Search results for: minimum spanning tree

Authors: Sunil Chandra, Triparna Barman, Vikas Gusain, Himanshu Rawat

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Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within the reserved forest, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differential burnt normalized ratio index (dNBR) approach that uses the burnt ratio values generated using Short Wave Infra Red (SWIR) band and Near Infra Red (NIR) bands of the Sentinel-2A image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel 2A bands. The training and testing data are generated from the sentinel-2A data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated in rugged terrain using spectral unmixing methods which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.

Keywords: dNBR, spectral unmixing, neural network, forest stratum

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Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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Authors: J. K. Kavitha, D. Manjula, U. Kanimozhi

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Mining frequent and high utility item sets have gained much significance in the recent years. When the data arrives sporadically, incremental and interactive rule mining and utility mining approaches can be adopted to handle user’s dynamic environmental needs and avoid redundancies, using previous data structures, and mining results. The dependence on recommendation systems has exponentially risen since the advent of search engines. This paper proposes a model for building a recommendation system that suggests frequent and high utility item sets over dynamic datasets for a cluster based location prediction strategy to predict user’s trajectories using the Efficient Incremental Rule Mining (EIRM) algorithm and the Fast Update Utility Pattern Tree (FUUP) algorithm. Through comprehensive evaluations by experiments, this scheme has shown to deliver excellent performance.

Keywords: data sets, recommendation system, utility item sets, frequent item sets mining

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Nemat Mohammadi, Yuki Nakayama

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After occurring Great East Japan earthquake and as a consequence the invasion of an extremely large Tsunami to the city, obligated many local governments to take into account certainly these kinds of issues. Poor preparation of local governments to deal with such kinds of disasters at that time and consequently lack of assistance delivery for local residents caused thousands of civilian casualties as well as billion dollars of economic damages. Those local governments who are responsible for governing such coastal areas, have to consider some countermeasures to deal with these natural disasters, prepare a comprehensive evacuation plan and contrive some feasible emergency plans for the purpose of victims’ reduction as much as possible. Under this evacuation plan, the local government should contemplate more about the traffic congestion during wide-area evacuation operation and estimate the minimum essential time to evacuate the whole city completely. This challenge will become more complicated for the government when the people who are affected by disasters are not only limited to the normal informed citizens but also some pregnant women, physically handicapped persons, old age citizens and foreigners or tourists who are not familiar with that conditions as well as local language are involved. The important issue to deal with this challenge is that how to inform these people to take a proper action right away noticing the Tsunami is coming. After overcoming this problem, next significant challenge is even more considerable. Next challenge is to evacuate the whole residents in a short period of time from the threated area to the safer shelters. In fact, most of the citizens will use their own vehicles to evacuate to the designed shelters and some of them will use the shuttle buses which are provided by local governments. The problem will arise when all residents want to escape from the threated area simultaneously and consequently creating a traffic jam on evacuation routes which will cause to prolong the evacuation time. Hence, this research mostly aims to calculate the minimum essential time to evacuate each region inside the threated area and find the evacuation start point for each region separately. This result will help the local government to visualize the situations and conditions during disasters and assist them to reduce the possible traffic jam on evacuation routes and consequently suggesting a comprehensive wide-area evacuation plan during natural disasters.

Keywords: BPR formula, disaster scenarios, evacuation completion time, wide-area evacuation

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Authors: Alan Luo, Hunter N. B. Moseley

