Search results for: similarity metrics
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1202

Search results for: similarity metrics

302 Evaluation of IMERG Performance at Estimating the Rainfall Properties through Convective and Stratiform Rain Events in a Semi-Arid Region of Mexico

Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

Abstract:

Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

Procedia PDF Downloads 39
301 Bridge Members Segmentation Algorithm of Terrestrial Laser Scanner Point Clouds Using Fuzzy Clustering Method

Authors: Donghwan Lee, Gichun Cha, Jooyoung Park, Junkyeong Kim, Seunghee Park

Abstract:

3D shape models of the existing structure are required for many purposes such as safety and operation management. The traditional 3D modeling methods are based on manual or semi-automatic reconstruction from close-range images. It occasions great expense and time consuming. The Terrestrial Laser Scanner (TLS) is a common survey technique to measure quickly and accurately a 3D shape model. This TLS is used to a construction site and cultural heritage management. However there are many limits to process a TLS point cloud, because the raw point cloud is massive volume data. So the capability of carrying out useful analyses is also limited with unstructured 3-D point. Thus, segmentation becomes an essential step whenever grouping of points with common attributes is required. In this paper, members segmentation algorithm was presented to separate a raw point cloud which includes only 3D coordinates. This paper presents a clustering approach based on a fuzzy method for this objective. The Fuzzy C-Means (FCM) is reviewed and used in combination with a similarity-driven cluster merging method. It is applied to the point cloud acquired with Lecia Scan Station C10/C5 at the test bed. The test-bed was a bridge which connects between 1st and 2nd engineering building in Sungkyunkwan University in Korea. It is about 32m long and 2m wide. This bridge was used as pedestrian between two buildings. The 3D point cloud of the test-bed was constructed by a measurement of the TLS. This data was divided by segmentation algorithm for each member. Experimental analyses of the results from the proposed unsupervised segmentation process are shown to be promising. It can be processed to manage configuration each member, because of the segmentation process of point cloud.

Keywords: fuzzy c-means (FCM), point cloud, segmentation, terrestrial laser scanner (TLS)

Procedia PDF Downloads 208
300 Optimizing Energy Efficiency: Leveraging Big Data Analytics and AWS Services for Buildings and Industries

Authors: Gaurav Kumar Sinha

Abstract:

In an era marked by increasing concerns about energy sustainability, this research endeavors to address the pressing challenge of energy consumption in buildings and industries. This study delves into the transformative potential of AWS services in optimizing energy efficiency. The research is founded on the recognition that effective management of energy consumption is imperative for both environmental conservation and economic viability. Buildings and industries account for a substantial portion of global energy use, making it crucial to develop advanced techniques for analysis and reduction. This study sets out to explore the integration of AWS services with big data analytics to provide innovative solutions for energy consumption analysis. Leveraging AWS's cloud computing capabilities, scalable infrastructure, and data analytics tools, the research aims to develop efficient methods for collecting, processing, and analyzing energy data from diverse sources. The core focus is on creating predictive models and real-time monitoring systems that enable proactive energy management. By harnessing AWS's machine learning and data analytics capabilities, the research seeks to identify patterns, anomalies, and optimization opportunities within energy consumption data. Furthermore, this study aims to propose actionable recommendations for reducing energy consumption in buildings and industries. By combining AWS services with metrics-driven insights, the research strives to facilitate the implementation of energy-efficient practices, ultimately leading to reduced carbon emissions and cost savings. The integration of AWS services not only enhances the analytical capabilities but also offers scalable solutions that can be customized for different building and industrial contexts. The research also recognizes the potential for AWS-powered solutions to promote sustainable practices and support environmental stewardship.

Keywords: energy consumption analysis, big data analytics, AWS services, energy efficiency

Procedia PDF Downloads 38
299 A Comparative Approach to the Concept of Incarnation of God in Hinduism and Christianity

Authors: Cemil Kutluturk

Abstract:

This is a comparative study of the incarnation of God according to Hinduism and Christianity. After dealing with their basic ideas on the concept of the incarnation of God, the main similarities and differences between each other will be examined by quoting references from their sacred texts. In Hinduism, the term avatara is used in order to indicate the concept of the incarnation of God. The word avatara is derived from ava (down) and tri (to cross, to save, attain). Thus avatara means to come down or to descend. Although an avatara is commonly considered as an appearance of any deity on earth, the term refers particularly to descents of Vishnu. According to Hinduism, God becomes an avatara in every age and entering into diverse wombs for the sake of establishing righteousness. On the Christian side, the word incarnation means enfleshment. In Christianity, it is believed that the Logos or Word, the Second Person of Trinity, presumed human reality. Incarnation refers both to the act of God becoming a human being and to the result of his action, namely the permanent union of the divine and human natures in the one Person of the Word. When the doctrines of incarnation and avatara are compared some similarities and differences can be found between each other. The basic similarity is that both doctrines are not bound by the laws of nature as human beings are. They reveal God’s personal love and concern, and emphasize loving devotion. Their entry into the world is generally accompanied by extraordinary signs. In both cases, the descent of God allows for human beings to ascend to God. On the other hand, there are some distinctions between two religious traditions. For instance, according to Hinduism there are many and repeated avataras, while Christ comes only once. Indeed, this is related to the respective cyclic and linear worldviews of the two religions. Another difference is that in Hinduism avataras are real and perfect, while in Christianity Christ is also real, yet imperfect; that is, he has human imperfections, except sin. While Christ has never been thought of as a partial incarnation, in Hinduism there are some partial and full avataras. The other difference is that while the purpose of Christ is primarily ultimate salvation, not every avatara grants ultimate liberation, some of them come only to save a devotee from a specific predicament.

