Search results for: image registration techniques

Authors: Veronica Diaz Quezada

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In this article, the performance and errors are featured and analysed in the limit problems solving of a real-valued function, in correspondence to competency-based education in engineering careers, in the south of Chile. The methodological component is contextualised in a qualitative research, with a descriptive and explorative design, with elaboration, content validation and application of quantitative instruments, consisting of two parallel forms of open answer tests, based on limit application problems. The mathematical competences and errors made by students from five engineering careers from a public University are identified and characterized. Results show better performance only to solve routine-context problem-solving competence, thus they are oriented towards a rational solution or they use a suitable problem-solving method, achieving the correct solution. Regarding errors, most of them are related to techniques and the incorrect use of theorems and definitions of real-valued function limits of real variable.

Keywords: engineering education, errors, limits, mathematics competences, problem solving

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Authors: Khalliyeva Gulnoz Iskandarovna, Mannonova Feruzabonu Sherali Qizi

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A scientific field called comparative literature or literary comparative studies compares two or more literary phenomena. One of the most important scientific fields nowadays, when global social, cultural, and literary relations are growing daily, is comparative literature. Any comparative investigation reveals shared and unique characteristics of literary phenomena, which provide the cornerstone for the creation of overarching theoretical principles that apply to all literature. Comparative analysis consists of objects, and they are their constituents. For researchers, it is enough to know this. Comparative analysis, in addition to the above-mentioned actions, also focuses on comparing the components of the objects of analysis with each other. The purpose of this article is to investigate comparative analysis in literature and to identify similarities and differences between comparable objects. Students, teachers, and researchers should be able to describe comparative research techniques and their fundamental ideas when studying this topic. They should also have a basic understanding of comparative literature and their summary.

Keywords: object, natural, social, spiritual, epistemological, logical, methodological, methodological, axiological tasks, stages of comparison, environment, internal features, and typical situations

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Authors: Rana Parween, Rob Marchant

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With the continued loss of global biodiversity despite the application of modern conservation techniques, it has become crucial to investigate non-conventional methods. Accelerated destruction of ecosystems due to altered land use, climate change, cultural and social change, necessitates the exploration of society-biodiversity attitudes and links. While the loss of species and their extinction is a well-known and well-documented process that attracts much-needed attention from researchers, academics, government and non-governmental organizations, the loss of traditional ecological knowledge and practices is more insidious and goes unnoticed. The growing availability of 'indirect experiences' such as the internet and media are leading to a disaffection towards nature and the 'Extinction of Experience'. Exacerbated by the lack of documentation of traditional practices and skills, there is the possibility for the 'extinction' of traditional practices and skills before they are fully recognized and captured. India, as a mega-biodiverse country, is also known for its historical conservation strategies entwined in traditional beliefs. Indigenous communities hold skillsets, knowledge, and traditions that have accumulated over multiple generations and may play an important role in conserving biodiversity today. This study explores the differences in knowledge and attitudes towards conserving biodiversity, of three different stakeholder groups living around Jim Corbett National Park, based on their age, traditions, and association with the protected area. A triangulation designed multi-strategy investigation collected qualitative and quantitative data through a questionnaire survey of village elders, the general public, and forest officers. Following an inductive approach to analyzing qualitative data, the thematic content analysis was followed. All coding and analysis were completed using NVivo 11. Although the village elders and some general public had vast amounts of traditional knowledge, most of it was related to animal husbandry and the medicinal value of plants. Village elders were unfamiliar with the concept of the term ‘biodiversity’ albeit their way of life and attitudes ensured that they care for the ecosystem without having the scientific basis underpinning biodiversity conservation. Inherently, village elders were keen to conserve nature; the superimposition of governmental policies without any tangible benefit or consultation was seen as detrimental. Alienating villagers and consequently the village elders who are the reservoirs of traditional knowledge would not only be damaging to the social network of the area but would also disdain years of tried and tested techniques held by the elders. Forest officers advocated for biodiversity and conservation education for women and children. Women, across all groups, when questioned about nature conservation, showed more interest in learning and participation. Biodiversity not only has an ethical and cultural value, but also plays a role in ecosystem function and, thus, provides ecosystem services and supports livelihoods. Therefore, underpinning and using traditional knowledge and incorporating them into programs of biodiversity conservation should be explored with a sense of urgency.

