Using TRACE and SNAP Codes to Establish the Model of Maanshan PWR for SBO Accident

In this research, TRACE code with the interface code-SNAP was used to simulate and analyze the SBO (station blackout) accident which occurred in Maanshan PWR (pressurized water reactor) nuclear power plant (NPP). There are four main steps in this research. First, the SBO accident data of Maanshan NPP were collected. Second, the TRACE/SNAP model of Maanshan NPP was established by using these data. Third, this TRACE/SNAP model was used to perform the simulation and analysis of SBO accident. Finally, the simulation and analysis of SBO with mitigation equipments was performed. The analysis results of TRACE are consistent with the data of Maanshan NPP. The mitigation equipments of Maanshan can maintain the safety of Maanshan in the SBO according to the TRACE predictions.

Using RASCAL Code to Analyze the Postulated UF6 Fire Accident

In this research, the RASCAL code was used to simulate and analyze the postulated UF6 fire accident which may occur in the Institute of Nuclear Energy Research (INER). There are four main steps in this research. In the first step, the UF6 data of INER were collected. In the second step, the RASCAL analysis methodology and model was established by using these data. Third, this RASCAL model was used to perform the simulation and analysis of the postulated UF6 fire accident. Three cases were simulated and analyzed in this step. Finally, the analysis results of RASCAL were compared with the hazardous levels of the chemicals. According to the compared results of three cases, Case 3 has the maximum danger in human health.

Composite Kernels for Public Emotion Recognition from Twitter

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.

Manufacturing Process of S-Glass Fiber Reinforced PEKK Prepregs

The aim of this study is to investigate the fundamental science/technology related to novel S-glass fiber reinforced polyether- ketone-ketone (GF/PEKK) composites and to gain insight into bonding strength and failure mechanisms. Different manufacturing techniques to make this high-temperature pre-impregnated composite (prepreg) were conducted i.e. mechanical deposition, electrostatic powder deposition, and dry powder prepregging techniques. Generally, the results of this investigation showed that it was difficult to control the distribution of the resin powder evenly on the both sides of the fibers within a specific percentage. Most successful approach was by using a dry powder prepregging where the fibers were coated evenly with an adhesive that served as a temporary binder to hold the resin powder in place onto the glass fiber fabric.

Automatic Extraction of Arbitrarily Shaped Buildings from VHR Satellite Imagery

Satellite imagery is one of the emerging technologies which are extensively utilized in various applications such as detection/extraction of man-made structures, monitoring of sensitive areas, creating graphic maps etc. The main approach here is the automated detection of buildings from very high resolution (VHR) optical satellite images. Initially, the shadow, the building and the non-building regions (roads, vegetation etc.) are investigated wherein building extraction is mainly focused. Once all the landscape is collected a trimming process is done so as to eliminate the landscapes that may occur due to non-building objects. Finally the label method is used to extract the building regions. The label method may be altered for efficient building extraction. The images used for the analysis are the ones which are extracted from the sensors having resolution less than 1 meter (VHR). This method provides an efficient way to produce good results. The additional overhead of mid processing is eliminated without compromising the quality of the output to ease the processing steps required and time consumed.

A Decade of Creating an Alternative Banking System in Tanzania: The Current State of Affairs of Islamic Banks

The concept of financial inclusion has been tabled in the whole world where practitioners, academicians, policy makers and economists are working hard to look for the best possible opportunities in order to enable the whole society to be in the banking cycle. The Islamic banking system is considered to be one of the said opportunities. Countries like the United Kingdom, United States of America, Malaysia, Saudi Arabia, the whole of the United Arab Emirates and many African countries have accommodated the aspect of Islamic banking in the conventional banking system as one of the financial inclusion strategies. This paper tries to analyse the current state of affairs of the Islamic Banking system in Tanzania in order to understand the improvement of the provision of Islamic banking products and services in the said country. The paper discusses the historical background of the banking system in Tanzania, the level of penetration of banking products and services and the coming of the Islamic banking system in the country. Furthermore, the paper discusses banking regulatory bodies, legal instruments governing banking operations as well as number of legal challenges facing Islamic banking operations in the country. Following a critical literature review, the paper discovered that there is no legal instrument which talks about the introduction and provision of Islamic banking system in Tanzania. Furthermore, the Islamic banking system was considered as a banking product which is absolutely incorrect because Islamic banking is considered to be as a banking system of its own. In addition to that, it has been discovered that lack of a proper regulatory system and legal instruments to harmonize the conventional and Islamic banking systems has resulted in the closure of one Islamic window in the country, which in the end affects the credibility of the newly introduced banking system. In its conclusive remarks, the paper suggests that Tanzania should work on all legal challenges affecting the smooth operations of the Islamic banking system. This can be in a way of adopting various Islamic banking legal models which are used in countries like Malaysia and others, or a borrowing legal harmonization process which has been adopted by the UK, Uganda, Nigeria and Kenya.

