Search results for: pixel-based change detection

Authors: Samuele Abagnato, Lucia Rigamonti

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Life-Cycle-Assessment (LCA) is an effective tool to quantify the environmental impacts of reuse models and recycling technologies for textiles. In this work, publications in the last ten years about LCA on textile waste are classified according to location, goal and scope, functional unit, waste composition, impact assessment method, impact categories, and sensitivity analysis. Twenty papers have been selected: 50% are focused only on recycling, 30% only on reuse, the 15% on both, while only one paper considers only the final disposal of the waste. It is found that reuse is generally the best way to decrease the environmental impacts of textiles waste management because of the avoided impacts of manufacturing a new item. In the comparison between a product made with recycled yarns and a product from virgin materials, in general, the first option is less impact, especially for the categories of climate change, water depletion, and land occupation, while for other categories, such as eutrophication or ecotoxicity, under certain conditions the impacts of the recycled fibres can be higher. Cultivation seems to have quite high impacts when natural fibres are involved, especially in the land use and water depletion categories, while manufacturing requires a remarkable amount of electricity, with its associated impact on climate change. In the analysis of the reuse processes, relevant importance is covered by the laundry phase, with water consumption and impacts related to the use of detergents. About the sensitivity analysis, it can be stated that one of the main variables that influence the LCA results and that needs to be further investigated in the modeling of the LCA system about this topic is the substitution rate between recycled and virgin fibres, that is the amount of recycled material that can be used in place of virgin one. Related to this, also the yield of the recycling processes has a strong influence on the results of the impact. The substitution rate is also important in the modeling of the reuse processes because it represents the number of avoided new items bought in place of the reused ones. Another aspect that appears to have a large influence on the impacts is consumer behaviour during the use phase (for example, the number of uses between two laundry cycles). In conclusion, to have a deeper knowledge of the impacts of a life-cycle approach of textile waste, further data and research are needed in the modeling of the substitution rate and of the use phase habits of the consumers.

Keywords: environmental impacts, life-cycle-assessment, textiles recycling, textiles reuse, textiles waste management

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Authors: Nikkey Keshri

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Arctic is a polar region located at the north of the earth. This consists of the Arctic Ocean and other parts of Canada, Russia, the United States, Denmark, Norway, Sweden, Finland, and Iceland. Arctic has vast natural resources which are exploited with modern technology, and the economic opening up of Russia has given new opportunities. All these states have connected with the Arctic region for economic activities and this effect the region ecology. The pollution problem is a serious threat to the people health living around pollution sources. Due to the prevailing worldwide sea and air currents, the Arctic area is the fallout region for long-range transport pollutants, and in some places the concentrations exceed the levels of densely populated urban areas. The Arctic is especially vulnerable to the effects of global warming, as has become apparent in the melting sea ice in recent years. Climate models predict much greater warming in the Arctic than the global average, resulting in significant international attention to the region. The global warming has an adverse impact on the climate, indigenous people, wildlife, and infrastructure. However, there are several opportunities that have emerged in the form of shipping routes, resources, and new territories. The shipping route through the Arctic is a reality and is currently navigable for a few weeks during summers. There are large deposits of oil and gas, minerals and fish and the surrounding countries with Arctic coastlines are becoming quite assertive about exercising their sovereignty over the newfound wealth. The main part of the research is that how the opening of Northern Sea Route is providing opportunities or problem in the Arctic and it is becoming geopolitically important. It focuses on the interest Arctic and non Arctic states, their present and anticipated global geopolitical aims. The Northern Sea Route might open up due to climate changes and that Iceland might benefit or has an impact from the situation. Efforts will be made to answer the research question: ‘Whether Opening of North Sea Route is providing opportunities or becoming a risk for Arctic region?’ Every research has a structure which usually called design. In this research, both Qualitative and Quantitative method is used in terms of various literature, maps, pie- charts, etc to find out the answer for the research question. The aim of this research is to find out the impact of Opening of North Sea Route over Arctic region and how this make arctic geopolitically important. The aim behind this research is to find out the impact of climate change and how the particular geographical area is being affected.