Keywords: biological diversity, mega-biodiverse countries, traditional ecological knowledge, society-biodiversity links

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Authors: D. Garg, S. Luthra, A. Haleem

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Reverse logistics (RL) is supposed to be a systematic procedure that helps in improving the environmental hazards and maintain business sustainability for industries. Industries in Indian are now opting for adoption of RL techniques in business. But, RL practices are not popular in Indian industries because of many barriers for its successful implementation. Therefore, need arises to identify and evaluate the barriers to implement RL practices by taking an Indian industries perspective. Literature review approach and case study approach have been adapted to identify relevant barriers to implement RL practices. Further, Fuzzy Decision Making Trial and Evaluation Laboratory methodology has been brought into use for evaluating causal relationships among the barriers to implement RL practices. Seven barriers out of ten barriers have been categorized into the cause group and remaining into effect group. This research will help Indian industries to manage these barriers towards effective implementing RL practices.

Keywords: barriers, decision making trial and evaluation laboratory (DEMATEL), fuzzy set theory, Indian industries, reverse logistics (RL)

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: I. Touaїbia, E. Azzag, O. Narjes

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Power supply networks are growing continuously and their reliability is getting more important than ever. The complexity of the whole network comprises numerous components that can fail and interrupt the power supply for the end user. Underground distribution systems are normally exposed to permanent faults, due to specific construction characteristics. In these systems, visual inspection cannot be performed. In order to enhance service restoration, accurate fault location techniques must be applied. This paper describes the different faults that affect the underground distribution system of SONELGAZ (National Society of Electricity and Gas of Algeria), and cable fault location procedure with impulse reflection method (TDR), based in the analyses of the cable response of the electromagnetic impulse, allows cable fault prelocation. The results are obtained from real test in the underground distribution feeder from electrical network of energy distribution company of Souk-Ahras, in order to know the influence of cable characteristics in the types and frequency of faults.

Keywords: distribution networks, fault location, TDR, underground cable

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Authors: Raghad A. Altowairgi

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With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Praveen Chandramenon, Andrew Gascoyne, Fideline Tchuenbou-Magaia

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Aquaponics offers a simple conclusive solution to the food and environmental crisis of the world. This approach combines the idea of Aquaculture (growing fish) to Hydroponics (growing vegetables and plants in a soilless method). Smart Aquaponics explores the use of smart technology including artificial intelligence and IoT, to assist farmers with better decision making and online monitoring and control of the system. Identification of different growth stages of Swiss Chard plants and predicting its harvest time is found to be important in Aquaponic yield management. This paper brings out the comparative analysis of a standard Aquaponics with a Vermiponics (Aquaponics with worms), which was grown in the controlled environment, by implementing IoT and deep learning-based growth stage segregation and harvest time prediction of Swiss Chards before and after applying an optimal freshwater replenishment. Data collection, Growth stage classification and Harvest Time prediction has been performed with and without water replenishment. The paper discusses the experimental design, IoT and sensor communication with architecture, data collection process, image segmentation, various regression and classification models and error estimation used in the project. The paper concludes with the results comparison, including best models that performs growth stage segregation and harvest time prediction of the Aquaponic and Vermiponic testbed with and without freshwater replenishment.

Keywords: aquaponics, deep learning, internet of things, vermiponics

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Authors: Vaibhav Barve

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Reversible information hiding has drawn a lot of interest as of late. Being reversible, we can restore unique computerized data totally. It is a plan where mystery data is put away in digital media like image, video, audio to maintain a strategic distance from unapproved access and security reason. By and large JPEG bit stream is utilized to store this key data, first JPEG bit stream is encrypted into all around sorted out structure and then this secret information or key data is implanted into this encrypted region by marginally changing the JPEG bit stream. Valuable pixels suitable for information implanting are computed and as indicated by this key subtle elements are implanted. In our proposed framework we are utilizing RC4 algorithm for encrypting JPEG bit stream. Encryption key is acknowledged by framework user which, likewise, will be used at the time of decryption. We are executing enhanced least significant bit supplanting steganography by utilizing genetic algorithm. At first, the quantity of bits that must be installed in a guaranteed coefficient is versatile. By utilizing proper parameters, we can get high capacity while ensuring high security. We are utilizing logistic map for shuffling of bits and utilization GA (Genetic Algorithm) to find right parameters for the logistic map. Information embedding key is utilized at the time of information embedding. By utilizing precise picture encryption and information embedding key, the beneficiary can, without much of a stretch, concentrate the incorporated secure data and totally recoup the first picture and also the original secret information. At the point when the embedding key is truant, the first picture can be recouped pretty nearly with sufficient quality without getting the embedding key of interest.

