Search results for: comparative morphological features

Authors: Shivam Yadav, Neelam Atri

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Cyanobacteria, the photosynthetic prokaryotes are indispensable components of paddy soil contribute substantially to the nitrogen economy however often appended with metal load. They are well known to play crucial roles in maintenance of soil fertility and rice productivity. Nickel is one such metal that plays a vital role in the cellular physiology, however at higher concentrations it exerts adverse effects. Arsenic is another toxic metalloid that negatively affects the cyanobacterial proliferation. However species-specific comparative responses under As and Ni is largely unknown. The present study focuses on the comparative effects of nickel (Ni2+) and arsenite (As(III)) on two diazotrophic cyanobacterial species (Anabaena doliolum and Anabaena sp. PCC7120) in terms of antioxidative aspects. Oxidative damage measured in terms of lipid peroxidation and peroxide content was significantly higher after As(III) than Ni treatment as compared to control. Similarly, all the studied enzymatic and non-enzymatic parameters of antioxidative defense system except glutathione reductase (GR) showed greater induction against As(III) than Ni. Moreover, integrating comparative analysis of all studied parameters also demonstrated interspecies variation in terms of stress adaptive strategies reflected through higher sensitivity of Anabaena doliolum over Anabaena PCC7120.

Keywords: antioxidative system, arsenic, cyanobacteria, nickel

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Authors: M. Areekijseree, W. Pongsawat, M. Pumipaiboon, C. Thepsithar, S. Sengsai, T. Chuen-Im

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Morphological interaction of porcine cumulus-oocyte complexes (pCOCs) was investigated on in vitro condition using electron microscope (SEM and TEM). The totals of 1,923 oocytes were round in shape, surrounded by zona pellucida with layer of cumulus cells ranging between 59.29-202.14 µm in size. They were classified into intact-, multi-, partial cumulus cell layer oocyte, and completely denuded oocyte, at the percentage composition of 22.80% 32.70%, 18.60%, and 25.90 % respectively. The pCOCs classified as intact- and multi cumulus cell layer oocytes were further culturing at 37°C with 5% CO2, 95% air atmosphere and high humidity for 44 h in M199 with Earle’s salts supplemented with 10% HTFCS, 2.2 mg/mL NaHCO3, 1 M Hepes, 0.25 mM pyruvate, 15 µg/mL porcine follicle-stimulating hormone, 1 µg/mL LH, 1µg/mL estradiol with ethanol, and 50 µg/mL gentamycin sulfate. On electron microscope study, cumulus cells were found to stick their processes to secrete substance from the sac-shape end into zona pellucida of the oocyte and also communicated with the neighboring cells through their microvilli on the beginning of incubation period. It is believed that the cumulus cells communicate with the oocyte by inserting the microvilli through this gap and embedded in the oocyte cytoplasm before secreting substance, through the sac-shape end of the microvilli, to inhibit primary oocyte development at the prophase I. Morphological changes of the complexes were observed after culturing for 24-44 h. One hundred percentages of the cumulus layers were expanded and cumulus cells were peeling off from the oocyte surface. In addition, the round-shape cumulus cells transformed themselves into either an elongate shape or a columnar shape, and no communication between cumulus neighboring cells. After 44 h of incubation time, diameter of oocytes surrounded by cumulus cells was larger than 0 h incubation. The effect of hormones in culture medium is exerted by their receptors present in porcine oocyte. It is likely that all morphological changes of the complexes after hormone treatment were to allow maturation of the oocyte. This study demonstrated that the association of hormones in M199 could promote porcine follicle activation in 44 h in vitro condition. This culture system should be useful for studying the regulation of early follicular growth and development, especially because these follicles represent a large source of oocytes that could be used in vitro for cell technology.

