Search results for: tree count

Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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Authors: Mohsen Negmeddin

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Throughout their history, ancient Egyptians had known several kinds and types of boats, which were made from two main kinds of materials, the local one, as the dried papyrus reeds and the local tree trunks, the imported one, as the boats which were made from Lebanon cedar tree trunks. A varied using of these boats, as the fish hunting small boats, the transportation and trade boats "Cargo Boats", as well as the ceremonial boats, and the warfare boats. The research is intending for the last one, the warfare boats and the river/maritime battles since the beginning of ancient Egyptian civilization at the pre-historic era up till the end of the second intermediate period, to reveal the kinds and types of those fighting ships before establishing the Egyptian navy at the beginning of the New Kingdome (1550-1770 B.C). Two methods will follow at this research, the mention of names and titles of these ships through the texts (ancient Egyptian language) resources, and the depiction of it at the scenes.

Keywords: the warfare boats, the maritime battles, the pre-historic era, the second intermediate period

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Authors: Amer Elgerwi, Abdelrazzag El-Magdoub, Abubakr El-Mahmoudy

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There are many bacterial infections affecting sheep that necessitates antibiotic intervention. Amoxicillin is among commonly used antibiotics in such case for its broad spectrum of activity. However, the side alterations in blood and organ function that may be associated during or after treatment are questionable. Therefore, the aim of the present study was to assess the possible alterations in blood parameters and organ function bio markers of sheep that may occur following intramuscular injection of amoxicillin. Amoxicillin has been administered intramuscularly to 10 sheep at a dosage regimen of 7 mg/kg of body weight for 5 successive days. Two types of blood samples (with and without anticoagulant) were collected from the jugular vein pre- and post-administration of the drug. Amoxicillin significantly (P < 0.001) increased total leukocyte count and (P < 0.05) absolute eosinophilic count when compared with those of the control samples. Aspartate aminotransferase, alkaline phosphatase and cholesterol were significantly (P < 0.05) higher than the corresponding control values. In addition, amoxicillin significantly (P < 0.05) increased blood urea nitrogen and creatinine but decreased phosphorus level when compared with those of prior-administration samples. These data may indicate that although the side changes caused by amoxicillin are minor in sheep, yet the liver and kidney functions should be monitored during its usage in therapy and it should be used with care for treatment of sheep with renal and/or hepatic impairments.

Keywords: amoxicillin, biogram, haemogram, sheep

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Authors: A. Khalique, T. Naseem, N. Haque, Z. Rasool

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The objective of current study was to investigate the effect of Bacillus subtilis PB6 (CloSTAT) as a probiotic in broilers. The corn-soybean based diet was divided into four treatment groups; T1 (basal diet with no probiotic and no Clostridium perfringens); T2 (basal diet challenged with C. perfringens without probiotic); T3 (basal diet challenged with C. perfringens having 0.05% probiotic); T4 (basal diet challenged with C. perfringens having 0.1% probiotic). Every treatment group had four replicates with 24 birds each. Body weight and feed intake were measured on weekly basis, while ileal bacterial count was recorded on day-28 following Clostridium perfringens challenge. The 0.1% probiotic treatment showed 7.2% increase in average feed intake (P=0.05) and 8% increase in body weight compared to T2. In 0.1% treatment body weight was 5% higher than T3 (P=0.02). It was also observed that 0.1% treatment had improved feed conversion ratio (1.77) on 6^th week. No effect of treatment was observed on mortality and ileal bacterial count. The current study indicated that 0.1% use of probiotic had positive response in C. perfringens challenged broilers.

