Search results for: information processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13198

Search results for: information processing

13018 Recognition of Objects in a Maritime Environment Using a Combination of Pre- and Post-Processing of the Polynomial Fit Method

Authors: R. R. Hordijk, O. J. G. Somsen

Abstract:

Traditionally, radar systems are the eyes and ears of a ship. However, these systems have their drawbacks and nowadays they are extended with systems that work with video and photos. Processing of data from these videos and photos is however very labour-intensive and efforts are being made to automate this process. A major problem when trying to recognize objects in water is that the 'background' is not homogeneous so that traditional image recognition technics do not work well. Main question is, can a method be developed which automate this recognition process. There are a large number of parameters involved to facilitate the identification of objects on such images. One is varying the resolution. In this research, the resolution of some images has been reduced to the extreme value of 1% of the original to reduce clutter before the polynomial fit (pre-processing). It turned out that the searched object was clearly recognizable as its grey value was well above the average. Another approach is to take two images of the same scene shortly after each other and compare the result. Because the water (waves) fluctuates much faster than an object floating in the water one can expect that the object is the only stable item in the two images. Both these methods (pre-processing and comparing two images of the same scene) delivered useful results. Though it is too early to conclude that with these methods all image problems can be solved they are certainly worthwhile for further research.

Keywords: image processing, image recognition, polynomial fit, water

Procedia PDF Downloads 507
13017 Role of mHealth in Effective Response to Disaster

Authors: Mohammad H. Yarmohamadian, Reza Safdari, Nahid Tavakoli

Abstract:

In recent years, many countries have suffered various natural disasters. Disaster response continues to face the challenges in health care sector in all countries. Information and communication management is a significant challenge in disaster scene. During the last decades, rapid advances in information technology have led to manage information effectively and improve communication in health care setting. Information technology is a vital solution for effective response to disasters and emergencies so that if an efficient ICT-based health information system is available, it will be highly valuable in such situation. Of that, mobile technology represents a nearly computing technology infrastructure that is accessible, convenient, inexpensive and easy to use. Most projects have not yet reached the deployment stage, but evaluation exercises show that mHealth should allow faster processing and transport of patients, improved accuracy of triage and better monitoring of unattended patients at a disaster scene. Since there is a high prevalence of cell phones among world population, it is expected the health care providers and managers to take measures for applying this technology for improvement patient safety and public health in disasters. At present there are challenges in the utilization of mhealth in disasters such as lack of structural and financial issues in our country. In this paper we will discuss about benefits and challenges of mhealth technology in disaster setting considering connectivity, usability, intelligibility, communication and teaching for implementing this technology for disaster response.

Keywords: information technology, mhealth, disaster, effective response

Procedia PDF Downloads 407
13016 Visual Template Detection and Compositional Automatic Regular Expression Generation for Business Invoice Extraction

Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

Abstract:

Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

Procedia PDF Downloads 97
13015 Crop Classification using Unmanned Aerial Vehicle Images

Authors: Iqra Yaseen

Abstract:

One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

Procedia PDF Downloads 64
13014 Integrated Model for Enhancing Data Security Performance in Cloud Computing

Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

Abstract:

Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud Ccomputing, data security, SAAS, PAAS, IAAS, Blowfish

Procedia PDF Downloads 450
13013 Modernization of Garri-Frying Technologies with Respect to Women Anthromophic Quality in Nigeria

Authors: Adegbite Bashiru Adeniyi, Olaniyi Akeem Olawale, Ayobamidele Sinatu Juliet

Abstract:

The study was carried out in the 6 South Western states of Nigeria to analyze socio-economic characteristic of garri processors and their anthropometric qualities with respect to modern technologies used in garri processing. About 20 respondents were randomly selected from each of the 6 workstations purposively considered for the study due to their daily processing activities already attracted high patronage of customers. These include Oguntolu village (Ogun State), Igoba-Akure (Ondo State), Imo-Ilesa (Osun State), Odo Oba-Ileri (Oyo State), Irasa village (Ekiti State) and Epe in Lagos state. Interview schedule was conducted for 120 respondents to elicit information. Data were analyzed using descriptive statistical tools. It was observed from the findings that respondents were in their most productive age range (36-45 years) except Ogun state where majority (45%) were relatively older than 45 years. A fewer processors were much younger than 26 years old. It furthers revealed that not less than 55% have body weight greater than 50.0 kilogram, also not less than 70% were taller than 1.5 meter. So also, the hand length and hand thickness of the majority were long and bulky which are considered suitable for operating some modern and improved technologies in garri-frying process. This information could be used by various technological developers to enhance production of modern equipment and tools for a greater efficiency.