Keywords: climate change, geopolitics, international relation, Northern Sea Route

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Authors: Heide Imai

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The paper will introduce and discuss specific examples of urban practices which take place within the dynamic urban landscape of contemporary Tokyo. The rising interest and importance of derelict places as resilient and creative clusters will be analysed, before relating this to the rediscovery of small urban niches and the emergence of different forms of social entrepreneurs. Secondly, two different case study areas will be introduced before discussing different forms of hybrid lifestyles, social micro scale enterprises and social innovations, understanding the concept of ‘small places of resilience’ as zones of human interaction, desire and care in which spontaneous practices take place.

Keywords: entrepreneurship, social innovation, Tokyo, urban regeneration

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Authors: Abdelaziz Fellah, Allaoua Maamir

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We propose a domain-independent merging-cluster filter approach complemented with a set of algorithms for identifying approximate duplicate entities efficiently and accurately within a single and across multiple data sources. The near-optimal merging-cluster filter (MCF) approach is based on the Monge-Elkan well-tuned algorithm and extended with an affine variant of the Smith-Waterman similarity measure. Then we present constant, variable, and function threshold algorithms that work conceptually in a divide-merge filtering fashion for detecting near duplicates as hierarchical clusters along with their corresponding representatives. The algorithms take recursive refinement approaches in the spirit of filtering, merging, and updating, cluster representatives to detect approximate duplicates at each level of the cluster tree. Experiments show a high effectiveness and accuracy of the MCF approach in detecting approximate duplicates by outperforming the seminal Monge-Elkan’s algorithm on several real-world benchmarks and generated datasets.

Keywords: data mining, data cleaning, approximate duplicates, near-duplicates detection, data mining applications and discovery

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Authors: Aisulu Tileukulova, Zhexebay Dauren

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Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

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Authors: Gerardette Darkwah, Gloria Ankar Brewoo, John Barimah, Gilbert Owiah Sampson, Vincent Abe-Inge

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Soft drinks which are widely consumed in Ghana have been reported in other countries to contain toxic heavy metals beyond the acceptable limits in other countries. Therefore, the objective of this study was to assess the quality characteristics of selected locally produced and marketed soft drinks. Three (3) different batches of 23 soft drinks were sampled from the Takoradi markets. The samples were prescreened for the presence of reducing sugars, phosphates, alcohol and carbon dioxide. The heavy metal contents and physicochemical properties were also determined with AOAC methods. The results indicated the presence of reducing sugars, carbon dioxide and the absence of alcohol in all the selected soft drink samples. The pH, total sugars, moisture, total soluble solids (TSS) and titratable acidity ranged from 2.42 – 3.44, 3.30 – 10.44%, 85.63 – 94.85%, 5.00 – 13.33°Brix, and 0.21 – 1.99% respectively. The concentration of heavy metals were also below detection limits in all samples. The quality of the selected were within specifications prescribed by regulatory bodies.

Keywords: heavy metal contamination, locally manufactured, quality, soft drinks

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Authors: M. Naeimi, H. Aghazadeh, E. Afjei, A. Siadatan

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In this paper, a novel view of air gap magnetic field analysis of synchronous reluctance motor and permanent magnet assisted synchronous reluctance motor under static eccentricity to provide the precise fault diagnosis based on three-dimensional finite element method is presented. Analytical nature of this method makes it possible to simulate reliable and precise model by considering the end effects and axial fringing effects. The results of the three-dimensional finite element analysis of synchronous reluctance motor and permanent magnet synchronous reluctance motor such as flux linkage, flux density, and compression both of SynRM and PM-SynRM for various eccentric motor conditions are obtained and analyzed. These results present useful information regarding to the detection of static eccentricity.