Keywords: Bacillus subtilis PB6, antibiotic growth promoters, Clostridium perfringens, broilers

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Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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Authors: Suhera M. Aburawi, Habiba A. El Jaafari, Soad A. Treesh, Abdulssalam M. Abu-Aisha, Faisal S. Alwaer, Reda A. Eltubuly, Medeha Elghedamsi

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Introduction: Infertility is a source of psychological, and sometimes social, stress on parents who desire to have children. Formaldehyde is used chiefly as disinfectant, preservative and in the chemical synthesis. The medical uses of formaldehyde are limited, but focused especially on laboratory use. Selenium is an essential trace mineral element for human; it is essential for sperm function and male fertility. Selenium deficiency has been linked to reproductive problems in animals. Objectives: To investigate the prophylactic and curative effect of selenium on male infertility induced by formaldehyde using male albino mice. Method: Forty male albino mice were used, weight 25-30 gm. Five groups of male mice (n=8) were used. Group 1 was daily administered water for injection (5ml/kg) for five days, group 2 was daily administered selenium (100 μg/kg) for five days, group 3 was daily administered formaldehyde (30mg/kg) for five days, group 4 (prophylaxis) was daily administered a combination of formaldehyde and selenium for five days, while group 5 (curative) was daily administered formaldehyde for five days followed by daily administration of selenium for the next five days. Intraperitoneal administration was adopted. At the end of the administration, seminal fluid was collected from vas deferens. Sperm count, morphology and motility were scored; histopathological screening of genital system was carried out. SPSS was applied for comparing groups. Results and conclusion: It was found that formaldehyde toxicity did not change the sperm count and percentage of motile sperm; unhealthy sperm was increased, while healthy sperm was decreased. Formaldehyde produces degeneration/damage to the male mice genital system. Selenium alone produce an increase in sperm count, volume of seminal fluid and the percentage of motile sperm. Selenium has prophylactic and curative effects against formaldehyde-induce genital system toxicity. Future work is recommended to find out if selenium protective effect is through antioxidant or other mechanisms.

Keywords: infertility, formaldehyde, selenium, male mice

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Authors: Faranak Beigmohammadi, Seyed Hadi Peighambardoust, Seyed Jamaledin Peighambardoust

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This study undertakes to investigate the ability of different kinds of nanocomposite films made of cloisite-30B with different percentages of silver and copper oxide nanoparticles incorporated into a low-density polyethylene (LDPE) polymeric matrix by a melt mixing method in order to inhibit the growth of microorganism in soy burger. The number of surviving cell of the total count was decreased by 3.61 log and mold and yeast diminished by 2.01 log after 8 weeks storage at 18 ± 0.5°C below zero, whilst pure LDPE did not has any antimicrobial effect. A composition of 1.3 % cloisite 30B-Ag and 2.7 % cloisite 30B-CuO for total count and 0 % cloisite 30B-Ag and 4 % cloisite 30B-CuO for yeast & mold gave optimum points in combined design test in Design Expert 7.1.5. Suitable microbial models were suggested for retarding above microorganisms growth in soy burger. To validation of optimum point, the difference between the optimum point of nanocomposite film and its repeat was not significant (p<0.05) by one-way ANOVA analysis using SPSS 17.0 software, while the difference was significant for pure film. Migration of metallic nanoparticles into a food stimulant was within the accepted safe level.

Keywords: modeling, nanocomposite film, packaging, soy burger

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Authors: Maria Lucia G. Lourenco, Viviane Y. Hibaru, Keylla H. N. P. Pereira, Fabiana F. Souza, Joao C. P. Ferreira, Simone B. Chiacchio, Luiz H. A. Machado

