Search results for: network security management

Authors: Tuji Jemal Ahmed, Abdi Mohammed, Geremew Geidare Kailo

Abstract:

Food security, foodborne illness, and food safety are critical issues that affect the East Harerghe region of Oromia, Ethiopia. Despite the region's potential for agriculture, food insecurity remains a significant problem, with many households experiencing chronic hunger and malnutrition. The region also experiences high rates of foodborne illnesses, including cholera, typhoid, and diarrhea, which are caused by poor hygiene and sanitation practices. Additionally, food safety is a significant challenge, particularly in rural areas, where there is a lack of infrastructure, inadequate food storage facilities, and limited access to information about food safety. There are several factors that contribute to the current situation in the East Harerghe region; firstly, the region is susceptible to natural disasters, for instance, drought, which affects crop yields and livestock production. Secondly, the region also experiences poor infrastructure, which affects the storage and transportation of food, particularly in rural areas. Thirdly, there is a lack of awareness and knowledge on good hygiene and sanitation practices, specifically during food handling, processing, and storage. Fourthly, unitability due to conflict and other forms of land degradation exacerbates food insecurity and malnutrition. Finally, limited access to financial resources and markets commonly affects smallholder farmers by their ability to produce and sell food. To address the current situation in that area, several potential solutions can be implemented; investment in infrastructure is necessary, especially in rural areas, to improve the storage and transportation of food. Education and awareness programs on good hygiene and sanitation practices should target local communities, smallholder farmers, and food vendors. Financial resources and markets should be made more accessible to smallholder farmers, particularly through the provision of credit and improved access to markets. Addressing the underlying causes of conflict and promoting peaceful coexistence can help to reduce displacement and loss of livelihoods. Finally, the enforcement of food safety regulations and the implementation of standards for food processing and storage facilities are necessary to ensure food safety. In conclusion, addressing the challenges of food security, foodborne illness, and food safety in the East Harerghe region requires a coordinated effort from various stakeholders, including the government, non-governmental organizations, and local communities. By implementing the solutions outlined above, the region can improve its food security, prevent foodborne illnesses, and keep food safe for its population. Eventually, building the resilience of communities to shocks such as droughts, floods, and conflict is necessary to ensure long-term food security in the region.

Keywords: foodborne illness, food handling, food safety, food security

Procedia PDF Downloads 101

Authors: Zohreh Hajiha

Abstract:

Culture affects the ability of the organization in expressing and achieving the goals. Organizational culture influences the selection of instruments applied in the management of organizations. All the instruments applied in organizations to control, promote and create innovations are influenced by organizational culture. This research studies organizational culture based on the cultural model of Muijen and its relationship with applying management accounting innovations in Iranian listed firms. Management accounting innovations of this study include activity-based costing, activity-based management, balanced scorecard, target costing, standard costing, quality costing, Kaizen costing and dimensions of organizational culture include support orientation, innovation orientation, rules orientation and goal orientation. 105 questionnaires were sent to financial executives of production companies and 73 questionnaires were returned. The findings show that there is a significant difference between organizational culture of firms that have applied management accounting innovations and those which have used these innovations less. Also, dimensions of support orientation and culture goal orientation are the highest in groups that apply management accounting innovations. The findings suggest that proper organization culture could promote the use od management accounting tools in Iranian firms.

Keywords: organizational culture, innovation, management accounting, muijen model

Procedia PDF Downloads 360

Authors: Mohammad Hossein Ahmadi, Vahid Haghighatdoost

Abstract:

Spatial databases have been an active area of research over years. In this paper, we study how to answer the General Time-Dependent Sequenced Route queries. Given the origin and destination of a user over a time-dependent road network graph, an ordered list of categories of interests and a departure time interval, our goal is to find the minimum travel time path along with the best departure time that minimizes the total travel time from the source location to the given destination passing through a sequence of points of interests belonging to each of the specified categories of interest. The challenge of this problem is the added complexity to the optimal sequenced route queries, where we assume that first the road network is time dependent, and secondly the user defines a departure time interval instead of one single departure time instance. For processing general time-dependent sequenced route queries, we propose two solutions as Discrete-Time and Continuous-Time Sequenced Route approaches, finding approximate and exact solutions, respectively. Our proposed approaches traverse the road network based on A*-search paradigm equipped with an efficient heuristic function, for shrinking the search space. Extensive experiments are conducted to verify the efficiency of our proposed approaches.

