Search results for: geological database

Authors: Osman Turkoglu, Alvin Estilo, Ritu Gupta, Liliam Pineda-Salgado, Rajesh Pandey

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Background: Hepatotoxicity can be linked to a variety of clinical symptoms and histopathological signs, posing a great challenge in the surveillance of suspected drug-induced liver injury (DILI) cases in the safety database. Additionally, the majority of such cases are rare, idiosyncratic, highly unpredictable, and tend to demonstrate unique individual susceptibility; these qualities, in turn, lend to a pharmacovigilance monitoring process that is often tedious and time-consuming. Objective: Develop a multifactorial algorithm to assist pharmacovigilance physicians in identifying high-risk hepatotoxicity cases associated with DILI from the sponsor’s safety database (Argus). Methods: Multifactorial selection criteria were established using Structured Query Language (SQL) and the TIBCO Spotfire® visualization tool, via a combination of word fragments, wildcard strings, and mathematical constructs, based on Hy’s law criteria and pattern of injury (R-value). These criteria excluded non-eligible cases from monthly line listings mined from the Argus safety database. The capabilities and limitations of these criteria were verified by comparing a manual review of all monthly cases with system-generated monthly listings over six months. Results: On an average, over a period of six months, the algorithm accurately identified 92% of DILI cases meeting established criteria. The automated process easily compared liver enzyme elevations with baseline values, reducing the screening time to under 15 minutes as opposed to multiple hours exhausted using a cognitively laborious, manual process. Limitations of the algorithm include its inability to identify cases associated with non-standard laboratory tests, naming conventions, and/or incomplete/incorrectly entered laboratory values. Conclusions: The newly developed multifactorial algorithm proved to be extremely useful in detecting potential DILI cases, while heightening the vigilance of the drug safety department. Additionally, the application of this algorithm may be useful in identifying a potential signal for DILI in drugs not yet known to cause liver injury (e.g., drugs in the initial phases of development). This algorithm also carries the potential for universal application, due to its product-agnostic data and keyword mining features. Plans for the tool include improving it into a fully automated application, thereby completely eliminating a manual screening process.

Keywords: automation, drug-induced liver injury, pharmacovigilance, post-marketing

Procedia PDF Downloads 143

Authors: Meng-Na Dai, Bao-Fang Wen, Gao-Pei Zhu, Chen-Xi Zhang, Jing Sun, Chang-Hai Tang, Zhi-Qiang Feng, Wen-Qiang Yin

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Based on the analysis of literature in the health emergency management in China with recent 10 years, this paper discusses the Chinese current research hotspots, development trends and shortcomings in this field, and provides references for scholars to conduct follow-up research. CNKI(China National Knowledge Infrastructure), Weipu, and Wanfang were the databases of this literature. The key words during the database search were health, emergency, and management with the time from 2009 to 2018. The duplicate, non-academic, and unrelated documents were excluded. 901 articles were included in the literature review database. The main indicators of abstraction were, the number of articles published every year, authors, institutions, periodicals, etc. There are some research findings through the analysis of the literature. Overall, the number of literature in the health emergency management in China has shown a fluctuating downward trend in recent 10 years. Specifically, there is a lack of close cooperation between authors, which has not constituted the core team among them yet. Meanwhile, in this field, the number of high-level periodicals and quality literature is scarce. In addition, there are a lot of research hotspots, such as emergency management system, mechanism research, capacity evaluation index system research, plans and capacity-building research, etc. In the future, we should increase the scientific research funding of the health emergency management, encourage collaborative innovation among authors in multi-disciplinary fields, and create high-quality and high-impact journals in this field. The states should encourage scholars in this field to carry out more academic cooperation and communication with the whole world and improve the research in breadth and depth. Generally speaking, the research in health emergency management in China is still insufficient and needs to be improved.

Keywords: health emergency management, research situation, bibliometrics, literature