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Many macromolecular structure entries in the Protein Data Bank (PDB) have a range of regional (localized) quality issues, be it derived from x-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy, or other experimental approaches. However, most PDB entries are judged by global quality metrics like R-factor, R-free, and resolution for x-ray crystallography or backbone phi-psi distribution statistics and average restraint violations for NMR. Regional quality is often ignored when PDB entries are re-used for a variety of structurally based analyses. The binding of ligands, especially ligands involved in energy metabolism, is of particular interest in many structurally focused protein studies. Using a regional quality metric that provides chemically interpretable information from electron density maps, a significant number of outliers in regional structural quality was detected across x-ray crystallographic PDB entries for proteins bound to biochemically critical ligands. In this study, a series of analyses was performed to evaluate both specific and general potential factors that could promote these outliers. In particular, these potential factors were the minimum distance to a metal ion, the minimum distance to a crystal contact, and the isotropic atomic b-factor. To evaluate these potential factors, Fisher’s exact tests were performed, using regional quality criteria of outlier (top 1%, 2.5%, 5%, or 10%) versus non-outlier compared to a potential factor metric above versus below a certain outlier cutoff. The results revealed a consistent general effect from region-specific normalized b-factors but no specific effect from metal ion contact distances and only a very weak effect from crystal contact distance as compared to the b-factor results. These findings indicate that no single specific potential factor explains a majority of the outlier ligand-bound regions, implying that human error is likely as important as these other factors. Thus, all factors, including human error, should be considered when regions of low structural quality are detected. Also, the downstream re-use of protein structures for studying ligand-bound conformations should screen the regional quality of the binding sites. Doing so prevents misinterpretation due to the presence of structural uncertainty or flaws in regions of interest.

Keywords: biomacromolecular structure, coenzyme, electron density discrepancy analysis, x-ray crystallography

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Authors: Farrukh Shahzad

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The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Keywords: Islamic resources, Muslim scholars, hadith, narrators, history, fiqh

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Authors: Methaq Algabr, Nabil Al-Hajj, Ameerh Jaber, Amtellah Alshotobi, Shaima'a Al-suryhi, Gadah Whaban, Nawal Alshehari

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Steam distillation of the essential oil of P. jaubertii was performed using a Clevenger apparatus. Essential oils were analyzed by gas chromatography-flame ionization detector (GC-FID) and gas chromatography coupled to chromatography–mass spectrometry (GC-MS). The major chemical components identified in P. jaubertii essential oil include carvotanacetone (63.975%), 1-methyl-1,2-propanedione (5.887%), 2,5-dimethoxy-para-cymene (3.303%) and ar-curcumene (3.276%). The antimicrobial activity of the essential oil of P. jaubertii was evaluated against all tested microorganisms. P. jaubertii essential oil inhibited all tested microorganisms except Escherichia coli with a minimum inhibitory concentration (MIC) of 5.0 μg/mL against Staphylococcus aureus.

Keywords: Pulicaria jaubertii, essential oil, antimicrobial, Carvotancetone

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Authors: Boce Zhang

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Strategic innovation of nanotechnology to promote food safety has drawn tremendous attentions among research groups, which includes the need for research support during the implementation of the Food Safety Modernization Act (FSMA) in the United States. There are urgent demands and knowledge gaps to the understanding of a) food-water-bacteria interface as for how pathogens persist and transmit during food processing and storage; b) minimum processing requirement needed to prevent pathogen cross-contamination in the food system. These knowledge gaps are of critical importance to the food industry. However, the lack of knowledge is largely hindered by the limitations of research tools. Our groups recently endeavored two novel engineering systems with biomimetics and microfluidics as a holistic approach to hazard analysis and risk mitigation, which provided unprecedented research opportunities to study pathogen behavior, in particular, contamination, and cross-contamination, at the critical food-water-pathogen interface. First, biomimetically-patterned surfaces (BPS) were developed to replicate the identical surface topography and chemistry of a natural food surface. We demonstrated that BPS is a superior research tool that empowers the study of a) how pathogens persist through sanitizer treatment, b) how to apply fluidic shear-force and surface tension to increase the vulnerability of the bacterial cells, by detaching them from a protected area, etc. Secondly, microfluidic devices were designed and fabricated to study the bactericidal kinetics in the sub-second time frame (0.1~1 second). The sub-second kinetics is critical because the cross-contamination process, which includes detachment, migration, and reattachment, can occur in a very short timeframe. With this microfluidic device, we were able to simulate and study these sub-second cross-contamination scenarios, and to further investigate the minimum sanitizer concentration needed to sufficiently prevent pathogen cross-contamination during the food processing. We anticipate that the findings from these studies will provide critical insight on bacterial behavior at the food-water-cell interface, and the kinetics of bacterial inactivation from a broad range of sanitizers and processing conditions, thus facilitating the development and implementation of science-based food safety regulations and practices to mitigate the food safety risks.

