Search results for: data storage

Authors: Sandip Mitra

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Studies on Governance and Accountability has often stressed the need to release Data in public domain to increase transparency ,which otherwise act as an evidence of performance. However, inefficient handling, lack of capacity and the dynamics of transfers (especially fund transfers) are important issues which need appropriate attention. E-Governance alone can not serve as a measure of transparency as long as a comprehensive planning is instituted. Studies on Governance and public exposure has often triggered public opinion in favour or against any government. The root of the problem (especially in local governments) lies in the management of the governance. The participation of the people in the local government functioning, the networks within and outside the locality, synergy with various layers of Government are crucial in understanding the activities of any government. Unfortunately, data on such issues are not released in the public domain .If they are at all released , the extraction of information is often hindered for complicated designs. A Study has been undertaken with a few local Governments in India. The data has been analysed to substantiate the views.

Keywords: accountability, e-governance, transparency, local government

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Authors: A. Ikusika, O. I. Poppola

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This study was carried out to delineate possible structures that may favour the accumulation of tantalite, a magnetic mineral. A ground based technique was employed using proton precision magnetometer G-856 AX. A total of ten geophysical traverses were established in the study area. The acquired magnetic field data were corrected for drift. The trend analysis was adopted to remove the regional gradient from the observed data and the resulting results were presented as profiles. Quantitative interpretation only was adopted to obtain the depth to basement using Peter half slope method. From the geological setting of the area and the information obtained from the magnetic survey, a conclusion can be made that the study area is underlain by a rock unit of accumulated minerals. It is therefore suspected that the overburden is relatively thin within the study area and the metallic minerals are in disseminated quantity and at a shallow depth.

Keywords: basement, drift, magnetic field data, tantalite, traverses

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Authors: Janne Engblom, Elias Oikarinen

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The understanding of housing price dynamics is of importance to a great number of agents: to portfolio investors, banks, real estate brokers and construction companies as well as to policy makers and households. A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models is dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Common Correlated Effects estimator (CCE) of dynamic panel data which also accounts for cross-sectional dependence which is caused by common structures of the economy. In presence of cross-sectional dependence standard OLS gives biased estimates. In this study, U.S housing price dynamics were examined empirically using the dynamic CCE estimator with first-difference of housing price as the dependent and first-differences of per capita income, interest rate, housing stock and lagged price together with deviation of housing prices from their long-run equilibrium level as independents. These deviations were also estimated from the data. The aim of the analysis was to provide estimates with comparisons of estimates between 1980-1999 and 2000-2012. Based on data of 50 U.S cities over 1980-2012 differences of short-run housing price dynamics estimates were mostly significant when two time periods were compared. Significance tests of differences were provided by the model containing interaction terms of independents and time dummy variable. Residual analysis showed very low cross-sectional correlation of the model residuals compared with the standard OLS approach. This means a good fit of CCE estimator model. Estimates of the dynamic panel data model were in line with the theory of housing price dynamics. Results also suggest that dynamics of a housing market is evolving over time.

Keywords: dynamic model, panel data, cross-sectional dependence, interaction model

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Authors: Felix U. Asoiro, Kingsley O. Anyichie, Meshack I. Simeon, Chinenye E. Azuka

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The work was aimed at studying the effects of microwave drying (450 W) and hot air oven drying on the drying kinetics and physico-functional properties of yams and cocoyams species. The yams and cocoyams were cut into chips of thicknesses of 3mm, 5mm, 7mm, 9mm, and 11mm. The drying characteristics of yam and cocoyam chips were investigated under microwave drying and hot air oven temperatures (50oC – 90oC). Drying methods, temperature, and thickness had a significant effect on the drying characteristics and physico-functional properties of yam and cocoyam. The result of the experiment showed that an increase in the temperature increased the drying time. The result also showed that the microwave drying method took lesser time to dry the samples than the hot air oven drying method. The iodine affinity of starch for yam was higher than that of cocoyam for the microwaved dried samples over those of hot air oven-dried samples. The results of the analysis would be useful in modeling the drying behavior of yams and cocoyams under different drying methods. It could also be useful in the improvement of shelf life for yams and cocoyams as well as designs of efficient systems for drying, handling, storage, packaging, processing, and transportation of yams and cocoyams.