Keywords: Avatara, Christianity, Hinduism, incarnation

Procedia PDF Downloads 228
298 Semi-Automatic Segmentation of Mitochondria on Transmission Electron Microscopy Images Using Live-Wire and Surface Dragging Methods

Authors: Mahdieh Farzin Asanjan, Erkan Unal Mumcuoglu

Abstract:

Mitochondria are cytoplasmic organelles of the cell, which have a significant role in the variety of cellular metabolic functions. Mitochondria act as the power plants of the cell and are surrounded by two membranes. Significant morphological alterations are often due to changes in mitochondrial functions. A powerful technique in order to study the three-dimensional (3D) structure of mitochondria and its alterations in disease states is Electron microscope tomography. Detection of mitochondria in electron microscopy images due to the presence of various subcellular structures and imaging artifacts is a challenging problem. Another challenge is that each image typically contains more than one mitochondrion. Hand segmentation of mitochondria is tedious and time-consuming and also special knowledge about the mitochondria is needed. Fully automatic segmentation methods lead to over-segmentation and mitochondria are not segmented properly. Therefore, semi-automatic segmentation methods with minimum manual effort are required to edit the results of fully automatic segmentation methods. Here two editing tools were implemented by applying spline surface dragging and interactive live-wire segmentation tools. These editing tools were applied separately to the results of fully automatic segmentation. 3D extension of these tools was also studied and tested. Dice coefficients of 2D and 3D for surface dragging using splines were 0.93 and 0.92. This metric for 2D and 3D for live-wire method were 0.94 and 0.91 respectively. The root mean square symmetric surface distance values of 2D and 3D for surface dragging was measured as 0.69, 0.93. The same metrics for live-wire tool were 0.60 and 2.11. Comparing the results of these editing tools with the results of automatic segmentation method, it shows that these editing tools, led to better results and these results were more similar to ground truth image but the required time was higher than hand-segmentation time

Keywords: medical image segmentation, semi-automatic methods, transmission electron microscopy, surface dragging using splines, live-wire

Procedia PDF Downloads 141
297 Towards an Enhanced Quality of IPTV Media Server Architecture over Software Defined Networking

Authors: Esmeralda Hysenbelliu

Abstract:

The aim of this paper is to present the QoE (Quality of Experience) IPTV SDN-based media streaming server enhanced architecture for configuring, controlling, management and provisioning the improved delivery of IPTV service application with low cost, low bandwidth, and high security. Furthermore, it is given a virtual QoE IPTV SDN-based topology to provide an improved IPTV service based on QoE Control and Management of multimedia services functionalities. Inside OpenFlow SDN Controller there are enabled in high flexibility and efficiency Service Load-Balancing Systems; based on the Loading-Balance module and based on GeoIP Service. This two Load-balancing system improve IPTV end-users Quality of Experience (QoE) with optimal management of resources greatly. Through the key functionalities of OpenFlow SDN controller, this approach produced several important features, opportunities for overcoming the critical QoE metrics for IPTV Service like achieving incredible Fast Zapping time (Channel Switching time) < 0.1 seconds. This approach enabled Easy and Powerful Transcoding system via FFMPEG encoder. It has the ability to customize streaming dimensions bitrates, latency management and maximum transfer rates ensuring delivering of IPTV streaming services (Audio and Video) in high flexibility, low bandwidth and required performance. This QoE IPTV SDN-based media streaming architecture unlike other architectures provides the possibility of Channel Exchanging between several IPTV service providers all over the word. This new functionality brings many benefits as increasing the number of TV channels received by end –users with low cost, decreasing stream failure time (Channel Failure time < 0.1 seconds) and improving the quality of streaming services.

Keywords: improved quality of experience (QoE), OpenFlow SDN controller, IPTV service application, softwarization

Procedia PDF Downloads 121
296 Gender and Language: Exploring Sociolinguistic Differences

Authors: Marvelyn F. Carolino, Charlene R. Cunanan, Gellien Faith O. Masongsong, Berlinda A. Ofrecio

Abstract:

This study delves into the language usage differences among men, women, and individuals with other gender preferences. It specifically centers on the sociolinguistic aspects within the English majors at the College of Education of Rizal Technological University-Pasig, spanning from the first-year to fourth-year levels. The researchers employed a triangulation approach for data collection, utilizing a validated self-made questionnaire, interviews, and observations. The results revealed that language usage among different genders is influenced by a combination of cultural norms, social dynamics, and technological factors. Cultural norms significantly shape how respondents use language, as they conform to expected speech patterns based on their gender. Social factors, such as peer pressure, were found to impact language usage for individuals of all genders. This influence was viewed as constructive for personal development rather than inhibiting performance or communication. In terms of technological factors, respondents strongly agreed that the time spent on social media and educational applications influenced their language use. These platforms provided opportunities to expand and enhance their vocabulary. Additionally, the study employed hypothesis testing through the z-test formula to assess the impact of demographic profiles on language usage differences among genders. The results indicated that gender, economic status, locality, and ethnicity did not show statistically significant differences in language use. This lack of significant variation in findings was attributed to the relatively homogeneous demographic profile of respondents, primarily composed of females with low-income backgrounds and Tagalog ethnicity. This demographic similarity likely minimized the diversity of responses.