Keywords: biomimetic materials, microbial food safety, microfluidic device, nanotechnology

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Authors: Sudeepti Dayal, Neelesh Gupta

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Image abbreviation is utilized for reducing the size of a file without demeaning the quality of the image to an objectionable level. The depletion in file size permits more images to be deposited in a given number of spaces. It also minimizes the time necessary for images to be transferred. Storage of medical images is a most researched area in the current scenario. To store a medical image, there are two parameters on which the image is divided, regions of interest and non-regions of interest. The best way to store an image is to compress it in such a way that no important information is lost. Compression can be done in two ways, namely lossy, and lossless compression. Under that, several compression algorithms are applied. In the paper, two algorithms are used which are, discrete cosine transform, applied to non-region of interest (lossy), and discrete wavelet transform, applied to regions of interest (lossless). The paper introduces SPIHT (set partitioning hierarchical tree) algorithm which is applied onto the wavelet transform to obtain good compression ratio from which an image can be stored efficiently.

Keywords: Compression ratio, DWT, SPIHT, DCT

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Authors: L. S. Chathurika

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Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

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Authors: Fengmei Li, Li Xu, Guoliang Xia

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Whey acidic proteins (WAP) domain-containing proteins in crustacean are involved in innate immune response against microbial invasion. In the present study, a novel double WAP domain (DWD)-containing protein gene 3 was identified from Chinese mitten crab Eriocheir sinensis (designated EsDWD3) by expressed sequence tag (EST) analysis and PCR techniques. The full-length cDNA of EsDWD3 was of 1223 bp, consisting of a 5′-terminal untranslated region (UTR) of 74 bp, a 3′ UTR of 727 bp with a polyadenylation signal sequence AATAAA and a polyA tail, and an open reading frame (ORF) of 423 bp. The ORF encoded a polypeptide of 140 amino acids with a signal peptide of 22 amino acids. The deduced protein sequence EsDWD3 showed 96.4 % amino acid similar to other reported EsDWD1 from E. sinensis, and phylogenetic tree analysis revealed that EsDWD3 had closer relationships with the reported two double WAP domain-containing proteins of E. sinensis species.

Keywords: Chinese mitten crab, Eriocheir sinensis, cloning, double WAP domain-containing protein

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Authors: Mais Khader, Xingjie Wei

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This research sheds light on female entrepreneurs by providing new insights on the survival predictions of companies led by females in the UK. This study aims to build a predictive machine learning model of the survival of female-led & co-led small & medium enterprises (SMEs) in the UK over the period 2000-2020. The predictive model built utilised a combination of financial and non-financial features related to both companies and their directors to predict SMEs' survival. These features were studied in terms of their contribution to the resultant predictive model. Five machine learning models are used in the modelling: Decision tree, AdaBoost, Naïve Bayes, Logistic regression and SVM. The AdaBoost model had the highest performance of the five models, with an accuracy of 73% and an AUC of 80%. The results show high feature importance in predicting companies' survival for company size, management experience, financial performance, industry, region, and females' percentage in management.

Keywords: company survival, entrepreneurship, females, machine learning, SMEs

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Ibrahim Siddig Hamid, Ikram Mohamed Eltayeb