Keywords: coco yam, drying, microwave, modeling, energy consumption, iodine affinity, drying ate

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Authors: M. Y. Bakeir

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Rough set theory is a recent approach for reasoning about data. It has achieved a large amount of applications in various real-life fields. The main idea of rough sets corresponds to the lower and upper set approximations. These two approximations are exactly the interior and the closure of the set with respect to a certain topology on a collection U of imprecise data acquired from any real-life field. The base of the topology is formed by equivalence classes of an equivalence relation E defined on U using the available information about data. The theory of generalized topology was studied by Cs´asz´ar. It is well known that generalized topology in the sense of Cs´asz´ar is a generalization of the topology on a set. On the other hand, many important collections of sets related with the topology on a set form a generalized topology. The notion of Nano topology was introduced by Lellis Thivagar, which was defined in terms of approximations and boundary region of a subset of an universe using an equivalence relation on it. The purpose of this paper is to introduce a new generalized topology in terms of rough set called nano generalized topology

Keywords: rough sets, topological space, generalized topology, nano topology

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Authors: C. Hamamura, V. Gialluca

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Much of the Eclectricity Distributors has about 70% of its electricity interruptions arising from cause "trees", alone or associated with wind and rain and with or without falling branch and / or trees. This contributes inexorably and significantly to outages, resulting in high costs as compensation in addition to the operation and maintenance costs. On the other hand, there is little data structure and solutions to better organize the trees pruning plan effectively, minimizing costs and environmentally friendly. This work describes the development of an algorithm to provide data of trees associated to power grid. The method is accomplished on several steps using satellite imagery and geographically vectorized grid. A sliding window like approach is performed to seek the area around the grid. The proposed method counted 764 trees on a patch of the grid, which was very close to the 738 trees counted manually. The trees data was used as a part of a larger project that implements a system to optimize tree pruning plan.

Keywords: image pattern recognition, trees pruning, trees recognition, neural network

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Authors: F. Taouche-Kheloui, O. Fedaoui-Akmoussi, K. Ait tahar, Li. Alex

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Currently, the reduction of energy consumption, through the use of abundant and recyclable natural materials, for better thermal insulation represents an important area of research. To this end, the use of bio-sourced materials has been identified as one of the green sectors with a very high economic development potential for the future. Because of its role in reducing the consumption of fossil-based raw materials, it contributes significantly to the storage of atmospheric carbon, limits greenhouse gas emissions and creates new economic opportunities. This study constitutes a contribution to the elaboration and the experimental characterization of the thermal behavior of a sawdust-reduced mortar matrix. We have taken into account the influence of the size of the grain fibers of sawdust, hence the use of three different ranges and also different percentage in the different confections. The intended practical application consists of producing a light weight compound at a lower cost to ensure a better thermal and acoustic behavior compared to that existing in the field, in addition to the desired resistances. Improving energy performance, while reducing greenhouse gas emissions from the building sector, is amongst the objectives to be achieved. The results are very encouraging and highlight the value of the proposed design of organic-source mortar panels which have specific mechanical properties acceptable for their use, low densities, lower cost of manufacture and labor, and above all a positive impact on the environment.

Keywords: mortar, sawdust waste, thermal, experimental, analysis

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Authors: C. Romero, R. Ortega, P. Sánchez-Camacho, P. Aguilar, V. Segur, J. Ruiz, G. Gutiérrez

