Search results for: maximal data sets
25104 Survey on Data Security Issues Through Cloud Computing Amongst Sme’s in Nairobi County, Kenya
Authors: Masese Chuma Benard, Martin Onsiro Ronald
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Businesses have been using cloud computing more frequently recently because they wish to take advantage of its advantages. However, employing cloud computing also introduces new security concerns, particularly with regard to data security, potential risks and weaknesses that could be exploited by attackers, and various tactics and strategies that could be used to lessen these risks. This study examines data security issues on cloud computing amongst sme’s in Nairobi county, Kenya. The study used the sample size of 48, the research approach was mixed methods, The findings show that data owner has no control over the cloud merchant's data management procedures, there is no way to ensure that data is handled legally. This implies that you will lose control over the data stored in the cloud. Data and information stored in the cloud may face a range of availability issues due to internet outages; this can represent a significant risk to data kept in shared clouds. Integrity, availability, and secrecy are all mentioned.Keywords: data security, cloud computing, information, information security, small and medium-sized firms (SMEs)
Procedia PDF Downloads 8425103 Cloud Design for Storing Large Amount of Data
Authors: M. Strémy, P. Závacký, P. Cuninka, M. Juhás
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Main goal of this paper is to introduce our design of private cloud for storing large amount of data, especially pictures, and to provide good technological backend for data analysis based on parallel processing and business intelligence. We have tested hypervisors, cloud management tools, storage for storing all data and Hadoop to provide data analysis on unstructured data. Providing high availability, virtual network management, logical separation of projects and also rapid deployment of physical servers to our environment was also needed.Keywords: cloud, glusterfs, hadoop, juju, kvm, maas, openstack, virtualization
Procedia PDF Downloads 35225102 Effect of Resistance Exercise on Hypothalamic-Pituitary-Gonadal Axis
Authors: Alireza Barari, Saeed Shirali, Ahmad Abdi
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Abstract: Introduction: Physical activity may be related to male reproductive function by affecting on thehypothalamic-pituitary-gonadal(HPG) axis. Our aim was to determine the effects of 6 weeks resistance exercise on reproductive hormones, HPG axis. The hypothalamic-pituitary-gonadal (HPG) axis refers tothe effects of endocrine glands in three-level including (i) the hypothalamic releasing hormone GnRH, which is synthesized in in a small heterogenous neuronal population and released in a pulsatile fashion, (ii) the anterior pituitary hormones, follicle-stimulating hormone(FSH) and luteinizing hormone (LH) and (iii) the gonadal hormones, which include both steroid such as testosterone (T), estradiol and progesterone and peptide hormones (such as inhibin). Hormonal changes that create a more anabolic environment have been suggested to contribute to the adaptation to strength exercise. Physical activity has an extensive impact on male reproductive function depending upon the intensity and duration of the exercise and the fitness level of the individual. However, strenuous exercise represents a physical stress and inflammation changed that challenges homeostasis. Materials and methods: Sixteen male volunteered were included in a 6-week control period followed by 6 weeks of resistance training (leg press, lat pull, chest press, squat, seatedrow, abdominal crunch, shoulder press, biceps curl and triceps press down) four times per week. intensity of training loading was 60%-75% of one maximum repetition. Participants performed 3 sets of 10 repetitions. Rest periods were two min between exercises and sets. Start with warm up exercises include: The muscles relax and stretch the body, which was for 10 minutes. Body composition, VO2max and the circulating level of free testosterone (fT), luteinizing hormone (LH), follicle-stimulating hormone (FSH), sex hormone binding globulin (SHBG) and inhibin B measured prior and post 6-week intervention. The hormonal levels of each serum sample were measured using commercially available ELISA kits. Analysis of anthropometrical data and hormonal level were compared using the independent samples t- test in both groups and using SPSS (version 19). P ≤ 0.05 was considered statistically significant. Results: For muscle strength, both lower- and upper-body strength were increased significantly. Aerobic fitness level improved in trained participant from 39.4 ± 5.6 to 41.9 ± 5.3 (P = 0.002). fT concentration rise progressively in the trained group and was significantly greater than those in the control group (P = 0.000). By the end of the 6-week resistance training, serum SHBG significantly increased in the trained group compared with the control group (P = 0.013). In response to resistance training, LH, FSH and inhibin B were not significantly changed. Discussion: According to our finfings, 6 weeks of resistance training induce fat loss without any changes in body weight and BMI. A decline of 25.3% in percentage of body fat with statiscally same weight was due to increase in muscle mass that happened during resistance exercise periods . Six weeks of resistance training resulted in significant improvement in BF%, VO2max and increasing strength and the level of fT and SHBG.Keywords: resistance, hypothalamic, pituitary, gonadal axis
Procedia PDF Downloads 39925101 Estimation of Missing Values in Aggregate Level Spatial Data
Authors: Amitha Puranik, V. S. Binu, Seena Biju
