeding without and with predigest. The results showed that the artificial feeding predigest able to replace the use of natural feed started zoea 3 generated based on the survival rate. Artificial feeding predigest provide a higher survival rate (16%) compared to artificial diets without predigest only 10.8%. However, feed predigest not give a different effect on the rate of development of stadia. Cell activity in larvae that received artificial feed predigest higher with RNA-DNA ratio of 8.88 compared with no predigest only 5:36. This research is very valuable information for crab hatchery hatchery scale households have limitations in preparing natural food.

Keywords: artificial feeding, development of stadia, larvae Portunus pelagicus, predigest

Procedia PDF Downloads 533

Authors: Kemka Ihemelandu, Chukwuemeka Ihemelandu

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Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes, a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone, have increasingly been recognized as a problem.Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN)models. CNN models are prone to biased output due to biases in the dataset used to train them. Our aim in this study was the optimization of convolutional neural network algorithms to mitigate bias in the automated diagnosis of melanoma. We hypothesized that our proposed training algorithms based on a data augmentation method to optimize the diagnostic accuracy of a CNN classifier by generating new training samples from the original ones will reduce bias in the automated diagnosis of melanoma. We applied geometric transformation, including; rotations, translations, scale change, flipping, and shearing. Resulting in a CNN model that provided a modifiedinput data making for a model that could learn subtle racial features. Optimal selection of the momentum and batch hyperparameter increased our model accuracy. We show that our augmented model reduces bias while maintaining accuracy in the automated diagnosis of melanoma.

Keywords: bias, augmentation, melanoma, convolutional neural network

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Authors: Chia-Chi Chang

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Most battery-driven wireless sensor devices will enter in sleep mode as soon as possible to extend the overall lifetime of a sensor network. It is necessary to turn off unnecessary radio and peripheral functions, especially the radio unit always consumes more energy than other components during wireless communication. The microcontroller is the most important part of the wireless sensor device. It is responsible for the manipulation of sensing data and communication protocols. The microcontroller always has different sleep modes, each with a different level of energy usage. The deeper the sleep, the lower the energy consumption. Most wireless sensor devices can only enter the sleep mode: the external low-frequency oscillator is still running to wake up the sleeping microcontroller when the sleep timer expires. In this paper, our sensor device can enter the extended sleep mode: none of the oscillator is running and the wireless sensor device has the nanoampere consumption and self-awaking ability. Finally, these wireless sensor devices were deployed in a smart home security network.

Keywords: wireless sensor network, battery-driven, sleep mode, home security

Procedia PDF Downloads 307

Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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Authors: Fotis I. Giasemis, Alexandros Sopasakis

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This study focuses on detecting traffic anomalies using generative models applied to real-time observations. By integrating a Graph Neural Network with an attention-based mechanism within the Spatiotemporal Generative Adversarial Network framework, we enhance the capture of both spatial and temporal dependencies in traffic data. Leveraging minute-by-minute observations from cameras distributed across Gothenburg, our approach provides a more detailed and precise anomaly detection system, effectively capturing the complex topology and dynamics of urban traffic networks.

Keywords: traffic, anomaly detection, GNN, GAN

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Authors: David B. Kisakye, Paul Mugabi

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Biomass briquettes have been identified as a plausible and close alternative to commonly used energy fuels such as charcoal and firewood, whose prices are escalating due to the dwindling natural resource base. However, briquettes do not seem to be as popular as would be expected. This study assessed the production, distribution, and acceptability of the briquettes in the Kampala district. A total of 60 respondents, 50 of whom were briquette users and 10 briquette producers, were sampled from five divisions of Kampala district to evaluate consumer acceptability, preference for briquette type and shape. Households and institutions were identified to be the major consumers of briquettes, while community-based organizations were the major distributors of briquettes. The Chi-square test of independence showed a significant association between briquette acceptability and briquette attributes of substitutability and low cost (p < 0,05). The Kruskal Wallis test showed that low-income class people preferred non-carbonized briquettes. Gender, marital status, and income level also cause variation in preference for spherical, stick, and honeycomb briquettes (p < 0,05). The major challenges faced by briquette users in Kampala were; production of a lot of ash, frequent crushing, and limited access to briquettes. The producers of briquettes were mainly challenged by regular machine breakdown, raw material scarcity, and poor carbonizing units. It was concluded that briquettes have a market and are generally accepted in Kampala. However, user preferences need to be taken into account by briquette produces, suitable cookstoves should be availed to users, and there is a need for standards to ensure the quality of briquettes.

