Search results for: low-temperature district heating network

Authors: Irna Farikhah

Abstract:

Converting low-grade waste heat into useful energy such as sound energy which can then be used to generate acoustic power in a thermoacoustic engine has become an attracting issue for researchers. The generated power in thermoacoustic engine can be used for driving a thermoacoustic cooler when they are installed in a tube. This cooler system can be called as a heat-driven thermoacoustic cooler. In this study, low heating temperature of the engine is discussed. In addition, having high efficiency of the whole cooler is also essential. To design a thermoacoustic cooler having high efficiency with using low-grade waste heat for the engine, the effect of mean pressure is investigated. By increasing the mean pressure, the heating temperature to generate acoustic power can be decreased from 557 °C to 300 °C. Moreover, the efficiency of the engine and cooler regenerators attain 67% and 47% of the upper limit values, respectively and 49% of the acoustical work generated by the engine regenerator is utilized in the cooler regenerator. As a result, the efficiency of the whole cooler becomes 15% of the upper limit value.

Keywords: cooler, mean pressure, performance, thermoacoustic

Procedia PDF Downloads 257

Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

Abstract:

The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

Procedia PDF Downloads 418

Authors: Tamekloe Michael Kossivi, Kenichi Matsui

Abstract:

Irrigation access is one of the essential rural development investment options that can significantly improve smallholder farmers’ agriculture productivity. Investment in irrigation infrastructural development to supply adequate water could improve food security, growth in income for farmers, poverty alleviation, and improve business and livelihood. This paper assesses smallholder farmers’ constraints and the needs to adopt small-scale irrigation for crops production in the South Tongu District of Ghana. The data collection involved database search, questionnaire survey, interview, and field work. The structured questionnaire survey was administered from September to November 2020 among 120 respondents in six purposively sampled irrigation communities in the District. The questions focused on small-scale irrigation development constraints and needs. As a result, we found that the respondents relied mainly on rainfall for agriculture production. They did not have adequate irrigation access. Even though the District is blessed with open arable lands and rich water sources for rice and vegetable production on a massive scale, water sources like the Lower Volta River, Tordzi River, and Avu Lagoon were not close enough to the respondents. The respondents faced inadequate credit support (100%), unreliable rainfall (76%), insufficient water supply (54%), and unreliable water delivery challenges on their farms (53%). Physical constraints for the respondents to adopt irrigation included flood (77%), drought (93%), inadequate irrigation technology (59%), and insufficient technical know-how (65%). Farmers were interested in investing in irrigation infrastructural development to enhance productivity on their farms only if they own the farmlands. External support from donors on irrigation systems did not allow smallholder farmers to control irrigation facilities.

Keywords: constraints, food security, needs, smallholder farmers, small-scale irrigation

Procedia PDF Downloads 137

Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez, Mehdi Mrad

Abstract:

We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defender-based-network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k > 1. We investigate some variations of the problem and suggest polynomial-time solutions.

Keywords: defense/attack strategies, large scale, networks, partitioning a network

Procedia PDF Downloads 283

Authors: Vishal H. Shukla, Sanjay B. Deshmukh

Abstract:

Traffic engineering, at its center, is the ability of moving traffic approximately so that traffic from a congested link is moved onto the unused capacity on another link. Traffic Engineering ensures the best possible use of the resources. Now to support traffic engineering in the today’s network, Multiprotocol Label Switching (MPLS) is being used which is very helpful for reliable packets delivery in an ongoing internet services. Here a topology is been implemented on GNS3 to focus on the analysis of the communication take place from one site to other through the ISP. The comparison is made between the IP network & MPLS network based on Bandwidth & Jitter which are one of the performance parameters using JPERF simulator.

Keywords: GNS3, JPERF, MPLS, traffic engineering, VMware

Procedia PDF Downloads 487

Authors: Afaneen Anwer, Samara M. Kamil

Abstract:

Load Forecast required prediction accuracy based on optimal operation and maintenance. A good accuracy is the basis of economic dispatch, unit commitment, and system reliability. A good load forecasting system fulfilled fast speed, automatic bad data detection, and ability to access the system automatically to get the needed data. In this paper, the formulation of the load forecasting is discussed and the solution is obtained by using artificial neural network method. A MATLAB environment has been used to solve the load forecasting schedule of Iraqi super grid network considering the daily load for three years. The obtained results showed a good accuracy in predicting the forecasted load.