Keywords: synchronous reluctance motor (SynRM), permanent magnet assisted synchronous reluctance motor (PMaSynRM), finite element method, static eccentricity, fault analysis

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Authors: Aayushi Pandey, Manoj Kumar Pandey, Ashutosh Tiwari, Kireet Kumar

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Glaciers play an important role in climate change and are sensitive phenomena of global climate change scenario. Glaciers in Himalayas are unique as they are predominantly valley type and are located in tropical, high altitude regions. These glaciers are often covered with debris which greatly affects ablation rate of glaciers and work as a sensitive indicator of glacier health. The aim of this study is to map high altitude Glacier surface with a focus on glacial lake and debris estimation using different techniques in Nagling glacier of dhauliganga basin in Himalayan region. Different Image Classification techniques i.e. thresholding on different band ratios and supervised classification using maximum likelihood classifier (MLC) have been used on high resolution sentinel 2A level 1c satellite imagery of 14 October 2017.Here Near Infrared (NIR)/Shortwave Infrared (SWIR) ratio image was used to extract the glaciated classes (Snow, Ice, Ice Mixed Debris) from other non-glaciated terrain classes. SWIR/BLUE Ratio Image was used to map valley rock and Debris while Green/NIR ratio image was found most suitable for mapping Glacial Lake. Accuracy assessment was performed using high resolution (3 meters) Planetscope Imagery using 60 stratified random points. The overall accuracy of MLC was 85 % while the accuracy of Band Ratios was 96.66 %. According to Band Ratio technique total areal extent of glaciated classes (Snow, Ice ,IMD) in Nagling glacier was 10.70 km2 nearly 38.07% of study area comprising of 30.87 % Snow covered area, 3.93% Ice and 3.27 % IMD covered area. Non-glaciated classes (vegetation, glacial lake, debris and valley rock) covered 61.93 % of the total area out of which valley rock is dominant with 33.83% coverage followed by debris covering 27.7 % of the area in nagling glacier. Glacial lake and Debris were accurately mapped using Band ratio technique Hence, Band Ratio approach appears to be useful for the mapping of debris covered glacier in Himalayan Region.

Keywords: band ratio, Dhauliganga basin, glacier mapping, Himalayan region, maximum likelihood classifier (MLC), Sentinel-2 satellite image

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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Authors: E. Kam, G. Karahan, H. Aslıyuksek, A. Bozkurt

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This study aims to determine the natural radioactivity levels in some foodstuffs produced in Turkey. For this purpose, 48 different foods samples were collected from different land parcels throughout the country. All samples were analyzed to designate both gross alpha and gross beta radioactivities and the radionuclides’ concentrations. The gross alpha radioactivities were measured as below 1 Bq kg^-1 in most of the samples, some of them being due to the detection limit of the counting system. The gross beta radioactivity levels ranged from 1.8 Bq kg^-1 to 453 Bq kg^-1, larger levels being observed in leguminous seeds while the highest level being in haricot bean. The concentrations of natural radionuclides in the foodstuffs were investigated by the method of gamma spectroscopy. High levels of ⁴⁰K were measured in all the samples, the highest activities being again in leguminous seeds. Low concentrations of ²³⁸U and ²²⁶Ra were found in some of the samples, which are comparable to the reported results in the literature. Based on the activity concentrations obtained in this study, average annual effective dose equivalents for the radionuclides ²²⁶Ra, ²³⁸U, and ⁴⁰K were calculated as 77.416 µSv y^-1, 0.978 µSv y^-1, and 140.55 µSv y^-1, respectively.

Keywords: foods, radioactivity, gross alpha, gross beta, annual equivalent dose, Turkey

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Authors: Walid Mousa, Mohamed Nayel, Ahmed Zaghawa, Akram Salama, Ahmed El-Sify, Hesham Rashad, Dina El-Shafey

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Mycoplasmosis in small ruminants constitutes a serious contagious problem in smallholders causing severe economic losses worldwide. This study was conducted to determine the clinical, Minimum Inhibitory Concentration (MIC) and molecular characterization of Mycoplasma species associated in sheep breeding herds in Menoufiya governorate, Egypt. Out of the examination of 400 sheep, 104 (26%) showed respiratory manifestations, nasal discharges, cough and conjunctivitis with systemic body reaction. Meanwhile, out of these examined sheep, only 56 (14%) were positive for mycoplasma isolation onto PPLO(Pleuropneumonia-like organisms) specific medium. The MIC for evaluating the efficacy of sensitivity of Mycoplasma isolates against different antibiotics groups revealed that both the Linospectin and Tylosin with 2ug, 0.25ug/ml concentration were the most effective antibiotics for Mycoplasma isolates. The application of PCR was the rapid, specific and sensitive molecular approach for detection of M. ovipneumoniae, and M. arginine at 390 and 326 bp, respectively, in all tested isolates. In conclusion, the diagnosis of Mycoplsamosis in sheep is important to achieve effective control measures and minimizing the disease dissemination among sheep herds.