Keywords: gender, language, sociolinguistics, differences

Procedia PDF Downloads 58
295 Hub Traveler Guidance Signage Evaluation via Panoramic Visualization Using Entropy Weight Method and TOPSIS

Authors: Si-yang Zhang, Chi Zhao

Abstract:

Comprehensive transportation hubs are important nodes of the transportation network, and their internal signage the functions as guidance and distribution assistance, which directly affects the operational efficiency of traffic in and around the hubs. Reasonably installed signage effectively attracts the visual focus of travelers and improves wayfinding efficiency. Among the elements of signage, the visual guidance effect is the key factor affecting the information conveyance, whom should be evaluated during design and optimization process. However, existing evaluation methods mostly focus on the layout, and are not able to fully understand if signage caters travelers’ need. This study conducted field investigations and developed panoramic videos for multiple transportation hubs in China, and designed survey accordingly. Human subjects are recruited to watch panoramic videos via virtual reality (VR) and respond to the surveys. In this paper, Pudong Airport and Xi'an North Railway Station were studied and compared as examples due to their high traveler volume and relatively well-developed traveler service systems. Visual attention was captured by eye tracker and subjective satisfaction ratings were collected through surveys. Entropy Weight Method (EWM) was utilized to evaluate the effectiveness of signage elements and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to further rank the importance of the elements. The results show that the degree of visual attention of travelers significantly affects the evaluation results of guidance signage. Key factors affecting visual attention include accurate legibility, obstruction and defacement rates, informativeness, and whether signage is set up in a hierarchical manner.

Keywords: traveler guidance signage, panoramic video, visual attention, entropy weight method, TOPSIS

Procedia PDF Downloads 35
294 Quality of Service Based Routing Algorithm for Real Time Applications in MANETs Using Ant Colony and Fuzzy Logic

Authors: Farahnaz Karami

Abstract:

Routing is an important, challenging task in mobile ad hoc networks due to node mobility, lack of central control, unstable links, and limited resources. An ant colony has been found to be an attractive technique for routing in Mobile Ad Hoc Networks (MANETs). However, existing swarm intelligence based routing protocols find an optimal path by considering only one or two route selection metrics without considering correlations among such parameters making them unsuitable lonely for routing real time applications. Fuzzy logic combines multiple route selection parameters containing uncertain information or imprecise data in nature, but does not have multipath routing property naturally in order to provide load balancing. The objective of this paper is to design a routing algorithm using fuzzy logic and ant colony that can solve some of routing problems in mobile ad hoc networks, such as nodes energy consumption optimization to increase network lifetime, link failures rate reduction to increase packet delivery reliability and providing load balancing to optimize available bandwidth. In proposed algorithm, the path information will be given to fuzzy inference system by ants. Based on the available path information and considering the parameters required for quality of service (QoS), the fuzzy cost of each path is calculated and the optimal paths will be selected. NS2.35 simulation tools are used for simulation and the results are compared and evaluated with the newest QoS based algorithms in MANETs according to packet delivery ratio, end-to-end delay and routing overhead ratio criterions. The simulation results show significant improvement in the performance of these networks in terms of decreasing end-to-end delay, and routing overhead ratio, and also increasing packet delivery ratio.

Keywords: mobile ad hoc networks, routing, quality of service, ant colony, fuzzy logic

Procedia PDF Downloads 36
293 Optimizing Super Resolution Generative Adversarial Networks for Resource-Efficient Single-Image Super-Resolution via Knowledge Distillation and Weight Pruning

Authors: Hussain Sajid, Jung-Hun Shin, Kum-Won Cho

Abstract:

Image super-resolution is the most common computer vision problem with many important applications. Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory requirements of GAN-based SR (mainly generators) lead to performance degradation and increased energy consumption, making it difficult to implement it onto resource-constricted devices. To relieve such a problem, In this paper, we introduce an optimized and highly efficient architecture for SR-GAN (generator) model by utilizing model compression techniques such as Knowledge Distillation and pruning, which work together to reduce the storage requirement of the model also increase in their performance. Our method begins with distilling the knowledge from a large pre-trained model to a lightweight model using different loss functions. Then, iterative weight pruning is applied to the distilled model to remove less significant weights based on their magnitude, resulting in a sparser network. Knowledge Distillation reduces the model size by 40%; pruning then reduces it further by 18%. To accelerate the learning process, we employ the Horovod framework for distributed training on a cluster of 2 nodes, each with 8 GPUs, resulting in improved training performance and faster convergence. Experimental results on various benchmarks demonstrate that the proposed compressed model significantly outperforms state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and image quality for x4 super-resolution tasks.

Keywords: single-image super-resolution, generative adversarial networks, knowledge distillation, pruning

Procedia PDF Downloads 58
292 Improving Chest X-Ray Disease Detection with Enhanced Data Augmentation Using Novel Approach of Diverse Conditional Wasserstein Generative Adversarial Networks

Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

Abstract:

Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

Procedia PDF Downloads 50
291 The Effects of an Immigration Policy on the Economic Integration of Migrants and on Natives’ Attitudes: The Case of Syrian Refugees in Turkey

Authors: S. Zeynep Siretioglu Girgin, Gizem Turna Cebeci

Abstract:

Turkey’s immigration policy is a controversial issue considering its legal, economic, social, and political and human rights dimensions. Formulation of an immigration policy goes hand in hand with political processes, where natives’ attitudes play a significant role. On the other hand, as was the case in Turkey, radical changes made in immigration policy or policies lacking transparency may cause severe reactions by the host society. The underlying discussion paper aims to analyze quantitatively the effects of the existing ‘open door’ immigration policy on the economic integration of Syrian refugees in Turkey, and on the perception of the native population of refugees. For the analysis, semi-structured in-depth interviews and focus group interviews have been conducted. After the introduction, a literature review is provided, followed by theoretical background on the explanation of natives’ attitudes towards immigrants. In the next section, a qualitative analysis of natives’ attitudes towards Syrian refugees is presented with the subtopics of (i) awareness, general opinions and expectations, (ii) open-door policy and management of the migration process, (iii) perception of positive and negative impacts of immigration, (iv) economic integration, and (v) cultural similarity. Results indicate that, natives concurrently have social, economic and security concerns regarding refugees, while difficulties regarding security and economic integration of refugees stand out. Socio-economic characteristics of the respondents, such as the educational level and employment status, are not sufficient to explain the overall attitudes towards refugees, while they can be used to explain the awareness of the respondents and the priority of the concerns felt.