Keywords: cumulus cells, electron microscopy, in vitro, porcine oocyte

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Authors: Benjawan Rangsikamol, Chutimet Srinilta

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This research paper deals with extraction of Thai character features using the proposed histogram projection so as to improve the recognition performance. The process starts with transformation of image files into binary files before thinning. After character thinning, the skeletons are entered into the proposed extraction using histogram projection (horizontal and vertical) to extract unique features which are inputs of the subsequent recognition step. The recognition rate with the proposed extraction technique is as high as 97 percent since the technique works very well with the idiosyncrasies of Thai characters.

Keywords: character recognition, histogram projection, multilayer perceptron, Thai character features extraction

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Abubakar Ibrahim, Muhammad Garba, Adelusi Oluwaseyi Abiodun

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Website development and administration has already become a very critical issue in many organisations due to the fact that most of the organisations have embraced the use of the internet to deliver their services and products seamlessly but even with huge advantages of being present on the internet, and website are very difficult and expensive to develop and maintain. In recent years, a number of open-source web Contents Management System (CMS) have been developed to allow organisations to internally develop and maintain their websites without the need to hire professional web developers to provide such services for them. This study aimed at performing a comparative analysis of the two most widely used open source CMS Joomla and wordpress, based on the following criteria: intuitiveness, responsiveness richness in features, meeting expectation, fill secured, ease of navigation, structure, and performance. Two identical applications were developed using the said CMS. In this study, a purposive sampling technique was adopted to administer the questionnaires, and a total of 50 respondents were selected to surf sites and fill out a questionnaire based on their experience on the two sites. Gt-matrix was used to carry out further analysis of the applications. The result shows that Joomla is the best for developing an e-commerce site due to the fact that it is best in terms of performance, better structure, meeting user expectations, rich features, and functionality. Even though Wordpress is intuitive and easy for navigation. One can still argue that Joomla is superior.

Keywords: open source, content management system, Joomla, WordPress

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Authors: B. Ben Amara, H. Mhiri Sellami

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Serious games adoption is increasing in multiple fields, including health, education, and business. In the same way, many research studied serious games (SGs) for various purposes such as classification, positive impacts, or learning outcomes. Although most of these research examine SG characteristics (SGCs) for conducting their studies, to author’s best knowledge, there is no consensus about features neither in number not in the description. In this paper, we conduct a literature review to collect essential game attributes regardless of the application areas and the study objectives. Firstly, we aimed to define Common SGCs (CSGCs) that characterize the game aspect, by gathering features having the same meanings. Secondly, we tried to identify specific features related to the application area or to the study purpose as a serious aspect. The findings suggest that any type of SG can be defined by a number of CSGCs depicting the gaming side, such as adaptability and rules. In addition, we outlined a number of specific SGCs describing the 'serious' aspect, including specific needs of the domain and indented outcomes. In conclusion, our review showed that it is possible to bridge the research gap due to the lack of consensus by using CSGCs. Moreover, these features facilitate the design and development of successful serious games in any domain and provide a foundation for further research in this area.

Keywords: serious game characteristics, serious games common aspects, serious games features, serious games outcomes

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Authors: Hyojin Lim, Cuong Nguyen Khac, Ho-Youl Jung

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In this paper, we propose moving object detection method which is helpful for driver to safely take his/her car out of parking lot. When moving objects such as motorbikes, pedestrians, the other cars and some obstacles are detected at the rear-side of host vehicle, the proposed algorithm can provide to driver warning. We assume that the host vehicle is just before departure. Gaussian Mixture Model (GMM) based background subtraction is basically applied. Pre-processing such as smoothing and post-processing as morphological filtering are added.We examine “which color space has better performance for detection of moving objects?” Three color spaces including RGB, YCbCr, and Y are applied and compared, in terms of detection rate. Through simulation, we prove that RGB space is more suitable for moving object detection based on background subtraction.