Keywords: agro-business, anthromorphic, modernization, proficiency

Procedia PDF Downloads 475
13012 Information Theoretic Approach for Beamforming in Wireless Communications

Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

Abstract:

Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

Procedia PDF Downloads 251
13011 Drivers of Farmers' Contract Compliance Behaviour: Evidence from a Case Study of Dangote Tomato Processing Plant in Northern Nigeria.

Authors: Umar Shehu Umar

Abstract:

Contract farming is a viable strategy agribusinesses rely on to strengthen vertical coordination. However, low contract compliance remains a significant setback to agribusinesses' contract performance. The present study aims to understand what drives smallholder farmers’ contract compliance behaviour. Qualitative information was collected through Focus Group Discussions to enrich the design of the survey questionnaire administered on a sample of 300 randomly selected farmers contracted by the Dangote Tomato Processing Plant (DTPP) in four regions of northern Nigeria. Novel transaction level data of tomato sales covering one season were collected in addition to socio-economic information of the sampled farmers. Binary logistic model results revealed that open fresh market tomato prices and payment delays negatively affect farmers' compliance behaviour while quantity harvested, education level and input provision correlated positively with compliance. The study suggests that contract compliance will increase if contracting firms devise a reliable and timely payment plan (e.g., digital payment), continue input and service provisions (e.g., improved seeds, extension services) and incentives (e.g., loyalty rewards, bonuses) in the contract.

Keywords: contract farming, compliance, farmers and processors., smallholder

Procedia PDF Downloads 24
13010 A Similarity Measure for Classification and Clustering in Image Based Medical and Text Based Banking Applications

Authors: K. P. Sandesh, M. H. Suman

Abstract:

Text processing plays an important role in information retrieval, data-mining, and web search. Measuring the similarity between the documents is an important operation in the text processing field. In this project, a new similarity measure is proposed. To compute the similarity between two documents with respect to a feature the proposed measure takes the following three cases into account: (1) The feature appears in both documents; (2) The feature appears in only one document and; (3) The feature appears in none of the documents. The proposed measure is extended to gauge the similarity between two sets of documents. The effectiveness of our measure is evaluated on several real-world data sets for text classification and clustering problems, especially in banking and health sectors. The results show that the performance obtained by the proposed measure is better than that achieved by the other measures.

Keywords: document classification, document clustering, entropy, accuracy, classifiers, clustering algorithms

Procedia PDF Downloads 480
13009 Giant Achievements in Food Processing

Authors: Farnaz Amidi Fazli

Abstract:

After long period of human experience about food processing from raw eating to canning of food in the last century now it is time to use novel technologies which are sometimes completely different from common technologies. It is possible to decontaminate food without using heat or the foods are stored without using cold chain. Pulsed electric field (PEF) processing is a non-thermal method of food preservation that uses short bursts of electricity, PEF can be used for processing liquid and semi-liquid food products. PEF processing offers high quality fresh-like liquid foods with excellent flavor, nutritional value, and shelf-life. High pressure processing (HPP) technology has the potential to fulfill both consumer and scientific requirements. The use of HPP for over 50 years has found applications in non-food industries. For food applications, ‘high pressure’ can be generally considered to be up to 600 MPa for most food products. After years, freezing has its high potential to food preservation due to new and quick freezing methods. Foods which are prepared by this technology have more acceptability and high quality comparing with old fashion slow freezing. Thus, quick freezing has further been adopted as a widespread commercial method for long-term preservation of perishable foods which improved both the health and convenience of everyone in the industrialised countries. Above parameters are achieved by Fluidised-bed freezing systems, freezing by immersion and Hydrofluidisation on the other hand new thawing methods like high-pressure, microwave, ohmic, and acoustic thawing have a key role in quality and adaptability of final product.