Procedia PDF Downloads 127

Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

Procedia PDF Downloads 128

Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

Procedia PDF Downloads 285

Authors: Iris Xiaohong Quan

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The global digital health market reached 175 billion U.S. dollars in 2019, and is expected to grow at about 25% CAGR to over 650 billion USD by 2025. Different terms such as digital health, e-health, mHealth, telehealth have been used in the field, which can sometimes cause confusion. The term digital health was originally introduced to refer specifically to the use of interactive media, tools, platforms, applications, and solutions that are connected to the Internet to address health concerns of providers as well as consumers. While mHealth emphasizes the use of mobile phones in healthcare, telehealth means using technology to remotely deliver clinical health services to patients. According to FDA, “the broad scope of digital health includes categories such as mobile health (mHealth), health information technology (IT), wearable devices, telehealth and telemedicine, and personalized medicine.” Some researchers believe that digital health is nothing else but the cultural transformation healthcare has been going through in the 21st century because of digital health technologies that provide data to both patients and medical professionals. As digital health is burgeoning, but research in the area is still inadequate, our paper aims to clear the definition confusion and provide an overall picture of digital health companies. We further investigate how business models are designed and differentiated in the emerging digital health sector. Both quantitative and qualitative methods are adopted in the research. For the quantitative analysis, our research data came from two databases Crunchbase and CBInsights, which are well-recognized information sources for researchers, entrepreneurs, managers, and investors. We searched a few keywords in the Crunchbase database based on companies’ self-description: digital health, e-health, and telehealth. A search of “digital health” returned 941 unique results, “e-health” returned 167 companies, while “telehealth” 427. We also searched the CBInsights database for similar information. After merging and removing duplicate ones and cleaning up the database, we came up with a list of 1464 companies as digital health companies. A qualitative method will be used to complement the quantitative analysis. We will do an in-depth case analysis of three successful unicorn digital health companies to understand how business models evolve and discuss the challenges faced in this sector. Our research returned some interesting findings. For instance, we found that 86% of the digital health startups were founded in the recent decade since 2010. 75% of the digital health companies have less than 50 employees, and almost 50% with less than 10 employees. This shows that digital health companies are relatively young and small in scale. On the business model analysis, while traditional healthcare businesses emphasize the so-called “3P”—patient, physicians, and payer, digital health companies extend to “5p” by adding patents, which is the result of technology requirements (such as the development of artificial intelligence models), and platform, which is an effective value creation approach to bring the stakeholders together. Our case analysis will detail the 5p framework and contribute to the extant knowledge on business models in the healthcare industry.

Keywords: digital health, business models, entrepreneurship opportunities, healthcare

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Authors: Stepanov Ivan, Musalimov Viktor, Monahov Uriy

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This report examines the current state of human gait simulator development based on the human hip joint model. This unit will create a database of human gait types, useful for setting up and calibrating mechano devices, as well as the creation of new systems of rehabilitation, exoskeletons and walking robots. The system has ample opportunity to configure the dimensions and stiffness, while maintaining relative simplicity.

Keywords: hip joint, human gait, physiotherapy, simulation

Procedia PDF Downloads 395

Authors: Ming-Hong Chen

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In the study, the mechanical and financial feasibility for the compressed air energy storage (CAES) system in the porous media reservoir in Taiwan is evaluated. In 2035, Taiwan aims to install 16.7 GW of wind power and 40 GW of photovoltaic (PV) capacity. However, renewable energy sources often generate more electricity than needed, particularly during winter. Consequently, Taiwan requires long-term, large-scale energy storage systems to ensure the security and stability of its power grid. Currently, the primary large-scale energy storage options are Pumped Hydro Storage (PHS) and Compressed Air Energy Storage (CAES). Taiwan has not ventured into CAES-related technologies due to geological and cost constraints. However, with the imperative of achieving net-zero carbon emissions by 2050, there's a substantial need for the development of a considerable amount of renewable energy. PHS has matured, boasting an overall installed capacity of 4.68 GW. CAES, presenting a similar scale and power generation duration to PHS, is now under consideration. Taiwan's geological composition, being a porous medium unlike salt caves, introduces flow field resistance affecting gas injection and extraction. This study employs a program analysis model to establish the system performance analysis capabilities of CAES. The finite volume model is then used to assess the impact of porous media, and the findings are fed back into the system performance analysis for correction. Subsequently, the financial implications are calculated and compared with existing literature. For Taiwan, the strategic development of CAES technology is crucial, not only for meeting energy needs but also for decentralizing energy allocation, a feature of great significance in regions lacking alternative natural resources.

Keywords: compressed-air energy storage, efficiency, porous media, financial feasibility

Procedia PDF Downloads 57

Authors: M. M. S. Prahastomi, M. Muhajir Saputra, Axel Derian

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Lapindo mud (LUSI ) phenomenon which occurred in Sidoarjo 2006 is a national scale of the geological phenomenon. This mudflow forms a mud volcano that spreads by time is in the need of serious treatment. Some further research has been conducted either by the application method of geodesy, geophysics, and subsurface geology, but still remains a mystery to this phenomenon. Sidoarjo Physiographic regions are included in the Kendeng zone flanked by Rembang zones in northern and Solo zones in southern. In this region revealed Kabuh formation, Jombang formation, and alluvium. In general, in the northern part of the area is composed of sedimentary rocks Sidoarjo klastika, epiklastic, pyroclastics, and older alluvium of the Early Pleistocene to Resen. The study was conducted with the literature study of the stratigraphy and regional geology as well as secondary data from observations coupled gravity method (Anomaly Bouger). The aim of the study is to reveal the subsurface geology structure pattern and the changes in mass flow. Gravity anomaly data were obtained from the calculation of the value of gravity and altitude, then processed into gravity anomaly contours which reflect changes in density of each group observed gravity. The gravity data could indicate a bottom surface which deformation occur the stronger or more intense to the south. Deformation in the form of gravity impairment was associated with a decrease in future density which is indicated by the presence of gas, water and gas bursts. Sectional analysis of changes in the measured value of gravity at different times indicates a change in the value of gravity caused by the presence of subsurface subsidence. While the gravity anomaly section describes the fault zone causes the zone to be unstable.