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Missing data is a common problem in spatial analysis especially at the aggregate level. Missing can either occur in covariate or in response variable or in both in a given location. Many missing data techniques are available to estimate the missing data values but not all of these methods can be applied on spatial data since the data are autocorrelated. Hence there is a need to develop a method that estimates the missing values in both response variable and covariates in spatial data by taking account of the spatial autocorrelation. The present study aims to develop a model to estimate the missing data points at the aggregate level in spatial data by accounting for (a) Spatial autocorrelation of the response variable (b) Spatial autocorrelation of covariates and (c) Correlation between covariates and the response variable. Estimating the missing values of spatial data requires a model that explicitly account for the spatial autocorrelation. The proposed model not only accounts for spatial autocorrelation but also utilizes the correlation that exists between covariates, within covariates and between a response variable and covariates. The precise estimation of the missing data points in spatial data will result in an increased precision of the estimated effects of independent variables on the response variable in spatial regression analysis.Keywords: spatial regression, missing data estimation, spatial autocorrelation, simulation analysis
Procedia PDF Downloads 38225100 Reductions of Control Flow Graphs
Authors: Robert Gold
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Control flow graphs are a well-known representation of the sequential control flow structure of programs with a multitude of applications. Not only single functions but also sets of functions or complete programs can be modelled by control flow graphs. In this case the size of the graphs can grow considerably and thus makes it difficult for software engineers to analyse the control flow. Graph reductions are helpful in this situation. In this paper we define reductions to subsets of nodes. Since executions of programs are represented by paths through the control flow graphs, paths should be preserved. Furthermore, the composition of reductions makes a stepwise analysis approach possible.Keywords: control flow graph, graph reduction, software engineering, software applications
Procedia PDF Downloads 55225099 Introduction to Paired Domination Polynomial of a Graph
Authors: Puttaswamy, Anwar Alwardi, Nayaka S. R.
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One of the algebraic representation of a graph is the graph polynomial. In this article, we introduce the paired-domination polynomial of a graph G. The paired-domination polynomial of a graph G of order n is the polynomial Dp(G, x) with the coefficients dp(G, i) where dp(G, i) denotes the number of paired dominating sets of G of cardinality i and γpd(G) denotes the paired-domination number of G. We obtain some properties of Dp(G, x) and its coefficients. Further, we compute this polynomial for some families of standard graphs. Further, we obtain some characterization for some specific graphs.Keywords: domination polynomial, paired dominating set, paired domination number, paired domination polynomial
Procedia PDF Downloads 23225098 Present Status, Driving Forces and Pattern Optimization of Territory in Hubei Province, China
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“National Territorial Planning (2016-2030)” was issued by the State Council of China in 2017. As an important initiative of putting it into effect, territorial planning at provincial level makes overall arrangement of territorial development, resources and environment protection, comprehensive renovation and security system construction. Hubei province, as the pivot of the “Rise of Central China” national strategy, is now confronted with great opportunities and challenges in territorial development, protection, and renovation. Territorial spatial pattern experiences long time evolution, influenced by multiple internal and external driving forces. It is not clear what are the main causes of its formation and what are effective ways of optimizing it. By analyzing land use data in 2016, this paper reveals present status of territory in Hubei. Combined with economic and social data and construction information, driving forces of territorial spatial pattern are then analyzed. Research demonstrates that the three types of territorial space aggregate distinctively. The four aspects of driving forces include natural background which sets the stage for main functions, population and economic factors which generate agglomeration effect, transportation infrastructure construction which leads to axial expansion and significant provincial strategies which encourage the established path. On this basis, targeted strategies for optimizing territory spatial pattern are then put forward. Hierarchical protection pattern should be established based on development intensity control as respect for nature. By optimizing the layout of population and industry and improving the transportation network, polycentric network-based development pattern could be established. These findings provide basis for Hubei Territorial Planning, and reference for future territorial planning in other provinces.Keywords: driving forces, Hubei, optimizing strategies, spatial pattern, territory
Procedia PDF Downloads 10525097 A Critical Examination of the Iranian National Legal Regulation of the Ecosystem of Lake Urmia
Authors: Siavash Ostovar