Keywords: quick freezing, thawing, high pressure, pulse electric, hydrofluidisation

Procedia PDF Downloads 295
13008 Decision Making, Reward Processing and Response Selection

Authors: Benmansour Nassima, Benmansour Souheyla

Abstract:

The appropriate integration of reward processing and decision making provided by the environment is vital for behavioural success and individuals’ well being in everyday life. Functional neurological investigation has already provided an inclusive image on affective and emotional (motivational) processing in the healthy human brain and has recently focused its interest also on the assessment of brain function in anxious and depressed individuals. This article offers an overview on the theoretical approaches that relate emotion and decision-making, and spotlights investigation with anxious or depressed individuals to reveal how emotions can interfere with decision-making. This research aims at incorporating the emotional structure based on response and stimulation with a Bayesian approach to decision-making in terms of probability and value processing. It seeks to show how studies of individuals with emotional dysfunctions bear out that alterations of decision-making can be considered in terms of altered probability and value subtraction. The utmost objective is to critically determine if the probabilistic representation of belief affords could be a critical approach to scrutinize alterations in probability and value representation in subjective with anxiety and depression, and draw round the general implications of this approach.

Keywords: decision-making, motivation, alteration, reward processing, response selection

Procedia PDF Downloads 444
13007 The Use of Image Processing Responses Tools Applied to Analysing Bouguer Gravity Anomaly Map (Tangier-Tetuan's Area-Morocco)

Authors: Saad Bakkali

Abstract:

Image processing is a powerful tool for the enhancement of edges in images used in the interpretation of geophysical potential field data. Arial and terrestrial gravimetric surveys were carried out in the region of Tangier-Tetuan. From the observed and measured data of gravity Bouguer gravity anomalies map was prepared. This paper reports the results and interpretations of the transformed maps of Bouguer gravity anomaly of the Tangier-Tetuan area using image processing. Filtering analysis based on classical image process was applied. Operator image process like logarithmic and gamma correction are used. This paper also present the results obtained from this image processing analysis of the enhancement edges of the Bouguer gravity anomaly map of the Tangier-Tetuan zone.

Keywords: bouguer, tangier, filtering, gamma correction, logarithmic enhancement edges

Procedia PDF Downloads 398
13006 Information Disclosure And Financial Sentiment Index Using a Machine Learning Approach

Authors: Alev Atak

Abstract:

In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

Procedia PDF Downloads 69
13005 Value Chain Analysis and Enhancement Added Value in Palm Oil Supply Chain

Authors: Juliza Hidayati, Sawarni Hasibuan

Abstract:

PT. XYZ is a manufacturing company that produces Crude Palm Oil (CPO). The fierce competition in the global markets not only between companies but also a competition between supply chains. This research aims to analyze the supply chain and value chain of Crude Palm Oil (CPO) in the company. Data analysis method used is qualitative analysis and quantitative analysis. The qualitative analysis describes supply chain and value chain, while the quantitative analysis is used to find out value added and the establishment of the value chain. Based on the analysis, the value chain of crude palm oil (CPO) in the company consists of four main actors that are suppliers of raw materials, processing, distributor, and customer. The value chain analysis consists of two actors; those are palm oil plantation and palm oil processing plant. The palm oil plantation activities include nurseries, planting, plant maintenance, harvesting, and shipping. The palm oil processing plant activities include reception, sterilizing, thressing, pressing, and oil classification. The value added of palm oil plantations was 72.42% and the palm oil processing plant was 10.13%.