Keywords: mud volcano, Lumpur Sidoarjo, Bouger anomaly, Indonesia

Procedia PDF Downloads 461

Authors: Hannah K. M. Tang, Muhammad Ateeq, Mark J. Lake, Badr Abdullah, Frederic A. Bezombes

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There is little research applying virtual reality (VR) to the treatment of musculoskeletal injury in athletes. This is despite their prevalence, and the implications for physical and psychological health. Nevertheless, developments of wireless VR headsets better facilitate dynamic movement in VR environments (VREs), and more research is expected in this emerging field. This systematic review identified publications that used VR interventions for the analysis or treatment of lower-limb musculoskeletal injury of athletes. It established a search protocol, and through narrative discussion, identified existing trends. Database searches encompassed four term sets: 1) VR systems; 2) musculoskeletal injuries; 3) sporting population; 4) movement outcome analysis. Overall, a total of 126 publications were identified through database searching, and twelve were included in the final analysis and discussion. Many of the studies were pilot and proof of concept work. Seven of the twelve publications were observational studies. However, this may provide preliminary data from which clinical trials will branch. If specified, the focus of the literature was very narrow, with very similar population demographics and injuries. The trends in the literature findings emphasised the role of VR and attentional focus, the strategic manipulation of movement outcomes, and the transfer of skill to the real-world. Causal inferences may have been undermined by flaws, as most studies were limited by the practicality of conducting a two-factor clinical-VR-based study. In conclusion, by assessing the exploratory studies, and combining this with the use of numerous developments, techniques, and tools, a novel application could be established to utilise VR with dynamic movement, for the effective treatment of specific musculoskeletal injuries of athletes.

Keywords: athletes, lower-limb musculoskeletal injury, rehabilitation, return-to-sport, virtual reality

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Authors: Abdulaziz Alakeel, Roaa Alamri, Abdulrahman Alomair, Mohammed Fouda

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Introduction: Ibrutinib is a selective, potent, and irreversible small-molecule inhibitor of Bruton's tyrosine kinase (BTK). It forms a covalent bond with a cysteine residue (CYS-481) at the active site of Btk, leading to inhibition of Btk enzymatic activity. The drug is indicated to treat certain type of cancers such as mantle cell lymphoma (MCL), chronic lymphocytic leukaemia and Waldenström's macroglobulinaemia (WM). Cardiac failure is a condition referred to inability of heart muscle to pump adequate blood to human body organs. There are multiple types of cardiac failure including left and right-sided heart failure, systolic and diastolic heart failures. The aim of this review is to evaluate the risk of cardiac failure associated with the use of ibrutinib and to suggest regulatory recommendations if required. Methodology: Signal Detection team at the National Pharmacovigilance Center (NPC) of Saudi Food and Drug Authority (SFDA) performed a comprehensive signal review using its national database as well as the World Health Organization (WHO) database (VigiBase), to retrieve related information for assessing the causality between cardiac failure and ibrutinib. We used the WHO- Uppsala Monitoring Centre (UMC) criteria as standard for assessing the causality of the reported cases. Results: Case Review: The number of resulted cases for the combined drug/adverse drug reaction are 212 global ICSRs as of July 2020. The reviewers have selected and assessed the causality for the well-documented ICSRs with completeness scores of 0.9 and above (35 ICSRs); the value 1.0 presents the highest score for best-written ICSRs. Among the reviewed cases, more than half of them provides supportive association (four probable and 15 possible cases). Data Mining: The disproportionality of the observed and the expected reporting rate for drug/adverse drug reaction pair is estimated using information component (IC), a tool developed by WHO-UMC to measure the reporting ratio. Positive IC reflects higher statistical association while negative values indicates less statistical association, considering the null value equal to zero. The results of (IC=1.5) revealed a positive statistical association for the drug/ADR combination, which means “Ibrutinib” with “Cardiac Failure” have been observed more than expected when compared to other medications available in WHO database. Conclusion: Health regulators and health care professionals must be aware for the potential risk of cardiac failure associated with ibrutinib and the monitoring of any signs or symptoms in treated patients is essential. The weighted cumulative evidences identified from causality assessment of the reported cases and data mining are sufficient to support a causal association between ibrutinib and cardiac failure.

Keywords: cardiac failure, drug safety, ibrutinib, pharmacovigilance, signal detection

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Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

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DNA Barcode, a short mitochondrial DNA fragment, made up of three subunits; a phosphate group, sugar and nucleic bases (A, T, C, and G). They provide good sources of information needed to classify living species. Such intuition has been confirmed by many experimental results. Species classification with DNA Barcode sequences has been studied by several researchers. The classification problem assigns unknown species to known ones by analyzing their Barcode. This task has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. To make this type of analysis feasible, heuristics, like progressive alignment, have been developed. Another tool for similarity search against a database of sequences is BLAST, which outputs shorter regions of high similarity between a query sequence and matched sequences in the database. However, all these methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. This method permits to avoid the complex problem of form and structure in different classes of organisms. On empirical data and their classification performances are compared with other methods. Our system consists of three phases. The first is called transformation, which is composed of three steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. The second is called approximation, which is empowered by the use of Multi Llibrary Wavelet Neural Networks (MLWNN).The third is called the classification of DNA Barcodes, which is realized by applying the algorithm of hierarchical classification.