Fabrication of Poly(Ethylene Oxide)/Chitosan/Indocyanine Green Nanoprobe by Co-Axial Electrospinning Method for Early Detection

Early detection of cancer could save human life and quality in insidious cases by advanced biomedical imaging techniques. Designing targeted detection system is necessary in order to protect of healthy cells. Electrospun nanofibers are efficient and targetable nanocarriers which have important properties such as nanometric diameter, mechanical properties, elasticity, porosity and surface area to volume ratio. In the present study, indocyanine green (ICG) organic dye was stabilized and encapsulated in polymer matrix which polyethylene oxide (PEO) and chitosan (CHI) multilayer nanofibers via co-axial electrospinning method at one step. The co-axial electrospun nanofibers were characterized as morphological (SEM), molecular (FT-IR), and entrapment efficiency of Indocyanine Green (ICG) (confocal imaging). Controlled release profile of PEO/CHI/ICG nanofiber was also evaluated up to 40 hours.

Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Classification of Computer Generated Images from Photographic Images Using Convolutional Neural Networks

This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.

Liquid Fuel Production via Catalytic Pyrolysis of Waste Oil

Pyrolysis of waste oil is an effective process to produce high quality liquid fuels. In this work, pyrolysis experiments of waste oil over Y zeolite were carried out in a semi-batch reactor under a flow of nitrogen at atmospheric pressure and at different reaction temperatures (350-450 oC). The products were gas, liquid fuel, and residue. Only liquid fuel was further characterized for its composition and properties by using gas chromatography, thermogravimetric analyzer, and bomb calorimeter. Experimental results indicated that the pyrolysis reaction temperature significantly affected both yield and composition distribution of pyrolysis oil. An increase in reaction temperature resulted in increased fuel yield, especially gasoline fraction. To obtain high amount of fuel, the optimal reaction temperature should be higher than 350 oC. A presence of Y zeolite in the system enhanced the cracking activity. In addition, the pyrolysis oil yield is proportional to the catalyst quantity.

Dead Bodies that Matter: A Consensual Qualitative Research on the Lived Experience of Embalmers

Embalmers are widely recognized as someone who mends the cadavers, but behind that is a great deal of work. These professionals are competent in physiology, chemicals, and cosmetics. Another is that such professionals face cadavers day-to-day. Given this background, the researchers intended to find out the lived experience of embalmers. The purpose of the present study is to discover the essence of the work of these professionals, to determine factors that influence their work, the depths of their life and on how the occupation affects upon physical, emotional-mental, spiritual, moral and social aspects. The researchers used the Consensual Qualitative Research, and eight embalmers, seven male and one female, from Manila and Bulacan were interviewed using open-ended questions and were used to triangulate the results. A primary research team conducted the consensus of domains, and an external auditor reviewed the results. A personal data sheet was also used, this helped the researchers group the respondents according to demographic profile. The results of the consensual qualitative research investigation revealed the four core components of the lived experience of embalmers which are motivation, struggles, acceptance, and contentment. The results revealed core components that play an important role in their everyday lives as an embalmer, daily hardships, and source of their pleasures. The present study will help future researchers, embalmers, and society.

