Search results for: edge detection algorithm

Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, LOO cycle, medial temporal atrophy

Procedia PDF Downloads 191

Authors: Simon B. N. Thompson

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Cortisol is essential to the regulation of the immune system and yawning is a pathological symptom of multiple sclerosis (MS). Electromyography activity (EMG) in the jaw muscles typically rises when the muscles are moved and with yawning is highly correlated with cortisol levels in healthy people. Saliva samples from 59 participants were collected at the start and after yawning, or at the end of the presentation of yawning-provoking stimuli, in the absence of a yawn, together with EMG data and questionnaire data: Hospital Anxiety and Depression Scale, Yawning Susceptibility Scale, General Health Questionnaire, demographic, health details. Exclusion criteria: chronic fatigue, diabetes, fibromyalgia, heart condition, high blood pressure, hormone replacement therapy, multiple sclerosis, stroke. Significant differences were found between the saliva cortisol samples for the yawners, t (23) = -4.263, p = 0.000, as compared with the non-yawners between rest and post-stimuli, which was non-significant. Significant evidence was found to support the Thompson Cortisol Hypothesis suggesting that rises in cortisol levels are associated with yawning. Further research is exploring the use of cortisol as an early diagnostic tool for MS. Ethics approval granted and professional code of conduct, confidentiality, and safety issues are approved therein.

Keywords: cortisol, multiple sclerosis, yawning, thompson cortisol hypothesis

Procedia PDF Downloads 370

Authors: K. Ali, M. F. Qamar, M. A. Zaman, M. Younus, I. Khan, S. Ehtisham-ul-Haque, R. Tamkeen, M. I. Rashid, Q. Ali

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This study centers on molecular identification of Haemonchus contortus and isolation of Benz-imidazoles (BZ) resistant strains. Different abattoirs’ of two geographic regions of Punjab (Pakistan) were frequently visited for the collection of worms. Out of 1500 (n=1500) samples that were morphologically confirmed as H. contortus, 30 worms were subjected to molecular procedures for isolation of resistant strains. Resistant worms (n=8) were further subjected to DNA gene sequencing. Bio edit sequence alignment editor software was used to detect the possible mutation, deletion, replacement of nucleotides. Genetic diversity was noticed and genetic variation existing in β-tubulin isotype 1 of the H. contortus population of small ruminants of different regions considered in this study. H. contortus showed three different type of genetic sequences. 75%, 37.5%, 25% and 12.5% of the studied samples showed 100% query cover and identity with isolates and clones of China, UK, Australia and other countries, respectively. Interestingly the neighbor countries such as India and Iran haven’t many similarities with the Pakistani isolates. Thus, it suggests that population density of same genetic makeup H. contortus is scattered worldwide rather than clustering in a single region.

Keywords: Haemonchus contortus, Benzimidazole resistant, β-tubulin-1 gene, abattoirs

Procedia PDF Downloads 167

Authors: C. N. Vanitha, M. Usha

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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

Procedia PDF Downloads 399

Authors: Raahil Sheikh, Abhishek Maurya, Priya Gujjar, Himanshu Dwivedi, Prathamesh Minde

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UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided.

Keywords: UAV, drone, autonomous system, thermal imaging

Procedia PDF Downloads 63

Authors: J. Al-Dmour, A. Sagahyroon, A. Al-Ali, S. Abusnana

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Radio Frequency Based Identification Systems have emerged as one of the possible valuable solutions that can be utilized in healthcare systems. Nowadays, RFID tags are available with built-in human vital signs sensors such as Body Temperature, Blood Pressure, Heart Rate, Blood Sugar level and Oxygen Saturation in Blood. This work proposes the design, implementation, and testing of an integrated mobile RFID-based health care system. The system consists of a wireless mobile vital signs data acquisition unit (RFID-DAQ) integrated with a fuzzy-logic–based software algorithm to monitor and assess patients conditions. The system is implemented and tested in ‘Rashid Center for Diabetes and Research’, Ajman, UAE. System testing results are compared with the Modified Early Warning System (MEWS) that is currently used in practice. We demonstrate that the proposed and implemented system exhibits an accuracy level that is comparable and sometimes better than the widely adopted MEWS system.