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Introduction: Breast cancer is a leading cause of death in CLM. (2.8% of all deaths in women and 13,8% of deaths from tumors in womens). It is the most tumor incidence in CLM region with 26.1% from all tumours, except nonmelanoma skin (Cancer Incidence in Five Continents, Volume X, IARC). Cancer registries are a good information source to estimate cancer incidence, however the data are usually available with a lag which makes difficult their use for health managers. By contrast, mortality and survival statistics have less delay. In order to serve for resource planning and responding to this problem, a method is presented to estimate the incidence of mortality and survival data. Objectives: To estimate the incidence of breast cancer by age group in CLM in the period 1991-2013. Comparing the data obtained from the model with current incidence data. Sources: Annual number of women by single ages (National Statistics Institute). Annual number of deaths by all causes and breast cancer. (Mortality Registry CLM). The Breast cancer relative survival probability. (EUROCARE, Spanish registries data). Methods: A Weibull Parametric survival model from EUROCARE data is obtained. From the model of survival, the population and population data, Mortality and Incidence Analysis MODel (MIAMOD) regression model is obtained to estimate the incidence of cancer by age (1991-2013). Results: The resulting model is: Ix,t = Logit [const + age1*x + age2*x2 + coh1*(t – x) + coh2*(t-x)2] Where: Ix,t is the incidence at age x in the period (year) t; the value of the parameter estimates is: const (constant term in the model) = -7.03; age1 = 3.31; age2 = -1.10; coh1 = 0.61 and coh2 = -0.12. It is estimated that in 1991 were diagnosed in CLM 662 cases of breast cancer (81.51 per 100,000 women). An estimated 1,152 cases (112.41 per 100,000 women) were diagnosed in 2013, representing an increase of 40.7% in gross incidence rate (1.9% per year). The annual average increases in incidence by age were: 2.07% in women aged 25-44 years, 1.01% (45-54 years), 1.11% (55-64 years) and 1.24% (65-74 years). Cancer registries in Spain that send data to IARC declared 2003-2007 the average annual incidence rate of 98.6 cases per 100,000 women. Our model can obtain an incidence of 100.7 cases per 100,000 women. Conclusions: A sharp and steady increase in the incidence of breast cancer in the period 1991-2013 is observed. The increase was seen in all age groups considered, although it seems more pronounced in young women (25-44 years). With this method you can get a good estimation of the incidence.

Keywords: breast cancer, incidence, cancer registries, castilla-la mancha

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Authors: They Shao Peng

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Machine vision system for inspection is an automated technology that is normally utilized to analyze items on the production line for quality control purposes, it also can be known as an automated visual inspection (AVI) system. By applying automated visual inspection, the existence of items, defects, contaminants, flaws, and other irregularities in manufactured products can be easily detected in a short time and accurately. However, AVI systems are still inflexible and expensive due to their uniqueness for a specific task and consuming a lot of set-up time and space. With the rapid development of mobile devices, smartphones can be an alternative device for the visual system to solve the existing problems of AVI. Since the smartphone-based AVI system is still at a nascent stage, this led to the motivation to investigate the smartphone-based AVI system. This study is aimed to provide a low-cost AVI system with high efficiency and flexibility. In this project, the object detection models, which are You Only Look Once (YOLO) model and Single Shot MultiBox Detector (SSD) model, are trained, evaluated, and integrated with the smartphone and webcam devices. The performance of the smartphone-based AVI is compared with the webcam-based AVI according to the precision and inference time in this study. Additionally, a mobile application is developed which allows users to implement real-time object detection and object detection from image storage.

Keywords: automated visual inspection, deep learning, machine vision, mobile application

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Authors: Islam Elsayed Hussein

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The aim of this paper is to discover the impact of students’ attitude towards social media and the skills required to adopt social media as a university e-learning (2.0) platform. In addition, it measures the effect of social media adoption on interactive learning effectiveness. The population of this study was students at Faculty of tourism and Hotels, Fayoum University. A questionnaire was used as a research instrument to collect data from respondents, which had been selected randomly. Data had been analyzed using quantitative data analysis method. Findings showed that the students have a positive attitude towards adopting social networking in the learning process and they have also good skills for effective use of social networking tools. In addition, adopting social media is effectively affecting the interactive learning environment.

Keywords: attitude, skills, e-learning 2.0, interactive learning, Egypt

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Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Sathapath Kilaso

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Nowadays, Today, wireless sensor networks are an important technology that works with Internet of Things. It is receiving various data from many sensor. Then sent to processing or storing. By wireless network or through the Internet. The devices around us are intelligent, can receiving/transmitting and processing data and communicating through the system. There are many applications of wireless sensor networks, such as smart city, smart farm, environmental management, weather. This article will explore the use of wireless sensor networks in Thailand and collect data from Thai Thesis database in 2012-2017. How to Implementing Wireless Sensor Network Technology. Advantage from this study To know the usage wireless technology in many fields. This will be beneficial for future research. In this study was found the most widely used wireless sensor network in agriculture field. Especially for smart farms. And the second is the adoption of the environment. Such as weather stations and water inspection.