Keywords: DNA barcode, electron-ion interaction pseudopotential, Multi Library Wavelet Neural Networks (MLWNN)

Procedia PDF Downloads 306

Authors: Ilona Pavlovska, Aneka Klavina, Agris Auce, Ivars Vanadzins, Alise Silova, Laura Komarovska, Linda Paegle, Baiba Silamikele, Linda Dobkevica

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Freshwater sapropel is a common material formed by complex biological transformations of Holocene sediments in the water basement of the lakes in Latvia that has the potential to be used as medical mud. Sapropel forms over a long period in shallow waters by slowly decomposing organic sediment and has different compositions depending on the location of the source, surroundings, the water regime, etc. Official geological survey of Latvia lakes, from Latvian lake database (ezeri.lv), used in the selection of the area of the exploration. The multifunctional effect of sapropel on the whole organism explained by its complex chemical and biological structure. This unique, organic substance and its ability to maintain heat for a long time ensures deep tissue warming and has a positive effect on the treatment of various joint and skin diseases. Sapropel is a valuable resource with multiple areas of application. Investigation of sapropel sediments and survey of the five sites selected according to the criteria performed in the current study. Also, our study includes sampling at different depths and their initial treatment, evaluation of external signs, and study of physical-chemical parameters, as well as analysis of biochemical parameters and evaluation of microbiological indicators. The main selection criteria were sapropel deposits depth, hydrological regime, the history of agriculture next to the lake, and the potential exposure to industrial waste. One hundred and five sapropel samples obtained from five lakes (Audzelu, Dunakla, Ivusku, Zielu, and Mazars Kivdalova) during the wintertime. The main goal of the study is to carry out detailed and systematic research on the medical properties of sapropel to be obtained in Latvia, to promote its scientifically based use in balneology, to develop new medical procedures and services, and to promote the development of new exportable products. Latvian freshwater sapropel could be used as raw material for getting sapropel extract and use it as a remedy. All mentioned above brings us to the main question for sapropel usage in medicine, balneology, and pharmacy “how to develop quality criteria for raw sapropel and its extracts. The research was co-financed by the project "Analysis of characteristics of medical sapropel and its usage for medical purposes and elaboration of industrial extraction methods" No.1.1.1.1/16/A/165.

Keywords: balneology, extracts, freshwater sapropel, Latvian lakes, medical mud, sapropel

Procedia PDF Downloads 253

Authors: Eman W. Boghdady, A. R. Shehata, M. A. Azem

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Database (DB) security demands permitting authorized users and prohibiting non-authorized users and intruders actions on the DB and the objects inside it. Organizations that are running successfully demand the confidentiality of their DBs. They do not allow the unauthorized access to their data/information. They also demand the assurance that their data is protected against any malicious or accidental modification. DB protection and confidentiality are the security concerns. There are four types of controls to obtain the DB protection, those include: access control, information flow control, inference control, and cryptographic. The cryptographic control is considered as the backbone for DB security, it secures the DB by encryption during storage and communications. Current cryptographic techniques are classified into two types: traditional classical cryptography using standard algorithms (DES, AES, IDEA, etc.) and chaos cryptography using continuous (Chau, Rossler, Lorenz, etc.) or discreet (Logistics, Henon, etc.) algorithms. The important characteristics of chaos are its extreme sensitivity to initial conditions of the system. In this paper, DB-security systems based on chaotic algorithms are described. The Pseudo Random Numbers Generators (PRNGs) from the different chaotic algorithms are implemented using Matlab and their statistical properties are evaluated using NIST and other statistical test-suits. Then, these algorithms are used to secure conventional DB (plaintext), where the statistical properties of the ciphertext are also tested. To increase the complexity of the PRNGs and to let pass all the NIST statistical tests, we propose two hybrid PRNGs: one based on two chaotic Logistic maps and another based on two chaotic Henon maps, where each chaotic algorithm is running side-by-side and starting from random independent initial conditions and parameters (encryption keys). The resulted hybrid PRNGs passed the NIST statistical test suit.

Keywords: algorithms and data structure, DB security, encryption, chaotic algorithms, Matlab, NIST

Procedia PDF Downloads 262

Authors: Abdorrasoul Malekpour, Mohammad Ghorbani Mojtaba Mortazavi, Mohammadreza Fattahi, Mohammad Hassan Meshkibaf, Ali Fakhrzad, Saeid Salehi, Saeideh Zahedi, Amir Ahmadimoghaddam, Parviz Farzadnia Dr., Mohammadreza Hajyani Asl Bs