Keywords: load forecasting, neural network, back-propagation algorithm, Iraqi power system

Procedia PDF Downloads 583

Authors: Prasenjit Singha, Sunil Yadav, Soumya Ranjan Mohantry, Ajay Kumar Shukla

Abstract:

Temperature distribution in the hematite ore mixed with 7.5% coal was predicted by solving a 1-D heat conduction equation using an implicit finite difference approach. In this work, it was considered a square slab of 20 cm x 20 cm, which assumed the coal to be uniformly mixed with hematite ore. It was solved the equations with the use of MATLAB 2018a software. Heat transfer effects in this 1D dimensional slab convective and the radiative boundary conditions are also considered. Temperature distribution obtained inside hematite slab by considering microwave heating time, thermal conductivity, heat capacity, carbon percentage, sample dimensions, and many other factors such as penetration depth, permittivity, and permeability of coal and hematite ore mixtures. The resulting temperature profile can be used as a guiding tool for optimizing the microwave-assisted carbothermal reduction process of hematite slab was extended to other dimensions as well, viz., 1 cm x 1 cm, 5 cm x 5 cm, 10 cm x 10 cm, 20 cm x 20 cm. The model predictions are in good agreement with experimental results.

Keywords: hematite ore, coal, microwave processing, heat transfer, implicit method, temperature distribution

Procedia PDF Downloads 169

Authors: Boukari Nassim

Abstract:

This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.

Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network

Procedia PDF Downloads 346

Authors: Zeta Dooly, Aidan Duane

Abstract:

The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

Procedia PDF Downloads 126

Authors: Yue Sun, Yuan Wang

Abstract:

Most of the earliest national industries in Wuhan are located along the Hanjiang River, and Qiaokou is considered to be a gathering place for Dahankou old industrial base. Zongguan Waterworks, Pacific Soap Factory, Fuxin Flour Factory, Nanyang Tobacco Factory and other hundred-year-old factories are located along Hanjiang River in Qiaokou District, especially the Gutian Industrial Zone, which was listed as one of 156 national restoration projects at the beginning of the founding of the People’s Republic of China. After decades of development, Qiaokou has become the gathering place of the chemical industry and secondary industry, causing damage to the city and serious pollution, becoming a marginalized area forgotten by the central city. In recent years, with the accelerated pace of urban renewal, Qiaokou has been constantly reforming and innovating, and has begun drastic changes in the transformation of old cities and the development of new districts. These factories have been listed as key reconstruction projects, and a large number of industrial heritage with historical value and full urban memory have been relocated, demolished and reformed, with only a few factory buildings preserved. Through the methods of industrial archaeology, image analysis, typology and field investigation, this paper analyzes and summarizes the spatial characteristics of industrial heritage in Qiaokou District, explores urban renewal from the perspective of industrial heritage protection, and provides design strategies for the regeneration of urban industrial sites and industrial heritage.

Keywords: industrial heritage, urban renewal, protection, urban memory

Procedia PDF Downloads 145

Authors: Ahmad Fauzi Makarim, Okkie Puspitorini, Hani'ah Mahmudah, Nur Adi Siswandari, Ari Wijayanti

Abstract:

As a maritime country, Indonesia needs a solution in maritime connectivity which can assist the maritime communication system which including communication from harbor to the ship or ship to ship. The needs of many application services for maritime communication, whether for safety reasons until voyage service to help the process of voyage activity needs connection with a high bandwith. To support the government efforts in handling that kind of problem, a research is conducted in maritime communication issue by applying the new developed technology in Indonesia, namely IEEE 802.11. In this research, 3 outdoor WiFi devices are used in which have a frequency of 5.8 GHz. Maritime of Tanjung Perak harbor in Surabaya until Karang Jamuang Island are used as the location of the research with defining permission of ship node spreading by Navigation District Class 1. That maritime area formed by state 1 and state 2 areas which are the narrow area with average wave height of 0.7 meter based on the data from BMKG S urabaya. After that, wave height used as one of the parameters which are used in analyzing characteristic of signal propagation at sea surface, so it can be determined on the coverage area of transmitter system. In this research has been used three samples of outdoor wifi, there is the coverage of device A can be determined about 2256 meter, device B 4000 meter, and device C 1174 meter. Then to analyze of network connectivity for the ship to ship is used AODV routing algorithm system based on the value of the power transmit was smallest of all nodes within the transmitter coverage.