Keywords: data embedding, decryption, encryption, reversible data hiding, steganography

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Authors: The Danh Phan

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House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy.

Keywords: house price prediction, regression trees, neural network, support vector machine, stepwise

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Authors: Erhong Sun, Xuchun Ye

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Technophobia, namely the fear or dislike of modern advanced technologies, plays a central role in age-related digital divides and is considered a new risk factor for older adults, which can affect the daily lives of people through low adherence to digital living. Indeed, there is considerable heterogeneity in the group of older adults who feel technophobia. Therefore, the aim of this study was to identify different technophobia typologies of older people and to examine their associations with the subjective age factor. A sample of 704 retired elderly over the age of 55 was recruited in China. Technophobia and subjective age were assessed with a questionnaire, respectively. Latent profile analysis was used to identify technophobia subgroups, using three dimensions including techno-anxiety, techno-paranoia, and privacy concerns as indicators. The association between the identified technophobia subgroups and subjective age was explored. In summary, four different technophobia typologies were identified among older adults in China. Combined with an investigation of personal background characteristics and subjective age, it draws a more nuanced image of the technophobia phenome among older adults in China. First, not all older adults suffer from technophobia, with about half of the elderly subjects belonging to the profiles of “Low-technophobia” and “Medium-technophobia.” Second, privacy concern plays an important role in the classification of technophobia among older adults. Third, subjective age might be a protective factor for technophobia in older adults. Although the causal direction between identified technophobia typologies and subjective age remains uncertain, our suggests that future interventions should better focus on subjective age by breaking the age stereotype of technology to reduce the negative effect of technophobia on older. Future development of this research will involve extensive investigation of the detailed impact of technophobia in senior populations, measurement of the negative outcomes, as well as formulation of innovative educational and clinical pathways.

Keywords: technophobia, older adults, latent profile analysis, subjective age

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Authors: Aishwarya Shekhar, Himanshu Sharma

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Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

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Authors: Quoc Hung Le Pham

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Human beings are motivated to satisfy the physiological needs and psychological needs. In the fundamental needs, bodily excretion is the most basic one, while physiological excretion refers to the final products produced in the process of discharging the body. This physiological process is a common human phenomenon. For instance, bodily secretion is totally natural, but people of various nationalities through the times avoid saying it directly. Terms like ‘shit’ are often negatively regarded as dirty, smelly and vulgar; it will lead people to negative thinking. In fact, it is in the psychology of human beings to avoid such unsightly terms. Especially in social situations where you have to take care of your image, and you have to release. The best way to solve this is to approach the use of euphemism. People prefer to say it as ‘answering nature's call’ or ‘to pass a motion’ instead. Chinese and Vietnamese nations are referring to use euphemisms to replace bodily secretions, so this research will take this phenomenon as the object aims to explore the similarities and dissimilarities between two languages euphemism. The basic of the niche of this paper is human physiological phenomenon excretion. As the preliminary results show, in expressing bodily secretions the deeply impacting factor is language and cultural factors. On language factor terms, two languages are using assonance to replace human nature discharge, whilst the dissimilarities are metonymy, loan word and personification. On culture factor terms, the convergences are metonymy and application of the semantically-contrary-word-euphemism, whilst the difference is Chinese euphemism using allusion but Vietnamese euphemism does not.

Keywords: cultural factors, euphemism, human needs, language factors

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Authors: Bayan Almofty, Yuto Yamaki, Tadamasa Terai, Sadahito Uto

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Culture techniques of skeletal muscle cells are advanced in the field of regenerative medicine and applied research of cultured muscle. As applied research of cultured muscle, myopathy (muscles disease) treatment is expected and development bio of actuator is also expected in biomedical engineering. Grayanotoxins (GTXs) is known as neurotoxins that enhance the permeability of cell membrane for Na ions. Grayanotoxins are extracted from a famous Pieris japonica and Ericaceae as well as a phytotoxin. In this study, we investigated the effect of GTXs on muscle cells (C2C12) contraction and membrane potential. Contraction of myotubes is induced by applied external electrical stimulation. Contraction and membrane potential change of skeletal muscle cells are induced by injection of current. We, therefore, concluded that effect of Grayanotoxins on contraction and membrane potential of C2C12 relate to acute toxicity of GTXs.