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Hepatitis B as an infectious disease has eight main genotypes (A–H). The aim of this study is to Bioinformatically identify Rare Codon Clusters (RCC) in proteins structure of HBV. For detection of protein family accession numbers (Pfam) of HBV proteins; used of uni-prot database and Pfam search tool were used. Obtained Pfam IDs were analyzed in Sherlocc program and RCCs in HBV proteins were detected. In further, the structures of TrEMBL entries proteins studied in PDB database and 3D structures of the HBV proteins and locations of RCCs were visualized and studied using Swiss PDB Viewer software. Pfam search tool have found nine significant hits and 0 insignificant hits in 3 frames. Results of Pfams studied in the Sherlocc program show this program not identified RCCs in the external core antigen (PF08290) and truncated HBeAg protein (PF08290). By contrast the RCCs become identified in Hepatitis core antigen (PF00906) Large envelope protein S (PF00695), X protein (PF00739), DNA polymerase (viral) N-terminal domain (PF00242) and Protein P (Pf00336). In HBV genome, seven RCC identified that found in hepatitis core antigen, large envelope protein S and DNA polymerase proteins and proteins structures of TrEMBL entries sequences that reported in Sherlocc program outputs are not complete. Based on situation of RCC in structure of HBV proteins, it suggested those RCCs are important in HBV life cycle. We hoped that this study provide a new and deep perspective in protein research and drug design for treatment of HBV.

Keywords: rare codon clusters, hepatitis B virus, bioinformatic study, infectious disease

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Authors: Rakhyun Kim, Sungho Tae

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Global environmental issues such as abnormal weathers due to global warming, resource depletion, and ecosystem distortions have been escalating due to rapid increase of population growth, and expansion of industrial and economic development. Accordingly, initiatives have been implemented by many countries to protect the environment through indirect regulation methods such as Environmental Product Declaration (EPD), in addition to direct regulations such as various emission standards. Following this trend, life cycle assessment (LCA) techniques that provide quantitative environmental information, such as Human Toxicity Potential (HTP), for buildings are being developed in the construction industry. However, at present, the studies on the environmental database of building materials are not sufficient to provide this support adequately. The purpose of this study is to analysis human toxicity potential of major building material production stage using life cycle assessment. For this purpose, the theoretical consideration of the life cycle assessment and environmental impact category was performed and the direction of the study was set up. That is, the major material in the global warming potential view was drawn against the building and life cycle inventory database was selected. The classification was performed about 17 kinds of substance and impact index, such as human toxicity potential, that it specifies in CML2001. The environmental impact of analysis human toxicity potential for the building material production stage was calculated through the characterization. Meanwhile, the environmental impact of building material in the same category was analyze based on the characterization impact which was calculated in this study. In this study, establishment of environmental impact coefficients of major building material by complying with ISO 14040. Through this, it is believed to effectively support the decisions of stakeholders to improve the environmental performance of buildings and provide a basis for voluntary participation of architects in environment consideration activities.

Keywords: human toxicity potential, major building material, life cycle assessment, production stage

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Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

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Authors: Arin Ghazarian, Cyril Rakovski

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Differential privacy has become the leading technique to protect the privacy of individuals in a database while allowing useful analysis to be done and the results to be shared. It puts a guarantee on the amount of privacy loss in the worst-case scenario. Differential privacy is not a toggle between full privacy and zero privacy. It controls the tradeoff between the accuracy of the results and the privacy loss using a single key parameter called

Keywords: arrhythmia, cardiology, differential privacy, ECG, epsilon, medi-cal data, privacy preserving analytics, statistical databases

Procedia PDF Downloads 140

Authors: Rajlakshmi Guha, Sajjad Ansari, Shazia Nasreen, Hirak Banerjee, Jiaul Paik

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Dyslexia is a neurocognitive disorder, affecting around fifteen percent of the Indian population. The symptoms include difficulty in reading alphabet, words, and sentences. This can be difficult at the phonemic or recognition level and may further affect lexical structures. Therapeutic intervention of dyslexic children post assessment is generally done by special educators and psychologists through one on one interaction. Considering the large number of children affected and the scarcity of experts, access to care is limited in India. Moreover, unavailability of resources and timely communication with caregivers add on to the problem of proper intervention. With the development of Educational Technology and its use in India, access to information and care has been improved in such a large and diverse country. In this context, this paper proposes an ICT enabled home-based intervention program for dyslexic children which would support the child, and provide an interactive interface between expert, parents, and students. The paper discusses the details of the database design and system layout of the program. Along with, it also highlights the development of different technical aids required to build out personalized android applications for the Indian dyslexic population. These technical aids include speech database creation for children, automatic speech recognition system, serious game development, and color coded fonts. The paper also emphasizes the games developed to assist the dyslexic child on cognitive training primarily for attention, working memory, and spatial reasoning. In addition, it talks about the specific elements of the interactive intervention tool that makes it effective for home based intervention of dyslexia.