Keywords: maritime of Indonesia, maritime communications, outdoor wifi, coverage, AODV

Procedia PDF Downloads 351

Authors: Gjergji Buzo

Abstract:

This paper presents the communist policy about tangible and intangible religious heritage in Pogradec District, Albania. The district of Pogradec lies in the southeast of Albania and consists of the municipality, located on the shore of Ohrid Lake, and 7 Administrative Units, with a population of about 61,530 inhabitants. From the statistical data provided by the Institute of Statistics, the city of Pogradec has 55.9% Muslims, 19.9% Orthodox, 1.4% Catholic and 1.1% Bektashi. While the religious affiliation in the Administrative Unit is as follows: Muslim 72.1%, Orthodox 3.32%, Catholic 1.18%, Bektashi 0.2%. The percentages are approximate values, taking into consideration that 13.8% of the total population preferred not to answer the question on religion and that for 2.4% of the persons who answered, the information provided was not relevant or stated. The percentage of the persons who declared themselves as believers without belonging to any religion was 5.5 and the persons who declared themselves as a non-believer and not belonging to any religion was 2.5. Number of persons who declared themselves as evangelists was 0.1% and the number of them declared as "other Christians" was 0.1%. About 80% of the population believe in God, and most of them practice one of the monotheist religions. We have divided religious practices into three major periods. The first is until 1967, when different religions were practiced in Pogradec in harmony with each other; the second is the period 1967-1990, during which the practice of religion was prohibited, and the period after 1990, when religious freedom was restored. This article is focused on the communist period 1967-1990 when Albania (and Pogradec as part of it) became the only atheist country in the world. The object of the study is the impact of these policies on spiritual and material religious identity. The communist regime destroyed or transformed the religious objects, whether Islamic or Christian and prohibited practicing religious rituals in Albania. They followed an education policy with an atheistic spirituality among young people, characterizing religion as opium for the people. All these left traces on the people and brought a deformation of the religious identity. In order to better understand the reality of that time and how this policy was experienced by the people, we conducted a survey in Pogradect District with the participation of 1000 people.

Keywords: communism policy, heritage, identity, religion, statistics, survey

Procedia PDF Downloads 65

Authors: Wanida Suwunniponth

Abstract:

The purpose of this research was to investigate the relationship between the factors of using online social network for tourism destination in case of Bangkok area in Thailand, by extending the use of technology acceptance model (TAM). This study employed by quantitative research and the target population were entrepreneurs and local people in Bangkok who use social network-Facebook concerning tourist destinations in Bangkok. Questionnaire was used to collect data from 300 purposive samples. The multiple regression analysis and path analysis were used to analyze data. The results revealed that most people who used Facebook for promoting tourism destinations in Bangkok perceived ease of use, perceived usefulness, perceived trust in using Facebook and influenced by social normative as well as having positive attitude towards using this application. Addition, the hypothesis results indicate that acceptance of online social network-Facebook was related to the positive attitude towards using of Facebook and related to their intention to use this application for tourism.

Keywords: Facebook, online social network, technology acceptance model, tourism destination

Procedia PDF Downloads 343

Authors: Molla Tadesse Lakew

Abstract:

This study was intended to identify the factors influencing the use of mobile phones in vegetable marketing in Fogera district. The use of mobile phones in vegetable marketing and factors influencing mobile phone use were specific objectives of the study. Three kebeles from the Fogera district were selected purposively based on their vegetable production potential. A simple random sampling technique (lottery method) was used to select 153 vegetable producer farmers. Interview schedule and key informants interviews were used to collect primary data. For analyzing the data, descriptive statistics like frequency and percentage, two independent t-tests, and chi-square were used. Furthermore, econometric analysis (binary logistic model) was used to assess the factors influencing mobile phone use for vegetable market information. Contingency coefficient and variance inflation factor were used to check multicollinearity problems between the independent variables. Of 153 respondents, 82 (61.72%) were mobile phone users, while 71 (38.28 %) were mobile phone nonusers. Moreover, the main use of mobile phones in vegetable marketing includes communicating at a distance to save time and minimizing transport costs, getting vegetable marketing price information, identifying markets and buyers to sell the vegetable, deciding when to sell the vegetable, negotiating with buyers for better vegetable prices and for searching of the fast market to avoid from losing of product through perishing. The model result indicated that the level of education, size of land, income, access to credit, and age were significant variables affecting the use of mobile phones in vegetable marketing. It could be recommended to encourage adult education or give training for farmers on how to operate mobile phones and create awareness for the elderly rural farmers as they are able to use the mobile phone for their vegetable marketing. Moreover, farmers should be aware that mobile phones are very important for those who own very small land to get maximum returns from their production. Lastly, providing access to credit and improving and diversifying income sources for the farmers to have mobile phones were recommended to improve the livelihood of farmers.