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The Iranian national Law on the Ramsar Convention (officially known as the Convention of International Wetlands and Aquatic Birds' Habitat Wetlands) was approved by the Senate and became a law in 1974 after the ratification of the National Council. There are other national laws with the aim of preservation of environment in the country. However, Lake Urmia which is declared a wetland of international importance by the Ramsar Convention in 1971 and designated a UNESCO Biosphere Reserve in 1976 is now at the brink of total disappearance due mainly to the climate change, water mismanagement, dam construction, and agricultural deficiencies. Lake Urmia is located in the north western corner of Iran. It is the third largest salt water lake in the world and the largest lake in the Middle East. Locally, it is designated as a National Park. It is, indeed, a unique lake both nationally and internationally. This study investigated how effective the national legal regulation of the ecosystem of Lake Urmia is in Iran. To do so, the Iranian national laws as Enforcement of Ramsar Convention in the country including three nationally established laws of (i) Five sets of laws for the programme of economic, social and cultural development of Islamic Republic of Iran, (ii) The Iranian Penal Code, (iii) law of conservation, restoration and management of the country were investigated. Using black letter law methods, it was revealed that (i) regarding the national five sets of laws; the benchmark to force the implementation of the legislations and policies is not set clearly. In other words, there is no clear guarantee to enforce these legislations and policies at the time of deviation and violation; (ii) regarding the Penal Code, there is lack of determining the environmental crimes, determining appropriate penalties for the environmental crimes, implementing those penalties appropriately, monitoring and training programmes precisely; (iii) regarding the law of conservation, restoration and management, implementation of this regulation is adjourned to preparation, announcement and approval of several categories of enactments and guidelines. In fact, this study used a national environmental catastrophe caused by drying up of Lake Urmia as an excuse to direct the attention to the weaknesses of the existing national rules and regulations. Finally, as we all depend on the natural world for our survival, this study recommended further research on every environmental issue including the Lake Urmia.Keywords: conservation, environmental law, Lake Urmia, national laws, Ramsar Convention, water management, wetlands
Procedia PDF Downloads 20025096 Immunization-Data-Quality in Public Health Facilities in the Pastoralist Communities: A Comparative Study Evidence from Afar and Somali Regional States, Ethiopia
Authors: Melaku Tsehay
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The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.Keywords: data quality, immunization, verification factor, pastoralist region
Procedia PDF Downloads 12325095 Optimal Dynamic Regime for CO Oxidation Reaction Discovered by Policy-Gradient Reinforcement Learning Algorithm
Authors: Lifar M. S., Tereshchenko A. A., Bulgakov A. N., Guda S. A., Guda A. A., Soldatov A. V.
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Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes - adsorption, activation, reaction, and desorption. These processes, in turn, depend on the inlet feed concentrations, temperature, and pressure. At stationary conditions, the active surface sites may be poisoned by reaction byproducts or blocked by thermodynamically adsorbed gaseous reagents. Thus, the yield of reaction products can significantly drop. On the contrary, the dynamic control accounts for the changes in the surface properties and adjusts reaction parameters accordingly. Therefore dynamic control may be more efficient than stationary control. In this work, a reinforcement learning algorithm has been applied to control the simulation of CO oxidation on a catalyst. The policy gradient algorithm is learned to maximize the CO₂ production rate based on the CO and O₂ flows at a given time step. Nonstationary solutions were found for the regime with surface deactivation. The maximal product yield was achieved for periodic variations of the gas flows, ensuring a balance between available adsorption sites and the concentration of activated intermediates. This methodology opens a perspective for the optimization of catalytic reactions under nonstationary conditions.Keywords: artificial intelligence, catalyst, co oxidation, reinforcement learning, dynamic control
Procedia PDF Downloads 12925094 Estimation of Carbon Sequestration and Air Quality of Terrestrial Ecosystems Using Remote Sensing Techniques
Authors: Kanwal Javid, Shazia Pervaiz, Maria Mumtaz, Muhammad Ameer Nawaz Akram
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Forests and grasslands ecosystems play an important role in the global carbon cycle. Land management activities influence both ecosystems and enable them to absorb and sequester carbon dioxide (CO2). Similarly, in Pakistan, these terrestrial ecosystems are well known to mitigate carbon emissions and have a great source to supply a variety of services such as clean air and water, biodiversity, wood products, wildlife habitat, food, recreation and carbon sequestration. Carbon sequestration is the main agenda of developed and developing nations to reduce the impacts of global warming. But the amount of carbon storage within these ecosystems can be affected by many factors related to air quality such as land management, land-use change, deforestation, over grazing and natural calamities. Moreover, the long-term capacity of forests and grasslands to absorb and sequester CO2 depends on their health, productivity, resilience and ability to adapt to changing conditions. Thus, the main rationale of this study is to monitor the difference in carbon amount of forests and grasslands of Northern Pakistan using MODIS data sets and map results using Geographic Information System. Results of the study conclude that forests ecosystems are more effective in reducing the CO2 level and play a key role in improving the quality of air.Keywords: carbon sequestration, grasslands, global warming, climate change.
