Search results for: deep feed forward neural network

Authors: Wafa' Slaibi Alsharafat

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Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.

Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection

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Authors: Zehra Aytac, Nurdilek Gulmezoglu

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Safflower has been grown for centuries for many purposes worldwide. Especially it is important for the orange-red dye from its petal and for its high-quality oil obtained from the seeds. The crop is high adaptable to areas with insufficient rainfall and poor soil conditions. The plant has a deep taproot that can draw moisture and plant nutrients from deep to the subsoil. The research was carried out to study the nitrogen (N) uptake of different safflower cultivars and lines at different stages of growth and different plant parts in the experimental field of Faculty of Agriculture, Eskişehir Osmangazi University under semi-arid conditions. Different safflower cultivars and lines of varied origins were used as the material. The cultivars and lines were planted in a Randomized Complete Block Design with three replications. Two different growth stages (flowering and harvest) and three different plant parts (head, stem+leaf and seed) were determined. The nitrogen concentration of different plant parts was determined by the Kjeldahl method. Statistical analysis were performed by analysis of variance for each growth stage and plant parts taking a level of p < 0.05 and p < 0.01 as significant according to the LSD test. As a result, N concentration showed significant differences among different plant parts and different growth stages for different safflower genotypes of varied origins.

Keywords: Carthamus tinctorius L., growth stages, head N, leaf N, N uptake, seed N, Safflower

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Authors: Hyeon Su Kim, Sungjin Park, Hae Ryung Chang, Hae Rim Jung, Young Zoo Ahn, Yon Hui Kim, Seungyoon Nam

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Ependymoma, one of the most common parenchymal spinal cord tumor, represents 3-6% of all CNS tumor. Especially intracranial ependymomas, which are more frequent in childhood, have a more poor prognosis and more malignant than spinal ependymomas. Although there are growing needs to understand pathogenesis, detailed molecular understanding of pathogenesis remains to be explored. A cancer cell is composed of complex signaling pathway networks, and identifying interaction between genes and/or proteins are crucial for understanding these pathways. Therefore, we explored each ependymoma in terms of differential expressed genes and signaling networks. We used Microsoft Excel™ to manipulate microarray data gathered from NCBI’s GEO Database. To analyze and visualize signaling network, we used web-based PATHOME algorithm and Cytoscape. We show HOX family and NEFL are down-regulated but SCL family is up-regulated in cerebrum and posterior fossa cancers over a spinal cancer, and JAK/STAT signaling pathway and Chemokine signaling pathway are significantly different in the both intracranial ependymoma comparing to spinal ependymoma. We are considering there may be an age-dependent mechanism under different histological pathogenesis. We annotated mutation data of each gene subsequently in order to find potential target genes.

Keywords: systems biology, ependymoma, deg, network analysis

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Authors: Yizhi Zhang, Xiaozan Wang, Mingming Guo, Pengpeng Li

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Introduction: The purpose of this study is to examine the effectiveness of after-school football training in improving the physical fitness of primary school students, so as to provide corresponding suggestions for carrying out after-school football training in primary schools. Methods: A total of 72 students from the experimental primary school of Mouping district, Yantai city, Shandong province, participated in this experiment. The experiment was conducted for two semesters. During the experiment period, the experimental group conducted one-hour football training after school from Monday to Thursday afternoon every week, and two hours of football training on Saturday morning every week. The control group conducted sports teaching and extracurricular activities as usual without other intervention. Before and after the experiment, both the experimental group and the control group underwent physical fitness tests according to the physical fitness test standards of Chinese students, including lung capacity, 50-meter run, one-minute skipping rope, sitting forward flexor, and one-minute sit-ups. The test results were all converted to the 100-point system according to the scoring standards. Results: (1) Before the experiment, there was no significant difference between the experimental group and the control group in various physical fitness indicators (p > 0.05). (2) After the experiment, the lung capacity score (T = 3.108, p < 0.05), the 50-meter run score (T = 6.593, p < 0.05), the skipping score (T = 9.227, p < 0.05), the sitting forward flexor score (T = 3.742, p < 0.05), and the sit-up score (T = 5.210, p < 0.05) of the experimental group were significantly higher than that of the control group. Conclusion: This study shows that the physical fitness of primary school students can be improved by football training in their spare time. It is suggested to carry out after-school football training activities in primary schools so as to effectively improve the physical fitness of pupils.

Keywords: after-school football training, physical fitness, primary school students, school sports

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Authors: Sanjida Akter, Ambali Alade Odebowale, Andrey E. Miroshnichenko, Haroldo T. Hattori

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Photodetectors (PDs) play a pivotal role in optoelectronics and optical devices, serving as fundamental components that convert light signals into electrical signals. As the field progresses, the integration of advanced materials with unique optical properties has become a focal point, paving the way for the innovation of novel PDs. This study delves into the exploration of a cutting-edge photodetector designed for deep and near ultraviolet (UV) applications. The photodetector is constructed with a composite of Zirconium Boride (ZrB2) and Chromium (Cr) alloy, deposited onto a 6H nitrogen-doped silicon carbide substrate. The determination of the optimal alloy thickness is achieved through Finite-Difference Time-Domain (FDTD) simulation, and the synthesis of the alloy is accomplished using radio frequency (RF) sputtering. Remarkably, the resulting photodetector exhibits an exceptional responsivity of 3.5 A/W under an applied voltage of -2 V, at wavelengths of 405 nm and 280 nm. This heterostructure not only exemplifies high performance but also provides a versatile platform for the development of near UV photodetectors capable of operating effectively in challenging conditions, such as environments characterized by high power and elevated temperatures. This study contributes to the expanding landscape of photodetector technology, offering a promising avenue for the advancement of optoelectronic devices in demanding applications.