Keywords: economic integration, immigration policy, integration policies, migrants, natives’ sentiments, perception, Syrian refugees, Turkey

Procedia PDF Downloads 327
290 Triangular Hesitant Fuzzy TOPSIS Approach in Investment Projects Management

Authors: Irina Khutsishvili

Abstract:

The presented study develops a decision support methodology for multi-criteria group decision-making problem. The proposed methodology is based on the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) approach in the hesitant fuzzy environment. The main idea of decision-making problem is a selection of one best alternative or several ranking alternatives among a set of feasible alternatives. Typically, the process of decision-making is based on an evaluation of certain criteria. In many MCDM problems (such as medical diagnosis, project management, business and financial management, etc.), the process of decision-making involves experts' assessments. These assessments frequently are expressed in fuzzy numbers, confidence intervals, intuitionistic fuzzy values, hesitant fuzzy elements and so on. However, a more realistic approach is using linguistic expert assessments (linguistic variables). In the proposed methodology both the values and weights of the criteria take the form of linguistic variables, given by all decision makers. Then, these assessments are expressed in triangular fuzzy numbers. Consequently, proposed approach is based on triangular hesitant fuzzy TOPSIS decision-making model. Following the TOPSIS algorithm, first, the fuzzy positive ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are defined. Then the ranking of alternatives is performed in accordance with the proximity of their distances to the both FPIS and FNIS. Based on proposed approach the software package has been developed, which was used to rank investment projects in the real investment decision-making problem. The application and testing of the software were carried out based on the data provided by the ‘Bank of Georgia’.

Keywords: fuzzy TOPSIS approach, investment project, linguistic variable, multi-criteria decision making, triangular hesitant fuzzy set

Procedia PDF Downloads 391
289 Role of Organizational Culture in Building Sustainable Employee’s Performance in Organizations: A Case Study of Zenith Bank PLC Jalingo Taraba State Nigeria

Authors: Jerome Nyameh

Abstract:

The most valuable asset in the existence of organization is the employees and their ability in maintain appreciable level of performance which support the goal of the organization and the ability to do that depend largely on the organizational culture and culture has been considered most currently as the factor that relate positively to organizational excellence and sustainable employee’s performance over the period of time An employee engagement program will not go far without first establishing the organizational culture that is required to support sustainability. This means integrating sustainability into the overall employee’s performance, with clear vision, goals and metrics. It means having strong culture and a collaborative governance structure that has been develop as a ways of doing things in the organization for decision making and resource allocation. It requires a rewards and recognition program to support and reinforce sustainability behaviors. With such a culture in place, organization will be able to develop a strategy that fully engages employees, while fully realizing the benefits of their contributions. The study investigated empirically the role of organizational culture building sustainable employee’s performance using Zenith bank PLC a model where organizational culture will build sustainable employees performance strategy for a lasting actualization of organizational was developed. In order to achieve the research objectives of (i) to assess how organizational culture can build sustainable employee’s performance (ii) to analyze the gap that exists between organizational culture and sustainable employee’s performance in the organization, a survey questionnaires of 20 items was administered to sixty respondents. The findings of this study have practical implications for organizational leaders, managers and employees, and their organizations, particularly commercial banks in Nigeria, besides offering scope for further research in the area of organizational culture and sustainable employee’s performance. It will also show a significance and positive relationship that exist between organizational culture and sustainable employee’s performance, as means of building viable organization with cultural uniqueness and excellence performance in the world of competition.

Keywords: organizational culture, sustainable employee’s performance, organizations, Zenith Bank PLC Nigeria

Procedia PDF Downloads 490
288 Influence of Water Reservoir Parameters on the Climate and Coastal Areas

Authors: Lia Matchavariani

Abstract:

Water reservoir construction on the rivers flowing into the sea complicates the coast protection, seashore starts to degrade causing coast erosion and disaster on the backdrop of current climate change. The instruments of the impact of a water reservoir on the climate and coastal areas are its contact surface with the atmosphere and the area irrigated with its water or humidified with infiltrated waters. The Black Sea coastline is characterized by the highest ecological vulnerability. The type and intensity of the water reservoir impact are determined by its morphometry, type of regulation, level regime, and geomorphological and geological characteristics of the adjoining area. Studies showed the impact of the water reservoir on the climate, on its comfort parameters is positive if it is located in the zone of insufficient humidity and vice versa, is negative if the water reservoir is found in the zone with abundant humidity. There are many natural and anthropogenic factors determining the peculiarities of the impact of the water reservoir on the climate, which can be assessed with maximum accuracy by the so-called “long series” method, which operates on the meteorological elements (temperature, wind, precipitations, etc.) with the long series formed with the stationary observation data. This is the time series, which consists of two periods with statistically sufficient duration. The first period covers the observations up to the formation of the water reservoir and another period covers the observations accomplished during its operation. If no such data are available, or their series is statistically short, “an analog” method is used. Such an analog water reservoir is selected based on the similarity of the environmental conditions. It must be located within the zone of the designed water reservoir, under similar environmental conditions, and besides, a sufficient number of observations accomplished in its coastal zone.