Keywords: Android applications, cognitive training, dyslexia, intervention

Procedia PDF Downloads 287

Authors: Chao Yang, Jinchuan Zhang, Yongqiang Xiong

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The Lower Cambrian Niutitang Formation shale (NFS) deposited in the marine deep-shelf environment in Southeast Upper Yangtze (SUY), possess excellent source rock basis for shale gas generation, however, it is currently challenged by being over-mature with strong tectonic deformations, leading to much uncertainty of gas-bearing potential. With emphasis on the shale gas enrichment of the NFS, analyses were made based on the regional gas-bearing differences obtained from field gas-desorption testing of 18 geological survey wells across the study area. Results show that the NFS bears low gas content of 0.2-2.5 m³/t, and the eastern region of SUY is higher than the western region in gas content. Moreover, the methane fraction also presents the similar regional differentiation with the western region less than 10 vol.% while the eastern region generally more than 70 vol.%. Through the analysis of geological theory, the following conclusions are drawn: Depositional environment determines the gas-enriching zones. In the western region, the Dengying Formation underlying the NFS in unconformity contact was mainly plateau facies dolomite with caves and thereby bears poor gas-sealing ability. Whereas the Laobao Formation underling the NFS in eastern region was a set of siliceous rocks of shelf-slope facies, which can effectively prevent the shale gas from escaping away from the NFS. The tectonic conditions control the gas-enriching bands in the SUY, which is located in the fold zones formed by the thrust of the Southern China plate towards to the Sichuan Basin. Compared with the western region located in the trough-like folds, the eastern region at the fold-thrust belts was uplifted early and deformed weakly, resulting in the relatively less mature level and relatively slight tectonic deformation of the NFS. Faults determine whether shale gas can be accumulated in large scale. Four deep and large normal faults in the study area cut through the Niutitang Formation to the Sinian strata, directly causing a large spillover of natural gas in the adjacent areas. For the secondary faults developed within the shale formation, the reverse faults generally have a positive influence on the shale accumulation while the normal faults perform the opposite influence. Overall, shale gas enrichment targets of the NFS, are the areas with certain thickness of siliceous rocks at the basement of the Niutitang Formation, and near the margin of the paleouplift with less developed faults. These findings provide direction for shale gas exploration in South China, and also provide references for the areas with similar geological conditions all over the world.

Keywords: over-mature marine shale, shale gas accumulation, structure-complicated area, Southeast Upper Yangtze

Procedia PDF Downloads 135

Authors: Yusuf Hussaini Atulukwu, Daramola Japheth, Tabitit S. Tabiti, Daramola Elizabeth Lara

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In view of the recent limitations faced by the township concerning poorly constructed and in some cases non - existence of drainage facilities that resulted into incessant flooding in some parts of the community poses threat to life,property and the environment. The research seeks to address this issue by showing the spatial distribution of drainage network in Bida Urban using Geographic information System techniques. Relevant features were extracted from existing Bida based Map using un-screen digitization and x, y, z, data of existing drainages were acquired using handheld Global Positioning System (GPS). These data were uploaded into ArcGIS 9.2, software, and stored in the relational database structure that was used to produce the spatial data drainage network of the township. The result revealed that about 40 % of the drainages are blocked with sand and refuse, 35 % water-logged as a result of building across erosion channels and dilapidated bridges as a result of lack of drainage along major roads. The study thus concluded that drainage network systems in Bida community are not in good working condition and urgent measures must be initiated in order to avoid future disasters especially with the raining season setting in. Based on the above findings, the study therefore recommends that people within the locality should avoid dumping municipal waste within the drainage path while sand blocked or weed blocked drains should be clear by the authority concerned. In the same vein the authority should ensured that contract of drainage construction be awarded to professionals and all the natural drainages caused by erosion should be addressed to avoid future disasters.

Keywords: drainage network, spatial, digitization, relational database, waste

Procedia PDF Downloads 323

Authors: S. P. Bansal, Mukesh Kumar Sharma, Ankit Prabhakar

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Luhri Hydroelectric Project Stage-I (210 MW) is a run of the river type development with a dam toe surface powerhouse (122m long, 50.50m wide, and 65.50m high) on the right bank of river Satluj in Himachal Pradesh, India. The project is located in the inner lesser Himalaya between Dhauladhar Range in the south and higher Himalaya in the north in the seismically active region. At the project, the location river is confined within narrow V-shaped valleys with little or no flat areas close to the river bed. Nearly 120m high cut slopes behind the powerhouse are proposed from the powerhouse foundation level of 795m to ± 915m to accommodate the surface powerhouse. The stability of 120m high cut slopes is a prime concern for the reason of risk involved. The slopes behind the powerhouse will be excavated in mainly in augen gneiss, fresh to weathered in nature, and biotite rich at places. The foliation joints are favorable and dipping inside the hill. Two valleys dipping steeper joints will be encountered on the slopes, which can cause instability during excavation. Geological exploration plays a vital role in designing and optimization of cut slopes. SWEDGE software has been used to analyze the geometry and stability of surface wedges in cut slopes. The slopes behind powerhouse have been analyzed in three zones for stability analysis by providing a break in the continuity of cut slopes, which shall provide quite substantial relief for slope stabilization measure. Pseudo static analysis has been carried out for the stabilization of wedges. The results indicate that many large wedges are forming, which have a factor of safety less than 1. The stability measures (support system, bench width, slopes) have been planned so that no wedge failure may occur in the future.