Keywords: consumer acceptability, biomass residues, briquettes, briquette producers, distribution, fuel, marketability, wood fuel

Procedia PDF Downloads 143

Authors: Nassiri Khalid, El Hibaoui Abdelaaziz et Hajar Moha

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In this paper, we introduce and analyse a probabilistic distributed algorithm for a construction of a minimum spanning tree on network. This algorithm is based on the handshake concept. Firstly, each network node is considered as a sub-spanning tree. And at each round of the execution of our algorithm, a sub-spanning trees are merged. The execution continues until all sub-spanning trees are merged into one. We analyze this algorithm by a stochastic process.

Keywords: Spanning tree, Distributed Algorithm, Handshake Algorithm, Matching, Probabilistic Analysis

Procedia PDF Downloads 658

Authors: Moshiur Rahman, Tahmida Jakia

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Bangladesh, a densely populated South Asian country is home to more than 160 million people. In two decades ago, the people of this developing nation drank heavily contaminated surface water. Over the past thirty years, the country, and its development partners, has undertaken extensive efforts to provide microbiologically safe groundwater based drinking water through the use of tube-wells. About 85% of the people now drink tube-well water from about 11 million tube-wells/hand pumps. However, diarrhoeal and other water-related diseases are still reported among the major causes of morbidity and mortality among Bangladeshi children. This implies that the mode of transmission of pathogens through water and/or other modes continue. In addition, massive scale arsenic contamination has been recently reported in the ground water. Thirty five million people may be at risk of consuming arsenic contaminated water exceeding 0.05 mg/l in Bangladesh. Drinking of arsenic contaminated water has been linked with skin problems, cancer, cardiovascular diseases, neurological diseases, eye problems, cancer of the internal organs, and other diseases. In the study area, Narail district, recent investigations about existing water quality situations indicated presence of low to high levels of arsenic, salinity, iron, manganese and bacteriological contamination risks. As challenges for safe water exist; it is likely that sanitation and food hygiene practices are poor which lead threat to ensure food security.The main attempt of this study is to find out the challenges to ensure food security andprovide probable solutions to ensure food safety towards 0.7 million of people in study area. A survey has been conducted at Lohagara and Kalia sub district of Narail district with a pretested questionnaire. Primary data are collected through a questionnaire, while secondary data are collected from pertinent offices as well as academic journals. FGD has also been done to know the knowledge regarding water, sanitation as well as food preparation and consumption practice of community people in study area. The major focus of this study is to assess the state of sanitation and food hygiene condition of rural people. It is found that most of the villagers have lack of knowledge about food safety. Open defecation rate is high which lead threat to ensure food security.

Keywords: food safety, challenges, hygiene, Bangladesh

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Authors: Manas Tripathi, Arunabha Mukhopadhyay

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In Cloud computing environment, cloud servers, sometimes may crash after receiving huge amount of request and cloud services may stop which can create huge loss to users of that cloud services. This situation is called Denial of Service (DoS) attack. In Distributed Denial of Service (DDoS) attack, an attacker targets multiple network paths by compromising various vulnerable systems (zombies) and floods the victim with huge amount of request through these zombies. There are many solutions to mitigate this challenge but most of the methods allows the attack traffic to arrive at Cloud Service Provider (CSP) and then only takes actions against mitigation. Here in this paper we are rather focusing on preventive mechanism to deal with these attacks. We analyze network topology and find most vulnerable paths beforehand without waiting for the traffic to arrive at CSP. We have used Dijkstra's and Yen’s algorithm. Finally, risk assessment of these paths can be done by multiplying the probabilities of attack for these paths with the potential loss.

