Search results for: small object detection

Authors: Ipsita Biswas, Arnab Sarkar, Ashikur Rahaman, Gopeswar Mukherjee, Subhrangsu Chatterjee, Shamee Bhattacharjee, Deba Prasad Mandal

Abstract:

One of the major reasons for the high mortality rate of lung cancer is the substantial delays in disease detection at late metastatic stages. It is of utmost importance to understand the detailed molecular signaling and detect the molecular markers that can be used for the early diagnosis of cancer. Several studies explored the emerging roles of long noncoding RNAs (lncRNAs) in various cancers as well as lung cancer. A long non-coding RNA LINC00273 was recently discovered to promote cancer cell migration and invasion, and its positive correlation with the pathological stages of metastasis may prove it to be a potential target for inhibiting cancer cell metastasis. Comparing real-time expression of LINC00273 in various human clinical cancer tissue samples with normal tissue samples revealed significantly higher expression in cancer tissues. This long intergenic noncoding RNA was found to be highly expressed in human liver tumor-initiating cells, human gastric adenocarcinoma AGS cell line, as well as human non-small cell lung cancer A549 cell line. SiRNA and shRNA-induced knockdown of LINC00273 in both in vitro and in vivo nude mice significantly subsided AGS and A549 cancer cell migration and invasion. LINC00273 knockdown also reduced TGF-β induced SNAIL, SLUG, VIMENTIN, ZEB1 expression, and metastasis in A549 cells. Plenty of reports have suggested the role of microRNAs of the miR200 family in reversing epithelial to mesenchymal transition (EMT) by inhibiting ZEB transcription factors. In this study, hsa-miR-200a-3p was predicted via IntaRNA-Freiburg RNA tools to be a potential target of LINC00273 with a negative free binding energy of −8.793 kcal/mol, and this interaction was verified as a confirmed target of LINC00273 by RNA pulldown, real-time PCR and luciferase assay. Mechanistically, LINC00273 accelerated TGF-β induced EMT by sponging hsa-miR-200a-3p which in turn liberated ZEB1 and promoted prometastatic functions in A549 cells in vitro as verified by real-time PCR and western blotting. The similar expression patterns of these EMT regulatory pathway molecules, viz. LINC00273, hsa-miR-200a-3p, ZEB1 and TGF-β, were also detected in various clinical samples like breast cancer tissues, oral cancer tissues, lung cancer tissues, etc. Overall, this LINC00273 mediated EMT regulatory signaling can serve as a potential therapeutic target for the prevention of lung cancer metastasis.

Keywords: epithelial to mesenchymal transition, long noncoding RNA, microRNA, non-small-cell lung carcinoma

Procedia PDF Downloads 148

Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

Abstract:

In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis

Procedia PDF Downloads 321

Authors: Peter Burggräf, Moritz Krunke, Hanno Voet

Abstract:

Due to shortening product and technology lifecycles, many companies use standardization approaches in product development and factory planning to reduce costs and time to market. Unlike large companies, where modular systems are already widely used, small and medium-sized companies often show a much lower degree of standardization due to lower scale effects and missing capacities for the development of these standards. To overcome these challenges, the development of industry sector specific standards in cooperations or by third parties is an interesting approach. This paper analyzes which branches that are mainly dominated by small or medium-sized companies might be especially interesting for the development of factory standards using the example of the German industry. For this, a key performance indicator based approach was developed that will be presented in detail with its specific results for the German industry structure.

Keywords: factory planning, factory standards, industry sector specific standardization, production planning

Procedia PDF Downloads 388

Authors: P. Senthil Kumari

Abstract:

Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

Procedia PDF Downloads 496

Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

Abstract:

A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: bistatic radar cross section, passive radar, propagation losses, radar coverage

Procedia PDF Downloads 327

Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

Abstract:

Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

Procedia PDF Downloads 216

Authors: Jonathan Heng, Yoong Cheah Huei

Abstract:

A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

Procedia PDF Downloads 175

Authors: Sara Martín, Ying Jie Zheng, César Hueso

Abstract:

International shipping is considered one of the largest sources of pollution in the world, accounting for 812 million tons of CO2 emissions in the year 2018. Current maritime decarbonisation is based on the implementation of new fuel alternatives, such as LNG, biofuels, and methanol, among others, which are less polluting as well as less efficient. Despite being a carbon-free and highly-developed technology, nuclear propulsion is hardly discussed as an alternative. Scientifically, it is believed that Small Modular Reactors (SMR) could be a promising solution to decarbonized maritime traffic due to their small dimensions and safety capabilities. However, as of today, there are no merchant ships powered by nuclear systems. Therefore, this project aims to understand the challenges of the development of nuclear-fuelled vessels by analysing all SMR designs to choose the most suitable one. In order not to fall into subjectivities, the Analytic Hierarchy Process (AHP) will be used to make the selection. This multiple-criteria evaluation technique analyses complex decisions by pairwise comparison of a number of evaluation criteria that can be applied to each SMR. The state-of-the-art 72 SMRs presented by the International Atomic Energy Agency (IAEA) will be analysed and ranked by a global parameter, calculated by applying the AHP methodology. The main target of the work is to find an adequate SMR system to power a ship. Top designs will be described in detail, and conclusions will be drawn from the results. This project has been conceived as an effort to foster the near-term development of zero-emission maritime traffic.

Keywords: international shipping, decarbonization, SMR, AHP, nuclear-fuelled vessels

Procedia PDF Downloads 117

Authors: Ka Ho Yau, Jan Frederick Engels, Kwok Kei Lai, Reinhard Renneberg

Abstract:

Lateral flow test is a prevalent technology in various sectors such as food, pharmacology and biomedical sciences. Colloidal gold (CG) is widely used as the signalling molecule because of the ease of synthesis, bimolecular conjugation and its red colour due to intrinsic SPRE. However, the production of colloidal gold is costly and requires vigorous conditions. The stability of colloidal gold are easily affected by environmental factors such as pH, high salt content etc. Silica nanoparticles are well known for its ease of production and stability over a wide range of solvents. Using reverse micro-emulsion (w/o), silica nanoparticles with different sizes can be produced precisely by controlling the amount of water. By incorporating different water-soluble dyes, a rainbow colour of the silica nanoparticles could be produced. Conjugation with biomolecules such as antibodies can be achieved after surface modification of the silica nanoparticles with organosilane. The optimum amount of the antibodies to be labelled was determined by Bradford Assay. In this work, we have demonstrated the ability of the dye-doped silica nanoparticles as a signalling molecule in lateral flow test, which showed a semi-quantitative measurement of the analyte. The image was further analysed for the LOD=10 ng of the analyte. The working range and the linear range of the test were from 0 to 2.15μg/mL and from 0 to 1.07 μg/mL (R2=0.988) respectively. The performance of the tests was comparable to those using colloidal gold with the advantages of lower cost, enhanced stability and having a wide spectrum of colours. The positives lines can be imaged by naked eye or by using a mobile phone camera for a better quantification. Further research has been carried out in multicolour detection of different biomarkers simultaneously. The preliminary results were promising as there was little cross-reactivity being observed for an optimized system. This approach provides a platform for multicolour detection for a set of biomarkers that enhances the accuracy of diseases diagnostics.

Keywords: colorimetric detection, immunosensor, paper-based biosensor, silica

Procedia PDF Downloads 375

Authors: Yuichi Morita, Yoshiteru Nakamori

Abstract:

In car dealer business of Japan, a sale professional is a key factor of company’s success. We hypothesize that, if a corporation knows what is the sales professionals’ trait of its corporation’s business field, it will be easier for a corporation to secure and nurture sales persons effectively. The lean human resources management will ensure business success and good performance of corporations, especially small and medium ones. The goal of the paper is to determine the traits of sales professionals for small-and medium-size car dealers, using chi-square test and the variable rough set model. As a result, the results illustrate that experience of job change, learning ability and product knowledge are important, and an academic background, building a career with internal transfer, experience of the leader and self-development are not important to be a sale professional. Also, we illustrate sales professionals’ traits are persistence, humility, improvisation and passion at business.