Keywords: wireless sensor network, smart city, survey, Adhoc Network

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Authors: Jaturong Som-ard

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The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings

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Authors: A. Bayaga

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This research provides a technical account of estimating Transition Probability using Time-homogeneous Markov Jump Process applying by South African HIV/AIDS data from the Statistics South Africa. It employs Maximum Likelihood Estimator (MLE) model to explore the possible influence of Transition Probability of mortality cases in which case the data was based on actual Statistics South Africa. This was conducted via an integrated demographic and epidemiological model of South African HIV/AIDS epidemic. The model was fitted to age-specific HIV prevalence data and recorded death data using MLE model. Though the previous model results suggest HIV in South Africa has declined and AIDS mortality rates have declined since 2002 – 2013, in contrast, our results differ evidently with the generally accepted HIV models (Spectrum/EPP and ASSA2008) in South Africa. However, there is the need for supplementary research to be conducted to enhance the demographic parameters in the model and as well apply it to each of the nine (9) provinces of South Africa.

Keywords: AIDS mortality rates, epidemiological model, time-homogeneous markov jump process, transition probability, statistics South Africa

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Authors: Ilham Ihoume, Rachid Tadili, Nora Arbaoui

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This study examines the effects of a solar-based heating system, in a north-‎south oriented agricultural greenhouse on the development of strawberry ‎plants during winter. This system relies on the circulation of water as a heat ‎transfer fluid in a closed circuit installed on the greenhouse roof to store heat ‎during the day and release it inside at night. A comparative experimental ‎study was conducted in two greenhouses, one experimental with the solar ‎heating system and the other for control without any heating system. Both ‎greenhouses are located on the terrace of the Solar Energy and Environment ‎Laboratory of the Mohammed V University in Rabat, Morocco. The devel-‎oped heating system consists of a copper coil inserted in double glazing and ‎placed on the roof of the greenhouse, a water pump circulator, a battery, and ‎a photovoltaic solar panel to power the electrical components. This inexpen-‎sive and environmentally friendly system allows the greenhouse to be heated ‎during the winter and improves its microclimate system. This improvement ‎resulted in an increase in the air temperature inside the experimental green-‎house by 6 °C and 8 °C, and a reduction in its relative humidity by 23% and ‎‎35% compared to the control greenhouse and the ambient air, respectively, ‎throughout the winter. For the agronomic performance, it was observed that ‎the production was 17 days earlier than in the control greenhouse.‎

Keywords: sustainability, solar energy, thermal energy storage.‎, greenhouse heating

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Authors: Marwa M. Ibrahim

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The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) off-grid system supplying a small remote gathering of four families using the HOMER software package. The second objective is to study the effect of wind energy system on the cost of generated electricity considering the cost of reducing CO₂ emissions as external benefit of wind turbines, no pollutant emission through the operational phase. The system consists of a small wind turbine, battery storage, and diesel generator. The electrical energy is to cater to the basic needs for which the daily load pattern is estimated at 8 kW peak. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for the selected site in Egypt. Using HOMER software, the simulation results shows that W/D/B systems are economical for the assumed community site as the price of generated electricity is about 0.285 $/kWh, without taking external benefits into considerations and 0.221 if CO₂ emissions taken into consideration W/D/B systems are more economical than alone diesel system as the COE is 0.432 $/kWh for diesel alone.