Procedia PDF Downloads 18725093 Identifying Critical Success Factors for Data Quality Management through a Delphi Study
Authors: Maria Paula Santos, Ana Lucas
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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort
Procedia PDF Downloads 21725092 Expression of Fused Plasmodium falciparum Orotate Phosphoribosyltransferase and Orotidine 5'-Monophosphate Decarboxylase in Escherichia coli
Authors: Waranya Imprasittichai, Patsarawadee Paojinda, Sudaratana R. Krungkrai, Nirianne Marie Q. Palacpac, Toshihiro Horii, Jerapan Krungkrai
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Fusion of the last two enzymes in the pyrimidine biosynthetic pathway in the inversed order by having COOH-terminal orotate phosphoribosyltransferase (OPRT) and NH2-terminal orotidine 5'-monophosphate decarboxylase (OMPDC), as OMPDC-OPRT, are described in many organisms. In this study, we constructed gene fusions of Plasmodium falciparum OMPDC-OPRT (1,836 bp) in pTrcHisA vector and expressed as an 6xHis-tag bifunctional protein in three Escherichia coli strains (BL21, Rosetta, TOP10) at 18 °C, 25 °C and 37 °C. The recombinant bifunctional protein was partially purified by Ni-Nitrilotriacetic acid-affinity chromatography. Specific activities of OPRT and OMPDC domains in the bifunctional enzyme expressed in E. coli TOP10 cells were approximately 3-4-fold higher than those in BL21 cells. There were no enzymatic activities when the construct vector expressed in Rosetta cells. Maximal expression of the fused gene was observed at 18 °C and the bifunctional enzyme had specific activities of OPRT and OMPDC domains in a ratio of 1:2. These results provide greater yields and better catalytic activities of the bifunctional OMPDC-OPRT enzyme for further purification and kinetic study.Keywords: bifunctional enzyme, orotate phosphoribosyltransferase, orotidine 5'-monophosphate decarboxylase, plasmodium falciparum
Procedia PDF Downloads 35425091 Rearrangement and Depletion of Human Skin Folate after UVA Exposure
Authors: Luai Z. Hasoun, Steven W. Bailey, Kitti K. Outlaw, June E. Ayling
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Human skin color is thought to have evolved to balance sufficient photochemical synthesis of vitamin D versus the need to protect not only DNA but also folate from degradation by ultraviolet light (UV). Although the risk of DNA damage and subsequent skin cancer is related to light skin color, the effect of UV on skin folate of any species is unknown. Here we show that UVA irradiation at 13 mW/cm2 for a total exposure of 187 J/cm2 (similar to a maximal daily equatorial dose) induced a significant loss of total folate in epidermis of ex vivo white skin. No loss was observed in black skin samples, or in the dermis of either color. Interestingly, while the concentration of 5 methyltetrahydrofolate (5-MTHF) fell in white epidermis, a concomitant increase of tetrahydrofolic acid was found, though not enough to maintain the total pool. These results demonstrate that UVA indeed not only decreases folate in skin, but also rearranges the pool components. This could be due in part to the reported increase of NADPH oxidase activity upon UV irradiation, which in turn depletes the NADPH needed for 5-MTHF biosynthesis by 5,10-methylenetetrahydrofolate reductase. The increased tetrahydrofolic acid might further support production of the nucleotide bases needed for DNA repair. However, total folate was lost at a rate that could, with strong or continuous enough exposure to ultraviolet radiation, substantially deplete light colored skin locally, and also put pressure on total body stores for individuals with low intake of folate.Keywords: depletion, folate, human skin, ultraviolet
Procedia PDF Downloads 38625090 Expression of PGC-1 Alpha Isoforms in Response to Eccentric and Concentric Resistance Training in Healthy Subjects
Authors: Pejman Taghibeikzadehbadr
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Background and Aim: PGC-1 alpha is a transcription factor that was first detected in brown adipose tissue. Since its discovery, PGC-1 alpha has been known to facilitate beneficial adaptations such as mitochondrial biogenesis and increased angiogenesis in skeletal muscle following aerobic exercise. Therefore, the purpose of this study was to investigate the expression of PGC-1 alpha isoforms in response to eccentric and concentric resistance training in healthy subjects. Materials and Methods: Ten healthy men were randomly divided into two groups (5 patients in eccentric group - 5 in eccentric group). Isokinetic contraction protocols included eccentric and concentric knee extension with maximum power and angular velocity of 60 degrees per second. The torques assigned to each subject were considered to match the workload in both protocols, with a rotational speed of 60 degrees per second. Contractions consisted of a maximum of 12 sets of 10 