Keywords: cut slopes, geotechnical investigations, Himalayan geology, surface powerhouse, wedge failure

Procedia PDF Downloads 109

Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

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Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

Procedia PDF Downloads 270

Authors: Marwa Djebbi, Hakim Gabtni

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Gravity is a continuously advancing method that has become a mature technology for geological studies. Increasingly, it has been used to complement and constrain traditional seismic data and even used as the only tool to get information of the sub-surface. In fact, in some regions the seismic data, if available, are of poor quality and hard to be interpreted. Such is the case for the current study area. The Nefza zone is part of the Tellian fold and thrust belt domain in the north west of Tunisia. It is essentially made of a pile of allochthonous units resulting from a major Neogene tectonic event. Its tectonic and stratigraphic developments have always been subject of controversies. Considering the geological and hydrogeological importance of this area, a detailed interdisciplinary study has been conducted integrating geology, seismic and gravity techniques. The interpretation of Gravity data allowed the delimitation of the dune reservoir and the identification of the regional lineaments contouring the area. It revealed the presence of three gravity lows that correspond to the dune of Zouara and Ouchtata separated along with a positive gravity axis espousing the Ain Allega_Aroub Er Roumane axe. The Bouguer gravity map illustrated the compartmentalization of the Zouara dune into two depressions separated by a NW-SE anomaly trend. This constitution was confirmed by the vertical derivative map which showed the individualization of two depressions with slightly different anomaly values. The horizontal gravity gradient magnitude was performed in order to determine the different geological features present in the studied area. The latest indicated the presence of NE-SW parallel folds according to the major Atlasic direction. Also, NW-SE and EW trends were identified. The maxima tracing confirmed this direction by the presence of NE-SW faults, mainly the Ghardimaou_Cap Serrat accident. The quality of the available seismic sections and the absence of borehole data in the region, except few hydraulic wells that been drilled and showing the heterogeneity of the substratum of the dune, required the process of gravity modeling of this challenging area that necessitates to be modeled for the geometrical characterization of the dune reservoir and determine the different stratigraphic series underneath these deposits. For more detailed and accurate results, the scale of study will be reduced in coming research. A more concise method will be elaborated; the 4D microgravity survey. This approach is considered as an expansion of gravity method and its fourth dimension is time. It will allow a continuous and repeated monitoring of fluid movement in the subsurface according to the micro gal (μgall) scale. The gravity effect is a result of a monthly variation of the dynamic groundwater level which correlates with rainfall during different periods.

Keywords: 3D gravity modeling, dune reservoir, heterogeneous substratum, seismic interpretation

Procedia PDF Downloads 291

Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

Procedia PDF Downloads 323

Authors: N. A. Kharisa, I. Wulandari, R. Narendratama, M. I. Faisal, K. Kirana, R. Zipora, I. Arfiansah, I. Suyanto

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Acquisition of geophysical survey with magnetic method has been done in manifestation of geothermalat Candi Umbul, Grabag, Magelang, Central Java Province on 10-12 May 2013. This objective research is interpretation to interpret structural geology that control geothermal system in CandiUmbul area. The research has been finished with area size 1,5 km x 2 km and measurement space of 150 m. And each point of line space survey is 150 m using PPM Geometrics model G-856. Data processing was started with IGRF and diurnal variation correction to get total magnetic field anomaly. Then, advance processing was done until reduction to pole, upward continuation, and residual anomaly. That results become next interpretation in qualitative step. It is known that the biggest object position causes low anomaly located in central of area survey that comes from hot spring manifestation and demagnetization zone that indicates the existence of heat source activity. Then, modeling the anomaly map was used for quantitative interpretation step. The result of modeling is rock layers and geological structure model that can inform about the geothermal system. And further information from quantitative interpretations can be interpreted about lithology susceptibility. And lithology susceptibilities are andesiteas heat source has susceptibility value of (k= 0.00014 emu), basaltic as alteration rock (k= 0.0016 emu), volcanic breccia as reservoir rock (k= 0.0026 emu), andesite porfirtic as cap rock (k= 0.004 emu), lava andesite (k= 0.003 emu), and alluvium (k= 0.0007 emu). The hot spring manifestation is controlled by the normal fault which becomes a weak zone, easily passed by hot water which comes from the geothermal reservoir.

Keywords: geological structure, geothermal system, magnetic, susceptibility

Procedia PDF Downloads 379

Authors: Rose A. Yemson, Ping Jiang, Oyedeji L. Inumoh

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The deployment of wireless sensor network has rapidly increased, however with the increased capacity and diversity of sensors, and applications ranging from biological, environmental, military etc. generates tremendous volume of data’s where more attention is placed on the distributed sensing and little on how to manage, analyze, retrieve and understand the data generated. This makes it more quite difficult to process live sensor data, run concurrent control and update because sensor data are either heavyweight, complex, and slow. This work will focus on developing a web service platform for automatic detection of sensors, acquisition of sensor data, storage of sensor data into a database, processing of sensor data using reconfigurable software components. This work will also create a web service based sensor data management system to monitor physical movement of an individual wearing wireless network sensor technology (SunSPOT). The sensor will detect movement of that individual by sensing the acceleration in the direction of X, Y and Z axes accordingly and then send the sensed reading to a database that will be interfaced with an internet platform. The collected sensed data will determine the posture of the person such as standing, sitting and lying down. The system is designed using the Unified Modeling Language (UML) and implemented using Java, JavaScript, html and MySQL. This system allows real time monitoring an individual closely and obtain their physical activity details without been physically presence for in-situ measurement which enables you to work remotely instead of the time consuming check of an individual. These details can help in evaluating an individual’s physical activity and generate feedback on medication. It can also help in keeping track of any mandatory physical activities required to be done by the individuals. These evaluations and feedback can help in maintaining a better health status of the individual and providing improved health care.