Keywords: gaussian mixture model, background subtraction, moving object detection, color space, morphological filtering

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Authors: Christopher J. Johnston

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This paper presents the finding of a research study in which novice (first and second year) elementary teachers (grades Kindergarten – six) evaluated various mathematics Virtual Manipulatives, websites, and Applets (tools) for use in mathematics instruction. Participants identified the criteria they used for evaluating these types of resources and provided recommendations for or against five pre-selected tools. During the study, participants participated in three data collection activities: (1) A brief Likert-scale survey which gathered information about their attitudes toward technology use; (2) An identification of criteria for evaluating technology tools; and (3) A review of five pre-selected technology tools in light of their self-identified criteria. Data were analyzed qualitatively using four theoretical categories (codes): Software Features (41%), Mathematics (26%), Learning (22%), and Motivation (11%). These four theoretical categories were then grouped into two broad categories: Content and Instruction (Mathematics and Learning), and Surface Features (Software Features and Motivation). These combined, broad categories suggest novice teachers place roughly the same weight on pedagogical features as they do technological features. Implications for mathematics teacher educators are discussed, and suggestions for future research are provided.

Keywords: mathematics education, novice teachers, technology, virtual manipulatives

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Authors: Amandeep Kaur, Ns Atri, Munruchi Kaur

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Mushrooms have shaped our environment in ways that we are only beginning to understand. The weather patterns, topography, flora and fauna of Punjab state in India create favorable growing conditions for thousands of species of mushrooms, but the complete region was unexplored when it comes to coprophilous mushrooms growing on herbivorous dung. Coprophilous mushrooms are the most specialized fungi ecologically, which germinate and grow directly on different types of animal dung or on manured soil. In the present work, the diversity of coprophilous mushrooms' of Family Psathyrellaceae of the order Agaricales is explored, their relationship to the human world is sketched out, and their supreme significance to life on this planet is revealed. During the investigation, different dung localities from 16 districts of Punjab state have been explored for the collection of material. The macroscopic features of the collected mushrooms were documented on the Field key. The hand cut sections of the various parts of carpophore, such as pileus, gills, stipe and the basidiospores details, were studied microscopically under different magnification. Various authentic publications were consulted for the identification of the investigated taxa. The classification, authentic names and synonyms of the investigated taxa are as per the latest version of Dictionary of Fungi and the MycoBank. The present work deals with the taxonomy of 81 collections belonging to 39 species spread over 05 coprophilous genera, namely Psathyrella, Panaeolus, Parasola, Coprinopsis, and Coprinellus of family Psathyrellaceae. In the text, the investigated taxa have been arranged as they appear in the key to the genera and species investigated. In this work, have been thoroughly examined for their macroscopic, microscopic, ecological, and chemical reaction details. The authors dig deeper to give indication of their ecology and the dung type where they can be obtained. Each taxon is accompanied by a detailed listing of its prominent features and an illustration with habitat photographs and line drawings of morphological and anatomical features. Taxa are organized as per their status in the keys, which allow easy recognition. All the taxa are compared with similar taxa. The study has shown that dung is an important substrate which serves as a favorable niche for the growth of a variety of mushrooms. This paper shows an insight what short-lived coprophilous mushrooms can teach us about sustaining life on earth!

Keywords: abundance, basidiomycota, biodiversity, seasonal availability, systematics

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Authors: Mateusz Hermyt, Pawel Kaczmarek, Weronika Rupik