Keywords: traits of sales professionals, variable precision rough sets theory, sales professional, sales professionals

Procedia PDF Downloads 377

Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

Abstract:

Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

Procedia PDF Downloads 255

Authors: Meysam Naeimi, Zili Li, Rolf Dollevoet

Abstract:

A new small–scale test rig developed for rolling contact fatigue (RCF) investigations in wheel–rail material. This paper presents the scaling strategy of the rig based on dimensional analysis and mechanical modelling. The new experimental rig is indeed a spinning frame structure with multiple wheel components over a fixed rail-track ring, capable of simulating continuous wheel-rail contact in a laboratory scale. This paper describes the dimensional design of the rig, to derive its overall scaling strategy and to determine the key elements’ specifications. Finite element (FE) modelling is used to simulate the mechanical behavior of the rig with two sample scale factors of 1/5 and 1/7. The results of FE models are compared with the actual railway system to observe the effectiveness of the chosen scales. The mechanical properties of the components and variables of the system are finally determined through the design process.

Keywords: new test rig, rolling contact fatigue, rail, small scale

Procedia PDF Downloads 469

Authors: Olga Orynycz, Andrzej Wasiak

Abstract:

Mathematical model describing energetic efficiency (defined as a ratio of energy obtained in the form of biofuel to the sum of energy inputs necessary to facilitate production) of agricultural subsystem as a function of technological parameters was developed. Production technology is characterized by parameters of machinery, topological characteristics of the plantation as well as transportation routes inside and outside of plantation. The relationship between the energetic efficiency of agricultural and industrial subsystems is also derived. Due to the assumed large area of the individual field, the operations last for several days increasing inter-fields routes because of several returns. The total distance driven outside of the fields is, however, small as compared to the distance driven inside of the fields. This results in small energy consumption during inter-fields transport that, however, causes a substantial decrease of the energetic effectiveness of the whole system.

Keywords: biofuel, energetic efficiency, EROEI, mathematical modelling, production system

Procedia PDF Downloads 339

Authors: Rafael Sousa Santos, Clara Pimena Do Vale, Barbara Bogoni, Poul Henning Kirkegaard

Abstract:

The representative component, a determining aspect of the architect's training, has been marked by an exponential and unprecedented development. However, the multiplication of possibilities has also multiplied uncertainties about architectural design teaching, and by extension, about the very principles of architectural education. In this paper, it is intended to present the results of a research developed on the following problem: the relation between the forms of representation and the architectural design teaching-learning processes. The research had as its object the educational model of two schools – the Politecnico di Milano (POLIMI) and the Faculty of Architecture of the University of Porto (FAUP) – and was led by three main objectives: to characterize the educational model followed in both schools focused on the representative component and its role; to interpret the relation between forms of representation and the architectural design teaching-learning processes; to consider their possibilities of valorisation. Methodologically, the research was conducted according to a qualitative embedded multiple-case study design. The object – i.e., the educational model – was approached in both POLIMI and FAUP cases considering its Context and three embedded unities of analysis: the educational Purposes, Principles, and Practices. In order to guide the procedures of data collection and analysis, a Matrix for the Characterization (MCC) was developed. As a methodological tool, the MCC allowed to relate the three embedded unities of analysis with the three main sources of evidence where the object manifests itself: the professors, expressing how the model is assumed; the architectural design classes, expressing how the model is achieved; and the students, expressing how the model is acquired. The main research methods used were the naturalistic and participatory observation, in-person-interview and documentary and bibliographic review. The results reveal the importance of the representative component in the educational model of both cases, despite the differences in its role. In POLIMI's model, representation is particularly relevant in the teaching of architectural design, while in FAUP’s model, it plays a transversal role – according to an idea of 'general training through hand drawing'. In fact, the difference between models relative to representation can be partially understood by the level of importance that each gives to hand drawing. Regarding the teaching of architectural design, the two cases are distinguished in the relation with the representative component: while in POLIMI the forms of representation serve essentially an instrumental purpose, in FAUP they tend to be considered also for their methodological dimension. It seems that the possibilities for valuing these models reside precisely in the relation between forms of representation and architectural design teaching. It is expected that the knowledge base developed in this research may have three main contributions: to contribute to the maintenance of the educational model of POLIMI and FAUP; through the precise description of the methodological procedures, to contribute by transferability to similar studies; through the critical and objective framework of the problem underlying the forms of representation and its relation with architectural design teaching, to contribute to the broader discussion concerning the contemporary challenges on architectural education.