Keywords: trip planning, time dependent, sequenced route query, road networks

Procedia PDF Downloads 321

Authors: Michael K. Adu, Boniface K. Alese, Olumide S. Ogunnusi

Abstract:

This paper brings to fore the inherent advantages in application of mobile agents to procure software products rather than downloading software content on the Internet. It proposes a system whereby the products come on compact disk with mobile agent as deliverable. The client/user purchases a software product, but must connect to the remote server of the software developer before installation. The user provides an activation code that activates mobile agent which is part of the software product on compact disk. The validity of the activation code is checked on connection at the developer’s end to ascertain authenticity and prevent piracy. The system is implemented by downloading two different software products as compare with installing same products on compact disk with mobile agent’s application. Downloading software contents from developer’s database as in the traditional method requires a continuously open connection between the client and the developer’s end, a fixed network is not economically or technically feasible. Mobile agent after being dispatched into the network becomes independent of the creating process and can operate asynchronously and autonomously. It can reconnect later after completing its task and return for result delivery. Response Time and Network Load are very minimal with application of Mobile agent.

Keywords: software products, software developer, internet, activation code, mobile agent

Procedia PDF Downloads 312

Authors: Jui-Chen Huang, Shou-Hsiung Cheng

Abstract:

This study examined their willingness to use telecare for people who have had experience falling in the last three months in Taiwan. This study adopted convenience sampling and a structural questionnaire to collect data. It was based on the definition and the constructs related to the Health Belief Model (HBM). HBM is comprised of seven constructs: perceived benefits (PBs), perceived disease threat (PDT), perceived barriers of taking action (PBTA), external cues to action (ECUE), internal cues to action (ICUE), attitude toward using (ATT), and behavioral intention to use (BI). This study adopted Fuzzy Neural Network (FNN) to put forward an effective method. It shows the dependence of ATT on PB, PDT, PBTA, ECUE, and ICUE. The training and testing data RMSE (root mean square error) are 0.028 and 0.166 in the FNN, respectively. The training and testing data RMSE are 0.828 and 0.578 in the regression model, respectively. On the other hand, as to the dependence of ATT on BI, as presented in the FNN, the training and testing data RMSE are 0.050 and 0.109, respectively. The training and testing data RMSE are 0.529 and 0.571 in the regression model, respectively. The results show that the FNN method is better than the regression analysis. It is an effective and viable good way.

Keywords: fall, fuzzy neural network, health belief model, telecare, willingness

Procedia PDF Downloads 201

Authors: Pablo Chico De Guzman, Cesar Sanchez

Abstract:

Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

Procedia PDF Downloads 203

Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

Abstract:

PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

Procedia PDF Downloads 149

Authors: Buse T. Aydın, Enver Ozdemir

Abstract:

In this study, a double layer authentication scheme between the aircraft and the Air Traffic Control (ATC) tower is designed to prevent any unauthorized aircraft from introducing themselves as friends. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or foe according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as a friend. In this method, even if embedded key is captured by the enemy aircraft, without the information of the second layer, the enemy can easily be determined. Overall, in this work, we present a more reliable system by adding a physical layer in the authentication process.

Keywords: ADS-B, communication with physical layer security, cryptography, identification friend or foe

Procedia PDF Downloads 161

Authors: K. Padmavathi, K. Sri Ramakrishna

Abstract:

This study describes a procedure for the detection of Left and Right Bundle Branch Block (LBBB and RBBB) ECG patterns using spectral Coherence(SC) technique and LM Neural Network. The Coherence function finds common frequencies between two signals and evaluate the similarity of the two signals. The QT variations of Bundle Blocks are observed in lead V1 of ECG. Spectral Coherence technique uses Welch method for calculating PSD. For the detection of normal and Bundle block beats, SC output values are given as the input features for the LMNN classifier. Overall accuracy of LMNN classifier is 99.5 percent. The data was collected from MIT-BIH Arrhythmia database.