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Trachyspermum ammi belongs to the family Apiaceae, is used traditionally for the treatment of gastrointestinal ailments, lack of appetite and bronchial problems as well used as antiseptic, antimicrobial, antipyretic, febrifugal and in the treatment of typhoid fever. Peganum harmala belongs to the family Zygophyllaceae it has been reported to have an antibacterial activity and used to treat depression and recurring fevers. It also used to kill algae, bacteria, intestinal parasites and molds. In Sudan, the combination of two plants are traditionally used for the treatment of bacillary dysentery. Bacillary dysentery is caused by one or more types of Shigella species bacteria mainly Shigella dysenteri and shigella flexneri. Bacillary dysentery is mainly found in hot countries like Sudan with poor hygiene and sanitation. Bacillary dysentery causes sudden onset of high fever and chills, abdominal pain, cramps and bloating, urgency to pass stool, weight loss, and dehydration and if left untreated it can lead to serious complications including delirium, convulsions and coma. A serious infection like this can be fatal within 24 hours. The objective of this study is to investigate the in vitro susceptibility of Sh. flexneri and Sh. dysenteriae to the T. ammi and P. harmala. T. ammi and P. harmala were extracted by 96% ethanol using Soxhlet apparatus. The antimicrobial activity of the extracts was investigated according to the disc diffusion method. The discs were prepared by soaking sterilized filter paper discs in 20 microliter of serially diluted solutions of each plant extract with the concentrations (100, 50, 25, 12.5, 6.25mg/dl) then placing them on Muller Hinton Agar plates that were inoculated with bacterial suspension separately, the plates were incubated for 24 hours at 37c and the minimum inhibitory concentration of the extract which was the least concentration of the extract to inhibit fungal growth was determined. The results showed the high antimicrobial activity of T. ammi extract with an average diameter zone ranging from 18-20 mm and its minimum inhibitory concentration was found to be 25 mg/ml against the two shigella species. P. harmala extract was found to have slight antibacterial effect against the two bacteria. This result justified the Sudanese traditional use of Trachyspermum ammi plant for the treatment of bacillary dysentery.

Keywords: harmala, peganum, shigella, trachyspermum

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Authors: S. Yessengabulov, A. Uyzbayeva

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Residential buildings fund of Kazakhstan was built in the Soviet time about 35-60 years ago without considering energy efficiency measures. Currently, most of these buildings are in a rundown condition and fail to meet the minimum of hygienic, sanitary and comfortable living requirements. The paper aims to examine the reports of recent building energy survey activities in the country and provide a possible solution for retrofitting existing housing stock built before 1989 which could be applicable for building envelope in cold climate. Methodology also includes two-dimensional modeling of possible practical solutions and further recommendations.

Keywords: energy audit, energy efficient buildings in Kazakhstan, retrofit, two-dimensional conduction heat transfer analysis

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Authors: Asmaa Zaki M., Ahmed Abd El Aziz, Heba A. Fayed, Moustafa H. Aly

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ISLs are the most popular choice for deep space communications because these links are attractive alternatives to present day microwave links. This paper explored the allowable high data rate in this link over different orbits, which is affected by variation in modulation scheme and detector type. Moreover, the objective of this paper is to optimize and analyze the performance of ISL in terms of Q-factor and Minimum Bit Error Rate (Min-BER) based on different detectors comprising some parameters.

Keywords: free space optics (FSO), field of view (FOV), inter satellite link (ISL), optical wireless communication (OWC)

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Authors: T. Damak, S. Houidi, M. A. Ben Ayed, N. Masmoudi

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The Versatile Video Coding standard (VVC) is actually under development by the Joint Video Exploration Team (or JVET). An Adaptive Multiple Transforms (AMT) approach was announced. It is based on different transform modules that provided an efficient coding. However, the AMT solution raises several issues especially regarding the complexity of the selected set of transforms. This can be an important issue, particularly for a future industrial adoption. This paper proposed an efficient hardware implementation of the most used transform in AMT approach: the DCT II. The developed circuit is adapted to different block sizes and can reach a minimum frequency of 192 MHz allowing an optimized execution time.

Keywords: adaptive multiple transforms, AMT, DCT II, hardware, transform, versatile video coding, VVC

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Authors: Karmveer Sheoran

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To make wireless communication a vast success is to use sunlight for wireless communication. We can use sunlight in upper atmosphere to encode messages to efficiently use sunlight. This use of sunlight for wireless communication will need encoders which will encode sunlight according to our message and then resultant will be spread in all atmospheres wherever sunlight goes, it will take our messages with it. With minimum requirement of cost in equipment used at the edge of atmosphere is where sunlight is being encoded. In this way a very high efficient wireless communication system can be designed. On receiver side we will need light detectors which will detect sunlight variations and will finally give the information contained i it. Sunlight can be encoded at a very high speed that nobody will be annoyed by flickering. It will be most sophisticated and efficient wireless communication ever designed. There are far more possibilities in this sunlight communication. Let us call it “Sunlight Communication".