Keywords: coast-constituent sediment, eustasy, meteorological parameters, seashore degradation, water reservoirs impact

Procedia PDF Downloads 23
287 Environmental Drivers of Ichthyofauna Species Diversity and Richness in the Lower Reaches of Warri River, a Typical Mangrove Ecosystem in the Niger Delta, Nigeria

Authors: F. O. Arimoro, F. N. Okonkwo, R. B. Ikomi

Abstract:

The environmental determinants structuring species richness has been generating interest recently but we still lack an understanding of these patterns in various regions (e.g. Afrotropical), and how seasons help to structure these patterns. Our aim was to assessed the environmental drivers importance in regulating species richness and community structure of fish species. The lchthyofauna assemblage of Warri River, Niger Delta area of Nigeria was studied between August 2013 and July 2014. A total of 1152 individuals representing 43 species in 23 families and 30 genera were caught. Of the 43 species recorded, 67.4%, 53.5% and 67.4% of the species occurred in Stations 1, 2 and 3 respectively. Eight taxa representing 18.6% of the total abundance were ubiquitous. The claroteid, Chrysichthys walkeri and the cichlid, Chromidotilapia guentheri were the most dominant species accounting for 19.2% and 6.0% respectively of the total catch. The species richness and general diversity were relatively higher in station 1 although Jaccard similarity index revealed that stations 1 and 3 were significantly similar while station 2 showed complete dissimilarity with stations 1 and 3. Canonical correspondence analysis indicated that dissolved oxygen, electrical conductivity, total nitrogen, Biochemical Oxygen demand and temperature were important variables structuring the overall fish assemblages. The presence of appreciable number of juveniles in this water body suggests that the Warri River is a breeding and nursery ground for fish species particularly those of brackish origin. These findings indicate that the water body is still useful as a good fishing ground for the rural communities and every effort should be put in place to ensure its protection and conservation for the production of healthy fish.

Keywords: Chrysichthys walkeri, fish communities, mangrove ecosystem, physicochemical parameters, Warri River

Procedia PDF Downloads 466
286 A Multivariate Statistical Approach for Water Quality Assessment of River Hindon, India

Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

Abstract:

River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: cluster analysis, multivariate statistical techniques, river Hindon, water quality

Procedia PDF Downloads 433
285 Exploring Students' Alternative Conception in Vector Components

Authors: Umporn Wutchana

Abstract:

An open ended problem and unstructured interview had been used to explore students’ conceptual and procedural understanding of vector components. The open ended problem had been designed based on research instrument used in previous physics education research. Without physical context, we asked students to find out magnitude and draw graphical form of vector components. The open ended problem was given to 211 first year students of faculty of science during the third (summer) semester in 2014 academic year. The students spent approximately 15 minutes of their second time of the General Physics I course to complete the open ended problem after they had failed. Consequently, their responses were classified based on the similarity of errors performed in the responses. Then, an unstructured interview was conducted. 7 students were randomly selected and asked to reason and explain their answers. The study results showed that 53% of 211 students provided correct numerical magnitude of vector components while 10.9% of them confused and punctuated the magnitude of vectors in x- with y-components. Others 20.4% provided just symbols and the last 15.6% gave no answer. When asking to draw graphical form of vector components, only 10% of 211 students made corrections. A majority of them produced errors and revealed alternative conceptions. 46.5% drew longer and/or shorter magnitude of vector components. 43.1% drew vectors in different forms or wrote down other symbols. Results from the unstructured interview indicated that some students just memorized the method to get numerical magnitude of x- and y-components. About graphical form of component vectors, some students though that the length of component vectors should be shorter than those of the given one. So then, it could be combined to be equal length of the given vectors while others though that component vectors should has the same length as the given vectors. It was likely to be that many students did not develop a strong foundation of understanding in vector components but just learn by memorizing its solution or the way to compute its magnitude and attribute little meaning to such concept.

Keywords: graphical vectors, vectors, vector components, misconceptions, alternative conceptions

Procedia PDF Downloads 169
284 Bioinformatics Approach to Support Genetic Research in Autism in Mali

Authors: M. Kouyate, M. Sangare, S. Samake, S. Keita, H. G. Kim, D. H. Geschwind

Abstract:

Background & Objectives: Human genetic studies can be expensive, even unaffordable, in developing countries, partly due to the sequencing costs. Our aim is to pilot the use of bioinformatics tools to guide scientifically valid, locally relevant, and economically sound autism genetic research in Mali. Methods: The following databases, NCBI, HGMD, and LSDB, were used to identify hot point mutations. Phenotype, transmission pattern, theoretical protein expression in the brain, the impact of the mutation on the 3D structure of the protein) were used to prioritize selected autism genes. We used the protein database, Modeller, and clustal W. Results: We found Mef2c (Gly27Ala/Leu38Gln), Pten (Thr131IIle), Prodh (Leu289Met), Nme1 (Ser120Gly), and Dhcr7 (Pro227Thr/Glu224Lys). These mutations were associated with endonucleases BseRI, NspI, PfrJS2IV, BspGI, BsaBI, and SpoDI, respectively. Gly27Ala/Leu38Gln mutations impacted the 3D structure of the Mef2c protein. Mef2c protein sequences across species showed a high percentage of similarity with a highly conserved MADS domain. Discussion: Mef2c, Pten, Prodh, Nme1, and Dhcr 7 gene mutation frequencies in the Malian population will be very informative. PCR coupled with restriction enzyme digestion can be used to screen the targeted gene mutations. Sanger sequencing will be used for confirmation only. This will cut down considerably the sequencing cost for gene-to-gene mutation screening. The knowledge of the 3D structure and potential impact of the mutations on Mef2c protein informed the protein family and altered function (ex. Leu38Gln). Conclusion & Future Work: Bio-informatics will positively impact autism research in Mali. Our approach can be applied to another neuropsychiatric disorder.