Keywords: mobile phone, farmers, vegetable marketing, Fogera District

Procedia PDF Downloads 73

Authors: Kebede Mengistu, Kassahun Alemu, Bikes Destaw

Abstract:

Introduction: Malnutrition continues to be a major public health problem in developing countries. It is the most important risk factor for the burden of diseases. It causes about 300, 000 deaths per year and responsible for more than half of all deaths in children. In Ethiopia, child malnutrition rate is one of the most serious public health problem and the highest in the world. High malnutrition rates in the country pose a significant obstacle to achieving better child health outcomes. Objective: To assess prevalence of malnutrition and associated factors among children aged 6-59 months at Hidabu Abote district, North shewa, Oromia. Methods: A community based cross sectional study was conducted on 820 children aged 6-59 months from September 8-23, 2012 at Hidabu Abote district. Multistage sampling method was used to select households. Children were selected from each kebeles by simple random sampling. Anthropometric measurements and structured questioners were used. Data was processed using EPi-info soft ware and exported to SPSS for analysis. Then after, sex, age, months, height, and weight transferred with HHs number to ENA for SMART 2007software to convert nutritional data into Z-scores of the indices; H/A, W/H and W/A. Bivariate and multivariate logistic regressions were used to identify associated factors of malnutrition. Results: The analysis this study revealed that, 47.6%, 30.9% and 16.7% of children were stunted, underweight and wasted, respectively. The main associated factors of stunting were found to be child age, family monthly income, children were received butter as pre-lacteal feeding and family planning. Underweight was associated with number of children HHs and children were received butter as per-lacteal feeding but un treatment of water in HHs only associated with wasting. Conclusion and recommendation: From the findings of this study, it is concluded that malnutrition is still an important problem among children aged 6-59 months. Therefore, especial attention should be given on intervention of malnutrition.

Keywords: children, Hidabu Abote district, malnutrition, public health

Procedia PDF Downloads 427

Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

Abstract:

This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

Procedia PDF Downloads 643

Authors: Yan Jia Jun

Abstract:

This paper analyzes procedural compliance and the handling of duty fulfillment applications in administrative lawsuits in China and Singapore. By examining cases such as Nanning Jiangnan District Market Supervision Bureau v. Yan Jiajun, Zhuzhou Tianyuan District Market Supervision Bureau v. Yan Wengao from China, and Tan Seet Eng v. Housing and Development Board (HDB) from Singapore, the study explores how procedural fairness affects litigation outcomes and governance. The paper concludes that both countries face challenges in procedural compliance, but also highlights unique approaches and lessons that can be drawn from each jurisdiction to improve governance, transparency, and legal compliance in administrative processes.

Keywords: administrative law, duty fulfillment, procedural justice, judicial review, administrative governance, government transparency, China-Singapore comparison

Procedia PDF Downloads 20

Authors: A. Hakimiyan, H. Namazi

Abstract:

Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

Procedia PDF Downloads 663

Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

Abstract:

Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat (APT), malware, network security, network packet, exploit kits

Procedia PDF Downloads 366

Authors: Bahareh Montakhabi

Abstract:

Earthquake is known as one of the deadliest natural disasters, with a high potential for damage to life and property. Some of Iran's cities were completely destroyed after major earthquakes, and the people of the region suffered a lot of mental, financial and psychological damage. Tehran is one of the cities located on the fault line. According to experts, the only city that could be severely damaged by a moderate earthquake in Earthquake Engineering Intensity Scale (EEIS) (70% destruction) is Tehran because Tehran is built precisely on the fault. Seismic risk assessment (SRA) of cities in the scale of urban areas and neighborhoods is the first phase of the earthquake crisis management process, which can provide the information required to make optimal use of available resources and facilities in order to reduce the destructive effects and consequences of an earthquake. This study has investigated strategies to promote safety and reduce the vulnerability of worn-out urban textures in the District 12 of Tehran to the potential risk of earthquake aimed at prioritizing the factors affecting the vulnerability of worn-out urban textures to earthquake crises and how to reduce them, using the analytical-exploratory method, analytical hierarchy process (AHP), Expert choice and SWOT technique. The results of SWAT and AHP analysis of the vulnerability of the worn-out textures of District 12 to internal threats (1.70) and external threats (2.40) indicate weak safety of the textures of District 12 regarding internal and external factors and a high possibility of damage.

Keywords: risk management, vulnerability, worn-out textures, earthquake

Procedia PDF Downloads 193

Authors: Jiawen Wang, Qijun Chen

Abstract:

The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

Procedia PDF Downloads 130

Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

Abstract:

Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

Procedia PDF Downloads 95

Authors: Trupti Chavan, Ramachandra Guda, Kameshwar Rao

Abstract:

The lack of data is a pain problem in medical image analysis using a convolutional neural network (CNN). This work uses various spatial transformation techniques to address the medical image augmentation issue for knee detection and localization using an enhanced single shot detector (SSD) network. The spatial transforms like a negative, histogram equalization, power law, sharpening, averaging, gaussian blurring, etc. help to generate more samples, serve as pre-processing methods, and highlight the features of interest. The experimentation is done on the OpenKnee dataset which is a collection of knee images from the openly available online sources. The CNN called enhanced single shot detector (SSD) is utilized for the detection and localization of the knee joint from a given X-ray image. It is an enhanced version of the famous SSD network and is modified in such a way that it will reduce the number of prediction boxes at the output side. It consists of a classification network (VGGNET) and an auxiliary detection network. The performance is measured in mean average precision (mAP), and 99.96% mAP is achieved using the proposed enhanced SSD with spatial transformations. It is also seen that the localization boundary is comparatively more refined and closer to the ground truth in spatial augmentation and gives better detection and localization of knee joints.

Keywords: data augmentation, enhanced SSD, knee detection and localization, medical image analysis, openKnee, Spatial transformations

Procedia PDF Downloads 154

Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

Abstract:

The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

Procedia PDF Downloads 283

Authors: Sohaibullah Zarghoon, Syed Yousaf, Cyril Belavy, Stanislav Duris, Samuel Emebu, Radek Matusu

Abstract:

Induction heating is extensively employed in industrial furnaces due to its swift response and high energy efficiency. Designing and optimising these furnaces necessitates the use of computer-aided simulations. This study aims to develop an accurate temperature field model for a rectangular steel billet in an induction furnace by leveraging various parameters in COMSOL Multiphysics software. The simulation analysis incorporated temperature dynamics, considering skin depth, temperature-dependent, and constant parameters of the steel billet. The resulting data-driven model was transformed into a state-space model using MATLAB's System Identification Toolbox for the purpose of designing a linear quadratic regulator (LQR). This controller was successfully implemented to regulate the core temperature of the billet from 1000°C to 1200°C, utilizing the distributed parameter system circuit.

Keywords: induction heating, LQR controller, skin depth, temperature field

Procedia PDF Downloads 41

Authors: Dorota Galeza

Abstract:

This paper argues that networks, such as the ECN and the American network, are affected by certain small events which are inherent to path dependence and preclude the full evolution towards efficiency. It is advocated that the American network is superior to the ECN in many respects due to its greater flexibility and longer history. This stems in particular from the creation of the American network, which was based on a small number of cases. Such structure encourages further changes and modifications which are not necessarily radical. The ECN, by contrast, was established by legislative action, which explains its rigid structure and resistance to change. It might be the case that the ECN is subject not so much to path dependence but to past dependence. It might have to be replaced, as happened to its predecessor. This paper is an attempt to transpose the superiority of the American network on to the ECN. It looks at concepts such as judicial cooperation, harmonization of procedure, peer review and regulatory impact assessments (RIAs), and dispute resolution procedures. The aim is to adopt these concepts into the EU setting without recourse to legal transplantation. The major difficulty is that many of these concepts have been tested only in the US and it is difficult to tell whether they could be modified to meet EU standards. Concepts such as judicial cooperation might be difficult due to different language traditions in EU member states. It is hoped that greater flexibility, as in the American network, would boost legitimacy and transparency.