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The egg tooth is a crucial structure during hatching of lizards and snakes. In contrast to birds, turtles, crocodiles, and monotremes, egg tooth of squamate reptiles is a true tooth sharing common features of structure and development with all the other teeth of vertebrates. The egg tooth; however, due to its function, exhibits structural differences in relation to regular teeth. External morphology seems to be important in the context of phylogenetic relationships within Squamata but up to date, there is scarce information concerning structure and development of the egg tooth at the submicroscopical level. In presented studies detailed analysis of the egg tooth development in grass snake has been performed with the usage of light (including fluorescent), transmission and scanning electron microscopy. Grass snake embryo’s heads have been used in our studies. Grass snake is common snake species occurring in most of Europe including Poland. The grass snake is characterized by the presence of single unpaired egg tooth (as in most squamates) in contrast to geckos and dibamids possessing paired egg teeth. Studies show changes occurring on the external morphology, tissue and cellular levels of differentiating egg tooth. The egg tooth during its development changes its curvature. Initially, faces directly downward and in the course of its differentiation, it gradually changes to rostro-ventral orientation. Additionally, it forms conical dentinal protrusions on the sides. Histological analysis showed that egg tooth development occurs in similar steps in relation to regular teeth. It undergoes initiation, bud, cap and bell morphological stages. Analyses focused on describing morphological changes in hard tissues (mainly dentin and predentin) of egg tooth and in cells which enamel organ consists of. It included: outer enamel epithelium, stratum intermedium, inner enamel epithelium, odontoblasts, and cells of dental pulp. All specimens used in the study were captured according to the Polish regulations concerning the protection of wild species. Permission was granted by the Local Ethics Commission in Katowice (41/2010; 87/2015) and the Regional Directorate for Environmental Protection in Katowice (WPN.6401.257.2015.DC).

Keywords: hatching, organogenesis, reptile, Squamata

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Authors: Bharatendra Rai

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Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

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Authors: Shuo Liu, Dan Liu

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In the field of named entity recognition, most of the research has been conducted around simple entities. However, for nested named entities, which still contain entities within entities, it has been difficult to identify them accurately due to their boundary ambiguity. In this paper, a hierarchical recognition model is constructed based on the grammatical structure and semantic features of Chinese text for boundary calculation based on lexical features. The analysis is carried out at different levels in terms of granularity, semantics, and lexicality, respectively, avoiding repetitive work to reduce computational effort and using the semantic features of words to calculate the boundaries of entities to improve the accuracy of the recognition work. The results of the experiments carried out on web-based microblogging data show that the model achieves an accuracy of 86.33% and an F1 value of 89.27% in recognizing nested named entities, making up for the shortcomings of some previous recognition models and improving the efficiency of recognition of nested named entities.

Keywords: coarse-grained, nested named entity, Chinese natural language processing, word embedding, T-SNE dimensionality reduction algorithm

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Naser Safdarian, Nader Jafarnia Dabanloo

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In this paper we used four features i.e. Q-wave integral, QRS complex integral, T-wave integral and total integral as extracted feature from normal and patient ECG signals to detection and localization of myocardial infarction (MI) in left ventricle of heart. In our research we focused on detection and localization of MI in standard ECG. We use the Q-wave integral and T-wave integral because this feature is important impression in detection of MI. We used some pattern recognition method such as Artificial Neural Network (ANN) to detect and localize the MI. Because these methods have good accuracy for classification of normal and abnormal signals. We used one type of Radial Basis Function (RBF) that called Probabilistic Neural Network (PNN) because of its nonlinearity property, and used other classifier such as k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) and Naive Bayes Classification. We used PhysioNet database as our training and test data. We reached over 80% for accuracy in test data for localization and over 95% for detection of MI. Main advantages of our method are simplicity and its good accuracy. Also we can improve accuracy of classification by adding more features in this method. A simple method based on using only four features which extracted from standard ECG is presented which has good accuracy in MI localization.

Keywords: ECG signal processing, myocardial infarction, features extraction, pattern recognition

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Authors: Khader S. Al-Aidmat, Venus W. Samawi

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Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

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Authors: Chieh-Fu Chang, Wan-Hsin Hsieh

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We have proposed a novel scheme— iterative word-extension (IWE) to enhance the cliff effect of Reed-Solomon codes regarding the error performance at a specific Eb/N0. The scheme can be readily extended to block codes and the important properties of IWE are further investigated here. In order to select proper block codes specifying the desired cliff Eb/N0, the associated features of IWE are explored. These properties and features grant IWE ability to enhance security regarding the received Eb/N0 in physical layer so that IWE scheme can cooperate with the traditional presentation layer approach — cryptography, to meet the secure requirements in diverse applications. The features and feasibility of IWE scheme in satellite communication are finally discussed.