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Isosporiasis is an affliction caused by coccidial protozoa belonging to genera Isospora spp. or Cystoisospora spp., which may parasitize the small and large intestines of dogs, of which neonates and young animals present higher risk of infection. This study aims at reporting a case of isosporiasis in neonate Pitbull dogs, as well as the diagnosis and treatment. Seven Pitbull puppies were admitted to the São Paulo State University (UNESP) Veterinary Hospital, Botucatu, São Paulo, Brazil, with history of yellowish diarrhea without mucus or blood for the past two days. The animals were five days old. The history of the mother, a primiparous two-year-old, revealed that she was properly vaccinated, not de-wormed and did not present diarrhea. The clinical examination revealed that the neonates weighted between 308 and 360 grams, and presented normal reflexes, moderate dehydration, body temperatures between 36.8 and 37.2 ºC, blood sugar between 103 and 124 mg/dL and normal appetite. A full blood count and a parasitology assay were performed to aid in the diagnosis. The full blood count detected eosinophilia, without any other relevant alterations. The parasitology assay (Willis-Molly & Faust) revealed the presence of Cystoisospora spp. The treatment was instituted with heated fluid therapy with Ringer’s Lactate (4 mL/100 g, subcutaneous) and antibiotic therapy with sulfamethoxazole-trimethoprim (15 mg/kg, orally) every 12 hours for ten days. The mother and other dogs that came in contact with the newborns were also treated. The environment was disinfected for 10 minutes with 1.6% quaternary ammonium. After 10 days, the newborns presented normal clinical signs and no alterations in the full blood count. Isosporiasis is an affliction with high mortality rates in litters that should be diagnosed and treated as soon as possible to increase the survival rates in these patients.

Keywords: Cystoisospora spp., neonatal infection, puppies, diarrhea,

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Authors: Eun-Ji Lee, Hye-Sung Park, Chan-Jung Lee, Won-Sik Kong

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We analyzed the DNA sequence of the ITS (Internal Transcribed Spacer) region of the 18S ribosomal gene and compared it with the gene sequence of T. fuciformis and Hypoxylon sp. in the BLAST database. The sequences of collected T. fuciformis and Hypoxylon sp. have over 99% homology in the T. fuciformis and Hypoxylon sp. sequence BLAST database. In order to select the optimal medium for T. fuciformis, five kinds of a medium such as Potato Dextrose Agar (PDA), Mushroom Complete Medium (MCM), Malt Extract Agar (MEA), Yeast extract (YM), and Compost Extract Dextrose Agar (CDA) were used. T. fuciformis showed the best growth on PDA medium, and Hypoxylon sp. showed the best growth on MCM. So as to investigate the optimum pH and temperature, the pH range was set to pH4 to pH8 and the temperature range was set to 15℃ to 35℃ (5℃ degree intervals). Optimum culture conditions for the T. fuciformis growth were pH5 at 25℃. Hypoxylon sp. were pH6 at 25°C. In order to confirm the most suitable carbon source, we used fructose, galactose, saccharose, soluble starch, inositol, glycerol, xylose, dextrose, lactose, dextrin, Na-CMC, adonitol. Mannitol, mannose, maltose, raffinose, cellobiose, ethanol, salicine, glucose, arabinose. In the optimum carbon source, T. fuciformis is xylose and Hypoxylon sp. is arabinose. Using the column test, we confirmed sawdust a suitable for T. fuciformis, since the composition of sawdust affects the growth of fruiting bodies of T. fuciformis. The sawdust we used is oak tree, pine tree, poplar, birch, cottonseed meal, cottonseed hull. In artificial cultivation of T. fuciformis with sawdust medium, T. fuciformis and Hypoxylon sp. showed fast mycelial growth on mixture of oak tree sawdust, cottonseed hull, and wheat bran.

Keywords: cultivation, optimal condition, tremella fuciformis, nutritional source

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Authors: Caleb B. Sagwa, Tobias O. Okeno, Alexander K. Kahi

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Dairy cattle production plays an important role in the Kenyan economy. However, high incidences of mastitis is a major setback to the productivity in this industry. The current dairy cattle breeding objective in Kenya does not include mastitis resistance, mainly because the economic value of mastitis resistance has not been determined. Therefore this study aimed at estimating the economic value of mastitis resistance in dairy cattle in Kenya. Initial input parameters were obtained from literature on dairy cattle production systems in the tropics. Selection index methodology was used to derive the economic value of mastitis resistance. Somatic cell count (SCC) was used an indicator trait for mastitis resistance. The economic value was estimated relative to milk yield (MY). Economic values were assigned to SCC in a selection index such that the overall gain in the breeding goal trait was maximized. The option of estimating the economic value for SCC by equating the response in the trait of interest to its index response was considered. The economic value of mastitis resistance was US $23.64 while maximum response to selection for MY was US $66.01. The findings of this study provide vital information that is a pre-requisite for the inclusion of mastitis resistance in the current dairy cattle breeding goal in Kenya.