Keywords: healthcare, fuzzy logic, MEWS, RFID

Procedia PDF Downloads 336

Authors: Eddy K. Mukadi

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This work is a documentary and descriptive study devoted to the epidemiological, clinical, histopathological and therapeutic profile of breast cancer deals with the department of gynecology and obstetrics of the university clinics of Kinshasa during the period from 1 January 2014 to 31 December 2014. We have identified 56 cases of breast cancer. These cancers accounted for 45.2% of gynecological mammary cancers. The youngest in our series was 18 years old while the oldest was 74 years old; And the mean age of these patients was 43.4 years and mostly multiparous (35.7%). Brides (60.7%) and bachelors (26.8%) were the most affected by breast cancer. The reasons for consultation were dominated by nodules in the breast (48.2%) followed by pain (35.7%) and nipple discharge (14.3%). In 89.2% of the cases, it was the advanced clinical stage (stage 3 and 4) and the infiltrating ductal carcinoma was the most frequent histological type (75%) The malignant tumor was mainly in the left breast (55.3%), and chemotherapy with hormone therapy and patey was the most convenient treatment (42.8%), while patey mastectomy was performed in 12.5% of patients. Because of the high incidence of breast cancer identified in our study, some preventive measures must be taken into account to address this public health problem, including breast autopalpation once a month, Early detection system development of a national breast cancer policy and the implementation of a national breast cancer control program.

Keywords: breast cancer, histopathological profile, epidemiological profile, Kinshasa

Procedia PDF Downloads 207

Authors: Rahmat Purwoko, Bambang Riyanto Trilaksono

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This paper gives comparison of INS/GNSS architecture namely Loosely Coupled and Tightly Coupled using Hardware in the Loop Simulation in Guided Missile RKX-200 rocket model. INS/GNSS Tightly Coupled architecture requires pseudo-range, pseudo-range rate, and position and velocity of each satellite in constellation from GPS (Global Positioning System) measurement. The Loosely Coupled architecture use estimated position and velocity from GNSS receiver. INS/GNSS architecture also requires angular rate and specific force measurement from IMU (Inertial Measurement Unit). Loosely Coupled arhitecture designed using 15 states Kalman Filter and Tightly Coupled designed using 17 states Kalman Filter. Integration algorithm calculation using ECEF frame. Navigation System implemented Zedboard All Programmable SoC.

Keywords: kalman filter, loosely coupled, navigation system, tightly coupled

Procedia PDF Downloads 297

Authors: Brizita Djordjevic, Bojana Vidovic, Milica Zrnic, Uros Cakar, Ivan Stankovic, Davor Korcok, Sladjana Sobajic

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Histamine is a biogenic amine, which is formed by enzymatic decarboxylation from the amino acid histidine. It can be found in foods such as fish and fish products, meat and fermented meat products, cheese, wine and beer. The presence of histamine in these foods can indicate microbiological spoilage or poor manufacturing processes. The consumption of food containing large amounts of histamine can have toxicological consequences. In 62 food products (31 canned fish products, 19 wines and 12 cheeses) from the market of Serbia the content of histamine was determined using enzyme-linked immunosorbent assay (ELISA) test kit according to the manufacturer's instructions (Immunolab GmbH, Kassel, Germany). The detection limits of this assay were 20 µg/kg for fish and cheese and 4 µg/L for wine. The concentration of histamine varied between 0.16-207 mg/kg in canned fish products, 0.03-1.47 mg/kg in cheeses and 0.01- 0.18 mg/L in wines. In all analyzed canned fish products the results obtained for the histamine were below the limits set by European and national legislation, so they can be considered acceptable and safe for the health consumers. The levels of histamine in analyzed cheeses and wines were very low and did not pose safety concerns.

Keywords: cheese, enzyme-linked immunosorbent assay, histamine, fish products, wine

Procedia PDF Downloads 441

Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

Procedia PDF Downloads 409

Authors: Mohammed A. Alfayyadh, Halla A. AlAbdulhadi, Mahdi H. Almubarak

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Purpose: Eales’ disease is an idiopathic vasculitis that affects the peripheral retina. It is characterized by recurrent vitreous hemorrhage as a complication of retinal neovascularization. It is more prevalent in India and affects young males. Here we present a patient with neovascular glaucoma as a rare first presentation of Eales’ disease. Observations: This is a 24-year-old Indian gentleman, who complained of a sudden decrease in vision in the left eye over less than 24 hours, along with frontal headache and eye pain for the last three weeks. Ocular examination revealed peripheral retinal ischemia in the right eye, very high intraocular pressure, rubeosis iridis, vitreous hemorrhage and extensive retinal ischemia in the left eye, vascular sheathing and neovascularization in both eyes. Purified protein derivative skin test was positive. The patient was managed with anti-glaucoma, intravitreal anti-vascular endothelial growth factor and laser photocoagulation. Systemic steroids and anti-tuberculous therapy were also initiated. Conclusions: Neovascular glaucoma is an infrequent complication of Eales’ disease. However, the lack of early detection of the disease in the early stages might lead to such serious complication.