Keywords: security, IWE, cliff effect, space communications

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Authors: Harun Sepet, Necmettin Tarakcioglu

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The present study investigated the impact strength and fracture mechanism of nano-CaCO3 and nanoclay reinforced HDPE nanocomposites by using Charpy impact test. The nano-CaCO3 and nanoclay reinforced HDPE granules were prepared by the melt blending method using a compounder system, which consists of industrial banbury mixer, single screw extruder and granule cutting in industrial-scale. The nano-CaCO3 and nanoclay reinforced HDPE granules were molded using an injection-molding machine as plates, and then impact samples were cut by using punching die from the nanocomposite plates. As a result of impact experiments, nano-CaCO3 and nanoclay reinforced HDPE nanocomposites were determined to have lower impact energy level than neat HDPE. Also, the impact strength of HDPE further decreased by addition nanoclay compared to nano-CaCO3. The occurred fracture areas with the impact were detected by SEM examination. It is understood that fracture surface morphology changes when nano-CaCO3 and nanoclay ratio increases. The fracture surface changes were examined to determine the fracture mechanism of nano-CaCO3 and nanoclay reinforced HDPE nanocomposites.

Keywords: charpy, HDPE, industrial scale nano-CaCO3, nanoclay, nanocomposite

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Authors: Ranajoy Bhattcharyya

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We estimate international product cycles as shifting product spaces by using 1976 to 2010 UN Comtrade data on all differentiated tradable products in all countries. We use a product space approach to identify the representative product baskets of high-, middle and low-income countries and then use these baskets to identify the patterns of change in comparative advantage of countries over time. We find evidence of a product cycle in two senses: First, high-, middle- and low-income countries differ in comparative advantage, and high-income products migrate to the middle-income basket. A similar pattern is observed for middle- and low-income countries. Our estimation of the lag shows that middle-income countries tend to quickly take up the products of high-income countries, but low-income countries take a longer time absorbing these products. Thus, the gap between low- and middle-income countries is considerably higher than that between middle- and high-income nations.

Keywords: product cycle, comparative advantage, representative product basket, ex-post data

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Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

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The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.

Keywords: emotion recognition, facial recognition, signal processing, machine learning

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Authors: Sharon Kun-Amornpong

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In this paper, ASEAN financial integration will be discussed from the perspective of the rule of law. The methodology of the paper is comparative regionalism. It will compare the role of the rule of law in ASEAN financial integration with that of the European Union with particular focuses on, for example, institutions and values. The paper argues that in the realm of financial integration, the rule of law is one of the most important factors that could help strengthen and promote financial integration in ASEAN. This is despite the fact that the ‘ASEAN Way’ emphasises non-interference and utilises a consensus-based cooperation rather than formal institutions. Nevertheless, the rule of law for ASEAN financial integration should be situated in its own historical, cultural, and political contexts. In addition, in the case of ASEAN, the rule of law cannot take root if it does not come from the demand of the people in this region. For instance, a reform or creation of legal institutions should not be imposed by international financial institutions. The paper will conclude that law has a normative force. It could shape expectation of market participants and promote deeper financial integration if norms that the law generates have become a significant norm in the society or industry.

Keywords: Association of Southeast Asian Nations, ASEAN, comparative regionalism, financial integration, the rule of law

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Authors: Belgherbi Aicha, Bessaid Abdelhafid

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In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. The first and fundamental step in all these studies is the semi-automatic liver and spleen segmentation that is still an open problem. In this paper, a semi-automatic liver and spleen segmentation method by the mathematical morphology based on watershed algorithm has been proposed. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological to extract the liver and spleen. The second step consists to improve the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce the over-segmentation problem by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. The aim of this work is to develop a method for semi-automatic segmentation liver and spleen based on watershed algorithm, improve the accuracy and the robustness of the liver and spleen segmentation and evaluate a new semi-automatic approach with the manual for liver segmentation. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work. The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts. Liver segmentation has achieved the sensitivity and specificity; sens Liver=96% and specif Liver=99% respectively. Spleen segmentation achieves similar, promising results sens Spleen=95% and specif Spleen=99%.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Andrea Schiffauerova, Amnah Alzeyoudi