Keywords: bioinformatics, endonucleases, autism, Sanger sequencing, point mutations

Procedia PDF Downloads 53
283 Response to Comprehensive Stress of Growing Greylag Geese Offered Alternative Fiber Sources

Authors: He Li Wen, Meng Qing Xiang, Li De Yong, Zhang Ya Wei, Ren Li Ping

Abstract:

Stress always exerts some extent adverse effects on the animal production, food safety and quality concerns. Stress is commonly-seen in livestock industry, but there is rare literature focusing on the effects of nutrition stress. What’s more, the research always concentrates on the effect of single stress additionally, there is scarce information about the stress effect on waterfowl like goose as they are commonly thought to be tolerant to stress. To our knowledge, it is not always true. The object of this study was to evaluate the response of growing Greylag geese offered different fiber sources to the comprehensive stress, primarily involving the procedures of fasting, transport, capture, etc. The birds were randomly selected to rear with the diets differing in fiber source, being corn straw silage (CSS), steam-exploded corn straw (SECS), steam-exploded wheat straw (SEWS), and steam-exploded rice straw (SERS), respectively. Blood samples designated for the determination of stress status were collected before (pre-stress ) and after (post-stress ) the stressors carried out. No difference (P>0.05) was found on the pre-stress blood parameters of growing Greylags fed alternative fiber sources. Irrespective of the dietary differences, the comprehensive stress decreased (P<0.01) the concentration of SOD and increased (P<0.01) that of CK. Between the dietary treatments, the birds fed CSS had a higher (P<0.05)post-stress concentration of MDA than those offered SECS, along with a similarity to those fed the other two fiber sources. There was no difference (P>0.05) found on the stress response of the birds fed different fiber sources. In conclusion, SOD and CK concentration in blood may be more sensitive in indicating stress status and dietary fiber source exerted no effect on the stress response of growing Greylags. There is little chance to improve the stress status by ingesting different fiber sources.

Keywords: blood parameter, fiber source, Greylag goose, stress

Procedia PDF Downloads 488
282 Multi-Sensor Image Fusion for Visible and Infrared Thermal Images

Authors: Amit Kumar Happy

Abstract:

This paper is motivated by the importance of multi-sensor image fusion with a specific focus on infrared (IR) and visual image (VI) fusion for various applications, including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like visible camera & IR thermal imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (infrared) that may be reflected or self-emitted. A digital color camera captures the visible source image, and a thermal infrared camera acquires the thermal source image. In this paper, some image fusion algorithms based upon multi-scale transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes the implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, they also make it hard to become deployed in systems and applications that require a real-time operation, high flexibility, and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity.

Keywords: image fusion, IR thermal imager, multi-sensor, multi-scale transform

Procedia PDF Downloads 87
281 Day Ahead and Intraday Electricity Demand Forecasting in Himachal Region using Machine Learning

Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

Abstract:

Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

Procedia PDF Downloads 44
280 Teaching Food Discourse in Cross-Cultural Communication Lectures at University

Authors: Sanjar Davronov

Abstract:

Linguistic research of food discourse helps to analyze gastronomic picture of the world which plays important role in cross-cultural communications. 20 hours lecture can’t provide broad knowledge about national picture of the world of native speakers whose language being studied by future translator students. This abstract analyses how to research food discourse in “Cross-cultural (or lingvo-cultural) communication” lectures for ESL students. During compare Uzbek and American national meals, we found some specific features of food names in both countries. For example: If names of food includes advertising character in USA restaurant menus like: New York strip Sirloin crowned with Fresh – squeezed orange and lemon with a hint of garlic; Uzbek meals names are too simple, short and force general afford in underlining action – preparation process like: “Dimlama” (dimla(verb-to stew)+ma(suffix of past perfect like- stew- stewed). “Qovurdoq” (qovur (verb- to fry)+ doq (suffix of adverb like “fried one”) but these are the most delicious and difficult in preparing national meals however it is heritage of national cuisine. There are also similarity between US and Uzbek food names which has geographical color - South African Lobster tail; Qashqadaryo tandiri (lamb prepared in “tandir” typical national oven with pine leafs in Qashkadarya region). Food for European people contains physical context more than spiritual but in Asian literature especially Uzbek food has some pragmatic stuff: salt and bread (associates with hospitality and humanity), don’t be faithlessness 40 for owners of house where you where a guest. We share some teaching techniques for food discourse analyzing lectures.

Keywords: cross-cultural communications, food discourse, ESL lectures, linguistic research

Procedia PDF Downloads 596
279 Investigating the Effectiveness of Multilingual NLP Models for Sentiment Analysis

Authors: Othmane Touri, Sanaa El Filali, El Habib Benlahmar

Abstract:

Natural Language Processing (NLP) has gained significant attention lately. It has proved its ability to analyze and extract insights from unstructured text data in various languages. It is found that one of the most popular NLP applications is sentiment analysis which aims to identify the sentiment expressed in a piece of text, such as positive, negative, or neutral, in multiple languages. While there are several multilingual NLP models available for sentiment analysis, there is a need to investigate their effectiveness in different contexts and applications. In this study, we aim to investigate the effectiveness of different multilingual NLP models for sentiment analysis on a dataset of online product reviews in multiple languages. The performance of several NLP models, including Google Cloud Natural Language API, Microsoft Azure Cognitive Services, Amazon Comprehend, Stanford CoreNLP, spaCy, and Hugging Face Transformers are being compared. The models based on several metrics, including accuracy, precision, recall, and F1 score, are being evaluated and compared to their performance across different categories of product reviews. In order to run the study, preprocessing of the dataset has been performed by cleaning and tokenizing the text data in multiple languages. Then training and testing each model has been applied using a cross-validation approach where randomly dividing the dataset into training and testing sets and repeating the process multiple times has been used. A grid search approach to optimize the hyperparameters of each model and select the best-performing model for each category of product reviews and language has been applied. The findings of this study provide insights into the effectiveness of different multilingual NLP models for Multilingual Sentiment Analysis and their suitability for different languages and applications. The strengths and limitations of each model were identified, and recommendations for selecting the most performant model based on the specific requirements of a project were provided. This study contributes to the advancement of research methods in multilingual NLP and provides a practical guide for researchers and practitioners in the field.