Keywords: cloud computing, DDoS, Dijkstra, Yen’s k-shortest path, network security

Procedia PDF Downloads 278

Authors: Albana Hasimi, Edlira Tako, Elvin Çomo, Partizan Malkaj, Blerina Papajani, Ledjan Malaj, Mirela Ndrita

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Many endeavors have been exerted during the last years for developing new artificial polymeric membranes which fulfill the demanded conditions for biomedical uses. One of the most tested polymers is Poly(vinyl alcohol) [PVA]. Ours groups, is based on the possibility of using PVA for personal protective equipment against covid. In them, we explore the possibility of modifying the properties of the polymer by adding Montmorillonite [MMT]. Heat-treatment above the glass transition temperature are used to improve mechanical properties mainly by increasing the crystallinity of the polymer, which acts as a physical network. Temperature-Modulated Differential Scanning Calorimetry (TMDSC) measurements indicated that the presence of 0.5% MMT in PVA causes a higher Tg value and shaped peak of crystallinity. Decomposition is observed at two of the melting points of the crystals during heating 25-240oC and overlap of the recrystallization ridges during cooling 240-25oC. This is indicative of the presence of two types (quality or structure ) of polymer crystals. On the other hand, some indication of improvement of the quality of the crystals by heat-treatment is given by the distinct non-reversing contribution to melting. Data on sorption and transport of water in polyvinyl alcohol films: PVA pure and PVA/MMT matrix, modified by thermal treatment, are presented. The thermal treatment has aftereffect the films become more rigid, and because of this, the water uptake is significantly lower in membranes. That is indicates by analysis of the resulting water uptake kinetics. The presence 0.5% w/w of MMT has no significant impact on the properties of PVA membranes. Water uptake kinetics deviates from Fick’s law due to slow relaxation of glassy polymer matrix for all membranes category.

Keywords: crystallinity, montmorillonite, nanocomposite, poly (vinyl alcohol)

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Authors: Ather Saeed, Arif Khan, Jeffrey Gosper

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Sensor devices are prone to errors and sudden node failures, which are difficult to detect in a timely manner when deployed in real-time, hazardous, large-scale harsh environments and in medical emergencies. Therefore, the loss of data can be life-threatening when the sensed phenomenon is not disseminated due to sudden node failure, battery depletion or temporary malfunctioning. We introduce a set of partial differential equations for localizing faults, similar to Green’s and Maxwell’s equations used in Electrostatics and Electromagnetism. We introduce a node organization and clustering scheme for self-stabilizing sensor networks. Green’s theorem is applied to regions where the curve is closed and continuously differentiable to ensure network connectivity. Experimental results show that the proposed GTFD (Green’s Theorem fault-detection and Self-stabilization) protocol not only detects faulty nodes but also accurately generates network stability graphs where urgent intervention is required for dynamically self-stabilizing the network.

Keywords: Green’s Theorem, self-stabilization, fault-localization, RSSI, WSN, clustering

Procedia PDF Downloads 75

Authors: Jared Oluoch

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Connected vehicles are equipped with wireless sensors that aid in Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication. These vehicles will in the near future provide road safety, improve transport efficiency, and reduce traffic congestion. One of the challenges for connected vehicles is how to ensure that information sent across the network is secure. If security of the network is not guaranteed, several attacks can occur, thereby compromising the robustness, reliability, and efficiency of the network. This paper discusses existing security mechanisms and unique properties of connected vehicles. The methodology employed in this work is exploratory. The paper reviews existing security solutions for connected vehicles. More concretely, it discusses various cryptographic mechanisms available, and suggests areas of improvement. The study proposes a combination of symmetric key encryption and public key cryptography to improve security. The study further proposes message aggregation as a technique to overcome message redundancy. This paper offers a comprehensive overview of connected vehicles technology, its applications, its security mechanisms, open challenges, and potential areas of future research.

Keywords: VANET, connected vehicles, 802.11p, WAVE, DSRC, trust, security, cryptography

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Authors: Ahmed Tarek, Ahmed Alveed

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Vehicle routing problem is a well-known re-search avenue in computing. Modern vehicle routing is more focused with the GPS-based coordinate system, as the state-of-the-art vehicle, and trucking systems are equipped with digital navigation. In this paper, a new two dimensional coordinate-based algorithm for addressing the vehicle routing problem for a supply chain network is proposed and explored, and the algorithm is compared with other available, and recently devised heuristics. For the algorithms discussed, which includes the pro-posed coordinate-based search heuristic as well, the advantages and the disadvantages associated with the heuristics are explored. The proposed algorithm is studied from the stand point of a small supermarket chain delivery network that supplies to its stores in four different states around the East Coast area, and is trying to optimize its trucking delivery cost. Minimizing the delivery cost for the supply network of a supermarket chain is important to ensure its business success.