Keywords: sunlight communication, emerging trends, wireless communication, wifi

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Authors: Itai Kohavi, Wojciech Nowiak

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This article explores the stagnation of the Israeli -Palestinian peace negotiation process, and the reasons behind the failure of more than 12 international initiatives to resolve the conflict. Twenty-seven top members of the Israeli national security elite (INSE) were interviewed, including heads of the negotiation teams, the National Security Council, the Mossad, and other intelligence and planning arms. The interviewees provided their insights on the Israeli challenges in reaching a sustainable and stable peace agreement and in dealing with the international pressure on Israel to negotiate a peace agreement while preventing anti-Israeli UN decisions and sanctions. The findings revealed a decision tree, with red herring deception strategies implemented to postpone the negotiation process and to delay major decisions during the negotiation process. Beyond the possible applications for the Israeli – Palestinian conflict, the findings shed more light on the phenomenon of rational deception of allies in a negotiation process, a subject less frequently researched as compared with deception of rivals.

Keywords: deception, Israeli-Palestinian conflict, negotiation, red herring, terrorist state, treadmill negotiation

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Authors: Sameer Ansari, Suhas Nitsure

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Biomimicry has made a big move into the built environment by adapting nature's solutions to human designs and inventions. We can examine numerous aspects of the built environment right from generating energy, fed by rainwater and powered by sun to over all land use impacts. This paper discusses the potential of a man made building which will work for the welfare of humans and reduce the impact of the harmful environment on us which we ourselves created for us. Building services inspired by nature such as building walls from homeostasis in organisms, natural ventilation from termites, artificial aggregates from natural aggregates, solar panels from photosynthesis and building structure itself compared to tree as a cantilever. Environmental services such as using CO2 as a feedstock for construction related activities, using Ornilux glasses and  saving birds from collision with buildings, using prefabricated steel for fast building members- save time and also negligible waste as no formwork is used. Maglev inspired car elevators in building which is unique and giving all together new direction to technology.

Keywords: biomimicry, green technology, maglev car elevator, civil engineering

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Authors: Ibrahim Ilker Ozyigit, Ertugrul Filiz, Seda Birbilener, Semsettin Kulac, Zeki Severoglu

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In this study, we have performed genetic diversity analysis of Tilia tomentosa genotypes by using randomly amplified polymorphic DNA (RAPD) primers. A total of 28 genotypes, including 25 members from the urban ecosystem and 3 genotypes from forest ecosystem as outgroup were used. 8 RAPD primers produced a total of 53 bands, of which 48 (90.6 %) were polymorphic. Percentage of polymorphic loci (P), observed number of alleles (Na), effective number of alleles (Ne), Nei's (1973) gene diversity (h), and Shannon's information index (I) were found as 94.29 %, 1.94, 1.60, 0.34, and 0.50, respectively. The unweighted pair-group method with arithmetic average (UPGMA) cluster analysis revealed that two major groups were observed. The genotypes of urban and forest ecosystems showed a high genetic similarity between 28% and 92% and these genotypes did not separate from each other in UPGMA tree. Also, urban and forest genotypes clustered together in principal component analysis (PCA).

Keywords: Tilia tomentosa, genetic diversity, urban ecosystem, RAPD, UPGMA

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Authors: M. Mahdavi, M. Mohseni, R. Rafiei, H. Yari

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Environmental factors can deteriorate the automotive coatings significantly. Such as UV radiations, humidity, hot-cold shock and destructive chemical compounds. Furthermore, some natural materials such as bird droppings and tree gums have the potential to degrade the coatings as well. The present work aims to study the mechanism of degradation for two automotive refinish coating (PU based) systems exposed to two types of biological materials, i.e. Arabic gum and the simulated bird dropping, pancreatin. To reach this goal, effects of these biological materials on surface properties and appearance were studied using different techniques including digital camera, FT-IR spectroscopy, optical microscopy, and gloss measurements. In addition, the thermo-mechanical behavior of coatings was examined by DMTA. It was found that cross-linking had a crucial role on the biological resistance of clear coat. The higher cross-linking enhanced biological resistance.