Keywords: somatic cell count, milk quality, payment system, breeding goal

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: breast cancer, mitotic count, machine learning, convolutional neural networks

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Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Feras Hanandeh, Majdi Shannag

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This research studies the different factors that could affect the Faculty of Information Technology in Hashemite University students’ accumulative average. The research paper verifies the student information, background, their academic records, and how this information will affect the student to get high grades. The student information used in the study is extracted from the student’s academic records. The data mining tools and techniques are used to decide which attribute(s) will affect the student’s accumulative average. The results show that the most important factor which affects the students’ accumulative average is the student Acceptance Type. And we built a decision tree model and rules to determine how the student can get high grades in their courses. The overall accuracy of the model is 44% which is accepted rate.

Keywords: data mining, classification, extracting rules, decision tree

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Authors: Jovana M. Ćirković, Aleksandar M. Radojković, Sanja Z. Perać, Jelena N. Jovanović, Zorica M. Branković, Slobodan D. Milanović, Ivan Lj. Milenković, Jovan N. Dobrosavljević, Nemanja V. Simović, Vanja M. Tadić, Ana R. Žugić, Goran O. Branković

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The protection of forests is a national interest and of strategic importance in every country. The spongy moth (Lymantria dispar) is a damaging invasive pest that can weaken and destroy trees by defoliating them. Chemical pesticides commonly used to protect forests against spongy moths not only have a negative impact on terrestrial and aquatic organisms/ecosystems but also often fail to provide significant protection. Therefore, many eco-friendly alternatives have been considered. Within this research, a new biopesticide was developed based on the method of nanoencapsulation of plant extracts in a biopolymer matrix, which provides a slow release of the active components during a substantial time period. The antifeedant activity of plant extracts of common (Fraxinus excelsior L.), manna (F. ornus L.) ash tree, and the tree of heaven Ailanthus altissima (Mill.) was tested on the spongy moth (Lymantria dispar L, 1758) larvae. To test the antifeedant activity of these compounds, the choice and non-choice tests in laboratory conditions for different plant extract concentrations (0.01, 0.1, 0.5, and 1 % v/v) were carried out. In both cases, the best results showed formulations based on the tree of heaven and common ash for the concentration of 1%, with deterioration indices of 163 and 132, respectively. The main benefit of these formulations is their versatility, effectiveness, prolonged effect, and because they are completely environmentally acceptable. Therefore, they can be considered for suppression of the spongy moth in forest ecosystems.

Keywords: Ailanthus altissima (Mill.), Fraxinus excelsior L., encapsulation, Lymantria dispar

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Authors: Yogesh Bacchaw, Ashish Dabade

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Nowadays oral health is raising concern in society. Acid producing microorganisms changes the oral pH and creates a favorable environment for microbial growth. This growth not only promotes dental decay but also bad breath. Generally Recognized As Safe (GRAS) listed component was incorporated in chewing gum as an antimicrobial agent. The chewing gum produced exhibited up to 9 hours of antimicrobial activity against oral microflora. The toxicity of GRAS component per RACC value of chewing gum was negligible as compared to actual toxicity level of GRAS component. The antibacterial efficiency of chewing gum was tested by using total plate count (TPC) and colony forming unit (CFU). Nine hours were required to microflora to reach TPC/CFU of before chewing gum consumption. This chewing gum not only provides mouth freshening activity but also helps in lowering dental decay, bad breath, and enamel whitening.