repetitions for the right leg, a rest time of 30 seconds between each set. At the beginning and end of the study, biopsy of the lateral broad muscle tissue was performed. Biopsies were performed in both distal and proximal directions of the lateral flank. To evaluate the expression of PGC1α-1 and PGC1α-4 genes, tissue analysis was performed in each group using Real-Time PCR technique. Data were analyzed using dependent t-test and covariance test. SPSS21 software and Exell 2013 software were used for data analysis. Results: The results showed that intra-group changes of PGC1α-1 after one session of activity were not significant in eccentric (p = 0.168) and concentric (p = 0.959) groups. Also, inter-group changes showed no difference between the two groups (p = 0.681). Also, intra-group changes of PGC1α-4 after one session of activity were significant in an eccentric group (p = 0.012) and concentric group (p = 0.02). Also, inter-group changes showed no difference between the two groups (p = 0.362). Conclusion: It seems that the lack of significant changes in the desired variables due to the lack of exercise pressure is sufficient to stimulate the increase of PGC1α-1 and PGC1α-4. And with regard to reviewing the answer, it seems that the compatibility debate has different results that need to be addressed.Keywords: eccentric contraction, concentric contraction, PGC1α-1 و PGC1α-4, human subject
Procedia PDF Downloads 7825089 SiC Merged PiN and Schottky (MPS) Power Diodes Electrothermal Modeling in SPICE
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This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model
Procedia PDF Downloads 40725088 The Effect of Sago Supplementation on Physiology and Performance in a Hot and Humid Environment
Authors: Che Jusoh, Mohd Rahimi, Toby Mundel
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This study was designed to investigate the physiological and performance effects of a local Malaysian native starch (Metroxylin sago) on cycling in a hot (30°C) and humid (78% RH) environment. Eight male, non-heat acclimated, well-trained club cyclists (VO2max 65 ± 10 ml kg-1 min-1, peak aerobic power 397 ± 71 W) completed one familiarization and three experimental trials in our laboratory simulating cycling in environmental conditions of heat and humidity. Each trial consisted of 45 minutes at a fixed workload (55% VO2max) followed by a 15 minute time-trial (~75% VO2max). Sago in porridge form was consumed 1h before exercise (Pre), in gel form during exercise (Dur) and compared to a control trial (Con), using a random, cross-over design. Plasma glucose concentration did not differ between trials (P = 0.06) with an increase from 4.1 ± 0.6 to 6.1 ± 1.6 mmol-1 (Con), 4.8 ± 1.7 to 5.7 ± 0.4 mmol-1 (Pre) and 4.7 ± 0.8 to 6.9 ± 1.4 mmol-1 (Dur) from start to end of exercise. Plasma lactate increased (P = 0.02) from 1.6 ± 0.3 to 7.6 ± 2.2 mmol-1 (Con), 1.7 ± 0.5 to 7.3 ± 2.9 mmol-1 (Pre) and 1.6 ± 0.2 to 7.3 ± 1.8 mmol-1 (Dur) with no effect of trial (P = 0.74). No differences were found between trials for RER (P = 0.328) with values of 0.93 ± 0.05 (Con), 0.94 ± 0.04 (Pre) and 0.92 ± 0.04 (Dur). There were no differences between trials in rectal (P = 0.64) and skin (P = 0.56) temperatures; values reaching 39.1 ± 0.5°C (Con), 38.9 ± 0.4°C (Pre) and 39.1 ± 0.4°C (Dur) for rectal and 32.7 ± 1.2°C (Con), 32.8 ± 1.4°C (Pre) and 32.8 ± 1.8°C (Dur) for skin temperature, respectively. Heart rate (P = 0.07) also did not differ between trials but reached maximal values by the end of time-trial for all trials. Performance was unaffected by trial (P = 0.98) with the average work completed in 15 minutes being 221 ± 33 kJ (Con), 222 ± 31 kJ (Pre) and 219 ± 32 kJ (Dur), respectively. Therefore, the results of this investigation do not support consumption of sago, either before or during exercise, in altering the thermoregulatory, metabolic or performance responses in a hot and humid environment.Keywords: hot and humid, physiology, time trial performance, thermoregulatory
Procedia PDF Downloads 40925087 Data Mining in Medicine Domain Using Decision Trees and Vector Support Machine
Authors: Djamila Benhaddouche, Abdelkader Benyettou
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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction
Procedia PDF Downloads 55925086 Analysis of Different Classification Techniques Using WEKA for Diabetic Disease
Authors: Usama Ahmed
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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.Keywords: data mining, classification, diabetes, WEKA
Procedia PDF Downloads 14725085 Exploring the Issue of Occult Hypoperfusion in the Pre-Hospital Setting
Authors: A. Fordham, A. Hudson