Keywords: responsivity, silicon carbide, ultraviolet photodetector, zirconium boride

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Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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Authors: Alhaji Musa Abdullahi, Usman Abdullahi, Adamu Lawan, Aminu Maidala

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Abstract 16 healthy lactating cows will be randomly selected for the trial and will be randomly divided in to 4 groups with 4 cows in each. They will be kept under similar management condition (conventional management system). Animals of relatively same weight and age will be used. After 11days for adaptation, feed intake and performance of the experimental animals will be determine. Milk sample will be collected at each milking in the morning and afternoon to determine; Milk yield, Milk fat percentage, Solid not fat percentage, Total solid percentage of milk. Cows dung will be observe to determine; Score 1 very loose watery stool, Score 2 semi solid with undigested raw material, Score 3 semi solid with less undigested raw material, Score 4 solid with very less undigested raw material, Score 5 good dung no undigested raw material. At the end of the experiment, blood samples will be analyzed for full blood counts and differentials {White Blood Cells (WBC), Red Blood Cells (RBC), Hemoglobin (Hb), Packed Cell Volume (PCV), Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin (MCH), Mean Corpuscular Hemoglobin Concentration (MCHC), Platelets (PLT), Lymphocytes (LYM), Basophils, Eosinophils and Monocytes Proportion (MXD) and Neutrophils (NEUT)} using automated hematology analyzer. Serum samples will be analyzed for heat shock transcription factors, heat shock proteins and hormones (Serum glucocorticoid, prolactin and cortisol). Moreover, biochemical analysis will also be conducted to check for Total protein (TP), Albumen (ALB), Globulin (GBL), Total cholesterol (TCH), glucose (G), sodium (Na+), potassium (K+), chloride (Cl-) and pH. Keywords: Lactating cows, milk composition, dung score and blood parameters.

Keywords: Lactating cows , Milk yield , Dung score , Blood parameters

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Authors: Bashir Abdu Muzakkari, Mohamad Afendee Mohamad, Mohd Fadzil Abdul Kadir

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Wireless Sensor Networks (WSNs) is an aggregation of several tiny, low-cost sensor nodes, spatially distributed to monitor physical or environmental status. WSN is constantly changing because of the rapid technological advancements in sensor elements such as radio, battery and operating systems. The Medium Access Control (MAC) protocols remain very vital in the WSN because of its role in coordinating communication amongst the sensors. Other than battery consumption, packet collision, network lifetime and latency are factors that largely depend on WSN MAC protocol and these factors have been widely treated in recent days. In this paper, we survey some latest proposed WSN Contention-based, Scheduling-based and Hybrid MAC protocols while presenting an examination, correlation of advantages and limitations of each protocol. Concentration is directed towards investigating the treatment of Quality of Service (QoS) performance metrics within these particular protocols. The result shows that majority of the protocols leaned towards energy conservation. We, therefore, believe that other performance metrics of guaranteed QoS such as latency, throughput, packet loss, network and bandwidth availability may play a critical role in the design of future MAC protocols for WSNs.

Keywords: WSN, QoS, energy consumption, MAC protocol

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Authors: Harshdeep Singh, Kuljeet Singh Anand

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Background: Cerebrovascular Accidents (CVA) cause abnormal or asymmetrical tendon reflexes contributing to motor impairments. Since the tendon reflexes are mediated by the spinal cord, their effects on cognitive performances are overlooked. This study aims to find the contributions of tendon reflexes on the performance of the Flanker task. Methods: A total population of 46 mixed subjects with movement disorders were recruited for the study. Deep tendon reflexes (DTR) of the biceps, triceps and brachioradialis were assessed for both upper extremities. Later, the Flanker task was performed on all the subjects, and the mean Reaction Time (RT) along with both the congruent and incongruent stimuli were evaluated. For the final analysis, the Kruskal Wallis test was performed to see the difference between the DTR and the performance of the Flanker Task. Results: The Kruskal Wallis test results showed a significant difference between the DTR scores, X²(2) = 11.328, p= 0.023 with the mean RT of the flanker task and X²(2) = 9.531, p= 0.049 with mean RT of the Incongruent Stimuli. Whereas the result found a non-significant difference in the mean RT of the Congruent Stimuli. Conclusion: Each DTR score is distributed differently with the mean RT of the flanker task and for the incongruent stimuli as well. Therefore, the tendon reflexes in PD may be contributing to the performance of the Flanker Task and may be an indicator of abnormal cognitive performance. Further research is needed to evaluate how the RTs are distributed with each DTR score.