Keywords: coordinate-based optimal routing, Hamiltonian Circuit, heuristic algorithm, traveling salesman problem, vehicle routing problem

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Authors: Muhammad Zafarullah Khan, Sumeera Abbasi

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The Farmers Field School (FFS) learning approach aims to improve knowledge of the farmers through integrated crop management and provide leadership in their decision making process. The study was conducted to assess the impact of FFS on vegetables production before and after FFS intervention in four villages of district Peshawar in cropping season 2012, by interviewing 80 FFS respondents, twenty from each selected village. It was observed from the study results that all the respondents were satisfied from the impact of FFS and they informed an increased in production in vegetables. It was further observed that after the implementation of FFS the sowing seed rate of tomato and cucumber were decreased from 0.185kg/kanal to 0.100 kg/ kanal and 0.120kg/kanal to 0.010kg/kanal where as the production of tomato and cucumber were increased from 8158.75kgs/kanal to 10302. 5kgs/kanal and 3230kgs/kanal to 5340kgs/kanal, respectively. The cost of agriculture inputs per kanal including seed cost, crop management, Farm Yard Manure, and weedicides in case of tomato were reduced by Rs.28, Rs. 3170, Rs.658and Rs 205 whereas in cucumber reduced by Rs.35, Rs.570, Rs 80 and Rs.430 respectively. Only fertilizers cost was increased by Rs. 2200 in case of tomato and Rs 465 in case of cucumber. Overall the cost was reduced to Rs 545 in tomato and Rs 490 in cucumber production.FFS provided a healthy vegetables and also reduced input cost by adopting integrated crop management. Therefore the promotion of FFS is needed to be planned for farmers to reduce cost of production, so that the more farmers should be benefited.

Keywords: impact, farmer field schools, vegetable production, Peshawar Khyber Pakhtunkhwa

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Authors: Meron Okbandrias

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The South African formal economy is rule-based economy, unlike most African and Asian markets. It has a highly developed financial market. In such a market, foreign migrants have dominated the small or spaza shops that service the poor. They are highly competitive and capture significant market share in South Africa. This paper analyses the factors that assisted the foreign migrants in having a competitive age. It does that by interviewing Somali, Bangladesh, and Ethiopian shop owners in Cape Town analysing the data through a narrative analysis. The paper also analyses the 2019 South African consumer report. The three migrant nationalities mentioned above dominate the spaza shop business and have significant distribution networks. The findings of the paper indicate that family, ethnic, and nationality based network, in that order of importance, form bases for a relationship-based business network that has trust as its mainstay. Therefore, this network ensures the pooling of resources and abiding by certain principles outside the South African rule-based system. The research identified practises like bulk buying within a community of traders, sharing information, buying from a within community distribution business, community based transportation system and providing seed capital for people from the community to start a business is all based on that relationship-based system. The consequences of not abiding by the rules of these networks are social and economic exclusion. In addition, these networks have their own commercial and social conflict resolution mechanisms aside from the South African justice system. Network theory and relationship based systems theory form the theoretical foundations of this paper.

Keywords: migrant, spaza shops, relationship-based system, South Africa

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Authors: Rejab Hajlaoui, Tarek Moulahi, Hervé Guyennet

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In a highway scenario, the vehicle speed can exceed 120 kmph. Therefore, any vehicle can enter or leave the network within a very short time. This mobility adversely affects the network connectivity and decreases the life time of all established links. To ensure an effective stability in vehicular ad hoc networks with minimum broadcasting storm, we have developed a weighted algorithm based on the k-medoids clustering algorithm (WKCA). Indeed, the number of clusters and the initial cluster heads will not be selected randomly as usual, but considering the available transmission range and the environment size. Then, to ensure optimal assignment of nodes to clusters in both k-medoids phases, the combined weight of any node will be computed according to additional metrics including direction, relative speed and proximity. Empirical results prove that in addition to the convergence speed that characterizes the k-medoids algorithm, our proposed model performs well both AODV-Clustering and OLSR-Clustering protocols under different densities and velocities in term of end-to-end delay, packet delivery ratio, and throughput.

Keywords: communication, clustering algorithm, k-medoids, sensor, vehicular ad hoc network

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Authors: Marcio Leal, Marta Villamil

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Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: artificial neural network, computer vision, dynamic time warping, infrared, sign language recognition

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Authors: B. Kekezoglu, C. Kocatepe, O. Arikan, Y. Hacialiefendioglu, G. Ucar

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One of the significant problems of energy systems is to supply economic and efficient energy to consumers. Therefore studies has been continued to reduce technical losses in the network. In this paper, the technical losses analyzed for a portion of European side of Istanbul MV distribution network for different compensation scenarios by considering real system and load data and results are presented. Investigated system is modeled with CYME Power Engineering Software and optimal capacity placement has been proposed to minimize losses.