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Background: Studies have suggested 16-25% of normotensive trauma patients with no clinical signs of shock have abnormal lactate and BD readings evidencing shock; a phenomenon known as occult hypoperfusion (OH). In light of the scarce quantity of evidence currently documenting OH, this study aimed to identify the prevalence of OH in the pre-hospital setting and explore ways to improve its identification and management. Methods: A quantitative retrospective data analysis was carried out on 75 sets of patient records for trauma patients treated by Kent Surrey Sussex Air Ambulance Trust between November 2013 and October 2014. The KSS HEMS notes and subsequent ED notes were collected. Trends between patients’ SBP on the scene, whether or not they received PRBCs on the scene as well as lactate and BD readings in the ED were assessed. Patients’ KSS HEMS notes written by the HEMS crew were also reviewed and recorded. Results: -Suspected OH was identified in 7% of the patients who did not receive PRBCs in the pre-hospital phase. -SBP heavily influences the physicians’ decision of whether or not to transfuse PRBCs in the pre-hospital phase. Preliminary conclusions: OH is an under-studied and underestimated phenomenon. We suggest a prospective trial is carried out to evaluate whether detecting trauma patients’ tissue perfusion status in the pre-hospital phase using portable devices capable of measuring serum BD and/or lactate could aid more accurate detection and management of all haemorrhaging trauma patients, including patients with OH.Keywords: occult hypoperfusion, PRBC transfusion, point of care testing, pre-hospital emergency medicine, trauma
Procedia PDF Downloads 35925084 Comprehensive Study of Data Science
Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly
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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.Keywords: data science, machine learning, data analytics, artificial intelligence
Procedia PDF Downloads 8225083 Analysis of Decentralized on Demand Cross Layer in Cognitive Radio Ad Hoc Network
Authors: A. Sri Janani, K. Immanuel Arokia James
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Cognitive radio ad hoc networks different unlicensed users may acquire different available channel sets. This non-uniform spectrum availability imposes special design challenges for broadcasting in CR ad hoc networks. Cognitive radio automatically detects available channels in wireless spectrum. This is a form of dynamic spectrum management. Cross-layer optimization is proposed, using this can allow far away secondary users can also involve into channel work. So it can increase the throughput and it will overcome the collision and time delay.Keywords: cognitive radio, cross layer optimization, CR mesh network, heterogeneous spectrum, mesh topology, random routing optimization technique
Procedia PDF Downloads 35925082 Machine Learning and Deep Learning Approach for People Recognition and Tracking in Crowd for Safety Monitoring
Authors: A. Degale Desta, Cheng Jian
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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning
Procedia PDF Downloads 16125081 Reversibility of Photosynthetic Activity and Pigment-protein Complexes Expression During Seed Development of Soybean and Black Soybean
Authors: Tzan-Chain Lee
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Seeds are non-leaves green tissues. Photosynthesis begins with light absorption by chlorophyll and then the energy transfer between two pigment-protein complexes (PPC). Most studies of photosynthesis and PPC expression were focused on leaves; however, during seeds’ development were rare. Developed seeds from beginning pod (stage R3) to dried seed (stage R8), and the dried seed after sowing for 1-4 day, were analyzed for their chlorophyll contents. Thornber and MARS gel systems analysis compositions of PPC. Chlorophyll fluorescence was used to detect maximal photosynthetic efficiency (Fv/Fm). During soybean and black soybean seeds development (stages R3-R6), Fv/Fm up to 0.8, and then down-regulated after full seed (stage R7). In dried seed (stage R8), the two plant seeds lost photosynthetic activity (Fv/Fm=0), but chlorophyll degradation only occurred in soybean after full seed. After seeds sowing for 4 days, chlorophyll drastically increased in soybean seeds, and Fv/Fm recovered to 0.8 in the two seeds. In PPC, the two soybean seeds contained all PPC during seeds development (stages R3-R6), including CPI, CPII, A1, AB1, AB2, and AB3. However, many proteins A1, AB1, AB2, and CPI were totally missing in the two dried seeds (stage R8). The deficiency of these proteins in dried seeds might be caused by the incomplete photosynthetic activity. After seeds germination and seedling exposed to light for 4 days, all PPC were recovered, suggesting that completed PPC took place in the two soybean seeds. This study showed the reversibility of photosynthetic activity and pigment-protein complexes during soybean and black soybean seeds development.Keywords: light-harvesting complex, pigment–protein complexes, soybean cotyledon, grana development