Multimodal Database of Emotional Speech, Video and Gestures

People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Records of Lepidopteron Borers (Lepidoptera) on Stored Seeds of Indian Himalayan Conifers

Many of the regeneration failures in conifers are often being attributed to heavy insect attack and pathogens during the period of seed formation and under storage conditions. Conifer berries and seed insects occur throughout the known range of the hosts and also limit the production of seed for nursery stock. On occasion, even entire seed crops are lost due to insect attacks. The berry and seeds of both the species have been found to be infected with insects. Recently, heavy damage to the berry and seeds of Juniper and Chilgoza Pine was observed in the field as well as in stored conditions, leading to reduction in the viability of seeds to germinate. Both the species are under great threat and regeneration of the species is very low. Due to lack of adequate literature, the study on the damage potential of seed insects was urgently required to know the exact status of the insect-pests attacking seeds/berries of both the pine species so as to develop pest management practices against the insect pests attack. As both the species are also under threat and are fighting for survival, so the study is important to develop management practices for the insect-pests of seeds/berries of Juniper and Chilgoza pine so as to evaluate in the nursery, as these species form major vegetation of their distribution zones. A six-year study on the management of insect pests of seeds of Chilgoza revealed that seeds of this species are prone to insect pests mainly borers. During present investigations, it was recorded that cones of are heavily attacked only by Dioryctria abietella (Lepidoptera: Pyralidae) in natural conditions, but seeds which are economically important are heavily infected, (sometimes up to 100% damage was also recorded) by insect borer, Plodia interpunctella (Lepidoptera: Pyralidae) and is recorded for the first time ‘to author’s best knowledge’ infesting the stored Chilgoza seeds. Similarly, Juniper berries and seeds were heavily attacked only by a single borer, Homaloxestis cholopis (Lepidoptera: Lecithoceridae) recorded as a new report in natural habitat as well as in stored conditions. During the present investigation details of insect pest attack on Juniper and Chilgoza pine seeds and berries was observed and suitable management practices were also developed to contain the insect-pests attack.

Big Brain: A Single Database System for a Federated Data Warehouse Architecture

Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Sub-Lethal Effects of Thiamethoxam and Pirimicarb on Life-Table Parameters of Diaeretiella rapae (Hymenoptera: Braconidae), Parasitoid of Lipaphis erysimi (Hemiptera: Aphididae)

Integrated Pest Management (IPM) aims to combine biological and chemical strategies and measures, hence highlighting the study of acute toxicity and sub-lethal effects of pesticides comprehensively. The present research focused on the side effects of thiamethoxam and pirimicarb sub-lethal concentrations on demographic parameters of Diaeretiella rapae (McIntosh Laboratory) (Hymenoptera: Braconidae). Adult parasitoids were exposed to LC25 of insecticides as well as distilled water as the control. The results showed that thiamethoxam adversely affected population parameters (r, λ, R0, T), adults' longevity, females' oviposition period and mean fecundity, and a similar trend was obtained for pirimicarb with the exception of generation time (T), the latter did not significantly change compared to the control. The intrinsic rate of increase (r) in the control and those treated with pirimicarb and thiamethoxam were 0.2801, 0.2064, 0.1525 days-1, respectively, and the sex ratio was biased toward females in all treatments. Furthermore, none of the insecticides influenced total pre-oviposition period (TPOP) and offspring emergence rate. In general, these results indicated that both insecticides potentially distort the demographic parameters of the parasitoid even at sub-lethal concentrations, and then they should not be considered for IPM program in the presence of D. rapae.

An Elaborate Survey on Node Replication Attack in Static Wireless Sensor Networks

Recent innovations in the field of technology led to the use of   wireless sensor networks in various applications, which consists of a number of small, very tiny, low-cost, non-tamper proof and resource constrained sensor nodes. These nodes are often distributed and deployed in an unattended environment, so as to collaborate with each other to share data or information. Amidst various applications, wireless sensor network finds a major role in monitoring battle field in military applications. As these non-tamperproof nodes are deployed in an unattended location, they are vulnerable to many security attacks. Amongst many security attacks, the node replication attack seems to be more threatening to the network users. Node Replication attack is caused by an attacker, who catches one true node, duplicates the first certification and cryptographic materials, makes at least one or more copies of the caught node and spots them at certain key positions in the system to screen or disturb the network operations. Preventing the occurrence of such node replication attacks in network is a challenging task. In this survey article, we provide the classification of detection schemes and also explore the various schemes proposed in each category. Also, we compare the various detection schemes against certain evaluation parameters and also its limitations. Finally, we provide some suggestions for carrying out future research work against such attacks.