Keywords: colony forming unit (CFU), chewing gum, generally recognized as safe (GRAS), microbial growth, microorganisms, oral health, RACC, total plate count (TPC), antimicrobial agent, enamel whitening, oral pH

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Chariton Christou, David Cornwell

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Production Sharing Contract (PSC) is the type of contract that is being used widely in our time. The financial crisis made the governments tightfisted and they do not have the resources to participate in a development of a field. Therefore, more and more countries introduce the PSC. The companies have the power and the money to develop the field with their own way. The main problem is the transparency of oil and gas companies especially in the PSC and how this can be achieved. Many discussions have been made especially in the U.K. What we are suggesting is a dynamic financial simulation with the help of a flow meter. The flow meter will count the production of each field every day (it will be installed in a pipeline). The production will be the basic input of the simulation. It will count the profit, the costs and more according to the information of the flow meter. In addition it will include the terms of the contract and the costs that have been paid. By all these parameters the simulation will be able to present in real time the information of a field (taxes, employees, R-factor). By this simulation the company will share some information with the government but not all of them. The government will know the taxes that should be paid and what is the sharing percentage of it. All of the other information could be confidential for the company. Furthermore, oil company could control the R-factor by changing the production each day to maximize its sharing percentages and as a result of this the profit. This idea aims to change the way that governments 'control' oil companies and bring a transparency evolution in the industry. With the help of a simulation every country could be next to the company and have a better collaboration.

Keywords: production sharing contracts, transparency, simulation

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Authors: Ghada S. Moussa

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Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

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Authors: Ian Marc G. Cabugsa, Kim Ryan Won, Kareem Mamac, Manuel Dee, Merlita Garcia

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An optimized cacao fermentation technique was developed for the cacao farmers of Davao City Philippines. Cacao samples with weights ranging from 150-250 kilograms were collected from various cacao farms in Davao City and Zamboanga City Philippines. Different fermentation techniques were used starting with design of the sweat box, prefermentation conditionings, number of days for fermentation and number of turns. As the beans are being fermented, its temperature was regularly monitored using a digital thermometer. The resultant cacao beans were assessed using physical and chemical means. For the physical assessment, the bean cut test, bean count tests, and sensory test were used. Quantification of theobromine, caffeine, and antioxidants in the form of equivalent quercetin was used for chemical assessment. Both the theobromine and caffeine were analyzed using HPLC method while the antioxidant was analyzed spectrometrically. To come up with the best fermentation procedure, the different assessment were given priority coefficients wherein the physical tests – taste test, cut, and bean count tests were given priority over the results of the chemical test. The result of the study was an optimized fermentation protocol that is readily adaptable and transferable to any cacao cooperatives or groups in Mindanao or even Philippines as a whole.

Keywords: cacao, fermentation, HPLC, optimization, Philippines

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Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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Authors: I. Ahmad, A. Hannan, S. Ahmad, M. Asif, M. F. Nawaz, M. A. Tanvir, M. F. Azhar

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During this research, a comprehensive survey of tree growing areas of Faisalabad district of Pakistan was conducted to observe the symptoms, spectrum, occurrence and severity of A. nilotica and E. camaldulensis decline. Objective of current research was to investigate specific fungal pathogens involved in decline of A. nilotica and E. camaldulensis. For this purpose, infected roots, bark, neck portion, stem, branches, leaves and infected soils were collected to identify associated fungi. Potato dextrose agar (PDA) and Czepak dox agar media were used for isolations. Identification of isolated fungi was done microscopically and different fungi were identified. During survey of urban locations of Faisalabad, disease incidence on Kikar and Eucalyptus was recorded as 3.9-7.9% and 2.6-7.1% respectively. Survey of Agroforest zones of Faisalabad revealed decline incidence on kikar 7.5% from Sargodha road while on Satiana and Jhang road it was not planted. In eucalyptus trees, 4%, 8% and 0% disease incidence was observed on Jhang road, Sargodha road and Satiana road respectively. The maximum fungus isolated from the kikar tree was Drechslera australiensis (5.00%) from the stem part. Aspergillus flavus also gave the maximum value of (3.05%) from the bark. Alternaria alternata gave the maximum value of (2.05%) from leaves. Rhizopus and Mucor spp. were recorded minimum as compared to the Drechslera, Alternaria and Aspergillus. The maximum fungus isolated from the Eucalyptus tree was Armillaria luteobubalina (5.00%) from the stem part. The other fungi isolated were Macrophamina phaseolina and A. niger.