Keywords: architectural design teaching, architectural education, educational models, forms of representation

Procedia PDF Downloads 114

Authors: Noureddine Henka, Sami Tazi, Mohamad Assaad

Abstract:

The electrical grid is a highly intricate system designed to transfer electricity from production areas to consumption areas. The Transmission System Operator (TSO) is responsible for ensuring the efficient distribution of electricity and maintaining the grid's safety and quality. However, due to the increasing integration of intermittent renewable energy sources, there is a growing level of uncertainty, which requires a faster responsive approach. A potential solution involves the use of electrical segmentation, which involves creating coherence zones where electrical disturbances mainly remain within the zone. Indeed, by means of coherent electrical zones, it becomes possible to focus solely on the sub-zone, reducing the range of possibilities and aiding in managing uncertainty. It allows faster execution of operational processes and easier learning for supervised machine learning algorithms. Electrical segmentation can be applied to various applications, such as electrical control, minimizing electrical loss, and ensuring voltage stability. Since the electrical grid can be modeled as a graph, where the vertices represent electrical buses and the edges represent electrical lines, identifying coherent electrical zones can be seen as a clustering task on graphs, generally called community detection. Nevertheless, a critical criterion for the zones is their ability to remain resilient to the electrical evolution of the grid over time. This evolution is due to the constant changes in electricity generation and consumption, which are reflected in graph structure variations as well as line flow changes. One approach to creating a resilient segmentation is to design robust zones under various circumstances. This issue can be represented through a multiplex graph, where each layer represents a specific situation that may arise on the grid. Consequently, resilient segmentation can be achieved by conducting community detection on this multiplex graph. The multiplex graph is composed of multiple graphs, and all the layers share the same set of vertices. Our proposal involves a model that utilizes a unified representation to compute a flattening of all layers. This unified situation can be penalized to obtain (K) connected components representing the robust electrical segmentation clusters. We compare our robust segmentation to the segmentation based on a single reference situation. The robust segmentation proves its relevance by producing clusters with high intra-electrical perturbation and low variance of electrical perturbation. We saw through the experiences when robust electrical segmentation has a benefit and in which context.

Keywords: community detection, electrical segmentation, multiplex graph, power grid

Procedia PDF Downloads 68

Authors: Zanjbeel Tabassum

Abstract:

The main purpose of any economic investment is to get profit at the end. As the investment in large organizations bears complexities, investors are influenced to invest in small or medium enterprises. With the increase of global competition in terms of quality and productivity, these small and medium-sized enterprises (SMEs) are trying to convert to modern production practices using Six Sigma. But this concept is still lacking in Pakistani SMEs. There are some critical success factors which influence the successful implementation of Six Sigma. Through this paper, an attempt has been made to identify various CSF for successful implementation of Six Sigma in Pakistani SMEs with the help of a structured survey. On the basis of responses to the questionnaire, factor analysis is performed on the selected critical success factors (from literature) to prioritize the critical factors and those are rated by calculating descriptive statistics. This paper will provide a base for Pakistani SMEs and future researchers working in six sigma implementation and help them to prepare a road map to eradicate the hurdles in six sigma implementation.

Keywords: critical success factors, SMEs, Six Sigma, CSF

Procedia PDF Downloads 271

Authors: Felicia Wong Yen Myan, James Walker

Abstract:

Development of micro topographies usually begins with the fabrication of a master stamp. Fabrication of such small structures can be technically challenging and expensive. These techniques are often used for applications where patterns only cover a small surface area (e.g. semiconductors, microfluidic channels). This research investigated the use of benchtop lithography to fabricate patterns with average widths of 50 and 100 microns on silicon wafer substrates. Further development of this method will attempt to layer patterns to create hierarchical structures. Photomasks consisted of patterns printed onto transparency films with a high resolution printer and a fully patterned 10cm by 10cm area has been successfully developed. UV exposure was carried out with a self-made array of ultraviolet LEDs that was positioned a distance above a glass diffuser. Observations under a light microscope and SEM showed that developed patterns exhibit an adequate degree of fidelity with patterns from the master stamp.