Keywords: palm oil, value chain, value added, supply chain

Procedia PDF Downloads 334
13004 A Location-Based Search Approach According to Users’ Application Scenario

Authors: Shih-Ting Yang, Chih-Yun Lin, Ming-Yu Li, Jhong-Ting Syue, Wei-Ming Huang

Abstract:

Global positioning system (GPS) has become increasing precise in recent years, and the location-based service (LBS) has developed rapidly. Take the example of finding a parking lot (such as Parking apps). The location-based service can offer immediate information about a nearby parking lot, including the information about remaining parking spaces. However, it cannot provide expected search results according to the requirement situations of users. For that reason, this paper develops a “Location-based Search Approach according to Users’ Application Scenario” according to the location-based search and demand determination to help users obtain the information consistent with their requirements. The “Location-based Search Approach based on Users’ Application Scenario” of this paper consists of one mechanism and three kernel modules. First, in the Information Pre-processing Mechanism (IPM), this paper uses the cosine theorem to categorize the locations of users. Then, in the Information Category Evaluation Module (ICEM), the kNN (k-Nearest Neighbor) is employed to classify the browsing records of users. After that, in the Information Volume Level Determination Module (IVLDM), this paper makes a comparison between the number of users’ clicking the information at different locations and the average number of users’ clicking the information at a specific location, so as to evaluate the urgency of demand; then, the two-dimensional space is used to estimate the application situations of users. For the last step, in the Location-based Search Module (LBSM), this paper compares all search results and the average number of characters of the search results, categorizes the search results with the Manhattan Distance, and selects the results according to the application scenario of users. Additionally, this paper develops a Web-based system according to the methodology to demonstrate practical application of this paper. The application scenario-based estimate and the location-based search are used to evaluate the type and abundance of the information expected by the public at specific location, so that information demanders can obtain the information consistent with their application situations at specific location.

Keywords: data mining, knowledge management, location-based service, user application scenario

Procedia PDF Downloads 86
13003 Sentiment Analysis of Fake Health News Using Naive Bayes Classification Models

Authors: Danielle Shackley, Yetunde Folajimi

Abstract:

As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

Procedia PDF Downloads 67
13002 Mapping of Alteration Zones in Mineral Rich Belt of South-East Rajasthan Using Remote Sensing Techniques

Authors: Mrinmoy Dhara, Vivek K. Sengar, Shovan L. Chattoraj, Soumiya Bhattacharjee

Abstract:

Remote sensing techniques have emerged as an asset for various geological studies. Satellite images obtained by different sensors contain plenty of information related to the terrain. Digital image processing further helps in customized ways for the prospecting of minerals. In this study, an attempt has been made to map the hydrothermally altered zones using multispectral and hyperspectral datasets of South East Rajasthan. Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) and Hyperion (Level1R) dataset have been processed to generate different Band Ratio Composites (BRCs). For this study, ASTER derived BRCs were generated to delineate the alteration zones, gossans, abundant clays and host rocks. ASTER and Hyperion images were further processed to extract mineral end members and classified mineral maps have been produced using Spectral Angle Mapper (SAM) method. Results were validated with the geological map of the area which shows positive agreement with the image processing outputs. Thus, this study concludes that the band ratios and image processing in combination play significant role in demarcation of alteration zones which may provide pathfinders for mineral prospecting studies.

Keywords: ASTER, hyperion, band ratios, alteration zones, SAM

Procedia PDF Downloads 253
13001 The Effect of Object Presentation on Action Memory in School-Aged Children

Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf

Abstract:

Enacted tasks are typically remembered better than when the same task materials are only verbally encoded, a robust finding referred to as the enactment effect. It has been assumed that enactment effect is independent of object presence but the size of enactment effect can be increased by providing objects at study phase in adults. To clarify the issues in children, free recall and cued recall performance of action phrases with or without using real objects were compared in 410 school-aged children from four age groups (8, 10, 12 and 14 years old). In this study, subjects were instructed to learn a series of action phrases under three encoding conditions, participants listened to verbal action phrases (VTs), performed the phrases (SPTs: subject-performed tasks), and observed the experimenter perform the phrases (EPTs: experimenter-performed tasks). Then, free recall and cued recall memory tests were administrated. The results revealed that the real object compared with imaginary objects improved recall performance in SPTs and EPTs, but more so in VTs. It was also found that the object presence was not necessary for the occurrence of the enactment effect but it was changed the size of enactment effect in all age groups. The size of enactment effect was more pronounced for imaginary objects than the real object in both free recall and cued recall memory tests in children. It was discussed that SPTs and EPTs deferentially facilitate item-specific and relation information processing and providing the objects can moderate the processing underlying the encoding conditions.