Keywords: NLP, multilingual, sentiment analysis, texts

Procedia PDF Downloads 60
278 Magneto-Hydrodynamic Mixed Convective Fluid Flow through Two Parallel Vertical Plates Channel with Hall, Chemical Reaction, and Thermal Radiation Effects

Authors: Okuyade Ighoroje Wilson Ata

Abstract:

Magneto-hydrodynamic mixed convective chemically reacting fluid flow through two parallel vertical plates channel with Hall, radiation, and chemical reaction effects are examined. The fluid is assumed to be chemically reactive, electrically conducting, magnetically susceptible, viscous, incompressible, and Newtonian; the plates are porous, electrically conductive, and heated to a high-temperature regime to generate thermal rays. The flow system is highly interactive, such that cross/double diffusion is present. The governing equations are partial differential equations transformed into ordinary differential equations using similarity transformation and solved by the method of Homotopy Perturbation. Expressions for the concentration, temperature, velocity, Nusselt number, Sherwood number, and Wall shear stress are obtained, computed, and presented graphically and tabularly. The analysis of results shows, amongst others, that an increase in the Raleigh number increases the main velocity and temperature but decreases the concentration. More so, an increase in chemical reaction rate increases the main velocity, temperature, rate of heat transfer from the terminal plate, the rate of mass transfer from the induced plate, and Wall shear stress on both the induced and terminal plates, decreasing the concentration, and the mass transfer rate from the terminal plate. Some of the obtained results are benchmarked with those of existing literature and are in consonance.

Keywords: chemical reaction, hall effect, magneto-hydrodynamic, radiation, vertical plates channel

Procedia PDF Downloads 60
277 Legal Allocation of Risks: A Computational Analysis of Force Majeure Clauses

Authors: Farshad Ghodoosi

Abstract:

This article analyzes the effect of supervening events in contracts. Contracts serve an important function: allocation of risks. In spite of its importance, the case law and the doctrine are messy and inconsistent. This article provides a fresh look at excuse doctrines (i.e., force majeure, impracticability, impossibility, and frustration) with a focus on force majeure clauses. The article makes the following contributions: First, it furnishes a new conceptual and theoretical framework of excuse doctrines. By distilling the decisions, it shows that excuse doctrines rests on the triangle of control, foreseeability, and contract language. Second, it analyzes force majeure clauses used by S&P 500 companies to understand the stickiness and similarity of such clauses and the events they cover. Third, using computational and statistical tools, it analyzes US cases since 1810 in order to assess the weight given to the triangle of control, foreseeability, and contract language. It shows that the control factor plays an important role in force majeure analysis, while the contractual interpretation is the least important factor. The Article concludes that it is the standard for control -whether the supervening event is beyond the control of the party- that determines the outcome of cases in the force majeure context and not necessarily the contractual language. This article has important implications on COVID-19-related contractual cases. Unlike the prevailing narrative that it is the language of the force majeure clause that’s determinative, this article shows that the primarily focus of the inquiry will be on whether the effects of COVID-19 have been beyond the control of the promisee. Normatively, the Article suggests that the trifactor of control, foreseeability, and contractual language are not effective for allocation of legal risks in times of crises. It puts forward a novel approach to force majeure clauses whereby that the courts should instead focus on the degree to which parties have relied on (expected) performance, in particular during the time of crisis.

Keywords: contractual risks, force majeure clauses, foreseeability, control, contractual language, computational analysis

Procedia PDF Downloads 116
276 STD-NMR Based Protein Engineering of the Unique Arylpropionate-Racemase AMDase G74C

Authors: Sarah Gaßmeyer, Nadine Hülsemann, Raphael Stoll, Kenji Miyamoto, Robert Kourist

Abstract:

Enzymatic racemization allows the smooth interconversion of stereocenters under very mild reaction conditions. Racemases find frequent applications in deracemization and dynamic kinetic resolutions. Arylmalonate decarboxylase (AMDase) from Bordetella Bronchiseptica has high structural similarity to amino acid racemases. These cofactor-free racemases are able to break chemically strong CH-bonds under mild conditions. The racemase-like catalytic machinery of mutant G74C conveys it a unique activity in the racemisation of pharmacologically relevant derivates of 2-phenylpropionic acid (profenes), which makes AMDase G74C an interesting object for the mechanistic investigation of cofactor-independent racemases. Structure-guided protein engineering achieved a variant of this unique racemase with 40-fold increased activity in the racemisation of several arylaliphatic carboxylic acids. By saturation–transfer–difference NMR spectroscopy (STD-NMR), substrate binding during catalysis was investigated. All atoms of the substrate showed interactions with the enzyme. STD-NMR measurements revealed distinct nuclear Overhauser effects in experiments with and without molecular conversion. The spectroscopic analysis led to the identification of several amino acid residues whose variation increased the activity of G74C. While single-amino acid exchanges increased the activity moderately, structure-guided saturation mutagenesis yielded a quadruple mutant with a 40 times higher reaction rate. This study presents STD-NMR as versatile tool for the analysis of enzyme-substrate interactions in catalytically competent systems and for the guidance of protein engineering.