Keywords: case report, Eales’ disease, mycobacterium tuberculosis, neovascular glaucoma

Procedia PDF Downloads 119

Authors: Xiuying Wang, Changliang Li, Bo Xu

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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

Procedia PDF Downloads 345

Authors: Shih-Wen Hsiao, Chu-Hsuan Lee, Rong-Qi Chen

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When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.

Keywords: 3D last design, customization, reverse engineering, weighted morphing, shape blending

Procedia PDF Downloads 333

Authors: G. Tamilpavai, C. Vishnuppriya

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Studying DNA (deoxyribonucleic acid) sequence is useful in biological processes and it is applied in the fields such as diagnostic and forensic research. DNA is the hereditary information in human and almost all other organisms. It is passed to their generations. Earlier stage detection of defective DNA sequence may lead to many developments in the field of Bioinformatics. Nowadays various tedious techniques are used to identify defective DNA. The proposed work is to analyze and identify the cancer-causing DNA motif in a given sequence. Initially the human DNA sequence is separated as k-mers using k-mer separation rule. The separated k-mers are clustered using Self Organizing Map (SOM). Using Levenshtein distance measure, cancer associated DNA motif is identified from the k-mer clusters. Experimental results of this work indicate the presence or absence of cancer causing DNA motif. If the cancer associated DNA motif is found in DNA, it is declared as the cancer disease causing DNA sequence. Otherwise the input human DNA is declared as normal sequence. Finally, elapsed time is calculated for finding the presence of cancer causing DNA motif using clustering formation. It is compared with normal process of finding cancer causing DNA motif. Locating cancer associated motif is easier in cluster formation process than the other one. The proposed work will be an initiative aid for finding genetic disease related research.

Keywords: bioinformatics, cancer motif, DNA, k-mers, Levenshtein distance, SOM

Procedia PDF Downloads 179

Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

Procedia PDF Downloads 186

Authors: Raahil Sheikh, Prathamesh Minde, Priya Gujjar, Himanshu Dwivedi, Abhishek Maurya

Abstract:

UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided

Keywords: UAV, autonomous systems, drones, geo thermal imaging

Procedia PDF Downloads 71

Authors: Hiroyuki Aoki

Abstract:

The physical properties of polymer materials are dependent on the conformation and molecular motion of a polymer chain. Therefore, the structure and dynamic behavior of the single polymer chain have been the most important concerns in the field of polymer physics. However, it has been impossible to directly observe the conformation of the single polymer chain in a bulk medium. In the current work, the novel techniques to study the conformation and dynamics of a single polymer chain are proposed. Since a fluorescence method is extremely sensitive, the fluorescence microscopy enables the direct detection of a single molecule. However, the structure of the polymer chain as large as 100 nm cannot be resolved by conventional fluorescence methods because of the diffraction limit of light. In order to observe the single chains, we developed the labeling method of polymer materials with a photo-switchable dye and the super-resolution microscopy. The real-space conformational analysis of single polymer chains with the spatial resolution of 15-20 nm was achieved. The super-resolution microscopy enables us to obtain the three-dimensional coordinates; therefore, we succeeded the conformational analysis in three dimensions. The direct observation by the nanometric optical microscopy would reveal the detailed information on the molecular processes in the various polymer systems.