Keywords: distribution system, optimal capacitor placement, reactive power compensation, technical losses

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Authors: Eusebio Odiari, Mark Birkin, Susan Grant-Muller, Nicolas Malleson

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Big data typically refers to consumer datasets revealing some detailed heterogeneity in human behavior, which if harnessed appropriately, could potentially revolutionize our understanding of the collective phenomena of the physical world. Inadvertent missing values skew these datasets and compromise the validity of the thesis. Here we discuss a conceptually consistent strategy for identifying other relevant datasets to combine with available big data, to plug the gaps and to create a rich requisite comprehensive dataset for subsequent analysis. Specifically, emphasis is on how these methodologies can for the first time enable the construction of more detailed pictures of passenger demand and drivers of mobility on the railways. These methodologies can predict the influence of changes within the network (like a change in time-table or impact of a new station), explain local phenomena outside the network (like rail-heading) and the other impacts of urban morphology. Our analysis also reveals that our new imputation data model provides for more equitable revenue sharing amongst network operators who manage different parts of the integrated UK railways.

Keywords: big-data, micro-simulation, mobility, ticketing-data, commuters, transport, synthetic, population

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Authors: Nabila Ihaddadene, Razika Ihaddadene, Abdelwahaab Betka

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1973 energy crisis (rising oil prices) pushed the world to consider other alternative energy resources to existing conventional energies consisting predominantly of hydrocarbons. Renewable energies such as solar, the wind and geothermal have received renewed interest, especially to preserve nature ( the low-temperature rise of global environmental problems). Solar energy as an available, cheap and environmental friendly alternative source has various applications such as heating, cooling, drying, power generation, etc. In short, there is no life on earth without this enormous nuclear reactor, called the sun. Among available solar collector designs, flat plate collector (FPC) is low-temperature applications (heating water, space heating, etc.) due to its simple design and ease of manufacturing. Flat plate collectors are permanently fixed in position and do not track the sun (non-concentrating collectors). They operate by converting solar radiation into heat and transferring that heat to a working fluid (usually air, water, water plus antifreeze additive) flowing through them. An FPC generally consists of the main following components: glazing, absorber plate of high absorptivity, fluid tubes welded to or can be an integral part of the absorber plate, insulation and container or casing of the above-mentioned components. Insulation is of prime importance in thermal applications. There are three main families of insulation: mineral insulation; vegetal insulation and synthetic organic insulation. The old houses of the inhabitants of North Africa were built of brick made of composite material that is clay and straw. These homes are characterized by their thermal comfort; i.e. the air inside these houses is cool in summer and warm in winter. So, the material composed from clay and straw act as a thermal insulation. In this research document, the polystyrene used as insulation in the ET200 flat plate solar collector is replaced by the cheapest natural material which is clay and straw. Trials were carried out on a solar energy demonstration system (ET 200). This system contains a solar collector, water storage tank, a high power lamp simulating solar energy and a control and command cabinet. In the experimental device, the polystyrene is placed under the absorber plate and in the edges of the casing containing the components of the solar collector. In this work, we have replaced the polystyrene of the edges by the composite material. The use of the clay and straw as insulation instead of the polystyrene increases temperature difference (T2-T1) between the inlet and the outlet of the absorber by 0.9°C; thus increases the useful power transmitted to water in the solar collector. Tank Water is well heated when using the clay and straw as insulation. However, it is less heated when using the polystyrene as insulation. Clay and straw material improves also the performance of the solar collector by 5.77%. Thus, it is recommended to use this cheapest non-polluting material instead of synthetic insulation to improve the performance of the solar collector.

Keywords: clay, insulation material, polystyrene, solar collector, straw

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Authors: Kirill Neverov

Abstract:

In the paper is considered issues of civic participation in context of changing political landscape of Argentina. Last two years, this South American country faced a drastic change of political course. Pro-peronist, left-oriented administration of Christina Fernandez de Kirchner were replaced by right of center Mauricio Macri's one. The study is focused on inclusive policy in conditions of political transformations. We use network analysis to figure out which actors are involved in participation and to describe connections between them. As a resuflt, we plan to receive map of transactions which form inclusive policy in Argentina.