Keywords: decline, frequency of mycoflora, A. nilotica and E. camaldulensis, Drechslera australiensis, Armillaria luteobubalina

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Authors: Ayuko Itsuki, Sachiyo Aburatani

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Soil neutral sugar contents in Kasuga-yama Hill Primeval Forest, which is a World Heritage Site in Nara, Japan consisting of lowland laurel-leaved forest where natural conditions have been preserved for more than 1,000 years, were examined using the two-step hydrolysis to clarify the source of the neutral sugar and relations with the neutral sugar constituted the soil organic matter and the microbial biomass. Samples were selected from the soil (L, F, H and A horizons) surrounding laurel-leaved (BB-1) and Carpinus japonica (BB-2 and PW) trees for analysis. The neutral sugars were one factor of increasing the fungal and bacterial biomass in the laurel-leaved forest soil (BB-1). The more neutral sugar contents in the Cryptomeria japonica forest soil (PW) contributed to the growth of the bacteria and fungi than those of in the Cryptomeria japonica forest soil (BB-2). The neutral sugars had higher correlation with the numbers of bacteria and fungi counted by the dilution plate count method than by the direct microscopic count method. The numbers of fungi had higher correlation with those of bacteria by the dilution plate method.

Keywords: forest soil, neutral sugars, soil organic matter, two-step hydrolysis

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Authors: Miguel Mellado, Cecilia Zapata

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Goats can be exploited in harsh environments due to their capacity to adjust to limited quantity and quality forage sources. In these environments, leguminous trees can be used as supplementary feeds as foliage and fruits of these trees can contribute to maintain or improve production efficiency in ruminants. The objective of this study was to determine the nutritional value of three leguminous trees heavily selected by goats in a xerophyllous shrubland. Chemical composition and in vitro dry matter disappearance (IVDMD) of leaves and pods from leucaena (Leucaena leucocephala), mesquite (Prosopis laevigata) and huisache (Acacia farnesiana) is presented. Crude protein (CP) ranged from 17.3% for leaves of huisache to 21.9% for leucaena. The neutral detergent fiber (NDF) content ranged from 39.0 to 40.3 with no difference among fodder threes. Across tree species, mean IVDMD was 61.6% for pods and 52.2% for leaves. IVDMD for leaves was highest (P < 0.01) for leucaena (54.9%) and lowest for huisache (47.3%). Condensed tannins in an acetonic extract were highest for leaves of huisache (45.3 mg CE/g DM) and lowest for mesquite (25.9 mg CE/g DM). Pods and leaves of huisache presented the highest number of secondary metabolites, mainly related to hydrobenzoic acid and flavonols; leucaena and mesquite presented mainly flavonols and anthocyanins. It was concluded that leaves and pods of leucaena, mesquite and huisache constitute valuable forages for ruminant livestock due to its low fiber, high CP levels, moderate in vitro fermentation characteristics and high mineral content. Keywords: Fodder tree; ruminants; secondary metabolites; minerals; tannins

Keywords: fodder tree, ruminants, secondary metabolites, minerals, tannins

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Authors: Azene Zenebe

Abstract:

Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.

Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science

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Authors: Bisi-Johnson, Mary A., Hamzart A. Oyelade, Kehinde A. Adediran, Saheed A. Akinola

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Geophagic and cosmetic clays are among potential nano-material which occur naturally and are of various forms. The use of these nano-clays is a common practice in both rural and urban areas mostly due to tradition and medicinal reasons. These naturally occurring materials can be valuable sources of nano-material by serving as nano-composites. The need to ascertain the safety of these materials is the motivation for this research. Physical Characterization based on the hue value and microbiological qualities of the nano-clays were carried out. The Microbial analysis of the clay samples showed considerable contamination with both bacteria and fungi with fungal contaminants taking the lead. This observation may not be unlikely due to the ability of fungi species to survive harsher growth conditions than bacteria. 'Atike pupa' showed no bacterial growth. The clay with the largest bacterial count was Calabash chalk (Igbanke), while that with the highest fungal count was 'Eko grey'. The most commonly isolated bacteria in this study were Clostridium spp. and Corynebacterium spp. while fungi included Aspergillus spp. These results are an indication of the need to subject these clay materials to treatments such as heating before consumption or topical usage thereby ascertaining their safety.

Keywords: nano-material, clay, microorganism, quality

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Authors: Hadi Ardiny, Amir Mohammad Beigzadeh

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Through the utilization of a combination of various sensors and data fusion methods, the detection of potential nuclear threats can be significantly enhanced by extracting more information from different data. In this research, an experimental and modeling approach was employed to track a radioactive source by combining a surveillance camera and a radiation detector (NaI). To run this experiment, three mobile robots were utilized, with one of them equipped with a radioactive source. An algorithm was developed in identifying the contaminated robot through correlation between camera images and camera data. The computer vision method extracts the movements of all robots in the XY plane coordinate system, and the detector system records the gamma-ray count. The position of the robots and the corresponding count of the moving source were modeled using the MCNPX simulation code while considering the experimental geometry. The results demonstrated a high level of accuracy in finding and locating the target in both the simulation model and experimental measurement. The modeling techniques prove to be valuable in designing different scenarios and intelligent systems before initiating any experiments.

Keywords: nuclear threats, radiation detector, MCNPX simulation, modeling techniques, intelligent systems

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Authors: Marwa Elkalla, E. Ali Abdelfadil, Ali. Mohamed. M. Sami, Ali M. Abdel-Monem

Abstract:

To assess the impact of the blood collection technique on clinical pathology markers and to establish reference intervals, a study was performed using normal, healthy C57BL/6 mice. Both sexes were employed, and they were randomly assigned to different groups depending on the phlebotomy technique used. The blood was drawn in one of four ways: intracardiac (IC), caudal vena cava (VC), caudal vena cava (VC) plus a peritoneal collection of any extravasated blood, or retroorbital phlebotomy (RO). Several serum biochemistries, such as a liver function test, a complete blood count with differentials, and a platelet count, were analysed from the blood and serum samples analysed. Red blood cell count, haemoglobin (p >0.002), hematocrit, alkaline phosphatase, albumin, total protein, and creatinine were all significantly greater in female mice. Platelet counts, specific white blood cell numbers (total, neutrophil, lymphocyte, and eosinophil counts), globulin, amylase, and the BUN/creatinine ratio were all greater in males. The VC approach seemed marginally superior to the IC approach for the characteristics under consideration and was linked to the least variation among both sexes. Transaminase levels showed the greatest variation between study groups. The aspartate aminotransferase (AST) values were linked with decreased fluctuation for the VC approach, but the alanine aminotransferase (ALT) values were similar between the IC and VC groups. There was a lot of diversity and range in transaminase levels between the MC and RO groups. We found that the RO approach, the only one tested that allowed for repeated sample collection, yielded acceptable ALT readings. The findings show that the test results are significantly affected by the phlebotomy technique and that the VC or IC techniques provide the most reliable data. When organising a study and comparing data to reference ranges, the ranges supplied here by collection method and sex can be utilised to determine the best approach to data collection. The authors suggest establishing norms based on the procedures used by each individual researcher in his or her own lab.