Keywords: bundle block, SC, LMNN classifier, welch method, PSD, MIT-BIH, arrhythmia database

Procedia PDF Downloads 282

Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

Abstract:

Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

Procedia PDF Downloads 316

Authors: Maram Saleh

Abstract:

Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

Procedia PDF Downloads 208

Authors: Safa Lazzem, Faouzi Jilani

Abstract:

The aim of this research is to investigate the impact of diversification strategy on the nature of the relationship between leverage and accrual-based earnings management through panel-estimation techniques based on a sample of 162 nonfinancial French firms indexed in CAC All-Tradable during the period from 2006 to 2012. The empirical results show that leverage increases encourage managers to manipulate earnings management. Our findings prove that the diversification strategy provides the needed context for this accounting practice to be possible in highly diversified firms. In addition, the results indicate that diversification moderates the relationship between leverage and accrual-based earnings management by changing the nature and the sign of this relationship.

Keywords: diversification, earnings management, leverage, panel-estimation techniques

Procedia PDF Downloads 150

Authors: Samira Mahmoudkelayeh, Katayoun Taghizade, Mitra Pourvaziri, Elnaz Asadian

Abstract:

Over the recent decades, depletion of resources and environmental concerns made researchers and practitioners present sustainable approaches. Since construction process consumes a great deal of both renewable and non-renewable resources, it is of great significance regarding environmental impacts. Choosing sustainable construction materials is a remarkable strategy presented in many researches and has a significant effect on building’s environmental footprint. This paper represents an assessment framework for selecting best sustainable materials for exterior enclosure in the city of Tehran based on sustainability principles (eco-friendly, cost effective and socio-cultural viable solutions). To perform a comprehensive analysis of environmental impacts, life cycle assessment, a cradle to grave approach is used. A questionnaire survey of construction experts has been conducted to determine the relative importance of criteria. Analytic Network Process (ANP) is applied as a multi-criteria decision-making method to choose sustainable material which consider interdependencies of criteria and sub-criteria. Finally, it prioritizes and aggregates relevant criteria into ultimate assessed score.

Keywords: sustainable materials, building, analytic network process, life cycle assessment

Procedia PDF Downloads 242

Authors: Opal Giulianelli, Pegah Zamani

Abstract:

Sustainable food has become a frequently debated topic in recent years due to a consumer push for environmentally sustainable food. While some research works on improving the monoculture farm systems that are currently in use, others focus on expanding the definition of sustainable food systems. This research looks at those concepts of alternative food systems applied to a more extensive city system. The goal is to create a theoretical site plan that could be implemented in emerging cities and other urban environments. This site plan combines the ideas of environmentally sustainable food development, such as food forests, urban farming, and community gardens. This would represent one part of a larger sustainable food system that can be altered depending on the environment or the people it is serving. However, this research is being carried out with the southeast United States in mind and, therefore, may prove difficult to apply to other regions, especially those of radically different climates.

Keywords: alternative food systems, urban design, food forests, aquaponics, hydroponics, food security, food system design

Procedia PDF Downloads 103

Authors: T. Alghamdi, G. Alaghband

Abstract:

In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

Procedia PDF Downloads 154

Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

Abstract:

Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

Procedia PDF Downloads 397

Authors: Rishabh Sharma

Abstract:

The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system

Procedia PDF Downloads 106

Authors: Christian Ndubisi Madu, Benjamin C. Ozumba, Ifeanyi E. Madu, Valentine E. Nnadi, Ikenna C. Ezeasor

Abstract:

The ability to generate power and achieve energy security is one of the driving forces behind the emerging ‘microgrid’ concept. Traditional power supply often operates with centralized infrastructure for generating, transmitting and distributing electricity. The inefficiency and the incessant power outages associated with the centralized power supply system in Nigeria has alienated many users who frequently turn to electric power generator sets to power their homes and offices. Such acts are unsustainable and lead to increase in the use of fossil fuels, generation of carbon dioxide emissions and other gases, and noise pollution. They also pose significant risks as they entail random purchases and storage of gasolines which are fire hazards. It is therefore important that organizations rethink their relationships to centralized power suppliers in other to improve energy accessibility and security. This study explores the energy planning processes and learning taking place at the University of Nigeria Enugu Campus as the school lead microgrid feasibility studies in its community. There is need to develop community partners to deal with the issue of energy efficiency and also to create a strategic alliance to confront political, regulatory and economic barriers to locally-based energy planning. Community-based microgrid can help to reduce the cost of adoption and diversify risks. This study offers insights into the ways in which microgrids can further democratize energy planning, procurement, and access, while simultaneously promoting efficiency and sustainability.