Keywords: refinish clear coat, pancreatin, Arabic gum, cross-linking, biological degradation

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Authors: Lakhdari Wassima, Ouffroukh Ammar, Dahliz Abderrahmène, Soud Adila, Hammi Hamida, M’lik Randa

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Prospected palm groves of Oued Righ regions (Ouargla, Algeria) allowed us to observe sudden death of palm trees aged between 05 and 70 years. Field examinations revealed abnormal clinical signs with sometimes a quick death of affected trees. Entomologic investigations have confirmed the absence of phytophagous insects on dead trees. Further investigations by questioning farmers on the global management of palm groves visited (Irrigation, water quality used, soil type, etc.) did not establish any relationship between these aspects and the death of palm trees, which naturally pushed us to focus our investigations for research on fungal pathogens. Thus, laboratory studies were conducted to know the real causes of this phenomenon, 13 fungi were found on different parts of the dead palm trees. The flowing fungal types were identified: 1-Diplodia phoenicum, 2-Theilaviopsis paradoxa, 3-Phytophthora sp, 4-Helminthosporium sp, 5-Stemphylium botryosum, 6-Alternaria sp, 7-Aspergillus niger, 8-Aspergillus sp.

Keywords: palm tree, death, fungal pathogens, Oued Righ

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Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

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In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

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Authors: Hirbod Varasteh, Hamidreza Gohari Darabkhani

Abstract:

The global warming and its impact on climate change is one of main challenges for current century. Global warming is mainly due to the emission of greenhouse gases (GHG) and carbon dioxide (CO₂) is known to be the major contributor to the GHG emission profile. Whilst the energy sector is the primary source for CO₂ emission, Carbon Capture and Storage (CCS) are believed to be the solution for controlling this emission. Oxyfuel combustion (Oxy-combustion) is one of the major technologies for capturing CO₂ from power plants. For gas turbines, several Oxy-combustion power cycles (Oxyturbine cycles) have been investigated by means of thermodynamic analysis. NetPower cycle is one of the leading oxyturbine power cycles with almost full carbon capture capability from a natural gas fired power plant. In this manuscript, sensitivity analysis of the heat exchanger design in NetPower cycle is completed by means of process modelling. The heat capacity variation and supercritical CO₂ with gaseous admixtures are considered for multi-zone analysis with Aspen Plus software. It is found that the heat exchanger design has a major role to increase the efficiency of NetPower cycle. The pinch-point analysis is done to extract the composite and grand composite curve for the heat exchanger. In this paper, relationship between the cycle efficiency and the minimum approach temperature (∆Tmin) of the heat exchanger has also been evaluated.  Increase in ∆Tmin causes a decrease in the temperature of the recycle flue gases (RFG) and an overall decrease in the required power for the recycled gas compressor. The main challenge in the design of heat exchangers in power plants is a tradeoff between the capital and operational costs. To achieve lower ∆Tmin, larger size of heat exchanger is required. This means a higher capital cost but leading to a better heat recovery and lower operational cost. To achieve this, ∆Tmin is selected from the minimum point in the diagrams of capital and operational costs. This study provides an insight into the NetPower Oxy-combustion cycle’s performance analysis and operational condition based on its heat exchanger design.

Keywords: carbon capture and storage, oxy-combustion, netpower cycle, oxy turbine cycles, zero emission, heat exchanger design, supercritical carbon dioxide, oxy-fuel power plant, pinch point analysis

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Authors: Najmeh Mohsenifar, Narjes Mohsenifar, Abbas Kargar

Abstract:

In this paper, has been presented a stable method for predicting the ECG signals through the RBF neural networks, by the PSO algorithm. In spite of quasi-periodic ECG signal from a healthy person, there are distortions in electro cardiographic data for a patient. Therefore, there is no precise mathematical model for prediction. Here, we have exploited neural networks that are capable of complicated nonlinear mapping. Although the architecture and spread of RBF networks are usually selected through trial and error, the PSO algorithm has been used for choosing the best neural network. In this way, 2 second of a recorded ECG signal is employed to predict duration of 20 second in advance. Our simulations show that PSO algorithm can find the RBF neural network with minimum MSE and the accuracy of the predicted ECG signal is 97 %.