Keywords: racemase, rational protein design, STD-NMR, structure guided saturation mutagenesis

Procedia PDF Downloads 282
275 Data Mining Model for Predicting the Status of HIV Patients during Drug Regimen Change

Authors: Ermias A. Tegegn, Million Meshesha

Abstract:

Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome (HIV/AIDS) is a major cause of death for most African countries. Ethiopia is one of the seriously affected countries in sub Saharan Africa. Previously in Ethiopia, having HIV/AIDS was almost equivalent to a death sentence. With the introduction of Antiretroviral Therapy (ART), HIV/AIDS has become chronic, but manageable disease. The study focused on a data mining technique to predict future living status of HIV/AIDS patients at the time of drug regimen change when the patients become toxic to the currently taking ART drug combination. The data is taken from University of Gondar Hospital ART program database. Hybrid methodology is followed to explore the application of data mining on ART program dataset. Data cleaning, handling missing values and data transformation were used for preprocessing the data. WEKA 3.7.9 data mining tools, classification algorithms, and expertise are utilized as means to address the research problem. By using four different classification algorithms, (i.e., J48 Classifier, PART rule induction, Naïve Bayes and Neural network) and by adjusting their parameters thirty-two models were built on the pre-processed University of Gondar ART program dataset. The performances of the models were evaluated using the standard metrics of accuracy, precision, recall, and F-measure. The most effective model to predict the status of HIV patients with drug regimen substitution is pruned J48 decision tree with a classification accuracy of 98.01%. This study extracts interesting attributes such as Ever taking Cotrim, Ever taking TbRx, CD4 count, Age, Weight, and Gender so as to predict the status of drug regimen substitution. The outcome of this study can be used as an assistant tool for the clinician to help them make more appropriate drug regimen substitution. Future research directions are forwarded to come up with an applicable system in the area of the study.

Keywords: HIV drug regimen, data mining, hybrid methodology, predictive model

Procedia PDF Downloads 115
274 Pharmaceutical Equivalence of Some Injectable Gentamicin Generics Used in Veterinary Practice in Nigeria

Authors: F. A. Gberindyer, M. O.Abatan, A. B. Saba

Abstract:

Background: Gentamicin is an aminoglycoside antibiotic used in the treatment of infections caused by Gram-negative aerobic bacteria organisms in human and animals. In Nigeria, there are arrays of multisource generic versions of injectable gentamicin sulphate in the drug markets. There is a high prevalence of counterfeit and substandard drugs in the third world countries with consequent effect on their therapeutic efficacy and safety. Aim: The aim of this study was to investigate pharmaceutical equivalence of some of these generics used in veterinary practice in Nigeria. Methodology: About 20 generics of injectable gentamicin sulphate were sampled randomly across Nigeria but 15 were analyzed for identity and potency. Identity test was done using Fourier transform infra red spectroscopy and the spectral for each product compared with that of the USP reference standard for similarity. Microbiological assay using agar diffusion method with E. coli as a test organism on nutrient agar was employed and the respective diameters of bacterial inhibition zones obtained after 24 hour incubation at 37°C. The percent potency for each product was thereafter calculated and compared with the official specification. Result And Discussion: None of the generics is produced in any African country. About 75 % of the products are imported from China whereas 60 % of the veterinary generics are manufactured in Holland. Absorption spectra for the reference and test samples were similar. Percent potencies of all test products were within the official specification of 95-115 %. Nigeria relies solely on imported injectable gentamicin sulphate products. All sampled generic versions passed both identity and potency tests. Clinicians should ensure that drugs are used rationally since the converse could be contributing to the therapeutic failures reported for most of these generics. Bioequivalence study is recommended to ascertain their interchangeability when parenteral extra venous routes are indicated.

Keywords: generics, gentamicin, identity, multisource, potency

Procedia PDF Downloads 404
273 Safeguarding Product Quality through Pre-Qualification of Material Manufacturers: A Ship and Offshore Classification Society's Perspective

Authors: Sastry Y. Kandukuri, Isak Andersen

Abstract:

Despite recent advances in the manufacturing sector, quality issues remain a frequent occurrence, and can result in fatal accidents, equipment downtime, and loss of life. Adequate quality is of high importance in high-risk industries such as sea-going vessels and offshore installations in which third party quality assurance and product control play an important essential role in ensuring manufacturing quality of critical components. Classification societies play a vital role in mitigating risk in these industries by making sure that all the stakeholders i.e. manufacturers, builders, and end users are provided with adequate rules and standards that effectively ensures components produced at a high level of quality based on the area of application and risk of its failure. Quality issues have also been linked to the lack of competence or negligence of stakeholders in supply value chain. However, continued actions and regulatory reforms through modernization of rules and requirements has provided additional tools for purchasers and manufacturers to confront these issues. Included among these tools are updated ‘approval of manufacturer class programs’ aimed at developing and implementing a set of standardized manufacturing quality metrics for use by the manufacturer and verified by the classification society. The establishment and collection of manufacturing and testing requirements described in these programs could provide various stakeholders – from industry to vessel owners – with greater insight into the state of quality at a given manufacturing facility, and allow stakeholders to anticipate better and address quality issues while simultaneously reducing unnecessary failures that are costly to the industry. The publication introduces, explains and discusses critical manufacturing and testing requirements set in a leading class society’s approval of manufacturer regime and its rationale and some case studies.

Keywords: classification society, manufacturing, materials processing, materials testing, quality control

Procedia PDF Downloads 331