Keywords: lithography, antifouling, marine, microtopography

Procedia PDF Downloads 283

Authors: Ali Al-Dahoud, Mohamed Fezari, Thamer Al-Rawashdeh, Ismail Jannoud

Abstract:

Monitoring and detecting faults on a set of Solar panels, using a wireless sensor network (WNS) is our contribution in this paper, This work is part of the project we are working on at Al-Zaytoonah University. The research problem has been exposed by engineers and technicians or operators dealing with PV panels maintenance, in order to monitor and detect faults within solar panels which affect considerably the energy produced by the solar panels. The proposed solution is based on installing WSN nodes with appropriate sensors for more often occurred faults on the 45 solar panels installed on the roof of IT faculty. A simulation has been done on nodes distribution and a study for the design of a node with appropriate sensors taking into account the priorities of the processing faults. Finally, a graphic user interface is designed and adapted to telemonitoring panels using WSN. The primary tests of hardware implementation gave interesting results, the sensors calibration and interference transmission problem have been solved. A friendly GUI using high level language Visial Basic was developed to carry out the monitoring process and to save data on Exel File.

Keywords: Arduino Mega microcnotroller, solar panels, fault-detection, simulation, node design

Procedia PDF Downloads 458

Authors: Diego Adrian Cardenas Jorge, Gerardo Mirando Guisado, Alfredo Barrientos Padilla

Abstract:

A system based on Affective Computing can detect and interpret human information like voice, facial expressions and body movement to detect emotions and execute a corresponding response. This data is important due to the fact that a person can communicate more effectively with emotions than can be possible with words. This information can be processed through technological components like Facial Recognition, Gait Recognition or Gesture Recognition. As of now, solutions proposed using this technology only consider one component at a given moment. This research investigation proposes two solutions based on Affective Computing taking into account more than one component for emotion detection. The proposals reflect the levels of dependency between hardware devices and software, as well as the interaction process between the system and the user which implies the development of scenarios where both proposals will be put to the test in a live environment. Both solutions are to be developed in code by software engineers to prove the feasibility. To validate the impact on society and business interest, interviews with stakeholders are conducted with an investment mind set where each solution is labeled on a scale of 1 through 5, being one a minimum possible investment and 5 the maximum.

Keywords: affective computing, emotions, emotion detection, face recognition, gait recognition

Procedia PDF Downloads 361

Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

Abstract:

Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

Procedia PDF Downloads 119

Authors: G. K. Viswanadh, B. Rajasekhar, G. Venkata Ramana

Abstract:

Water distribution networks play a vital role in ensuring a reliable supply of clean water to urban areas. However, they face several challenges, including pressure control, pump speed optimization, and burst event detection. This paper combines insights from two studies to address these critical issues in Water distribution networks, focusing on the specific context of Kapra Municipality, India. The first part of this research concentrates on optimizing pressure control and pump speed in complex Water distribution networks. It utilizes the EPANET- MATLAB Toolkit to integrate EPANET functionalities into the MATLAB environment, offering a comprehensive approach to network analysis. By optimizing Pressure Reduce Valves (PRVs) and variable speed pumps (VSPs), this study achieves remarkable results. In the Benchmark Water Distribution System (WDS), the proposed PRV optimization algorithm reduces average leakage by 20.64%, surpassing the previous achievement of 16.07%. When applied to the South-Central and East zone WDS of Kapra Municipality, it identifies PRV locations that were previously missed by existing algorithms, resulting in average leakage reductions of 22.04% and 10.47%. These reductions translate to significant daily Water savings, enhancing Water supply reliability and reducing energy consumption. The second part of this research addresses the pressing issue of burst event detection and localization within the Water Distribution System. Burst events are a major contributor to Water losses and repair expenses. The study employs wireless sensor technology to monitor pressure and flow rate in real time, enabling the detection of pipeline abnormalities, particularly burst events. The methodology relies on transient analysis of pressure signals, utilizing Cumulative Sum and Wavelet analysis techniques to robustly identify burst occurrences. To enhance precision, burst event localization is achieved through meticulous analysis of time differentials in the arrival of negative pressure waveforms across distinct pressure sensing points, aided by nodal matrix analysis. To evaluate the effectiveness of this methodology, a PVC Water pipeline test bed is employed, demonstrating the algorithm's success in detecting pipeline burst events at flow rates of 2-3 l/s. Remarkably, the algorithm achieves a localization error of merely 3 meters, outperforming previously established algorithms. This research presents a significant advancement in efficient burst event detection and localization within Water pipelines, holding the potential to markedly curtail Water losses and the concomitant financial implications. In conclusion, this combined research addresses critical challenges in Water distribution networks, offering solutions for optimizing pressure control, pump speed, burst event detection, and localization. These findings contribute to the enhancement of Water Distribution System, resulting in improved Water supply reliability, reduced Water losses, and substantial cost savings. The integrated approach presented in this paper holds promise for municipalities and utilities seeking to improve the efficiency and sustainability of their Water distribution networks.