Procedia PDF Downloads 14825080 Biofilm Text Classifiers Developed Using Natural Language Processing and Unsupervised Learning Approach
Authors: Kanika Gupta, Ashok Kumar
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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database
Procedia PDF Downloads 17025079 Effect of Kinesio Taping on Anaerobic Power and Maximum Oxygen Consumption after Eccentric Exercise
Authors: Disaphon Boobpachat, Nuttaset Manimmanakorn, Apiwan Manimmanakorn, Worrawut Thuwakum, Michael J. Hamlin
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Objectives: To evaluate effect of kinesio tape compared to placebo tape and static stretching on recovery of anaerobic power and maximal oxygen uptake (Vo₂max) after intensive exercise. Methods: Thirty nine untrained healthy volunteers were randomized to 3 groups for each intervention: elastic tape, placebo tape and stretching. The participants performed intensive exercise on the dominant quadriceps by using isokinetic dynamometry machine. The recovery process was evaluated by creatine kinase (CK), pressure pain threshold (PPT), muscle soreness scale (MSS), maximum voluntary contraction (MVC), jump height, anaerobic power and Vo₂max at baseline, immediately post-exercise and post-exercise day 1, 2, 3 and 7. Results: The kinesio tape, placebo tape and stretching groups had significant changes of PPT, MVC, jump height at immediately post-exercise compared to baseline (p < 0.05), and changes of MSS, CK, anaerobic power and Vo₂max at day 1 post-exercise compared to baseline (p < 0.05). There was no significant difference of those outcomes among three groups. Additionally, all experimental groups had little effects on anaerobic power and Vo₂max compared to baseline and compared among three groups (p > 0.05). Conclusion: Kinesio tape and stretching did not improve recovery of anaerobic power and Vo₂max after eccentric exercise compared to placebo tape.Keywords: stretching, eccentric exercise, Wingate test, muscle soreness
Procedia PDF Downloads 13025078 Pregnancy and Birth Outcomes of Single versus Multiple Embryo Transfer in Gestational Surrogacy Arrangements: A Systematic Review
Authors: Jutharat Attawet, Alex Y. Wang, Cindy M. Farquhar, Elizabeth A. Sullivan
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Background: Adverse maternal and perinatal outcomes of multiple pregnancies resulting from multiple embryo transfers (ET) has become significant concerns. This is particularly relevant for gestational carriers since they usually do not have infertility issues. Single embryo transfer (SET) therefore has been encouraged to assist reproductive technology (ART) practice in order to reduce multiple pregnancies. Objectives: This systematic review aims to investigate the pregnancy and birth outcomes of SET and multiple ET in surrogacy arrangements. Search methods: This study is a systematic review. Electronic databases were searched from CINAHL, Medline, Embase, Scopus and ProQuest for studies from 1980 to 2017. Cross-references and national ART reports were also manual searchings. Articles without restriction of English language and study types were accessed. Carrier cycles involving in SET and multiple ET were identified in database searching. The main outcome measures including clinical pregnancy, live delivery and multiple deliveries per gestational carrier cycle were compared between SET and multiple ET. Mantel-Haenzel risk ratios (RRs) with 95% confidence intervals (CIs), using the numbers of outcome events in SET and multiple ET of each study were calculated suing RevMan5.3. Outcomes: The search returned 97 articles of which 5 met the inclusion criteria. Approximately 50% of carrier cycles were transferred a single embryo and 50% were transferred more than one embryo. The clinical pregnancy rate (CPR) was 39% for SET and 53% for multiple ET, which was not significantly different with RR = 0.83 (95% CI: 0.67-1.03). The live delivery rate was 33% for SET and 57% for multiple ET which was not significantly different with RR = 0.78 (95% CI: 0.61-1.00). The multiple delivery rate per carrier was greater risks in the multiple ET carrier cycles (RR =0.4, 95% CI: 0.01-0.26). There were 104 sets of twins (including one set of twins selectively reduced from triplets to twins) and 1 set of triples in the multiple ET carrier cycle. In the SET carrier cycles, there were 2 sets of twins. Significance of the study: SET should be advocated among surrogate carriers to prevent multiple pregnancies and subsequent adverse outcomes for both carrier and baby. Surrogacy practice should be reviewed and surrogate carriers should be fully informed of the risk of adverse maternal and birth outcome of multiple pregnancies due to multiple embryo transfers.Keywords: assisted reproduction, birth outcomes, carrier, gestational surrogacy, multiple embryo transfer, multiple pregnancy, pregnancy outcomes, single embryo transfer, surrogate mother, systematic review