Keywords: renewable energy, hybrid energy system, on-off grid system, simulation, optimization and environmental impacts

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Authors: Xiaofang Wei

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Harmful Algal Blooms are a recurrent disturbing occurrence in Lake Erie that has caused significant negative impacts on water quality and aquatic ecosystem around Great Lakes areas in the United States. Targeting the recent HAB events in western Lake Erie, this paper utilizes satellite imagery and hydrological modeling to monitor HAB cyanobacteria blooms and analyze the impacts of agricultural activities from Maumee watershed, the biggest watershed of Lake Erie and agriculture dominant.SWAT (Soil & Water Assessment Tool) Model for Maumee watershed was established with DEM, land use data, crop data layer, soil data, and weather data, and calibrated with Maumee River gauge stations data for streamflow and nutrients. Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) was applied to remove atmospheric attenuation and cyanobacteria Indices were calculated from Landsat OLI imagery to study the intensity of HAB events in the years 2015, 2017, and 2019. The agricultural practice and nutrients management within the Maumee watershed was studied and correlated with HAB cyanobacteria indices to study the relationship between HAB intensity and nutrient loadings. This study demonstrates that hydrological models and satellite imagery are effective tools in HAB monitoring and modeling in rivers and lakes.

Keywords: harmful algal bloom, landsat OLI imagery, SWAT, HAB cyanobacteria

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Authors: Chante J. De Klerk

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The potential of music to facilitate superior performance during high to elite level gymnastics conditioning instigated this research. A team of seven gymnasts completed a fixed conditioning programme eight times, alternating the two variable conditions. Four sessions of each condition were conducted: without music (session 1), with music (session 2), without music (3), with music (4), without music (5), and so forth. Quantitative data were collected in both conditions through physiological monitoring of the gymnasts, and administration of the Situational Motivation Scale (SIMS). Statistical analysis of the physiological data made it possible to quantify the presence as well as the magnitude of the musical intervention’s impact on various aspects of the gymnasts' physiological functioning during conditioning. The SIMS questionnaire results were used to evaluate if their motivation towards conditioning was altered by the intervention. Thematic analysis of qualitative data collected through semi-structured interviews revealed themes reflecting the gymnasts’ sentiments towards the data collection process. Gymnast-specific descriptions and experiences of the team as a whole were integrated with the quantitative data to facilitate greater dimension in establishing the impact of the intervention. The results showed positive physiological, motivational, and emotional effects. In the presence of music, superior sympathetic nervous activation, and energy efficiency, with more economic breathing, dominated the physiological data. Fatigue and arousal levels (emotional and physiological) were also conducive to improved conditioning outcomes compared to conventional conditioning (without music). Greater levels of positive affect and motivation emerged in analysis of both the SIMS and interview data sets. Overall, the intervention was found to promote psychophysiological coherence during the physical activity. In conclusion, a strategically constructed musical intervention, designed to accompany a gymnastics conditioning session for high to elite level gymnasts, has ergogenic potential.

Keywords: arousal, fatigue, gymnastics conditioning, motivation, musical intervention, psychophysiological coherence

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Authors: Jeffrey Cacho, Sherwin Reyes

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The research targeted enhancing energy utilization and reducing waste in roasting processes, particularly in Camarines Norte, where Bounty Agro Ventures Incorporated dominates through brands such as Chooks-to-Go, Uling Roaster, and Reyal. Competitors like Andok’s and Baliwag Lechon Manok also share the market. A staggering 90% of these businesses use traditional glass-type roasting furnaces fueled by wood charcoal, leading to significant energy loss and inefficiency due to suboptimal heat conservation. Only a mere 10% employ electric ovens. Many available furnaces, typically constructed from industrial materials through welding and other metal joining techniques, are not energy-efficient. Cost-prohibitive commercial options compel some micro-enterprises to fabricate their furnaces. The study proposed developing an eco-friendly, cost-effective roasting furnace with excellent heat retention. The distinct design aimed to reduce cooks' heat exposure and overall fuel consumption. The furnace features an angle bar frame, a combustion chute for fuel burning, a heat-retaining clay-walled chamber, and a top cover, all contributing to improved energy savings and user safety.