Keywords: polymer materials, single molecule, super-resolution techniques, conformation

Procedia PDF Downloads 296

Authors: Areti Okalidou, Paul D. Hatzigiannakoglou, Aikaterini Vatou, George Kyriafinis

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Young children are nowadays adept at using technology. Hence, computer-based auditory training programs (CBATPs) have become increasingly popular in aural rehabilitation for children with hearing loss and/or with cochlear implants (CI). Yet, their clinical utility for prognostic, diagnostic, and monitoring purposes has not been explored. The purposes of the study were: a) to develop an updated version of the auditory rehabilitation tool for Greek-speaking children with cochlear implants, b) to develop a database for behavioral responses, and c) to compare accuracy rates and reaction times in children differing in hearing status and other medical and demographic characteristics, in order to assess the tool’s clinical utility in prognosis, diagnosis, and progress monitoring. The updated version of the auditory rehabilitation tool was developed on a tablet, retaining the User-Centered Design approach and the elements of the Virtual Reality (VR) serious game. The visual stimuli were farm animals acting in simple game scenarios designed to trigger children’s responses to animal sounds, names, and relevant sentences. Based on an extended version of Erber’s auditory development model, the VR game consisted of six stages, i.e., sound detection, sound discrimination, word discrimination, identification, comprehension of words in a carrier phrase, and comprehension of sentences. A familiarization stage (learning) was set prior to the game. Children’s tactile responses were recorded as correct, false, or impulsive, following a child-dependent set up of a valid delay time after stimulus offset for valid responses. Reaction times were also recorded, and the database was in Εxcel format. The tablet version of the auditory rehabilitation tool was piloted in 22 preschool children with Νormal Ηearing (ΝΗ), which led to improvements. The study took place in clinical settings or at children’s homes. Fifteen children with CI, aged 5;7-12;3 years with post-implantation 0;11-5;1 years used the auditory rehabilitation tool. Eight children with CI were monolingual, two were bilingual and five had additional disabilities. The control groups consisted of 13 children with ΝΗ, aged 2;6-9;11 years. A comparison of both accuracy rates, as percent correct, and reaction times (in sec) was made at each stage, across hearing status, age, and also, within the CI group, based on presence of additional disability and bilingualism. Both monolingual Greek-speaking children with CI with no additional disabilities and hearing peers showed high accuracy rates at all stages, with performances falling above the 3rd quartile. However, children with normal hearing scored higher than the children with CI, especially in the detection and word discrimination tasks. The reaction time differences between the two groups decreased in language-based tasks. Results for children with CI with additional disability or bilingualism varied. Finally, older children scored higher than younger ones in both groups (CI, NH), but larger differences occurred in children with CI. The interactions between familiarization of the software, age, hearing status and demographic characteristics are discussed. Overall, the VR game is a promising tool for tracking the development of auditory skills, as it provides multi-level longitudinal empirical data. Acknowledgment: This work is part of a project that has received funding from the Research Committee of the University of Macedonia under the Basic Research 2020-21 funding programme.

Keywords: VR serious games, auditory rehabilitation, auditory training, children with cochlear implants

Procedia PDF Downloads 75

Authors: Antonio Boggia, Luisa Paolotti, Gianluca Massei, Lucia Rocchi, Elaine Pace, Maria Attard

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The aim of this paper is to present a methodology and a computer model for sustainability assessment based on the integration of Multi-criteria Decision Analysis (MCDA) with a Geographic Information System (GIS). It presents the result of a study for the implementation of a model for measuring sustainability to address the policy actions for the improvement of sustainability at territory level. The aim is to rank areas in order to understand the specific technical and/or financial support that is required to develop sustainable growth. Assessing sustainable development is a multidimensional problem: economic, social and environmental aspects have to be taken into account at the same time. The tool for a multidimensional representation is a proper set of indicators. The set of indicators must be integrated into a model, that is an assessment methodology, to be used for measuring sustainability. The model, developed by the Environmental Laboratory of the University of Perugia, is called GeoUmbriaSUIT. It is a calculation procedure developed as a plugin working in the open-source GIS software QuantumGIS. The multi-criteria method used within GeoUmbriaSUIT is the algorithm TOPSIS (Technique for Order Preference by Similarity to Ideal Design), which defines a ranking based on the distance from the worst point and the closeness to an ideal point, for each of the criteria used. For the sustainability assessment procedure, GeoUmbriaSUIT uses a geographic vector file where the graphic data represent the study area and the single evaluation units within it (the alternatives, e.g. the regions of a country, or the municipalities of a region), while the alphanumeric data (attribute table), describe the environmental, economic and social aspects related to the evaluation units by means of a set of indicators (criteria). The use of the algorithm available in the plugin allows to treat individually the indicators representing the three dimensions of sustainability, and to compute three different indices: environmental index, economic index and social index. The graphic output of the model allows for an integrated assessment of the three dimensions, avoiding aggregation. The presence of separate indices and graphic output make GeoUmbriaSUIT a readable and transparent tool, since it doesn’t produce an aggregate index of sustainability as final result of the calculations, which is often cryptic and difficult to interpret. In addition, it is possible to develop a “back analysis”, able to explain the positions obtained by the alternatives in the ranking, based on the criteria used. The case study presented is an assessment of the level of sustainability in the six regions of Malta, an island state in the middle of the Mediterranean Sea and the southernmost member of the European Union. The results show that the integration of MCDA-GIS is an adequate approach for sustainability assessment. In particular, the implemented model is able to provide easy to understand results. This is a very important condition for a sound decision support tool, since most of the time decision makers are not experts and need understandable output. In addition, the evaluation path is traceable and transparent.