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This paper studies patterns of innovation within national constitutional context. Its objective is to examine national systems of innovation in biotechnology in six leading innovative countries: the US, Japan, Germany, the UK, France and Canada. The framework proposed for this purpose consists of specific factors considered critical for the development of national systems of innovation, which are industry size, innovative activities, area of specialization, industry structure, national policy, the level of government intervention, the stock of knowledge in universities and industries, knowledge transfer from universities to industry and country-specific conditions for start-ups. The paper then uses the framework to provide detailed cross-country comparisons while highlighting particular features of national institutional context which affect the creation and diffusion of scientific knowledge within the system. The study is primarily based on the extensive survey of literature and it is complemented by the quantitative analysis of the patent data extracted from the United States Patent and Trademark Office (USPTO). The empirical analysis provides numerous insights and greatly complements the data gained from the literature and other sources. The final cross-country comparative analysis identifies three patterns followed by the national innovation systems in the six countries. The proposed cross-country relative positioning analysis may help in drawing policy implications and strategies leading to the enhancement of national competitive advantage and innovation capabilities of nations.

Keywords: comparative analysis, framework, national systems of innovation, patent analysis, United States Patent and Trademark Office (USPTO)

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Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova

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We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.

Keywords: cybersecurity, epidemiology, cyber epidemiology, malware

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Authors: Nalanda Roy

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The project will offer a fresh and critical perspective into the Tokyo Trial judgment led by the Indian Jurist Dr. Radha Binod Pal. The project will focus on the Third World Approach to International Law (TWAIL) methodology to examine the relevance of international law from the post-colonial perspectives. The project will analyze Pal’s dissenting arguments from a new and comparative perspective, apply for work from other disciplines, and create an understanding of the significance of the historic judgment considering its contemporary relevance, and fill in the gaps that exist in the call for global justice.

Keywords: Tokyo trial, third world, judgment, international law

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Abigail Tan, Heng Liang Tan, Vanessa Ding, James Hui, Eng Hin Lee, Andre Choo

Abstract:

Introduction: Comparative oncology investigates the similarities in spontaneous carcinogenesis between humans and animals, in order to identify treatments that can benefit these patients. Companion animals (CA), like canines and felines, are of special interest when it comes to studying human cancers due to their exposure to the same environmental factors and develop tumours with similar features. The purpose of this study is to explore the cross-reactivity of monoclonal antibodies (mAbs) across cancers in humans and CA. Material and Methods: A panel of CA mAbs generated in the lab was screened on multiple human cancer cell lines through flow cytometry to identify for positive binders. Shortlisted candidates were then characterised by biochemical and functional assays e.g., antibody-drug conjugate (ADC) and western blot assays, including glycan studies. Results: Candidate mAb KP52 was generated from whole-cell immunisation using feline mammary carcinoma. KP52 showed strong positive binding to human cancer cells, such as breast cancer and ovarian cancer. Furthermore, KP52 demonstrated strong killing ( > 50%) as an ADC with Saporin as the payload. Western blot results revealed the molecular weight of the antigen targets to be approximately 45kD and 50kD under reduced conditions. Glycan studies suggest that the epitope is glycan in nature, specifically an O-linked glycan. Conclusion: Candidate mAb KP52 has a therapeutic potential as an ADC against feline mammary cancer, human ovarian cancer, human mammary cancer, human pancreatic cancer, and human gastric cancer.