Procedia PDF Downloads 40425077 Hybrid Approach for Software Defect Prediction Using Machine Learning with Optimization Technique
Authors: C. Manjula, Lilly Florence
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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.Keywords: decision tree, genetic algorithm, machine learning, software defect prediction
Procedia PDF Downloads 32925076 Biogas Production from Kitchen Waste for a Household Sustainability
Authors: Vuiswa Lucia Sethunya, Tonderayi Matambo, Diane Hildebrandt
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South African’s informal settlements produce tonnes of kitchen waste (KW) per year which is dumped into the landfill. These landfill sites are normally located in close proximity to the household of the poor communities; this is a problem in which the young children from those communities end up playing in these landfill sites which may result in some health hazards because of methane, carbon dioxide and sulphur gases which are produced. To reduce this large amount of organic materials being deposited into landfills and to provide a cleaner place for those within the community especially the children, an energy conversion process such as anaerobic digestion of the organic waste to produce biogas was implemented. In this study, the digestion of various kitchen waste was investigated in order to understand and develop a system that is suitable for household use to produce biogas for cooking. Three sets of waste of different nutritional compositions were digested as per acquired in the waste streams of a household at mesophilic temperature (35ᵒC). These sets of KW were co-digested with cow dung (CW) at different ratios to observe the microbial behaviour and the system’s stability in a laboratory scale system. The gas chromatography-flame ionization detector analyses have been performed to identify and quantify the presence of organic compounds in the liquid samples from co-digested and mono-digested food waste. Acetic acid, propionic acid, butyric acid and valeric acid are the fatty acids which were studied. Acetic acid (1.98 g/L), propionic acid (0.75 g/L) and butyric acid (2.16g/L) were the most prevailing fatty acids. The results obtained from organic acids analysis suggest that the KW can be an innovative substituent to animal manure for biogas production. The faster degradation period in which the microbes break down the organic compound to produce the fatty acids during the anaerobic process of KW also makes it a better feedstock during high energy demand periods. The C/N ratio analysis showed that from the three waste streams the first stream containing vegetables (55%), fruits (16%), meat (25%) and pap (4%) yielded more methane-based biogas of 317mL/g of volatile solids (VS) at C/N of 21.06. Generally, this shows that a household will require a heterogeneous composition of nutrient-based waste to be fed into the digester to acquire the best biogas yield to sustain a households cooking needs.Keywords: anaerobic digestion, biogas, kitchen waste, household
Procedia PDF Downloads 19925075 Performance Evaluation of Adsorption Refrigerating Systems
Authors: Nadia Allouache, Omar Rahli
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Many promising technologies have been developed to harness the sun's energy. These technologies help in economizing energy and environmental protection. The solar refrigerating systems are one of these important technologies. In addition to environmental benefits and energy saving, adsorption refrigerating systems have many advantages such as lack of moving parts, simplicity of construction and low operating costs. The work aimed to establish the main factors that affect the performances of an adsorption refrigerating system using different geometries of adsorbers and different adsorbent-adsorbate pairs. The numerical modeling of the heat and mass transfer in the system, using various working pairs, such as: activated carbon-ammonia, calcium chlorid-ammonia, activated carbon fiber- methanol and activated carbon AC35-methanol, show that the adsorber design can influence the system performances; The thermal performances of system are better in the annular configuration case. An optimal value of generating temperature is observed in annular adsorber case for which the thermal performance of the cooling system is maximal. While in the plate adsorber, above a certain value of generating temperature, the performance of the system remains almost constant. The environmental conditions such as solar radiation and pressure have a great influence in the system efficiency, and the choice of the working pair depends on the environmental conditions and the geometry of the adsorber.Keywords: adsorber geometry, numerical modeling, optimal environmental conditions, working pairs.
Procedia PDF Downloads 79