Keywords: HTML, java, javascript, MySQL, sunspot, UML, web-based, wireless network sensor

Procedia PDF Downloads 205

Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

Procedia PDF Downloads 153

Authors: Saleh Alshehri

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Human skin detection is a vital step in many applications. Some of the applications are critical especially those related to security. This leverages the importance of a high-performance detection algorithm. To validate the accuracy of the algorithm, image databases are usually used. However, the suitability of these image databases is still questionable. It is suggested that the suitability can be measured mainly by the span the database covers of the color space. This research investigates the validity of three famous image databases.

Keywords: image databases, image processing, pattern recognition, neural networks

Procedia PDF Downloads 255

Authors: Khaled Albriki, Feiyu Wang

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The failed rifted epicratonic Sirt basin is located in the northern margin of the African Plate with an area of approximately 600,000 km2. The organofacies' classification, characterization, and its distribution vertically and horizontally are carried out in 7 main troughs with 32 typical selected wells. 7 geological and geochemical cross sections including Rock-Eval data and % TOC data are considered in order to analyze and to characterize the main organofacies with respect to their geochemical and geological controls and also to remove the ambiguity behind the complexity of the orgnofacies types and distributions in the basin troughs from where the oil and gas are generated and migrated. This study confirmes that there are four different classical types of organofacies distributed in Sirt basin F, D/E, C, and B. these four clasical types of organofacies controls the type and amount of the hydrocarbon discovered in Sirt basin. Oil bulk property data from more than 20 oil and gas fields indicate that D/E organoface are significant oil and gas contributors similar to B organoface. In the western Sirt basin in Zallah-Dur Al Abd, Hagfa, Kotla, and Dur Atallha troughs, F organoface is identified for Etel formation, Kalash formation and Hagfa formation having % TOC < 0.6, whereas the good quality D/E and B organofacies present in Rachmat formation and Sirte shale formation both have % TOC > 1.1. Results from the deepest trough (Ajdabiya), Etel (Gas pron in Whadyat trough), Kalash, and Hagfa constitute F organofacies, mainly. The Rachmat and Sirt shale both have D/E to B organofacies with % TOC > 1.2, thus indicating the best organofacies quality in Ajdabiya trough. In Maragh trough, results show that Etel F organofacies and D/E, C to B organofacies related to Middle Nubian, Rachmat, and Sirte shale have %TOC > 0.66. Towards the eastern Sirt basin, in troughs (Hameimat, Faregh, and Sarir), results show that the Middle Nubian, Etel, Rachmat, and Sirte shales are strongly dominated by D/E, C to B (% TOC > 0.75) organofacies.

Keywords: Etel, Mid-Nubian, organic facies, Rachmat, Sirt basin, Sirte shale

Procedia PDF Downloads 123

Authors: Nopparet Thammasaranyakun

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This research objects are: 1: To study the biodiversity of medicinal plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province. 2: To study the use of medicinal plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province. 3: To provide a database of information on biodiversity for food and medicinal plants and medicinal tourism economies along the Phu Sing district Sisaket province. 4: Learn to create a biodiversity of medicinal plants used as food and treatment by Journeys economic Phu Sing district Sisaket province Boundaries used in this study was the Phu Sing district. Population and Agricultural Development Center, rayong Mun due to the initiative for youth Local, Government Health officials, community leaders, teachers, students, schools, the local people and tourists. Sage wisdom to know the herbs and women's groups, OTOP Phu Sing district in SiisaKet province. By selecting the specific data that way. The process of participatory action research (PAR) is a community-based research. The method of collecting qualitative data. (Qualitative) tool is used from context, Community areas, interview and Taped recordings. Observation and focus group data was statistically analyzed using descriptive statistics (Descriptive Statistics). The results findings: 1- A study of the biodiversity of plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province. Were used in the dry season and the rainy season find the medicinal plants of 251 species 41 types of drugs. 2- The study utilized medicinal plants used as food and the treatment of indigenous Phu Sing Sisaket province. Found 251 species have medicinal properties that are used for food and medicinal purposes 41 types of drugs. 3- Of the database technology of biodiversity for food and medicinal plants used by local treatment Phu Sing district Sisaket province. A data base of 251 medicinal species 41 types of drugs is used for food and medicinal properties Sisaket province. 4- learning the biodiversity of medicinal plants used for food and medicinal tourism economies along the Phu Sing district Sisaket province.

Keywords: utilization of biodiversity, peaces herbals, used as Food, Sing district, sisaket

Procedia PDF Downloads 347