Keywords: ADC, comparative oncology, mAb, therapeutic

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Authors: Sami Michael Ayodele

Abstract:

Cordyceps are members of the fungi family Cordycepitaceae which are formally in Clavicipitaceae. They parasitize the larvae and adults of different susceptible arthropods. They are highly priced and have been reported to be highly medicinal. Cordyceps have been used for centuries in traditional medicine in China and other Asian countries. Survey studies were carried out to determine the presence of Cordyceps and another entomopathogenic fungal floral in North Central Nigeria for two consecutive years. Thirty samples were collected, twenty-eight were identified, and two were unidentified. Most identified species belong to Ophiocordyceps species (20samples), Cordyceps species (4samples) and Isaria species (4samples). The species identified were: Cordyceps pseudomilitaris, Cordyceps tuberculata, Cordyceps cylindrical, Ophiocordyceps nutans, O. criminals, O. oxycephala, O. kniphofioides and Isaria sinclairii. The morphological and microscopic features of the collected and identified species were similar to those reported in other countries. This is the first official report on the presence of Cordyceps species in Nigeria. Further collections from different ecological regions of Nigeria will show the richness of the floral diversity of these entomopathogenic and medicinal mushrooms in Nigeria.

Keywords: cordyceps, entomopathogenic, medicinal, North Central, Nigeria

Procedia PDF Downloads 62

Authors: Kholoud Abdelmaksoud, Mahmoud Emam, Wael Al-Metwaly

Abstract:

Egypt is known as cradle of civilization due to its ancient history and archeological sites, but Egypt possess also a cradle of Geo-sites, which qualify it to be listed as one of the most important Geo-heritage sites all over the country. Geology and landscape in Abu-Roash area is considered as one of the most important geological places (geo-sites) inside Cairo which help us to know and understand geology and geologic processes, so the area is used mainly for geological education purposes, also the area contain an archeological sites; pyramid complex, tombs, and Coptic monastery which give the area unique importance. Abu-Roash area is located inside Cairo 9 km north of the Giza Pyramids, which make the accessibility to the area easy and safe, the geology of Abu-Roash constitutes a complex Cretaceous sedimentary succession mass with showing outstanding tectonic features (Syrian Arc system event), these features are considered as a Geo-heritage, which will be the main designation of ‘Geo-parks’ establishing. The research is dealing with the numerous geo-sites found in the area, and its geologic and archeological importance, the relation between geo-sites and archeology, also the research proposed a detailed maps for these sites depicting Geo-routes and the hazardous places surrounding Abu-Roash area. The research is proposing a new proposal not applied in Egypt before, establishing a Geo-park, to promote this unique geo-heritage from hazardous factors and anthropogenic effects, also it will offer geo-educational opportunities to the general public and to the scientific community, enhancement of Geo-tourism which will be linked easily with the Ancient Egyptian tourism, it will also provide a significant economic benefit to Abu-Roash residential area. Finally, the research recommends that The United Nations Educational, Scientific and Cultural Organizations promote conservation of geological and geo-morphological heritage to list this area for its importance under the umbrella of geo-parks.

Keywords: geo-park, geo-sites, Abu-roash, archaeological sites, geo-tourism

Procedia PDF Downloads 274

Authors: S. Mohajer , R. M. Taha, M. Adel

Abstract:

Developing our knowledge of when pineapple roots grow can lead to improved water, fertilizer applications, and more precise culture management. This paper presents current understanding of morphological traits in pineapple roots, highlighting studies using incubation periods and various solid MS media treated with different sucrose concentrations and pH, which directly assess in vitro environmental factors. Rooting parameters had different optimal sucrose concentrations and incubation periods. All shoots failed to root in medium supplemented with sucrose at 5 g/L and no roots formed within the first 45 days in medium enriched with sucrose at 10 g/L. After 75 days, all shoots rooted in medium enriched with 10 and 20 g/L sucrose. Moreover, MS medium supplied with 20 g/L sucrose resulted in the longest and the highest number of roots with 27.3 mm and 4.7, respectively. Root function, such as capacity for P and N uptake, declined rapidly with root length. As a result, the longer the incubation period, the better the rooting responses would be.

Keywords: environmental factors, in vitro rooting, pineapple, tissue culture

Procedia PDF Downloads 358