Keywords: clinical, pathology, blood, effect

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi

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Background:-Due to the essential role of the foot in movement, foot disorders (FDs) have significant impacts on activity and quality of life. Many studies confirmed the association between FDs and demographic characteristics. On the other hand, recent advances in data collection and statistical analysis led to an increase in the volume of databases. Analysis of patient’s data through the decision tree can be used to explore the relationship between demographic characteristics and FDs. Significance of the study: This study aimed to investigate the relationship between demographic characteristics with common FDs. The second purpose is to better inform foot intervention, we classify FDs based on demographic variables. Methodologies: We analyzed 2323 subjects with pes-planus (PP), pes-cavus (PC), hallux-valgus (HV) and plantar-fasciitis (PF) who were referred to a foot therapy clinic between 2015 and 2021. Subjects had to fulfill the following inclusion criteria: (1) weight between 14 to 150 kilogram, (2) height between 30 to 220, (3) age between 3 to 100 years old, and (4) BMI between 12 to 35. Medical archives of 2323 subjects were recorded retrospectively and all the subjects examined by an experienced physician. Age and BMI were classified into five and four groups, respectively. 80% of the data were randomly selected as training data and 20% tested. We build a decision tree model to classify FDs using demographic characteristics. Findings: Results demonstrated 981 subjects from 2323 (41.9%) of people who were referred to the clinic with FDs were diagnosed as PP, 657 (28.2%) PC, 628 (27%) HV and 213 (9%) identified with PF. The results revealed that the prevalence of PP decreased in people over 18 years of age and in children over 7 years. In adults, the prevalence depends first on BMI and then on gender. About 10% of adults and 81% of children with low BMI have PP. There is no relationship between gender and PP. PC is more dependent on age and gender. In children under 7 years, the prevalence was twice in girls (10%) than boys (5%) and in adults over 18 years slightly higher in men (62% vs 57%). HV increased with age in women and decreased in men. Aging and obesity have increased the prevalence of PF. We conclude that the accuracy of our approach is sufficient for most research applications in FDs. Conclusion:-The increased prevalence of PP in children is probably due to the formation of the arch of the foot at this age. Increasing BMI by applying high pressure on the foot can increase the prevalence of this disorder in the foot. In PC, the Increasing prevalence of PC from women to men with age may be due to genetics and innate susceptibility of men to this disorder. HV is more common in adult women, which may be due to environmental reasons such as shoes, and the prevalence of PF in obese adult women may also be due to higher foot pressure and housekeeping activities.

Keywords: decision tree, demographic characteristics, foot disorders, machine learning

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Authors: Chuan-Ching Sue, Kai-Chun Chuang

Abstract:

Peer-to-Peer (P2P) live streaming systems still suffer a challenge when thousands of new peers want to join into the system in a short time, called flash crowd, and most of new peers suffer long start-up delay. Recent studies have proposed a slot-based user access control mechanism, which periodically determines a certain number of new peers to enter the system, and a user batch join mechanism, which divides new peers into several tree structures with fixed tree size. However, the slot-based user access control mechanism is difficult for accurately determining the optimal time slot length, and the user batch join mechanism is hard for determining the optimal tree size. In this paper, we propose a structured access control (SAC) mechanism, which constructs new peers to a multi-layer mesh structure. The SAC mechanism constructs new peer connections layer by layer to replace periodical access control, and determines the number of peers in each layer according to the system’s remaining upload bandwidth and average video rate. Furthermore, we propose an analytical model to represent the behavior of the system growth if the system can utilize the upload bandwidth efficiently. The analytical result has shown the similar trend in system growth as the SAC mechanism. Additionally, the extensive simulation is conducted to show the SAC mechanism outperforms two previously proposed methods in terms of system growth and start-up delay.

Keywords: peer-to-peer, live video streaming system, flash crowd, start-up delay, access control

Procedia PDF Downloads 305