Keywords: GIS, multi-criteria analysis, sustainability assessment, sustainable development

Procedia PDF Downloads 271

Authors: Dan Kanmegne

Abstract:

Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

Procedia PDF Downloads 134

Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

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The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

Procedia PDF Downloads 154

Authors: Salaam Mujeeb, Adeola Segun, Abdullahi Olasunkanmi

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Dementia is becoming a major concern as the world population is increasing and elderly populations are being neglected. Liver and kidney Diseases have been implicated as risk factors in the etiology of Dementia. This study, therefore, evaluates the plasma Gamma Glutamyl Transferase (GGT) activity and plasma Electrolytes in other to find an association between the biomarkers and Dementia. The subjects (38) were age and sex-matched with their corresponding controls and structured questionnaires were used to obtain medical information. Using spectrophotometric and ion selective Electrode techniques respectively, we found and elevated GGT activity in the Dementia Subjects. Remarkably, no association was found between the plasma Electrolytes level and Dementia subjects. It was also observed that severity of Dementia worsens with age. Moreover, the condition of the dementia subjects worsens with reducing weight. Furthermore, the presence of Comorbidity e.g. Hypertension, Obesity, Diabetes and Habits like Smoking, Drugs and Alcohol consumption interferes with Electrolyte balance. Weight loss monitoring and IBM check are advised in Elderly individuals particularly females as they may be inductive of early or future cognitive impairments. Therefore, it might be useful as an early detection tool. Government and society should invest more on the Geriatric population by establishing Old people's home and providing social care services.

Keywords: clinical characteristics, dementia, electrolytes, gamma glutamyl transpeptidase, GGT

Procedia PDF Downloads 315

Authors: Sidi Mohamed Mesli, Mohamed Habchi, Arslane Boudghene Stambouli, Rafik Benallal

Abstract:

The BaMnMF7 (M=Fe,V, transition metal fluoride glass, assuming isomorphous replacement) have been structurally studied through the simultaneous simulation of their neutron diffraction patterns by reverse Monte Carlo (RMC) and by the Hybrid Reverse Monte Carlo (HRMC) analysis. This last is applied to remedy the problem of the artificial satellite peaks that appear in the partial pair distribution functions (PDFs) by the RMC simulation. The HRMC simulation is an extension of the RMC algorithm, which introduces an energy penalty term (potential) in acceptance criteria. The idea of this work is to apply the Buckingham potential at the title glass by ignoring the van der Waals terms, in order to make a fit of the partial pair distribution functions and give the most possible realistic features. When displaying the partial PDFs, we suggest that the Buckingham potential is useful to describe average correlations especially in similar interactions.

Keywords: fluoride glasses, RMC simulation, hybrid RMC simulation, Buckingham potential, partial pair distribution functions

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Authors: Zhi Liu, Hui Jiang, Jin Li, Kunhao Chen, Langfang Zhang

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Fast acquisition of the seismic information and accurate assessment of the earthquake disaster is the key problem for emergency rescue after a destructive earthquake. In order to meet the requirements of the earthquake emergency response and rescue for the cities and counties, a quasi real-time comprehensive evaluation system for earthquake disaster is developed. Based on monitoring data of Micro-Electro-Mechanical Systems (MEMS) strong motion network, structure database of a county area and the real-time disaster information by the mobile terminal after an earthquake, fragility analysis method and dynamic correction algorithm are synthetically obtained in the developed system. Real-time evaluation of the seismic disaster in the county region is finally realized to provide scientific basis for seismic emergency command, rescue and assistant decision.