Keywords: skeletal muscle cells C2C12, grayanotoxins, contraction, membrane potential, acute toxicity, pytotoxin, motubes

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Authors: Kheireddine El-Boubbou

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Drug delivery to target human acute myeloid leukemia (AML) using a nanoparticulate chemotherapeutic formulation that can deliver drugs selectively to AML cancer is hugely needed. In this work, we report the development of a nanoformulation made of polymeric-stabilized multifunctional magnetic iron oxide nanoparticles (PMNP) loaded with the anticancer drug Doxorubicin (Dox) as a promising drug carrier to treat AML. Dox@PMNP conjugates simultaneously exhibited high drug content, maximized fluorescence, and excellent release properties. Nanoparticulate uptake and cell death following addition of Dox@PMNPs were then evaluated in different types of human AML target cells, as well as on normal human cells. While the unloaded MNPs were not toxic to any of the cells, Dox@PMNPs were found to be highly toxic to the different AML cell lines, albeit at different inhibitory concentrations (IC₅₀ values), but showed very little toxicity towards the normal cells. In comparison, free Dox showed significant potency concurrently to all the cell lines, suggesting huge potentials for the use of Dox@PMNPs as selective AML anticancer cargos. Live confocal imaging, fluorescence and electron microscopy confirmed that Dox is indeed delivered to the nucleus in relatively short periods of time, causing apoptotic cell death. Importantly, this targeted payload may potentially enhance the effectiveness of the drug in AML patients and may further allow physicians to image leukemic cells exposed to Dox@PMNPs using MRI.

Keywords: magnetic nanoparticles, drug delivery, acute myeloid leukemia, iron oxide, cancer nanotherapy

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Authors: Driss Haddouche

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Pastoral crisis in Algeria has its origins in rangeland degradation which are the main factor in any activity in the steppe zones. Indeed, faced with the increasing human and animal population on a living space smaller and smaller, there is an overuse of what remains of the steppe range lands, consequently the not sustainability of biomass production. Knowing the amount of biomass available, the practice of grazing options, taking into account the use of "Use Factor" factor remains an essential method for managing pastoral resources. This factor has three options: at 40% Conservative pasture; at 60 % the beginning of overgrazing; at 80% destructive grazing. Accessibility on the pasture is based on our field observations of a type any flock along a grazing cycle. The main purpose of these observations is to highlight the speed of herd grazing situation. Several individuals from the herd were timed to arrive at an average duration of about 5 seconds to move between two tufts of grass, separated by a distance of one meter. This gives a rate of 5 s/m (0.72 km/h) flat. This speed varies depending on the angle of the slope. Knowing the speed and slope of each pixel of the study area, given by the digital elevation model of Spot Image (MNE) and whose pitch is 15 meters, a map of pasture according to the distances is generated. Knowing the stocking and biomass available, the examination of the common Mécheria at regular distances (8.64 km or 12 hours of grazing, 17.28 km or 24 hours of grazing and 25.92 Km or 36 hours of grazing), offers three different options (conservation grazing resource: utilization at 40%; overgrazing statements for use at 60% and grazing destructive for use by more than 80%) for each distance traveled by sheep from the starting point is the town of Mécheria.

Keywords: pastoral crisis, biomass, animal charge, use factor, Algeria

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Authors: Hafida Bouarfa, Mohamed Abed

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The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory.