Keywords: MIC, mycoplasmosis, PCR, sheep

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Authors: Krishna Raj Regmi

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A “Climate change adaptation and disaster risk management for sustainable agriculture” project was implemented in Nepal, a Himalayan country during 2008 to 2013 sponsored jointly by Food and Agriculture Organization (FAO) and United Nations Development Programme (UNDP), Nepal. The paper is based on the results and findings of this joint pilot project. The climate change events such as increased intensity of erratic rains in short spells, trend of prolonged drought, gradual rise in temperature in the higher elevations and occurrence of cold and hot waves in Terai (lower plains) has led to flash floods, massive erosion in the hills particularly in Churia range and drying of water sources. These recurring natural and climate-induced disasters are causing heavy damages through sedimentation and inundation of agricultural lands, crops, livestock, infrastructures and rural settlements in the downstream plains and thus reducing agriculture productivity and food security in the country. About 65% of the cultivated land in Nepal is rainfed with drought-prone characteristics and stabilization of agricultural production and productivity in these tracts will be possible through adoption of rainfed and drought-tolerant technologies as well as efficient soil-water management by the local communities. The adaptation and mitigation technologies and options identified by the project for soil erosion, flash floods and landslide control are on-farm watershed management, sloping land agriculture technologies (SALT), agro-forestry practices, agri-silvi-pastoral management, hedge-row contour planting, bio-engineering along slopes and river banks, plantation of multi-purpose trees and management of degraded waste land including sandy river-bed flood plains. The stress tolerant technologies with respect to drought, floods and temperature stress for efficient utilization of nutrient, soil, water and other resources for increased productivity are adoption of stress tolerant crop varieties and breeds of animals, indigenous proven technologies, mixed and inter-cropping systems, system of rice/wheat intensification (SRI), direct rice seeding, double transplanting of rice, off-season vegetable production and regular management of nurseries, orchards and animal sheds. The alternate energy use options and resource conservation practices for use by local communities are installation of bio-gas plants and clean stoves (Chulla range) for mitigation of green house gas (GHG) emissions, use of organic manures and bio-pesticides, jatropha cultivation, green manuring in rice fields and minimum/zero tillage practices for marshy lands. The efficient water management practices for increasing productivity of crops and livestock are use of micro-irrigation practices, construction of water conservation and water harvesting ponds, use of overhead water tanks and Thai jars for rain water harvesting and rehabilitation of on-farm irrigation systems. Initiation of some works on community-based early warning system, strengthening of met stations and disaster database management has made genuine efforts in providing disaster-tailored early warning, meteorological and insurance services to the local communities. Contingent planning is recommended to develop coping strategies and capacities of local communities to adopt necessary changes in the cropping patterns and practices in relation to adverse climatic and disaster risk conditions. At the end, adoption of awareness raising and capacity development activities (technical and institutional) and networking on climate-induced disaster and risks through training, visits and knowledge sharing workshops, dissemination of technical know-how and technologies, conduct of farmers' field schools, development of extension materials and their displays are being promoted. However, there is still need of strong coordination and linkage between agriculture, environment, forestry, meteorology, irrigation, climate-induced pro-active disaster preparedness and research at the ministry, department and district level for up-scaling, implementation and institutionalization of climate change and disaster risk management activities and adaptation mitigation options in agriculture for sustainable livelihoods of the communities.

Keywords: climate change adaptation, disaster risk management, soil-water management practices, sustainable agriculture