Keywords: pressure reduce valve, complex networks, variable speed pump, wavelet transform, burst detection, CUSUM (Cumulative Sum), water pipeline monitoring

Procedia PDF Downloads 76

Authors: Arūnas Gudinavičius, Andrius Šuminas

Abstract:

The analysis of scholarly journals formats is fragmented and needs to be studied from a point of view of scientific communication. While PDF is to the author’s best knowledge probably the most popular digital format of XXI century, but there are more formats available: HTML, EPUB, etc. Our aim is to analyze how these formats important to the readers and what is their contribution to scientific communication. We want to investigate how printed journals are still popular between scholars and does different formats are preferred between fields of science . In most cases, publishing of scientific journals are examined from a narrow perspective of a particular university science affair administrators or research funding institution. We believe that more data o n formats used in scholarly periodicals currently published in Lithuania as well as in Eastern Europe are needed. Science communication is often analyzed as a directed chain of information in the author-publisher-reader cycle. The paper is focusing on the publishing part of this chain. A distinction is made between formal and informal forms of scientific communication, which is relevant in today's context, when both forms of communication intertwine and complement each other. In our research, we will analyze formal documentary (formats of publication of scientific articles) communication - scientific information recorded in a certain medium and formatted in certain format (printed, PDF, HTML, EPUB, etc.). In our research, we will analyze the stage of publication of research results in scientific journals and their dissemination through specific publication formats. The paper is to systematize and analyze the various types of formats of scientific journal published in XXI century in Lithuania (small publishing market). The research analyses the case of small European country and presents publishing formats characteristics of the publication of scientific periodicals.

Keywords: scientific communication, scientific journals, publishing formats, reading

Procedia PDF Downloads 89

Authors: Hafid Smaili, Wilfred Rouwhorst, Paul Frost

Abstract:

The trend of recent accident and incident cases worldwide show that the state-of-the-art automation and operations, for current and future demanding operational environments, does not provide the desired level of operational safety under crew peak workload conditions, specifically in complex situations such as loss-of-control in-flight (LOC-I). Today, the short term focus is on preparing crews to recognise and handle LOC-I situations through upset recovery training. This paper describes the cockpit integration aspects and piloted assessment of both a manually assisted and automatic upset detection and recovery system that has been developed and demonstrated within the European Advanced Cockpit for Reduction Of StreSs and workload (ACROSS) programme. The proposed system is a function that continuously monitors and intervenes when the aircraft enters an upset and provides either manually pilot-assisted guidance or takes over full control of the aircraft to recover from an upset. In order to mitigate the highly physical and psychological impact during aircraft upset events, the system provides new cockpit functionalities to support the pilot in recovering from any upset both manually assisted and automatically. A piloted simulator assessment was made in Oct-Nov 2015 using ten pilots in a representative civil large transport fly-by-wire aircraft in terms of the preference of the tested upset detection and recovery system configurations to reduce pilot workload, increase situational awareness and safe interaction with the manually assisted or automated modes. The piloted simulator evaluation of the upset detection and recovery system showed that the functionalities of the system are able to support pilots during an upset. The experiment showed that pilots are willing to rely on the guidance provided by the system during an upset. Thereby, it is important for pilots to see and understand what the aircraft is doing and trying to do especially in automatic modes. Comparing the manually assisted and the automatic recovery modes, the pilot’s opinion was that an automatic recovery reduces the workload so that they could perform a proper screening of the primary flight display. The results further show that the manually assisted recoveries, with recovery guidance cues on the cockpit primary flight display, reduced workload for severe upsets compared to today’s situation. The level of situation awareness was improved for automatic upset recoveries where the pilot could monitor what the system was trying to accomplish compared to automatic recovery modes without any guidance. An improvement in situation awareness was also noticeable with the manually assisted upset recovery functionalities as compared to the current non-assisted recovery procedures. This study shows that automatic upset detection and recovery functionalities are likely to positively impact the operational safety by means of reduced workload, improved situation awareness and crew stress reduction. It is thus believed that future developments for upset recovery guidance and loss-of-control prevention should focus on automatic recovery solutions.