Keywords: case based reasoning, fuzzy logic, fuzzy case based reasoning, seismic vulnerability

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Authors: Zahra Asgharpour, Eric Renteria, Sebastian De Boodt

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There is a growing trend towards personalization of medical care, as evidenced by the emphasis on outcomes based medicine, the latest developments in CT and MR imaging and personalized treatment in a variety of surgical disciplines. 3D Printing has been introduced and applied in the medical field since 2000. The first applications were in the field of dental implants and custom prosthetics. According to recent publications, 3D printing in the medical field has been used in a wide range of applications which can be organized into several categories including implants, prosthetics, anatomical models and tissue bioprinting. Some of these categories are still in their infancy stage of the concept of proof while others are in application phase such as the design and manufacturing of customized implants and prosthesis. The approach of 3D printing in this category has been successfully used in the health care sector to make both standard and complex implants within a reasonable amount of time. In this study, some of the clinical applications of 3D printing in design and manufacturing of a patient-specific hip implant would be explained. In cases where patients have complex bone geometries or are undergoing a complex revision on hip replacement, the traditional surgical methods are not efficient, and hence these patients require patient-specific approaches. There are major advantages in using this new technology for medical applications, however, in order to get this technology widely accepted in medical device industry, there is a need for gaining more acceptance from the medical device regulatory offices. This is a challenge that is moving onward and will help the technology find its way at the end as an accepted manufacturing method for medical device industry in an international scale. The discussion will conclude with some examples describing the future directions of 3D Medical Printing.

Keywords: CT/MRI, image processing, 3D printing, medical devices, patient specific implants

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Authors: Musthaya Patchanee

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The study of Sanitary landfill in Bang Nok-khwaek municipality consists of two procedures. First, to survey and create the spatial database by using physical factor, environmental factor, economical factor and social factor to follow the method of Geographic information system: GIS, second, to analyze the proper spatial for allocating the sanitary landfill in Bang Nok-khwaek municipality by using Overlay techniques to calculate the weighting linear total in Arc GIS program. The study found that there are 2.49 sq.km. proper spatial for the sanitary landfill in Bang Nok-khwaek municipals city which is 66.76% of the whole area. The highest proper spatial is 0.02 sq.km. which is 0.54%, The high proper spatial is 0.3 sq.km. which is 8.04%, the moderate spatial is 1.62 sq.km. which is 43.43% and the low proper spatial is 0.55 sq.km. which is 14.75%. These results will be used as the guideline to select the sanitary landfill area in accordance with sanitation standard for Subdistrict Administrative Organization and Subbdistrict Municipality in Samut Songkhram provice.

Keywords: Geographic Information System (GIS), sanitary landfill, Bang Nok-Khwaek municipality, Subdistrict Administrative Organization

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Authors: Chen-En Lin, Lih-Rou Rau, Jiunn-Woei Liaw, Shiao-Wen Tsai

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The unique optical properties of plasmon resonance metallic particles have attracted considerable applications in the fields of physics, chemistry and biology. Metal-Enhanced Fluorescence (MEF) effect is one of the useful applications. MEF effect stated that fluorescence intensity can be quenched or be enhanced depending on the distance between fluorophores and the metal nanoparticles. Silver nanoparticles have used widely in antibacterial studies. However, the major limitation for silver nanoparticles (AgNPs) in biomedical application is well-known cytotoxicity on cells. There were numerous literatures have been devoted to overcome the disadvantage. The aim of the study is to evaluate the cytotoxicity and biocompatibility of silica coated AgNPs against NIH-3T3 cells. The results were shown that NIH-3T3 cells started to detach, shrink, become rounded and finally be irregular in shape after 24 h of exposure at 10 µg/ml AgNPs. Besides, compared with untreated cells, the cell viability significantly decreased to 60% and 40% which were exposed to 10 µg/ml and 20 µg/ml AgNPs respectively. The result was consistent with previously reported findings that AgNPs induced cytotoxicity was concentration dependent. However, the morphology and cell viability of cells appeared similar to the control group when exposed to 20 µg/ml of silica coated AgNPs. We further utilized the dark-field hyperspectral imaging system to analysis the optical properties of the intracellular nanoparticles. The image displayed that the red shift of the surface plasmonic resonances band of the enclosed AgNPs further confirms the agglomerate of the AgNPs rather than their distribution in cytoplasm. In conclusion, the study demonstrated the silica coated of AgNPs showed well biocompatibility and significant lower cytotoxicity compared with bare AgNPs.