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Authors: Sakshi Bhalla

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On the one hand, given their seemingly simplistic, near universal usage and understanding, emoji are discarded as a potential step back in the evolution of communication. On the other, their effectiveness, pervasiveness, and adaptability across and within contexts are undeniable. In this study, the responses of 40 people (categorized by age) were recorded based on a uniform two-part questionnaire where they were required to a) identify the meaning of 15 emoji when placed in isolation, and b) interpret the meaning of the same 15 emoji when placed in a context-defining posting on Twitter. Their responses were studied on the basis of deviation from their responses that identified the emoji in isolation, as well as the originally intended meaning ascribed to the emoji. Based on an analysis of these results, it was discovered that each of the five age categories uses, understands and perceives emoji differently, which could be attributed to the degree of exposure they have undergone. For example, in the case of the youngest category (aged < 20), it was observed that they were the least accurate at correctly identifying emoji in isolation (~55%). Further, their proclivity to change their response with respect to the context was also the least (~31%). However, an analysis of each of their individual responses showed that these first-borns of social media seem to have reached a point where emojis no longer inspire their most literal meanings to them. The meaning and implication of these emoji have evolved to imply their context-derived meanings, even when placed in isolation. These trends carry forward meaningfully for the other four groups as well. In the case of the oldest category (aged > 35), however, the trends indicated inaccuracy and therefore, a higher incidence of a proclivity to change their responses. When studied in a continuum, the responses indicate that slowly and steadily, emoji are evolving from pictograms to ideograms. That is to suggest that they do not just indicate a one-to-one relation between a singular form and singular meaning. In fact, they communicate increasingly complicated ideas. This is much like the evolution of ancient hieroglyphics on papyrus reed or cuneiform on Sumerian clay tablets, which evolved from simple pictograms to progressively more complex ideograms. This evolution within communication is parallel to and contingent on the simultaneous evolution of communication. What’s astounding is the capacity of humans to leverage different platforms to facilitate such changes. Twiterese, as it is now called, is one of the instances where language is adapting to the demands of the digital world. That it does not have a spoken component, an ostensible grammar, and lacks standardization of use and meaning, as some might suggest, may seem like impediments in qualifying it as the 'language' of the digital world. However, that kind of a declarative remains a function of time, and time alone.

Keywords: communication, emoji, language, Twitter

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Authors: Stephen Tullis, M. David DiDonato, Hong Sung Park

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Rowing boats (shells) are often steered by a small rudder operated by one of the backward-facing rowers; the attention required of that athlete then slightly decreases the power that that athlete can provide. Reducing the steering distraction would then increase the overall boat speed. Races are straight 2000 m courses with each boat in a 13.5 m wide lane marked by small (~15 cm) widely-spaced (~10 m) buoys, and the boat trajectory is affected by both cross-currents and winds. An optical buoy recognition and tracking system has been developed that provides the boat’s location and orientation with respect to the lane edges. This information is provided to the steering athlete as either: a simple overlay on a video display, or fed to a simplified autopilot system giving steering directions to the athlete or directly controlling the rudder. The system is then effectively a “lane-assist” device but with small, widely-spaced lane markers viewed from a very shallow angle due to constraints on camera height. The image is captured with a lightweight 1080p webcam, and most of the image analysis is done in OpenCV. The colour RGB-image is converted to a grayscale using the difference of the red and blue channels, which provides good contrast between the red/yellow buoys and the water, sky, land background and white reflections and noise. Buoy detection is done with thresholding within a tight mask applied to the image. Robust linear regression using Tukey’s biweight estimator of the previously detected buoy locations is used to develop the mask; this avoids the false detection of noise such as waves (reflections) and, in particular, buoys in other lanes. The robust regression also provides the current lane edges in the camera frame that are used to calculate the displacement of the boat from the lane centre (lane location), and its yaw angle. The interception of the detected lane edges provides a lane vanishing point, and yaw angle can be calculated simply based on the displacement of this vanishing point from the camera axis and the image plane distance. Lane location is simply based on the lateral displacement of the vanishing point from any horizontal cut through the lane edges. The boat lane position and yaw are currently fed what is essentially a stripped down marine auto-pilot system. Currently, only the lane location is used in a PID controller of a rudder actuator with integrator anti-windup to deal with saturation of the rudder angle. Low Kp and Kd values decrease unnecessarily fast return to lane centrelines and response to noise, and limiters can be used to avoid lane departure and disqualification. Yaw is not used as a control input, as cross-winds and currents can cause a straight course with considerable yaw or crab angle. Mapping of the controller with rudder angle “overall effectiveness” has not been finalized - very large rudder angles stall and have decreased turning moments, but at less extreme angles the increased rudder drag slows the boat and upsets boat balance. The full system has many features similar to automotive lane-assist systems, but with the added constraints of the lane markers, camera positioning, control response and noise increasing the challenge.