Keywords: aircraft accidents, automatic flight control, loss-of-control, upset recovery

Procedia PDF Downloads 204

Authors: M. A. Badr, A. N. Mohib, M. M. Ibrahim

Abstract:

The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) system supplying a remote small gathering of six families using HOMER software package. The electrical energy is to cater for the basic needs for which the daily load pattern is estimated. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for two sites. Using HOMER software, the simulation results showed that W/D/B systems are economical for the assumed community sites as the price of generated electricity is about 0.308 $/kWh, without taking external benefits into considerations. W/D/B systems are more economical than W/B or diesel alone systems, as the COE is 0.86 $/kWh for W/B and 0.357 $/kWh for diesel alone.

Keywords: optimum energy systems, remote electrification, renewable energy, wind turbine systems

Procedia PDF Downloads 397

Authors: Niddal Imam, Vassilios G. Vassilakis

Abstract:

After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

Procedia PDF Downloads 68

Authors: Muhammad Afiq Anaqi Bin Baharudin, Muhammad Izamuddin Bin Mohd Nasir, Syarifuddin Bin Sujuanda, Muhammad Syahmi Rusyaidi Bin Sham Suddin, Danish Hakimi Bin kamaruzaman, Muhammad Haqimi Nazim Bin Hasmanizam, Mohammad Akmal Zakwan Bin Amran, Muhammad Alparizi Bin Latif

Abstract:

In particular, for small and medium enterprises (SMBs) in Malaysia, process safety management (PSM) is a crucial component of industrial safety. Limited resources, a lack of technical know-how, and linguistic and cultural obstacles are just a few of the difficulties SMBs in Malaysia encounter while putting PSM programmes into practice. A number of studies have emphasised the significance of leadership commitment, hazard identification and assessment, and employee involvement in the execution of effective PSM programmes, which are crucial for preventing accidents and incidents. In the literature, there has been a lot of discussion on the creation of specialised PSM frameworks for SMBs in Malaysia. Several studies have proposed implementation frameworks for PSM programmes that are based on recognised worldwide standards. Despite the significance of PSM in ensuring industrial safety, there are still a number of gaps in the literature on PSM in Malaysian SMBs. These gaps include the need for additional research on the efficiency of PSM programmes in reducing accidents and incidents in SMBs as well as the development of more specialised approaches to implementing PSM programmes in SMBs with limited resources and technical expertise. The goal of this review is to give a thorough overview of the body of research on PSM in Malaysian SMBs while highlighting important findings, points of contention, and knowledge gaps that need to be filled in.

Keywords: process safety management, occupational safety and health (OSH), small businesses, medium businesses, malaysia

Procedia PDF Downloads 112

Authors: Bello Gonzalez, Setten Van M., Brouwer M.