Keywords: microgrid, energy efficiency, sustainability, energy security

Procedia PDF Downloads 375

Authors: Mamouni Mohammed Dhiya Eddine

Abstract:

This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

Procedia PDF Downloads 220

Authors: Manish Gupta

Abstract:

Following the E-Commerce era, M-Commerce is the next big phase in the technology involvement and advancement. This paper intends to explore how Indian consumers are influenced to adopt the M-commerce. In this paper, the revised Technology Acceptance Model (TAM) has been presented on the basis of the most dominant factors that affect the adoption of M-Commerce in Indian scenario. Furthermore, an analytical questionnaire approach was carried out to collect data from Indian consumers. These collected data were further used for the validation of the presented model. Findings indicate that customization, convenience, instant connectivity, compatibility, security, download speed in M-Commerce affect the adoption behavior. Furthermore, the findings suggest that perceived usefulness and attitude towards M-Commerce are positively influenced by number of M-Commerce drivers (i.e. download speed, compatibility, convenience, security, customization, connectivity, and input mechanism).

Keywords: M-Commerce, perceived usefulness, technology acceptance model, perceived ease of use

Procedia PDF Downloads 312

Authors: Rade M. Ciric

Abstract:

The paper shows the development and implementation of the syllabus of the subject 'Distribution and Industrial Networks', attended by the vocational specialist Year 4 students of the Electric Power Engineering study programme at the Higher Education Technical School of Vocational Studies in Novi Sad. The aim of the subject is to equip students with the knowledge necessary for planning, exploitation and management of distributive and industrial electric power networks in an open electricity market environment. The results of the evaluation of educational outcomes on the subject are presented and discussed.

Keywords: engineering education, power distribution network, syllabus implementation, outcome evaluation

Procedia PDF Downloads 402

Authors: Solomon Eghosa Uhunamure, Karabo Shale

Abstract:

Biogas technology has emerged as a promising solution for sustainable development, enhancing energy security while mitigating environmental hazards. Interest in biogas for household energy is growing due to its potential to address both energy and waste management challenges. To ensure biogas production contributes meaningfully to South Africa's future energy landscape, understanding public perceptions is essential for shaping effective policy measures. A household survey revealed that lower awareness of biogas correlates with reduced social and cultural acceptance, however, after providing basic information—such as a definition, a diagram, or one of two simple messages—support for biogas increased by 10% to 15% compared to the baseline. These findings highlight the critical role of awareness in building support for biogas as a key component of South Africa's decarbonization strategy.

Keywords: awareness, barriers, biogas, environmental benefits, South Africa

Procedia PDF Downloads 32

Authors: K. Ismail, A. Ali, R. C. Hasan, I. Khalil, Z. Bachok, N. M. Said, A. M. Muslim, M. S. Che Din, W. S. Chong

Abstract:

The marine ecosystem in Malaysia holds invaluable potential in terms of economics, food security, pharmaceuticals components and protection from natural hazards. Although exploration of oil and gas industry and fisheries are active within Malaysian waters, knowledge of the seascape and ecological functioning of benthic habitats is still extremely poor in the marine parks around Malaysia due to the lack of detailed seafloor information. Consequently, it is difficult to manage marine resources effectively, protect ecologically important areas and set legislation to safeguard the marine parks. The limited baseline data hinders scientific linkage to support effective marine spatial management in Malaysia. This became the main driver behind the first seabed mapping effort at the national level. Taman Laut Labuan (TLL) is located to the west coast of Sabah and to the east of South China Sea. The total area of TLL is approximately 158.15 km2, comprises of three islands namely Pulau Kuraman, Rusukan Besar and Rusukan Kecil and is characterised by shallow fringing reef with few submerged shallow reef. The unfamiliar rocky shorelines limit the survey of multibeam echosounder to area with depth more than 10 m. Whereas, singlebeam and side scan sonar systems were used to acquire the data for area with depth less than 10 m. By integrating data from multibeam bathymetry and backscatter with singlebeam bathymetry and side sonar images, we produce a substrate map and coral coverage map for the TLL using i) marine landscape mapping technique and ii) RSOBIA ArcGIS toolbar (developed by T. Le Bas). We take the initiative to explore the ability of aerial drone and satellite image (WorldView-3) to derive the depths and substrate type within the intertidal and subtidal zone where it is not accessible via acoustic mapping. Although the coverage was limited, the outcome showed a promising technique to be incorporated towards establishing a guideline to facilitate a standard practice for efficient marine spatial management in Malaysia.