Keywords: auto-pilot, lane-assist, marine, optical, rowing

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Authors: Margarita Santi Becerra Santiago

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The following document addresses the descriptive analysis under the qualitative approach of resilient leadership that allows us to know the importance of the application of a new leadership model to face the new challenges within the gastronomic companies in Mexico. Likewise, to know the main factors that influence resilient leaders and companies to develop new skills to elaborate strategies that contribute to overcoming adversities and managing change. Adversities in a company always exist and challenge us to move and apply our knowledge to be competitive as well as to strengthen our work team through motivation to achieve efficiency and develop in a good organizational climate.

Keywords: challenges, efficiency, leadership, resilience skills

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Authors: Li Minghui, Min Shaorong, Zhang Jun

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This paper aims for studying the operational efficiency of surface warship’s motorized evasion to acoustic homing torpedo. It orderly developed trajectory model, self-guide detection model, vessel evasion model, as well as anti-torpedo error model in three-dimensional space to make up for the deficiency of precious researches analyzing two-dimensionally confrontational models. Then, making use of the Monte Carlo method, it carried out the simulation for the confrontation process of evasion in the environment of MATLAB. At last, it quantitatively analyzed the main factors which determine vessel’s survival probability. The results show that evasion relative bearing and speed will affect vessel’s survival probability significantly. Thus, choosing appropriate evasion relative bearing and speed according to alarming range and alarming relative bearing for torpedo, improving alarming range and positioning accuracy and reducing the response time against torpedo will improve the vessel’s survival probability significantly.

Keywords: acoustic homing torpedo, vessel evasion, monte carlo method, torpedo defense, vessel's survival probability

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Authors: Montaceur Zaghdoud, Mohamed Moussaoui, Jalel Akaichi

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Frequent subgraph mining refers usually to graph matching and it is widely used in when analyzing big data with large graphs. A lot of research works dealt with structural exact or inexact graph matching but a little attention is paid to semantic matching when graph vertices and/or edges are attributed and typed. Therefore, it seems very interesting to integrate background knowledge into the analysis and that extracted frequent subgraphs should become more pruned by applying a new semantic filter instead of using only structural similarity in graph matching process. Consequently, this paper focuses on developing a new hybrid approximate structuralsemantic graph matching to discover a set of frequent subgraphs. It uses simultaneously an approximate structural similarity function based on graph edit distance function and a possibilistic vertices similarity function based on affinity function. Both structural and semantic filters contribute together to prune extracted frequent set. Indeed, new hybrid structural-semantic frequent subgraph mining approach searches will be suitable to be applied to several application such as community detection in social networks.

Keywords: approximate graph matching, hybrid frequent subgraph mining, graph mining, possibility theory

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Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

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Authors: Jeremy Johnson, Craig Nitschke, Luke Kelly

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Fire regimes, climate and topographic gradients interact to influence ecosystem structure and function across fire-prone, montane landscapes worldwide. Biota have developed a range of adaptations to historic fire regime thresholds, which allow them to persist in these environments. In south-eastern Australia, a signal of fire regime changes is emerging across these landscapes, and anthropogenic climate change is likely to be one of the main drivers of an increase in burnt area and more frequent wildfire over the last 25 years. This shift has the potential to modify vegetation structure and composition at broad scales, which may lead to landscape patterns to which biota are not adapted, increasing the likelihood of local extirpation of some mammal species. This study aimed to address concerns related to the influence of abrupt changes in fire regimes on mammal populations in montane landscapes. It first examined the impact of climate, topography, and vegetation on fire patterns and then explored the consequences of these changes on mammal populations and their habitats. Field studies were undertaken across diverse vegetation, fire severity and fire frequency gradients, utilising camera trapping and passive acoustic monitoring methodologies and the collection of fine-scale vegetation data. Results show that drought is a primary contributor to fire regime shifts at the landscape scale, while topographic factors have a variable influence on wildfire occurrence at finer scales. Frequent, high severity wildfire influenced forest structure and composition at broad spatial scales, and at fine scales, it reduced occurrence of hollow-bearing trees and promoted coarse woody debris. Mammals responded differently to shifts in forest structure and composition depending on their habitat requirements. This study highlights the complex interplay between fire regimes, environmental gradients, and biotic adaptations across temporal and spatial scales. It emphasizes the importance of understanding complex interactions to effectively manage fire-prone ecosystems in the face of climate change.