Financial Burden of Family for the Children with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is the fastest growing serious developmental disorder characterized by social deficits, communicative difficulties, and repetitive behaviors. ASD is an emerging public health issue globally which is associated with huge financial burden to the family, community and the nation. The aim of this study was to assess the financial burden of family for the children with Autism spectrum Disorder. This cross-sectional study was carried out from July 2015 to June 2016 among 154 children with ASD to assess the financial burden of family. Data were collected by face-to-face interview with semi-structured questionnaire following systematic random sampling technique. Majority (73.4%) children were male and mean (±SD) age was 6.66 ± 2.97 years. Most (88.8%) of the children were from urban areas with average monthly family income Tk. 41785.71±23936.45. Average monthly direct cost of the children was Tk.17656.49 ± 9984.35, while indirect cost was Tk. 13462.90 ± 9713.54 and total treatment cost was Tk. 23076.62 ± 15341.09. Special education cost (Tk. 4871.00), cost of therapy (Tk. 4124.07) and travel cost (Tk. 3988.31) were the major types of direct cost, while loss of income (Tk.14570.18) was the chief indirect cost incurred by the families. The study found that majority (59.8%) of the children attended special schools were incurred Tk.20001-78700 as total treatment cost, which were statistically significant (p

Methodology for Developing an Intelligent Tutoring System Based on Marzano’s Taxonomy

The Mexican educational system faces diverse challenges related with the quality and coverage of education. The development of Intelligent Tutoring Systems (ITS) may help to solve some of them by helping teachers to customize their classes according to the performance of the students in online courses. In this work, we propose the adaptation of a functional ITS based on Bloom’s taxonomy called Sistema de Apoyo Generalizado para la Enseñanza Individualizada (SAGE), to measure student’s metacognition and their emotional response based on Marzano’s taxonomy. The students and the system will share the control over the advance in the course, so they can improve their metacognitive skills. The system will not allow students to get access to subjects not mastered yet. The interaction between the system and the student will be implemented through Natural Language Processing techniques, thus avoiding the use of sensors to evaluate student’s response. The teacher will evaluate student’s knowledge utilization, which is equivalent to the last cognitive level in Marzano’s taxonomy.

Comparison of Real-Time PCR and FTIR with Chemometrics Technique in Analysing Halal Supplement Capsules

Halal authentication and verification in supplement capsules are highly required as the gelatine available in the market can be from halal or non-halal sources. It is an obligation for Muslim to consume and use the halal consumer goods. At present, real-time polymerase chain reaction (RT-PCR) is the most common technique being used for the detection of porcine and bovine DNA in gelatine due to high sensitivity of the technique and higher stability of DNA compared to protein. In this study, twenty samples of supplements capsules from different products with different Halal logos were analyzed for porcine and bovine DNA using RT-PCR. Standard bovine and porcine gelatine from eurofins at a range of concentration from 10-1 to 10-5 ng/µl were used to determine the linearity range, limit of detection and specificity on RT-PCR (SYBR Green method). RT-PCR detected porcine (two samples), bovine (four samples) and mixture of porcine and bovine (six samples). The samples were also tested using FT-IR technique where normalized peak of IR spectra were pre-processed using Savitsky Golay method before Principal Components Analysis (PCA) was performed on the database. Scores plot of PCA shows three clusters of samples; bovine, porcine and mixture (bovine and porcine). The RT-PCR and FT-IR with chemometrics technique were found to give same results for porcine gelatine samples which can be used for Halal authentication.

Investigation of the Effect of Nano-Alumina Particles on Adsorption Property of Acrylic Fiber

The flue gas from fossil fuels combustion contains harmful pollutants dangerous for human health and environment. One of the air pollution control methods to restrict the emission of these pollutants is based on using the nanoparticle in adsorption process. In the present research, gamma nano-alumina particle is added to polyacrylonitrile (PAN) polymer through simple loading method, and the adsorption capacity of the wet spun fiber is investigated. The results of exposure the fiber to the acid gases including SO2, CO, NO2, NO, and CO2 show the noticeable increase of gas adsorption capacity on fiber contains nanoparticle. The research has been conducted in Acrylic II Plant of Polyacryl Iran Corporation.