Keywords: civic participation, Argentina, political transformation, network analysis

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Authors: Ibrahim Hakeem

Abstract:

Biosolids are stabilised sewage sludge produced from wastewater treatment processes. Biosolids contain valuable plant nutrient which facilitates their beneficial reuse in agricultural land. However, the increasing levels of legacy and emerging contaminants such as heavy metals (HMs), PFAS, microplastics, pharmaceuticals, microbial pathogens etc., are restraining the direct land application of biosolids. Pyrolysis of biosolids can effectively degrade microbial and organic contaminants; however, HMs remain a persistent problem with biosolids and their pyrolysis-derived biochar. In this work, we demonstrated the integrated processing of biosolids involving the acid pre-treatment for HMs removal and selective reduction of ash-forming elements followed by the bench-scale pyrolysis of the treated biosolids to produce quality biochar and bio-oil enriched with valuable platform chemicals. The pre-treatment of biosolids using 3% v/v H₂SO₄ at room conditions for 30 min reduced the ash content from 30 wt% in raw biosolids to 15 wt% in the treated sample while removing about 80% of limiting HMs without degrading the organic matter. The preservation of nutrients and reduction of HMs concentration and mobility via the developed hydrometallurgical process improved the grade of the treated biosolids for beneficial land reuse. The co-removal of ash-forming elements from biosolids positively enhanced the fluidised bed pyrolysis of the acid-treated biosolids at 700 ℃. Organic matter devolatilisation was improved by 40%, and the produced biochar had higher surface area (107 m²/g), heating value (15 MJ/kg), fixed carbon (35 wt%), organic carbon retention (66% dry-ash free) compared to the raw biosolids biochar with surface area (56 m²/g), heating value (9 MJ/kg), fixed carbon (20 wt%) and organic carbon retention (50%). Pre-treatment also improved microporous structure development of the biochar and substantially decreased the HMs concentration and bioavailability by at least 50% relative to the raw biosolids biochar. The integrated process is a viable approach to enhancing value recovery from biosolids.

Keywords: biosolids, pyrolysis, biochar, heavy metals

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Authors: Junia Braga, Antonio carlos Martins, Marcos Racilan

Abstract:

Drawing on the ecological approach, this paper reports a qualitative study that aims to understand how mobile technologies were integrated during the pandemic in the context of language teaching and the use of these technologies in post-pandemic times. Seventy-six teachers answered a questionnaire about their experiences. The findings show how the network with peers scaffolded this experience and played a crucial role in their appropriation of those technologies. They also suggest that this network may have contributed to the normalisation of digital technology use.

Keywords: ecological perspective, language teaching, mobile technologies, teacher education

Procedia PDF Downloads 108

Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

Abstract:

The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

Procedia PDF Downloads 119

Authors: Mayank Sharma

Abstract:

Groundwater has been a matter of great concern in the past years due to the depletion in the water table. This has resulted from the over-exploitation of groundwater resources. Sub-surface exploration of groundwater is a great way to identify the groundwater potential of an area. Thus, in order to meet the water needs for irrigation in the study area, there was a need for a tube well to be installed. Therefore, a Geophysical investigation was carried out to find the most suitable point of drilling and sinking of tube well that encounters an aquifer. Hence, an electrical resistivity survey of geophysical exploration was used to know the aquifer zones of the area. The Vertical Electrical Sounding (VES) method was employed to know the subsurface geology of the area. Seven vertical electrical soundings using Schlumberger electrode array were carried out, having the maximum AB electrode separation of 700m at selected points in Ayma, Kharagpur-1 block of Paschim Midnapore district, West Bengal. The VES was done using an IGIS DDR3 Resistivity meter up to an approximate depth of 160-180m. The data was interpreted, processed and analyzed. Based on all the interpretations using the direct method, the geology of the area at the points of sounding was interpreted. It was established that two deeper clay-sand sections exist in the area at a depth of 50-70m (having resistivity range of 40-60ohm-m) and 70-160m (having resistivity range of 25-35ohm-m). These aquifers will provide a high yield of water which would be sufficient for the desired irrigation in the study area.

Keywords: VES method, Schlumberger method, electrical resistivity survey, geophysical exploration

Procedia PDF Downloads 196