Keywords: electrocardiogram, RBF artificial neural network, PSO algorithm, predict, accuracy

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Authors: Yasser M. Saad, Amr A. El Hanafy, Saleh A. Alkarim, Hussein A. Almehdar, Elrashdy M. Redwan

Abstract:

Camels are substantial providers of transport, milk, sport, meat, shelter, security and capital in many countries, particularly in Saudi Arabia. Inter simple sequence repeat technique was used to detect the genetic variations among some camel breeds (Majaheim, Safra, Wadah, and Hamara). Actual number of alleles, effective number of alleles, gene diversity, Shannon’s information index and polymorphic bands were calculated for each evaluated camel breed. Neighbor-joining tree that re-constructed for evaluated these camel breeds showed that, Hamara breed is distantly related from the other evaluated camels. In addition, the polymorphic sites, haplotypes and nucleotide diversity were identified for some camelidae cox1 gene sequences (obtained from NCBI). The distance value between C. bactrianus and C. dromedarius (0.072) was relatively low. Analysis of genetic diversity is an important way for conserving Camelus dromedarius genetic resources.

Keywords: camel, genetics, ISSR, neighbor-joining

Procedia PDF Downloads 455

Authors: Manami Masuda, Mariko Era, Takayoshi Kawahara, Takahide Kanyama, Hiroshi Morita

Abstract:

Objectives: Fatty acid salts are a type of anionic surfactant and are produced from fatty acids and alkali. Moreover, fatty acid salts are known to have potent antibacterial activities. Acanthamoeba is ubiquitously distributed in the environment including sea water, fresh water, soil and even from the air. Although generally free-living, Acanthamoeba can be an opportunistic pathogen, which could cause a potentially blinding corneal infection known as Acanthamoeba keratitis. So, in this study, we evaluated the anti-amoeba activity of fatty acid salts and fatty acids to Acanthamoeba castellanii ATCC 30010. Materials and Methods: The antibacterial activity of 9 fatty acid salts (potassium butyrate (C4K), caproate (C6K), caprylate (C8K), caprate (C10K), laurate (C12K), myristate (C14K), oleate (C18:1K), linoleate (C18:2K), linolenate (C18:3K)) tested on cells of Acanthamoeba castellanii ATCC 30010. Fatty acid salts (concentration of 175 mM and pH 10.5) were prepared by mixing the fatty acid with the appropriate amount of KOH. The amoeba suspension mixed with KOH with a pH adjusted solution was used as the control. Fatty acids (concentration of 175 mM) were prepared by mixing the fatty acid with Tween 80 (20 %). The amoeba suspension mixed with Tween 80 (20 %) was used as the control. The anti-amoeba method, the amoeba suspension (3.0 × 104 cells/ml trophozoites) was mixed with the sample of fatty acid potassium (final concentration of 175 mM). Samples were incubated at 30°C, for 10 min, 60 min, and 180 min and then the viability of A. castellanii was evaluated using plankton counting chamber and trypan blue stainings. The minimum inhibitory concentration (MIC) against Acanthamoeba was determined using the two-fold dilution method. The MIC was defined as the minimal anti-amoeba concentration that inhibited visible amoeba growth following incubation (180 min). Results: C8K, C10K, and C12K were the anti-amoeba effect of 4 log-unit (99.99 % growth suppression of A. castellanii) incubated time for 180 min against A. castellanii at 175mM. After the amoeba, the suspension was mixed with C10K or C12K, destroying the cell membrane had been observed. Whereas, the pH adjusted control solution did not exhibit any effect even after 180 min of incubation with A. castellanii. Moreover, C6, C8, and C18:3 were the anti-amoeba effect of 4 log-unit incubated time for 60 min. C4 and C18:2 exhibited a 4-log reduction after 180 min incubation. Furthermore, the minimum inhibitory concentration (MIC) was determined. The MIC of C10K, C12K and C4 were 2.7 mM. These results indicate that C10K, C12K and C4 have high anti-amoeba activity against A. castellanii and suggest C10K, C12K and C4 have great potential for antimi-amoeba agents.

Keywords: Fatty acid salts, anti-amoeba activities, Acanthamoeba, fatty acids

Procedia PDF Downloads 464