Keywords: action memory, enactment effect, item-specific processing, object, relational processing, school-aged children

Procedia PDF Downloads 213
13000 Building Knowledge Society: The Imperative Role of Library and Information Centres (LICs) in Developing Countries

Authors: Desmond Chinedu Oparaku, Oyemike Victor Benson, Ifeyinwa A. Ariole

Abstract:

A critical examination of the emerging knowledge society reveals that library and information centres have a significant role to play in the building of knowledge society. The major highlights of this paper include: the conceptual analysis of knowledge society, overview of library and information centres in developing countries, role of libraries and information centre in building up of knowledge society, library and information professionals as factor in building knowledge, challenges faced by Library and Information Centres (LICs) in building knowledge society, strategies for building knowledge society. The position of this paper is that in spite of the influx of varied information and communication technologies in the information industry which is the driving force of knowledge society, there is a dire need for Libraries and Information Centres (LIC) to contribute positively to the migration and transition processes from the information society to knowledge-based society.

Keywords: information and communication technology (ICT), information centres, information industry, information society

Procedia PDF Downloads 347
12999 An Improved C-Means Model for MRI Segmentation

Authors: Ying Shen, Weihua Zhu

Abstract:

Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy

Procedia PDF Downloads 203
12998 Quantitative Analysis of Multiprocessor Architectures for Radar Signal Processing

Authors: Deepak Kumar, Debasish Deb, Reena Mamgain

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Radar signal processing requires high number crunching capability. Most often this is achieved using multiprocessor platform. Though multiprocessor platform provides the capability of meeting the real time computational challenges, the architecture of the same along with mapping of the algorithm on the architecture plays a vital role in efficiently using the platform. Towards this, along with standard performance metrics, few additional metrics are defined which helps in evaluating the multiprocessor platform along with the algorithm mapping. A generic multiprocessor architecture can not suit all the processing requirements. Depending on the system requirement and type of algorithms used, the most suitable architecture for the given problem is decided. In the paper, we study different architectures and quantify the different performance metrics which enables comparison of different architectures for their merit. We also carried out case study of different architectures and their efficiency depending on parallelism exploited on algorithm or data or both.

Keywords: radar signal processing, multiprocessor architecture, efficiency, load imbalance, buffer requirement, pipeline, parallel, hybrid, cluster of processors (COPs)

Procedia PDF Downloads 380
12997 Rehabilitation of the Blind Using Sono-Visualization Tool

Authors: Ashwani Kumar

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In human beings, eyes play a vital role. A very less research has been done for rehabilitation of blindness for the blind people. This paper discusses the work that helps blind people for recognizing the basic shapes of the objects like circle, square, triangle, horizontal lines, vertical lines, diagonal lines and the wave forms like sinusoidal, square, triangular etc. This is largely achieved by using a digital camera, which is used to capture the visual information present in front of the blind person and a software program, which achieves the image processing operations, and finally the processed image is converted into sound. After the sound generation process, the generated sound is fed to the blind person through headphones for visualizing the imaginary image of the object. For visualizing the imaginary image of the object, it needs to train the blind person. Various training process methods had been applied for recognizing the object.

Keywords: image processing, pixel, pitch, loudness, sound generation, edge detection, brightness

Procedia PDF Downloads 357
12996 The Influence of Concreteness on English Compound Noun Processing: Modulation of Constituent Transparency

Authors: Turgut Coskun

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'Concreteness effect' refers to faster processing of concrete words and 'compound facilitation' refers to faster response to compounds. In this study, our main goal was to investigate the interaction between compound facilitation and concreteness effect. The latter might modulate compound processing basing on constituents’ transparency patterns. To evaluate these, we created lists for compound and monomorphemic words, sub-categorized them into concrete and abstract words, and further sub-categorized them basing on their transparency. The transparency conditions were opaque-opaque (OO), transparent-opaque (TO), and transparent-transparent (TT). We used RT data from English Lexicon Project (ELP) for our comparisons. The results showed the importance of concreteness factor (facilitation) in both compound and monomorphemic processing. Important for our present concern, separate concrete and abstract compound analyses revealed different patterns for OO, TO, and TT compounds. Concrete TT and TO conditions were processed faster than Concrete OO, Abstract OO and Abstract TT compounds, however, they weren’t processed faster than Abstract TO compounds. These results may reflect on different representation patterns of concrete and abstract compounds.