Keywords: quasi real-time, earthquake disaster data collection, MEMS accelerometer, dynamic correction, comprehensive evaluation

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Authors: Glauco M. M. M. Lustosa, João Paulo C. Costa, Sonia M. Zanetti, Mario Cilense, Leinig Antônio Perazolli, Maria Aparecida Zaghete

Abstract:

The contamination of the environment has been one of the biggest problems of our time, mostly due to developments of many industries. SnO2 is an n-type semiconductor with band gap about 3.5 eV and has its electrical conductivity dependent of type and amount of modifiers agents added into matrix ceramic during synthesis process, allowing applications as sensing of gaseous pollutants on ambient. The chemical synthesis by polymeric precursor method consists in a complexation reaction between tin ion and citric acid at 90 °C/2 hours and subsequently addition of ethyleneglycol for polymerization at 130 °C/2 hours. It also prepared polymeric resin of zinc, cobalt and niobium ions. Stoichiometric amounts of the solutions were mixed to obtain the systems (Zn, Nb)-SnO2 and (Co, Nb) SnO2 . The metal immobilization reduces its segregation during the calcination resulting in a crystalline oxide with high chemical homogeneity. The resin was pre-calcined at 300 °C/1 hour, milled in Atritor Mill at 500 rpm/1 hour, and then calcined at 600 °C/2 hours. X-Ray Diffraction (XDR) indicated formation of SnO2 -rutile phase (JCPDS card nº 41-1445). The characterization by Scanning Electron Microscope of High Resolution showed spherical ceramic powder nanostructured with 10-20 nm of diameter. 20 mg of SnO2 -based powder was kept in 20 ml of isopropyl alcohol and then taken to an electrophoretic deposition (EPD) system. The EPD method allows control the thickness films through the voltage or current applied in the electrophoretic cell and by the time used for deposition of ceramics particles. This procedure obtains films in a short time with low costs, bringing prospects for a new generation of smaller size devices with easy integration technology. In this research, films were obtained in an alumina substrate with interdigital electrodes after applying 2 kV during 5 and 10 minutes in cells containing alcoholic suspension of (Zn, Nb)-SnO2 and (Co, Nb) SnO2 of powders, forming a sensing layer. The substrate has designed integrated micro hotplates that provide an instantaneous and precise temperature control capability when a voltage is applied. The films were sintered at 900 and 1000 °C in a microwave oven of 770 W, adapted by the research group itself with a temperature controller. This sintering is a fast process with homogeneous heating rate which promotes controlled growth of grain size and also the diffusion of modifiers agents, inducing the creation of intrinsic defects which will change the electrical characteristics of SnO2 -based powders. This study has successfully demonstrated a microfabricated system with an integrated micro-hotplate for detection of CO and NO2 gas at different concentrations and temperature, with self-heating SnO2 - based nanoparticles films, being suitable for both industrial process monitoring and detection of low concentrations in buildings/residences in order to safeguard human health. The results indicate the possibility for development of gas sensors devices with low power consumption for integration in portable electronic equipment with fast analysis. Acknowledgments The authors thanks to the LMA-IQ for providing the FEG-SEM images, and the financial support of this project by the Brazilian research funding agencies CNPq, FAPESP 2014/11314-9 and CEPID/CDMF- FAPESP 2013/07296-2.

Keywords: chemical synthesis, electrophoretic deposition, self-heating, gas sensor

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Authors: A. Abbou, V. Makis, N. Salari

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We study the condition-based maintenance (CBM) problem of a system subject to stochastic deterioration. The system is composed of three units (or modules): (i) Module 1 deterioration follows a Markov process with two operational states and one failure state. The operational states are partially observable through periodic condition monitoring. (ii) Module 2 deterioration follows a Gamma process with a known failure threshold. The deterioration level of this module is fully observable through periodic inspections. (iii) Only the operating age information is available of Module 3. The lifetime of this module has a general distribution. A CBM policy prescribes when to initiate a maintenance intervention and which modules to repair during intervention. Our objective is to determine the optimal CBM policy minimizing the long-run expected average cost of operating the system. This is achieved by formulating a Markov decision process (MDP) and developing the value iteration algorithm for solving the MDP. We provide numerical examples illustrating the cost-effectiveness of the optimal CBM policy through a comparison with heuristic policies commonly found in the literature.