Keywords: habitat mapping, marine spatial management, South China Sea, National seabed mapping

Procedia PDF Downloads 224

Authors: Hossein Bakhtiari, Mathias Cehlin, Jan Akander

Abstract:

Envelopes with low thermal performance is a common characteristic in many European historic buildings which leads to higher energy demand for heating and cooling as well as insufficient thermal comfort for the occupants. This paper presents the results of a study on the thermal comfort in the City Hall (Rådhuset) in Gävle, Sweden. This historic building is currently used as an office building. It is equipped with two relatively modern mechanical heat recovery ventilation systems with displacement ventilation supply devices in the offices. The district heating network heats the building via pre-heat supply air and radiators. Summer cooling comes from an electric heat pump that rejects heat into the exhaust ventilation air. A building management system controls HVAC equipment (heating, ventilation and air conditioning). The methodology is based on on-site measurements, data logging on the management system and evaluating the occupants’ perception of a summer and a winter period indoor environment using a standardized questionnaire. The main aim of the study is to investigate whether or not it is enough to have modernized HVAC systems to get adequate thermal comfort in a historic building with poor envelope performance used as an office building in Nordic climate conditions.

Keywords: historic buildings, on-site measurements, standardized questionnaire, thermal comfort

Procedia PDF Downloads 374

Authors: G. Suja, J. Sreekumar, A. N. Jyothi, V. S. Santhosh Mithra

Abstract:

Worldwide concerns regarding food safety, environmental degradation and threats to human health have generated interest in alternative systems like organic farming. Tropical tuber crops, cassava, sweet potato, yams, and aroids are food-cum-nutritional security-cum climate resilient crops. These form stable or subsidiary food for about 500 million global population. Cassava, yams (white yam, greater yam, and lesser yam) and edible aroids (elephant foot yam, taro, and tannia) are high energy tuberous vegetables with good taste and nutritive value. Seven on-station field experiments at ICAR-Central Tuber Crops Research Institute, Thiruvananthapuram, India and seventeen on-farm trials in three districts of Kerala, were conducted over a decade (2004-2015) to compare the varietal response, yield, quality and soil properties under organic vs conventional system in these crops and to develop a learning system based on the data generated. The industrial, as well as domestic varieties of cassava, the elite and local varieties of elephant foot yam and taro and the three species of Dioscorea (yams), were on a par under both systems. Organic management promoted yield by 8%, 20%, 9%, 11% and 7% over conventional practice in cassava, elephant foot yam, white yam, greater yam and lesser yam respectively. Elephant foot yam was the most responsive to organic management followed by yams and cassava. In taro, slight yield reduction (5%) was noticed under organic farming with almost similar tuber quality. The tuber quality was improved with higher dry matter, starch, crude protein, K, Ca and Mg contents. The anti-nutritional factors, oxalate content in elephant foot yam and cyanogenic glucoside content in cassava were lowered by 21 and 12.4% respectively. Organic plots had significantly higher water holding capacity, pH, available K, Fe, Mn and Cu, higher soil organic matter, available N, P, exchangeable Ca and Mg, dehydrogenase enzyme activity and microbial count. Organic farming scored significantly higher soil quality index (1.93) than conventional practice (1.46). The soil quality index was driven by water holding capacity, pH and available Zn followed by soil organic matter. Organic management enhanced net profit by 20-40% over chemical farming. A case in point is the cost-benefit analysis in elephant foot yam which indicated that the net profit was 28% higher and additional income of Rs. 47,716 ha-1 was obtained due to organic farming. Cost-effective technologies were field validated. The on-station technologies developed were validated and popularized through on-farm trials in 10 sites (5 ha) under National Horticulture Mission funded programme in elephant foot yam and seven sites in yams and taro. The technologies are included in the Package of Practices Recommendations for crops of Kerala Agricultural University. A learning system developed using artificial neural networks (ANN) predicted the performance of elephant foot yam organic system. Use of organically produced seed materials, seed treatment in cow-dung, neem cake, bio-inoculant slurry, farmyard manure incubated with bio-inoculants, green manuring, use of neem cake, bio-fertilizers and ash formed the strategies for organic production. Organic farming is an eco-friendly management strategy that enables 10-20% higher yield, quality tubers and maintenance of soil health in tuber crops.