Keywords: abstract word, compound representation, concrete word, constituent transparency, processing speed

Procedia PDF Downloads 162
12995 Arousal, Encoding, And Intrusive Memories

Authors: Hannah Gutmann, Rick Richardson, Richard Bryant

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Intrusive memories following a traumatic event are not uncommon. However, in some individuals, these memories become maladaptive and lead to prolonged stress reactions. A seminal model of PTSD explains that aberrant processing during trauma may lead to prolonged stress reactions and intrusive memories. This model explains that elevated arousal at the time of the trauma promotes data driven processing, leading to fragmented and intrusive memories. This study investigated the role of elevated arousal on the development of intrusive memories. We measured salivary markers of arousal and investigated what impact this had on data driven processing, memory fragmentation, and subsequently, the development of intrusive memories. We assessed 100 healthy participants to understand their processing style, arousal, and experience of intrusive memories. Participants were randomised to a control or experimental condition, the latter of which was designed to increase their arousal. Based on current theory, participants in the experimental condition were expected to engage in more data driven processing and experience more intrusive memories than participants in the control condition. This research aims to shed light on the mechanisms underlying the development of intrusive memories to illustrate ways in which therapeutic approaches for PTSD may be augmented for greater efficacy.

Keywords: stress, cortisol, SAA, PTSD, intrusive memories

Procedia PDF Downloads 164
12994 Reactive Learning about Food Waste Reduction in a Food Processing Plant in Gauteng Province, South Africa

Authors: Nesengani Elelwani Clinton

Abstract:

This paper presents reflective learning as an opportunity commonly available and used for food waste learning in a food processing company in the transition to sustainable and just food systems. In addressing how employees learn about food waste during food processing, the opportunities available for food waste learning were investigated. Reflective learning appeared to be the most used approach to learning about food waste. In the case of food waste learning, reflective learning was a response after employees wasted a substantial amount of food, where process controllers and team leaders would highlight the issue to employees who wasted food and explain how food waste could be reduced. This showed that learning about food waste is not proactive, and there continues to be a lack of structured learning around food waste. Several challenges were highlighted around reflective learning about food waste. Some of the challenges included understanding the language, lack of interest from employees, set times to reach production targets, and working pressures. These challenges were reported to be hindering factors in understanding food waste learning, which is not structured. A need was identified for proactive learning through structured methods. This is because it was discovered that in the plant, where food processing activities happen, the signage and posters that are there are directly related to other sustainability issues such as food safety and health. This indicated that there are low levels of awareness about food waste. Therefore, this paper argues that food waste learning should be proactive. The proactive learning approach should include structured learning materials around food waste during food processing. In the structuring of the learning materials, individual trainers should be multilingual. This will make it possible for those who do not understand English to understand in their own language. And lastly, there should be signage and posters in the food processing plant around food waste. This will bring more awareness around food waste, and employees' behaviour can be influenced by the posters and signage in the food processing plant. Thus, will enable a transition to a just and sustainable food system.

Keywords: sustainable and just food systems, food waste, food waste learning, reflective learning approach

Procedia PDF Downloads 62
12993 Legal Issues of Collecting and Processing Big Health Data in the Light of European Regulation 679/2016

Authors: Ioannis Iglezakis, Theodoros D. Trokanas, Panagiota Kiortsi

Abstract:

This paper aims to explore major legal issues arising from the collection and processing of Health Big Data in the light of the new European secondary legislation for the protection of personal data of natural persons, placing emphasis on the General Data Protection Regulation 679/2016. Whether Big Health Data can be characterised as ‘personal data’ or not is really the crux of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Another key point is that the application of some provisions of GPDR to Big Health Data may both absolve the data controller of his legal obligations and deprive the data subject of his rights (e.g., the right to be informed), ultimately undermining the fundamental right to the protection of personal data of natural persons. Moreover, data subject’s rights (e.g., the right not to be subject to a decision based solely on automated processing) are heavily impacted by the use of AI, algorithms, and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have a substantial impact on individuals. On the other hand, as the COVID-19 pandemic has revealed, Big Data analytics can offer crucial sources of information. In this respect, this paper identifies and systematises the legal provisions concerned, offering interpretative solutions that tackle dangers concerning data subject’s rights while embracing the opportunities that Big Health Data has to offer. In addition, particular attention is attached to the scope of ‘consent’ as a legal basis in the collection and processing of Big Health Data, as the application of data analytics in Big Health Data signals the construction of new data and subject’s profiles. Finally, the paper addresses the knotty problem of role assignment (i.e., distinguishing between controller and processor/joint controllers and joint processors) in an era of extensive Big Health data sharing. The findings are the fruit of a current research project conducted by a three-member research team at the Faculty of Law of the Aristotle University of Thessaloniki and funded by the Greek Ministry of Education and Religious Affairs.

Keywords: big health data, data subject rights, GDPR, pandemic

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12992 Detecting and Disabling Digital Cameras Using D3CIP Algorithm Based on Image Processing

Authors: S. Vignesh, K. S. Rangasamy

Abstract:

The paper deals with the device capable of detecting and disabling digital cameras. The system locates the camera and then neutralizes it. Every digital camera has an image sensor known as a CCD, which is retro-reflective and sends light back directly to its original source at the same angle. The device shines infrared LED light, which is invisible to the human eye, at a distance of about 20 feet. It then collects video of these reflections with a camcorder. Then the video of the reflections is transferred to a computer connected to the device, where it is sent through image processing algorithms that pick out infrared light bouncing back. Once the camera is detected, the device would project an invisible infrared laser into the camera's lens, thereby overexposing the photo and rendering it useless. Low levels of infrared laser neutralize digital cameras but are neither a health danger to humans nor a physical damage to cameras. We also discuss the simplified design of the above device that can used in theatres to prevent piracy. The domains being covered here are optics and image processing.

Keywords: CCD, optics, image processing, D3CIP

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12991 A Mathematical-Based Formulation of EEG Fluctuations

Authors: Razi Khalafi

Abstract:

Brain is the information processing center of the human body. Stimuli in form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modeling of the EEG signal in case external stimuli but it can be used for the modeling of brain response in case of internal stimuli.

Keywords: Brain, stimuli, partial differential equation, response, eeg signal

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12990 Image Processing and Calculation of NGRDI Embedded System in Raspberry

Authors: Efren Lopez Jimenez, Maria Isabel Cajero, J. Irving-Vasqueza

Abstract:

The use and processing of digital images have opened up new opportunities for the resolution of problems of various kinds, such as the calculation of different vegetation indexes, among other things, differentiating healthy vegetation from humid vegetation. However, obtaining images from which these indexes are calculated is still the exclusive subject of active research. In the present work, we propose to obtain these images using a low cost embedded system (Raspberry Pi) and its processing, using a set of libraries of open code called OpenCV, in order to obtain the Normalized Red-Green Difference Index (NGRDI).

Keywords: Raspberry Pi, vegetation index, Normalized Red-Green Difference Index (NGRDI), OpenCV

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12989 A Forward-Looking View of the Intellectual Capital Accounting Information System

Authors: Rbiha Salsabil Ketitni

Abstract:

The entire company is a series of information among themselves so that each information serves several events and activities, and the latter is nothing but a large set of data or huge data. The enormity of information leads to the possibility of losing it sometimes, and this possibility must be avoided in the institution, especially the information that has a significant impact on it. In most cases, to avoid the loss of this information and to be relatively correct, information systems are used. At present, it is impossible to have a company that does not have information systems, as the latter works to organize the information as well as to preserve it and even saves time for its owner and this is the result of the speed of its mission. This study aims to provide an idea of an accounting information system that opens a forward-looking study for its manufacture and development by researchers, scientists, and professionals. This is the result of most individuals seeing a great contradiction between the work of an information system for moral capital and does not provide real values when measured, and its disclosure in financial reports is not distinguished by transparency.

Keywords: accounting, intellectual capital, intellectual capital accounting, information system

Procedia PDF Downloads 44