Keywords: ECN, networks, regulation, competition

Procedia PDF Downloads 428

Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

Abstract:

A functional model to mimic the functional correctness of a neural network compute accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of GCC compilers to the BF-16 datatype, which we addressed with a native BF-16 generator integrated into our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex neural network accelerator design by proposing a functional model-based scoreboard or software model using SystemC. The proposed functional model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT, bringing up micro-steps of execution.

Keywords: ISA, neural network, Brain Float-16, DUT

Procedia PDF Downloads 94

Authors: Edward P. Guillen, A. Karina Martinez Barliza

Abstract:

Powerline Communications (PLC) as last mile solution to provide communication services, has the advantage of transmitting over channels already used for electrical distribution. However these channels have been not designed with this purpose, for that reason telecommunication companies in Colombia want to know how good would be using PLC in costs and network performance in comparison to cable modem or DSL. This paper analyzes PLC throughput for residential complex scenarios using a PLC network scenarios and some statistical results are shown.

Keywords: home network, power line communication, throughput analysis, power factor, cost, last mile solution

Procedia PDF Downloads 266

Authors: Johnson O. Adeogo, Ayodele S. Oluwole, O. Akinsanmi, Olawale J. Olaluyi

Abstract:

In this 5G network, very high traffic density in densely populated areas, most especially in densely populated areas, is one of the key requirements. Radiation reduction becomes one of the major concerns to secure the future life of mobile network users in ultra-dense network areas using an improved coordinated multipoint technology. Coordinated Multi-Point (CoMP) is based on transmission and/or reception at multiple separated points with improved coordination among them to actively manage the interference for the users. Small cells have two major objectives: one, they provide good coverage and/or performance. Network users can maintain a good quality signal network by directly connecting to the cell. Two is using CoMP, which involves the use of multiple base stations (MBS) to cooperate by transmitting and/or receiving at the same time in order to reduce the possibility of electromagnetic radiation increase. Therefore, the influence of the screen guard with rubber condom on the mobile transceivers as one major piece of equipment radiating electromagnetic radiation was investigated by mobile network users amidst ultra-dense networks in 5g. The results were compared with the same mobile transceivers without screen guards and rubber condoms under the same network conditions. The 5 cm distance from the mobile transceivers was measured with the help of a ruler, and the intensity of Radio Frequency (RF) radiation was measured using an RF meter. The results show that the intensity of radiation from various mobile transceivers without screen guides and condoms was higher than the mobile transceivers with screen guides and condoms when call conversation was on at both ends.

Keywords: ultra-dense networks, mobile network users, 5g, coordinated multi-point.

Procedia PDF Downloads 103

Authors: Minakshi Jain, Sachin Yadav

Abstract:

Gram Panchayat is the smallest unit of Democracy in India. Grassroots Democracy has been further strengthened by implementation of the 73rd Constitutional Amendment act (CAA) in 1992. To analyse the impact of grassroots democracy the three villages are selected, which have the representation of each section of the society. The selected villages belongs to the same block and district of Haryana state. Villages are selected to access the marginalized group such as women and other backward class. These groups are isolated and do not participate in the grassroots level development process. The caste continue to be a relevant factor in determining the rural leadership. The earlier models of Panchayati Raj failed to benefit the marginalized groups of the society. The 73rd CAA, advocates a uniform three tier system of Panchayat at District level (Zilla Panchayat), Taluka/Block level (Block Panchayat), and village level (Gram Panchayat). The socio-economic profile of representatives in each village is important factor in rural development. The study will highlight the socio-economic profile of elected members at gram Panchayat level, Block Level and District level. The analysis reveals that there is a need to educate and develop the capacity and capability of the elected representative. Training must be imparted to all of them to enable them to function as per provision in the act. The paper will analyse the impact of act on rural development than propose some measures to further strengthen the Panchayati Raj Institution (PRI’s) at grassroots level.

Keywords: democracy, rural development, marginalized people, function

Procedia PDF Downloads 326