Keywords: eco-agriculture, quality, root crops, healthy soil, yield

Procedia PDF Downloads 335

Authors: Vivek Kumar Singh, Tripti Singh

Abstract:

An ad hoc wireless network consists of mobile networks which creates an underlying architecture for communication without the help of traditional fixed-position routers. Ad-hoc On-demand Distance Vector (AODV) is a routing protocol used for Mobile Ad hoc Network (MANET). Nevertheless, the architecture must maintain communication routes although the hosts are mobile and they have limited transmission range. There are different protocols for handling the routing in the mobile environment. Routing protocols used in fixed infrastructure networks cannot be efficiently used for mobile ad-hoc networks, so that MANET requires different protocols. This paper presents the performance analysis of the routing protocols used various parameter-patterns with Two-ray model.

Keywords: AODV, packet transmission rate, pause time, ZRP, QualNet 6.1

Procedia PDF Downloads 828

Authors: Hossein Nikandam Kermanshah, Babak Samavatian, Akbar Hemmati Sabet, Mohammad Ahmadpanah

Abstract:

This is a quasi-experimental study that has been conducted in order to compare the effectiveness of social skills training and stress management training on self-esteem and aggression in first grade high school students. Forty-five people were selected from research community and were put randomly in there groups of social skills training, stress management training and control ones. Collecting data tools in this study was devise, self-esteem and AGQ aggression questionnaire. Self-esteem and aggression questionnaires has been conducted as the pre-test and post-test. Social skills training and stress management groups participated in eight 1.5 hour session in a week. But control group did not receive any therapy. For descriptive analysis of data, statistical indicators like mean, standard deviation were used, and in inferential statistics level multi variable covariance analysis have been used. The finding result show that group training social skills and stress management is significantly effective on the self-esteem and aggression, there is a meaningful difference between training social skills and stress management on self-esteem that the preference is with group social skills training, in the difference between group social skills training and stress management on aggression, the preference is with group stress management.

Keywords: social skill training, stress management training, self-esteem aggression, psychological sciences

Procedia PDF Downloads 470

Authors: Liuhui Zhu, Peng Zeng

Abstract:

The rural revitalization strategy means to take the country and the city on the same level, and achieve urban-rural integration and comprehensive development of rural areas. Beijing-Tianjin-Hebei rural areas have always been the weak links in the region, with prominently uneven development between urban and rural areas. The rural areas need to join the overall regional synergy. Based on the analysis of the characteristics and problems of rural development in the region from the perspective of production-living-ecology space, the paper proposes the township as the basic unit for rural revitalization according to the overall requirements of the rural revitalization strategy. The basic unit helps to realize resource arrangement, functional organization, and collaborative governance organized by the production-living-ecology spatial network. The paper summarizes the planning strategies for the basic unit. Through spatial cognition and spatial reconstruction, the three space is networked through the base, nodes, and connections to improve the comprehensive value of rural areas and achieve the multiple goals of rural revitalization.

Keywords: rural revitalization, Beijing-Tianjin-Hebei region, township level, production-living-ecology spatial network

Procedia PDF Downloads 195

Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

Abstract:

Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: causality, defect causes, social network analysis, association rule mining

Procedia PDF Downloads 367

Authors: Ratri Werdiningtyas, Yongping Wei, Andrew Western

Abstract:

This paper contributes to on-going attempts at bringing together land, water and environmental policy in catchment management. A tension remains in defining the boundaries of policy integration. Most of Integrated Water Resource Management is valued as rhetoric policy. It is far from being achieved on the ground because the socio-ecological system has not been understood and developed into complete and coherent problem representation. To clarify the feature of integration, this article draws on institutional fit for public policy integration and uses these insights in an empirical setting to identify the mechanism that can facilitate effective public integration for catchment management. This research is based on the journey of Victoria’s government from 1890-2016. A total of 274 Victorian Acts related to land, water, environment management published in those periods has been investigated. Four conditions of integration have been identified in their co-evolution: (1) the integration policy based on reserves, (2) the integration policy based on authority interest, (3) policy based on integrated information and, (4) policy based coordinated resource, authority and information. Results suggest that policy coordination among their policy instrument is superior rather than policy integration in the case of catchment management.

Keywords: catchment management, co-evolution, policy integration, phase

Procedia PDF Downloads 247