Abstract:

The chicken small intestine represents a dynamic and complex organ in which the enzymatic digestion and absorption of nutrients take place. The development of an in vitro fermentation chicken small intestinal model could be used as an alternative to explore the interaction between the microbiota and nutrient metabolism and to enhance the efficacy of targeting interventions to improve animal health. In the present study we have developed an in vitro fermentation chicken ileum microbiota model for unrevealing the complex interaction of ileum microbial community under physiological conditions. A two-vessel continuous fermentation process simulating in real-time the physiological conditions of the ileum content (pH, temperature, microaerophilic/anoxic conditions, and peristaltic movements) has been standardized as a proof of concept. As inoculum, we use a pool of ileum microbial community obtained from chicken broilers at the age of day 14. The development and validation of the model provide insight into the initial characterization of the ileum microbial community and its dynamics over time-related to nutrient assimilation and fermentation. Samples can be collected at different time points and can be used to determine the microbial compositional structure, dynamics, and diversity over time. The results of studies using this in vitro model will serve as the foundation for the development of a whole small intestine in vitro fermentation chicken gastrointestinal model to complement our already established in vitro fermentation chicken caeca model. The insight gained from this model could provide us with some information about the nutritional strategies to restore and maintain chicken gut homeostasis. Moreover, the in vitro fermentation model will also allow us to study relationships between gut microbiota composition and its dynamics over time associated with nutrients, antimicrobial compounds, and disease modelling.

Keywords: broilers, in vitro model, ileum microbiota, fermentation

Procedia PDF Downloads 44

Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

Abstract:

Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

Procedia PDF Downloads 54

Authors: Dmitry Dikarev, Ajit Nimbalker, Alexei Davydov

Abstract:

Polar coding is a novel example of error correcting codes, which can achieve Shannon limit at block length N→∞ with log-linear complexity. Active research is being carried to adopt this theoretical concept for using in practical applications such as 5th generation wireless communication systems. Cyclic redundancy check (CRC) error detection code is broadly used in conjunction with successive cancellation list (SCL) decoding algorithm to improve finite-length polar code performance. However, there are two issues: increase of code block payload overhead by CRC bits and decrease of CRC error-detection capability. This paper proposes a method to control CRC overhead and false alarm rate of polar decoding. As shown in the computer simulations results, the proposed method provides the ability to use any set of CRC polynomials with any list size while maintaining the desired level of false alarm rate. This level of flexibility allows using polar codes in 5G New Radio standard.

Keywords: 5G New Radio, channel coding, cyclic redundancy check, list decoding, polar codes

Procedia PDF Downloads 233

Authors: Shingo Murakami, Shinichi Enoki

Abstract:

In structures, stress concentration is a factor of fatigue fracture. Basically, the stress concentration is a phenomenon that should be avoided. However, it is difficult to avoid the stress concentration. Therefore, relaxation of the stress concentration is important. The stress concentration arises from notches and circular holes. There is a relaxation method that a composite patch covers a notch and a circular hole. This relaxation method is used to repair aerial wings, but it is not systematized. Composites are more expensive than single materials. Accordingly, we propose the relaxation method that a single material patch covers a notch and a circular hole, and aim to systematize this relaxation method. We performed FEA (Finite Element Analysis) about an object by using a three-dimensional FEA model. The object was that a patch adheres to a plate with a circular hole. And, a uniaxial tensile load acts on the patched plate with a circular hole. In the three-dimensional FEA model, it is not easy to model the adhesion layer. Basically, the yield stress of the adhesive is smaller than that of adherents. Accordingly, the adhesion layer gets to plastic deformation earlier than the adherents under the yield stress of adherents. Therefore, we propose the three-dimensional FEA model which is applied a nonlinear elastic region to the adhesion layer. The nonlinear elastic region was calculated by a bilinear approximation. We compared the analysis results with the tensile test results to confirm whether the analysis model has usefulness. As a result, the analysis results agreed with the tensile test results. And, we confirmed that the analysis model has usefulness. As a result that the three-dimensional FEA model was used to the analysis, it was confirmed that an out-of-plane deformation occurred to the patched plate with a circular hole. The out-of-plane deformation causes stress increase of the patched plate with a circular hole. Therefore, we investigate that the out-of-plane deformation affects relaxation of the stress concentration in the plate with a circular hole on this relaxation method. As a result, it was confirmed that the out-of-plane deformation inhibits relaxation of the stress concentration on the plate with a circular hole.

Keywords: stress concentration, patch, out-of-plane deformation, Finite Element Analysis

Procedia PDF Downloads 260