Keywords: reliability, maintenance optimization, Markov decision process, heuristics

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Authors: Benalia Nadia, Zerzouri Nora, Ben Si Ali Nadia

Abstract:

Abstract: Among the many different modern heuristic optimization methods, genetic algorithms (GA) and the particle swarm optimization (PSO) technique have been attracting a lot of interest. The GA has gained popularity in academia and business mostly because to its simplicity, ability to solve highly nonlinear mixed integer optimization problems that are typical of complex engineering systems, and intuitiveness. The mechanics of the PSO methodology, a relatively recent heuristic search tool, are modeled after the swarming or cooperative behavior of biological groups. It is suitable to compare the performance of the two techniques since they both aim to solve a particular objective function but make use of distinct computing methods. In this article, PSO and GA optimization approaches are used for the parameter tuning of the power system stabilizer and Proportional integral derivative regulator. Load angle and rotor speed variations in the single machine infinite bus bar system is used to measure the performance of the suggested solution.

Keywords: SMIB, genetic algorithm, PSO, transient stability, power system stabilizer, PID

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Authors: Kefaya Qaddoum

Abstract:

Most of greenhouse growers desire a determined amount of yields in order to accurately meet market requirements. The purpose of this paper is to model a simple but often satisfactory supervised classification method. The original naive Bayes have a serious weakness, which is producing redundant predictors. In this paper, utilized regularization technique was used to obtain a computationally efficient classifier based on naive Bayes. The suggested construction, utilized L1-penalty, is capable of clearing redundant predictors, where a modification of the LARS algorithm is devised to solve this problem, making this method applicable to a wide range of data. In the experimental section, a study conducted to examine the effect of redundant and irrelevant predictors, and test the method on WSG data set for tomato yields, where there are many more predictors than data, and the urge need to predict weekly yield is the goal of this approach. Finally, the modified approach is compared with several naive Bayes variants and other classification algorithms (SVM and kNN), and is shown to be fairly good.

Keywords: tomato yield prediction, naive Bayes, redundancy, WSG

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Authors: H. Mousavi, M. Sharifi, H. Pourvaziri

Abstract:

Redundancy Allocation Problem (RAP) is a well-known mathematical problem for modeling series-parallel systems. It is a combinatorial optimization problem which focuses on determining an optimal assignment of components in a system design. In this paper, to be more practical, we have considered the problem of redundancy allocation of series system with interval valued reliability of components. Therefore, during the search process, the reliabilities of the components are considered as a stochastic variable with a lower and upper bounds. In order to optimize the problem, we proposed a simulated annealing based on cloud theory (CBSAA). Also, the Monte Carlo simulation (MCS) is embedded to the CBSAA to handle the random variable components’ reliability. This novel approach has been investigated by numerical examples and the experimental results have shown that the CBSAA combining MCS is an efficient tool to solve the RAP of systems with interval-valued component reliabilities.

Keywords: redundancy allocation problem, simulated annealing, cloud theory, monte carlo simulation

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Authors: Kiran Fatima, Kashif Ali

Abstract:

Staphylococcus aureus is an opportunistic human as well as animal pathogen that causes a variety of diseases. A total of 70 staphylococci isolates were obtained from soil, water, yogurt, and clinical samples. The likely staphylococci clinical isolates were identified phenotypically by different biochemical tests. Molecular identification was done by PCR using species-specific 16S rRNA primer pairs, and finally, 50 isolates were found to be positive as Staphylococcus aureus, sciuri, xylous and cohnii. Screened isolates were further analyzed by several microbiological diagnostics tests, including gram staining, coagulase, capsule, hemolysis, fermentation of glucose, lactose, maltose, and sucrose tests enzymatic reactions. It was found that 78%, 81%, and 51% of isolates were positive for gelatin hydrolysis, protease, and lipase activities, respectively. Antibiogram analysis of isolated Staphylococcus aureus strains with respect to different antimicrobial agents revealed resistance patterns ranging from 57 to 96%. Our study also shows 70% of strains to be MRSA, 54.3% as VRSA, and 54.3% as both MRSA and VRSA. All the identified isolates were subjected to detection of mecA, nuc, and hlb genes, and 70%, 84%, and 40% were found to harbour mecA, nuc, and hlb genes, respectively. The current investigation is highly important and informative for the high-level multidrug-resistant Staphylococcus aureus infections inclusive also of methicillin and vancomycin.

Keywords: MRSA, VRSA, mecA, MSSA

Procedia PDF Downloads 121