Keywords: silver nanoparticles, silica, cell viability, morphology

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Authors: Ananta Kumar Das, Sujit Kumar Chakrabarti

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Architectural tactics such as heartbeat, ping-echo, encapsulate, encrypt data are techniques that are used to achieve quality attributes of a system. Detecting architectural tactics has several benefits: it can aid system comprehension (e.g., legacy systems) and in the estimation of quality attributes such as safety, security, maintainability, etc. Architectural tactics are typically spread over the source code and are implicit. For large codebases, manual detection is often not feasible. Therefore, there is a need for automated methods of detection of architectural tactics. This paper presents a formalization of the heartbeat architectural tactic and a program analytic approach to detect this tactic in source code. The experiment of the proposed method is done on a set of Java applications. The outcome of the experiment strongly suggests that the method compares well with a manual approach in terms of its sensitivity and specificity, and far supersedes a manual exercise in terms of its scalability.

Keywords: software architecture, architectural tactics, detecting architectural tactics, program analysis, AST, alias analysis

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Authors: Abbas Anser, Ahmad Irfan

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The main purpose of the VAV (Variable Air Volume) in Heating, Ventilation, and Air Conditioning (HVAC) system is to reduce energy consumption and make the buildings comfortable for the occupants. For better performance of the air conditioning system, different control techniques have been developed. In this paper, an Improved Sliding Mode Control (ISMC), based on Power Rate Exponential Reaching Law (PRERL), has been implemented on a VAV air conditioning system. Through the proposed technique, fast response and robustness have been achieved. To verify the efficacy of ISMC, a comparison of the suggested control technique has been made with Exponential Reaching Law (ERL) based SMC. And secondly, chattering, which is unfavorable as it deteriorates the mechanical parts of the air conditioning system by the continuous movement of the mechanical parts and consequently it increases the energy loss in the air conditioning system, has been alleviated. MATLAB/SIMULINK results show the effectiveness of the utilized scheme, which ensures the enhancement of the energy efficiency of the VAV air conditioning system.

Keywords: PID, SMC, HVAC, PRERL, feedback linearization, VAV, chattering

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Authors: Luqman Ali Shah, Murtaza Sayed, Mohammad Siddiq

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Three-dimensional cross-linked polymer microgels with temperature responsive N-isopropyl acrylamide (NIPAM) and pH-sensitive methacrylic acid (MAA) were successfully synthesized by free radical emulsion polymerization with different amount of MAA. Silver and gold nanoparticles with size of 6.5 and 3.5 nm (±0.5 nm) respectively were homogeneously reduced inside these materials by chemical reduction method at pH 2.78 and 8.36 for the preparation of hybrid materials. The samples were characterized by FTIR, DLS and TEM techniques. The catalytic activity of the hybrid materials was investigated for the reduction of 4-nitrophenol (4- NP) using NaBH4 as reducing agent by UV-visible spectroscopy. The hybrid polymer network synthesized at pH 8.36 shows enhanced catalytic efficiency compared to catalysts synthesized at pH 2.78. In this study, it has been explored that catalyst activity strongly depends on amount of MAA, synthesis pH and type of metal nanoparticles entrapped.

Keywords: cross-linked polymer microgels, free radical polymerization, metal nanoparticles, catalytic activity, comparative study

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Authors: Ngozi Claribelle Nwogu, Mohammed Nasir Kajama, Oyoh Kechinyere, Edward Gobina

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Atmospheric carbon dioxide emissions are considered as the greatest environmental challenge the world is facing today. The challenges to control the emissions include the recovery of CO2 from flue gas. This concern has been improved due to recent advances in materials process engineering resulting in the development of inorganic gas separation membranes with excellent thermal and mechanical stability required for most gas separations. This paper therefore evaluates the performance of a highly selective inorganic membrane for CO2 recovery applications. Analysis of results obtained is in agreement with experimental literature data. Further results show the prediction performance of the membranes for gas separation and the future direction of research. The materials selection and the membrane preparation techniques are discussed. Method of improving the interface defects in the membrane and its effect on the separation performance has also been reviewed and in addition advances to totally exploit the potential usage of this innovative membrane.

Keywords: carbon dioxide, gas separation, inorganic ceramic membrane, permselectivity

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Authors: Luis Andrey Fajardo Fajardo

Abstract:

We are immersed in complex systems. The human brain, the galaxies, the snowflakes are examples of complex systems. An area of interest in Complex systems is the chaos theory. This revolutionary field of science presents different ways of study than determinism and reductionism. Here is where in junction with the Nonlinear DSP, chaos theory offer valuable techniques that establish a link between time series and complex theory in terms of complex networks, so that, the study of signals can be explored from the graph theory. Recently, some people had purposed a method to transform time series in graphs, but no one had developed a suitable implementation in Python with signals extracted from Chaotic Systems or Complex systems. That’s why the implementation in Python of an existing method to transform one dimensional chaotic signals from time domain to graph domain and some measures that may reveal information not extracted in the time domain is proposed.