Keywords: biomass roasting furnace, heat storage, combustion chute, start-up roasting business

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Authors: Huang Bai-Cheng

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When deploying the Oriented Fast and Rotated Binary Robust Independent Elementary Feature (BRIEF) (ORB) extraction algorithm on field-programmable gate arrays (FPGA), the access of global storage for 31×31 pixel patches of the features has become the bottleneck of the system efficiency. Therefore, a feature zone strategy has been proposed. Zones are searched as features are detected. Pixels around the feature zones are extracted from global memory and distributed into patches corresponding to feature coordinates. The proposed FPGA structure is targeted on a Xilinx FPGA development board of Zynq UltraScale+ series, and multiple datasets are tested. Compared with the streaming pixel patch extraction method, the proposed architecture obtains at least two times acceleration consuming extra 3.82% Flip-Flops (FFs) and 7.78% Look-Up Tables (LUTs). Compared with the non-streaming one, the proposed architecture saves 22.3% LUT and 1.82% FF, causing a latency of only 0.2ms and a drop in frame rate for 1. Compared with the related works, the proposed strategy and hardware architecture have the superiority of keeping a balance between FPGA resources and performance.

Keywords: feature extraction, real-time, ORB, FPGA implementation

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Authors: Shinji Kawakura, Ryosuke Shibasaki

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We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.

Keywords: advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: María Laura Guevara Campos

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The increasing number of vending machines makes it easy for people to find them more frequently in stores, universities, workplaces, and even hospitals. These machines usually offer products with high contents of sugar and fat, which, if consumed regularly, can result in serious health threats, as overweight and obesity. Additionally, the energy consumption of these machines tends to be high, which has an impact on the environment as well. In order to promote the consumption of healthy food, a vending machine was designed to give the customer the opportunity to choose between a customized fruit salad and a customized fruit juice, both of them prepared instantly with the ingredients selected by the customer. The main parameters considered to design the machine were: the storage of the preferred fruits in a salad and/or in a juice according to a survey, the size of the machine, the use of ecologic recipients, and the overall energy consumption. The methodology used for the design was the one proposed by the German Association of Engineers for mechatronics systems, which breaks the design process in several stages, from the elaboration of a list of requirements through the establishment of the working principles and the design concepts to the final design of the machine, which was done in a 3D modelling software. Finally, with the design of this machine, the aim is to contribute to the development and implementation of healthier vending machines that offer freshly-made products, which is not being widely attended at present.

Keywords: design, design methodology, mechatronics systems, vending machines

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Authors: E. A. Krasikov

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Dependence of the materials properties on neutron irradiation intensity (flux) is a key problem while usage data of the accelerated materials irradiation in test reactors for forecasting of their capacity for work in realistic (practical) circumstances of operation. Investigations of the reactor pressure vessel steel radiation degradation dependence on fast neutron fluence (embrittlement kinetics) at low flux reveal the instability in the form of the scatter of the experimental data and wave-like sections of embrittlement kinetics appearance. Disclosure of the steel degradation oscillating is a sign of the steel structure cyclic self-recovery transformation as it take place in self-organization processes. This assumption has received support through the discovery of the similar ‘anomalous’ data in scientific publications and by means of own additional experiments. Data obtained stimulate looking-for ways to management of the structural steel radiation stability (for example, by means of nano - structure modification for radiation defects annihilation intensification) for creation of the intelligent self-recovering material. Expected results: - radiation degradation theory and mechanisms development, - more adequate models of the radiation embrittlement elaboration, - surveillance specimen programs improvement, - methods and facility development for usage data of the accelerated materials irradiation for forecasting of their capacity for work in realistic (practical) circumstances of operation, - search of the ways for creating of the radiation stable self-recovery intelligent materials.

Keywords: degradation, radiation, steel, wave-like kinetics

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

Abstract:

This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Ramanen Sugunesegran, Michael L. Williams

Abstract:

Over the past two decades surgical approaches for mitral valve (MV) disease have evolved with the advent of minimally invasive techniques. Robotic mitral valve repair (RMVr) safety and efficacy has been well documented, however, mid- to long-term data are limited. The aim of this review was to provide a comprehensive analysis of the available mid- to long-term term data for RMVr. Electronic searches of five databases were performed to identify all relevant studies reporting minimum 5-year data on RMVr. Pre-defined primary outcomes of interest were overall survival, freedom from MV reoperation and freedom from moderate or worse mitral regurgitation (MR) at 5-years or more post-RMVr. A meta-analysis of proportions or means was performed, utilizing a random effects model, to present the data. Kaplan-Meier curves were aggregated using reconstructed individual patient data. Nine studies totaling 3,300 patients undergoing RMVr were identified. Rates of overall survival at 1-, 5- and 10-years were 99.2%, 97.4% and 92.3%, respectively. Freedom from MV reoperation at 8-years post RMVr was 95.0%. Freedom from moderate or worse MR at 7-years was 86.0%. Rates of early post-operative complications were low with only 0.2% all-cause mortality and 1.0% cerebrovascular accident. Reoperation for bleeding was low at 2.2% and successful RMVr was 99.8%. Mean intensive care unit and hospital stay were 22.4 hours and 5.2 days, respectively. RMVr is a safe procedure with low rates of early mortality and other complications. It can be performed with low complication rates in high volume, experienced centers. Evaluation of available mid-term data post-RMVr suggests favorable rates of overall survival, freedom from MV reoperation and freedom from moderate or worse MR recurrence.

Keywords: mitral valve disease, mitral valve repair, robotic cardiac surgery, robotic mitral valve repair

Procedia PDF Downloads 73

Authors: Waraporn Boonchieng, Ekkarat Boonchieng, Wilawan Senaratana, Jaras Singkaew

Abstract:

Geographical information system (GIS) is a designated system widely used for collecting and analyzing geographical data. Since the introduction of ultra-mobile, 'smart' devices, investigators, clinicians, and even the general public have had powerful new tools for collecting, uploading and accessing information in the field. Epidemiology paired with GIS will increase the efficacy of preventive health care services. The objective of this study is to apply GPS location services that are available on the common mobile device with district health systems, storing data on our private cloud system. The mobile application has been developed for use on iOS, Android, and web-based platforms. The system consists of two parts of district health information, including recorded resident data forms and individual health recorded data forms, which were developed and approved by opinion sharing and public hearing. The application's graphical user interface was developed using HTML5 and PHP with MySQL as a database management system (DBMS). The reporting module of the developed software displays data in a variety of views, from traditional tables to various types of high-resolution, layered graphics, incorporating map location information with street views from Google Maps. Multi-extension exporting is also supported, utilizing standard platforms such as PDF, PNG, JPG, and XLS. The data were collected in the database beginning in March 2013, by district health volunteers and district youth volunteers who had completed the application training program. District health information consisted of patients’ household coordinates, individual health data, social and economic information. This was combined with Google Street View data, collected in March 2014. Studied groups consisted of 16,085 (67.87%) and 47,811 (59.87%) of the total 23,701 households and 79,855 people were collected by the system respectively, in Saraphi district, Chiang Mai Province. The report generated from the system has had a major benefit directly to the Saraphi District Hospital. Healthcare providers are able to use the basic health data to provide a specific home health care service and also to create health promotion activities according to medical needs of the people in the community.

Keywords: health, public health, GIS, geographic information system

Procedia PDF Downloads 318

Authors: Paula M. R. Correia, Marta Gonzaga, Luis M. Batista, Luísa Beirão-Costa, Raquel F. P. Guiné

Abstract:

The purpose of the present work was to develop an innovative food product with good textural and sensorial characteristics. The product, a new type of bread, was prepared with wheat (90%) and lupin (10%) flours, without the addition of any conservatives. Several experiences were also done to find the most appropriate proportion of lupin flour. The optimized product was characterized considering the rheological, physical-chemical and sensorial properties. The water absorption of wheat flour with 10% of lupin was higher than that of the normal wheat flours, and Wheat Ceres flour presented the lower value, with lower dough development time and high stability time. The breads presented low moisture but a considerable water activity. The density of bread decreased with the introduction of lupin flour. The breads were quite white, and during storage the colour parameters decreased. The lupin flour clearly increased the number of alveolus, but the total area increased significantly just for the Wheat Cerealis bread. The addition of lupin flour increased the hardness and chewiness of breads, but the elasticity did not vary significantly. Lupin bread was sensorially similar to wheat bread produced with WCerealis flour, and the main differences are the crust rugosity, colour and alveolus characteristics.

Keywords: Lupin flour, physical-chemical properties, sensorial analysis, wheat flour

Procedia PDF Downloads 504

Authors: Oscar E. Cariceo, Claudia V. Casal

Abstract:

Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

Procedia PDF Downloads 158