Keywords: fire, ecology, biodiversity, landscape ecology

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Authors: Othman Saleh Al-Razgan

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Obesity establishes an epidemic along with an array of comorbidities and this call for careful clinical assessment, to identify causal factors and comprehensive management. In Kuwait, this epidemic reflects the progressive, socio-economic and age-related issues, along with the shift of nutrition from traditional to modern-style. The current research attempts to narrate the obesity and related health issues in Kuwait, with a special emphasis on the magnitude of the issue in Kuwait, nutrition transition over the past three decades, change in life-style, and possible solution for this issue.

Keywords: clinical assessment, comorbidities, obesity, socio-economic

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Authors: N. S. A. Rahim, N. N. Abu Mansor, M. I. Saidi, N. R. A. Rahim, K. F. Adrutdin

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The use of coaching as one of organizational culture with the contribution of the involvement of line manager roles is an important to update employees’ knowledge and skills continuously. In healthcare sector, it is dynamic that nurse must update their knowledge and skills to keep pace with change. This paper attempts to discuss the involvement of line manager roles towards creating a coaching culture who give their support and innovation towards motivate nurses to give their best performance either in public or private hospitals.

Keywords: nursing, line managers’ roles, coaching, coaching culture

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Authors: Rahul Agarwal, Ashutosh Singh

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Colorectal cancer (CRC) also refers as bowel cancer or colon cancer. It involves the development of abnormal growth of cells in colon or rectum part of the body. This work leads to the development of a miRNA database in colorectal cancer. We named this database- miCoRe. This database comprises of all validated colon-rectal cancer miRNAs information from various published literature with an effectual knowledge based information retrieval system. miRNAs have been collected from various published literature reports. MySQL is used for main-framework of miCoRe while the front-end was developed in PHP script. The aim of developing miCoRe is to create a comprehensive central repository of colorectal carcinoma miRNAs with all germane information of miRNAs and their target genes. The current version of miCoRe consists of 238 miRNAs which are known to be implicated in malignancy of CRC. Alongside with miRNA information, miCoRe also contains the information related to the target genes of these miRNA. miCoRe furnishes the information about the mechanism of incidence and progression of the disease, which would further help the researchers to look for colorectal specific miRNAs therapies and CRC specific targeted drug designing. Moreover, it will also help in development of biomarkers for the better and early detection of CRC and will help in better clinical management of the disease.

Keywords: colorectal cancer, database, miCoRe, miRNAs

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Authors: Seung-Jun Yu, Hwan-Jun Choi, Hyoung-Kyu Song

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Among spatial diversity scheme, orthogonal space-time block code (OSTBC) and cyclic delay diversity (CDD) have been widely studied for the cooperative wireless relaying system. However, conventional OSTBC and CDD cannot cope with change in the number of relays owing to low throughput or error performance. In this paper, we propose a cooperative cyclic delay diversity (CDD) scheme that use hierarchical modulation at the source and adaptive modulation based on cyclic redundancy check (CRC) code at the relays.

Keywords: adaptive modulation, cooperative communication, CDD, OSTBC

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Authors: A. Mostaani, M. P. Pereira, B. F. Rolfe

Abstract:

The increasing application of Advanced High Strength Steel (AHSS) in the automotive industry to fulfill crash requirements has introduced higher levels of wear in stamping dies and parts. Therefore, understanding wear behaviour in sheet metal forming is of great importance as it can help to reduce the high costs currently associated with tool wear. At the contact between the die and the sheet, the tips of hard tool asperities interact with the softer sheet material. Understanding the deformation that occurs during this interaction is important for our overall understanding of the wear mechanisms. For these reasons, the scratching of a perfectly plastic material by a rigid indenter has been widely examined in the literature; with finite element modelling (FEM) used in recent years to further understand the behaviour. The ‘wear mode diagram’ has been commonly used to classify the deformation regime of the soft work-piece during scratching, into three modes: ploughing, wedge formation, and cutting. This diagram, which is based on 2D slip line theory and upper bound method for perfectly plastic work-piece and rigid indenter, relates different wear modes to attack angle and interfacial strength. This diagram has been the basis for many wear studies and wear models to date. Additionally, it has been concluded that galling is most likely to occur during the wedge formation mode. However, there has been little analysis in the literature of how the material behaviour and deformation conditions associated with metal forming processes influence the wear behaviour. Therefore, the first aim of this work is first to use a commercial FEM package (Abaqus/Explicit) to build a 3D model to capture wear modes during scratching with indenters with different attack angles and different interfacial strengths. The second goal is to utilise the developed model to understand how wear modes might change in the presence of bulk deformation of the work-piece material as a result of the metal forming operation. Finally, the effect of the work-piece material properties, including strain hardening, will be examined to understand how these influence the wear modes and wear behaviour. The results show that both strain hardening and substrate deformation can change the critical attack angle at which the wedge formation regime is activated.

Keywords: finite element, pile-up, scratch test, wear mode

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Authors: Muthukumarasamy Govindarajan

Abstract:

Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

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Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

Abstract:

Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

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Authors: Mamta M. Barapatre, V. N. Sahare

Abstract:

Since from long time two wheeled vehicle self-balancing has always been a back-breaking task for both human and robots. Leaning a bicycle driving is long time process and goes through building knowledge base for parameter decision making while balancing robots. In order to create this machine learning phase with embedded system the proposed system is designed. The system proposed aims to construct a bicycle automaton, power-driven by an electric motor, which could balance by itself and move along a specific path. This path could be wavy with bumps and varying widths. The key aim was to construct a cycle which self-balances itself by controlling its handle. In order to take a turn, the mass was transferred to the center. In order to maintain the stability, the bicycle bot automatically turned the handle and a turn. Some problems were faced by the team which were Speed, Steering mechanism through mass- distribution (leaning), Center of mass location and gyroscopic effect of its wheel. The idea proposed have potential applications in automation of transportation system and is most efficient.

Keywords: gyroscope-flywheel, accelerometer, servomotor-controller, self stability concept

Procedia PDF Downloads 256

Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon

Abstract:

We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particle­based multiplexing, using patented Firefly hydrogel particles, with single­ step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target­-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.

Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry

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Authors: Murat Sözen

Abstract:

It is not at all difficult to estimate which level today’s technology reaches considering that humankinds space-faring in early 1950s. Technology is a means to help achieve goals and people can produce systems on their physical and mental abilities. Needed and used as tools in all areas of life and became a necessity and dependency, technology, widely used in the military field. To be a revolutionary change in the military matters, opportunities offered by technology should be put into practice. Tech makes weapons, sensors, platforms and soldiers carrying them more effective. To increase this efficiency in the battlefield defense industry is seeking every advantage of technology. In this study, the applicability of existing and on-going augmented reality applications for Armed Forces will be evaluated.

Keywords: augmented reality, battlefield, military, virtual reality

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Authors: Md. Mazharul Anwar, Md. Samim Hossain Molla, Md. Akkas Ali, Mian Sayeed Hassan

Abstract:

After 68 years, the agreement between Bangladesh and India was ratified on 6 June 2015 and Bangladesh received 111 Indian enclaves. Millions of farm household lived in these previous enclaves, being detached from the mainland of the country, they were socially, economically and educationally deprived people in the world. This study was undertaken to compare of the Stochastic Frontier Analysis (SFA) and the constant returns to scale (CRS) and variable returns to scale (VRS) output-oriented DEA models, based on a sample of 300 farms from the three largest enclaves of Bangladesh in 2017. However, the aim of the study was not only to compare estimates of technical efficiency obtained from the two approaches, but also to examine the determinants of inefficiency. The results from both the approaches indicated that there is a potential for increasing farm production through efficiency improvement and that farmers' age, educational level, new technology dissemination and training on crop production technology have a significant effect on efficiency. The detection and measurement of technical inefficiency and its determinants can be used as a basis of policy recommendations.

Keywords: DEA approach, previous enclaves, SFA approach, technical inefficiency

Procedia PDF Downloads 110