Keywords: Python, complex systems, graph theory, dynamical systems

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Authors: Fuad Ali Mohammed Al-Yarimi

Abstract:

Many algorithms have been proposed to provide privacy preserving in data mining. These protocols are based on two main approaches named as: the perturbation approach and the Cryptographic approach. The first one is based on perturbation of the valuable information while the second one uses cryptographic techniques. The perturbation approach is much more efficient with reduced accuracy while the cryptographic approach can provide solutions with perfect accuracy. However, the cryptographic approach is a much slower method and requires considerable computation and communication overhead. In this paper, a new scalable protocol is proposed which combines the advantages of the perturbation and distortion along with cryptographic approach to perform privacy preserving in distributed frequent itemset mining on horizontally distributed data. Both the privacy and performance characteristics of the proposed protocol are studied empirically.

Keywords: anonymity data, data mining, distributed frequent itemset mining, gaussian perturbation, perturbation approach, privacy preserving data mining

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Authors: Raghuveer Kaur, Kartikay Sharma, Ashu Khanna

Abstract:

Earnings management has been present from times immemorial. The recent downfall of giant enterprises like Enron, Satyam and WorldCom has brought a lot of focus on the study and detection of earnings management. The present study is an attempt to study earnings management in one of the fastest emerging economy - India. The study makes an attempt to understand earnings management in different sectors of the economy. The paper first tests a hypothesis to check whether different sectors of India are engaged in earnings management or not. In the later section the paper aims to study the level of earnings management in 6 popular sectors of India: IT&BPO, Retail, Telecom, Biotech, Hotels and coffee. To measure earnings management two popular techniques of detecting earnings management has been employed: Modified Jones Model and Beniesh M Score. A total of 332 companies were studied. Publicly available data from Capitaline database has been used. The paper also classifies the top and bottom five performers on the basis of sales turnover in each sector and identifies whether they manage their earnings or not.

Keywords: earnings management, India, modified Jones model, Beneish M score

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Authors: Zabihullah Mahdi, Khwaja Naweed Seddiqi, Shigeo Honma

Abstract:

Through many types of research and practical studies, it has been identified that the average oil recovery factor of a petroleum reservoir is about 30 to 35 %. This study is focused on enhanced oil recovery by laboratory experiment and graphical investigation based on Buckley-Leverett theory. Horizontal oil displacement by water, in a petroleum reservoir is analyzed under the Buckley-Leverett frontal displacement theory. The extraction and prerequisite of this theory are based and pursued focusing on the key factors that control displacement. The theory is executable to the waterflooding method, which is generally employed in petroleum engineering reservoirs to sustain oil production recovery, and the techniques for evaluating the average water saturation behind the water front and the oil recovery factors in the reservoirs are presented. In this paper, the Buckley-Leverett theory handled to an experimental model and the amount of recoverable oil are investigated to be over 35%. The irreducible water saturation, viz. connate water saturation, in the reservoir is also a significant inspiration for the recovery.

Keywords: Buckley-Leverett theory, waterflooding technique, petroleum engineering, immiscible displacement

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Authors: Chigbo Emmanuel Ikechukwu

Abstract:

Constructed wetlands are seen as a potential means of ameliorating the poor quality water that derives from coal and gold mining operations. However, the processes whereby a wetland environment is able to improve water quality are not well understood and techniques for optimising their performance poorly developed. A parameter that may be manipulated in order to improve the treatment capacity of a wetland is the substrate in which the aquatic plants are rooted. This substrate can provide an environment wherein sulphate reducing bacteria, which contribute to the removal of contaminants from the water, are able to flourish. The bacteria require an energy source which is largely provided by carbon in the substrate. This paper discusses the form in which carbon is most suitable for the bacteria and describes the results of a series of experiments in which different materials were used as substrate. Synthetic acid mine drainage was passed through an anaerobic bioreactor that contained either compost or cow manure. The effluent water quality was monitored with respect to time and the effect of the substrate composition discussed.

Keywords: constructed wetland, bacteria, carbon, acid mine drainage, sulphate

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