Keywords: cerebrovascular accidents, deep tendon reflexes, flanker task, reaction time, congruent stimuli, incongruent stimuli

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Authors: Aqeel Ahmed Shad, Tanveer Ahmad, Muhammad Farooq Iqbal, Muhammad Javaid Asad

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The supplemental effects of novel protease produced from Bacillus subtilis K-5 and beta-mannanase were evaluated on growth performance, carcass characteristics, nutrients digestibility, blood profile and intestinal morphometry of broilers fed guar meal (Cyamopsis tetragonoloba) based diets with reduced Crude Protein (CP), Essential Amino Acids (EAAs), and Metabolizable energy (ME) contents. One-day old Ross 308 broiler chicks (n=360) were randomly allotted to thirty six experimental units in a way that each of the nine dietary treatments received four replicates with ten birds per replicate. A control diet without guar meal (0GM) was formulated with standard nutrient specifications of Ross 308 for the starter and finisher phases. Two negative control diets, one with 5% (5GM) and second with 10% (10GM) guar meal, were formulated with reduction of 5% CP, 5% EAAs and 80 Kcal/kg ME. These three basal diets (no enzyme) were supplemented with novel protease enzyme (PROT) and commercial beta-mannanase (Beta-M) enzyme. The birds were reared up to 35d of age. The data on weekly body weight gain (BWG) and feed intake were recorded to compute feed:gain for the starter (0-21d) and finisher (22-35d) phases. At the end of 35d of experimental period, four birds per experimental unit were randomly selected for blood samples collection and later slaughtered for ileal digesta, intestinal tract and carcass trait sampling. The data on overall performance (1-35d) indicated improved (P<0.05) BWG and feed:gain in birds supplemented with PROT (1.41% and 1.67) and Beta-M (2.79% and 1.64) than non-supplemented groups. Improved (P<0.05) carcass yield, breast meat yield and thigh meat yield were noted with the supplementation of Beta-M. However, non-significant (P>0.05) effect on carcass traits was noted in broiler fed guar meal based PROT supplemented diets. Crude protein digestibility, nitrogen retention (Nret) and apparent digestibility coefficient for nitrogen (ADCN) were improved (P<0.05) only with PROT. The improvement in apparent metabolizable energy (AME) and apparent metabolizable energy corrected for nitrogen (AMEn) was noted (P<0.05) with both supplemented enzymes. However, no effect (P>0.05) of enzyme addition was noted on blood glucose, total protein and cholesterol. Improved villus height of duodenum, jejunum and ileum was noted (P<0.05) with the addition of both enzymes. The EAAs digestibility was improved (P<0.05) only with PROT. In conclusion, beta-mannanase and protease supplementation better improved the overall bird performance in low nutrient profile guar meal based diets than non-supplemented diets.

Keywords: novel protease, guar meal, broilers, low protein diets, low metabolizable energy diets, nutrients digestibility

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Authors: Mehrnaz Aminifar

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The relation between textural parameters and casein network on release of aromatic compounds was investigated over 90-days of ripening. Low DE maltodextrin and WPI were used to modify the textural properties of low fat brined cheese. Hardness, brittleness and compaction of casein network were affected by addition of maltodextrin and WPI. Textural properties and aroma release from cheese texture were affected by interaction of WPI protein-cheese protein and maltodexterin-cheese protein.

Keywords: aroma release, brined cheese, maltodexterin, WPI

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Authors: Cheila Pereira, Sara C. Cunha, Miguel A. Faria, José O. Fernandes

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The increasing world population brings several concerns, one of which is food security and sustainability. To meet this challenge, aquaculture, the farming of aquatic animals and plants, including fish, mollusks, bivalves, and algae, has experienced sustained growth and development in recent years. Recent advances in this industry have focused on reducing its economic and environmental costs, for example, the substitution of protein sources in fish feed. Plant-based proteins are now a common approach, and while it is a greener alternative to animal-based proteins, there are some disadvantages, such as their putative content and intoxicants such as mycotoxins. These are naturally occurring plant contaminants, and their exposure in fish can cause health problems, stunted growth or even death, resulting in economic losses for the producers and health concerns for the consumers. Different works have demonstrated the presence of both AFB1 (aflatoxin B1) and ENNB1 (enniatin B1) in fish feed and their capacity to be absorbed and bioaccumulate in the fish organism after digestion, further reaching humans through fish ingestion. The aim of this work was to evaluate the bioaccessibility of both mycotoxins in samples of Sparus aurata muscle using a static digestion model based on the INFOGEST protocol. The samples were subjected to different cooking procedures – raw, grilled and fried – and different seasonings – none, thyme and ginger – in order to evaluate their potential reduction effect on mycotoxins bioaccessibility, followed by the evaluation of the intestinal transport of both compounds with an in vitro cell model composed of Caco-2/HT-29 co-culture monolayers, simulating the human intestinal epithelium. The bioaccessible fractions obtained in the digestion studies were used in the transport studies for a more realistic approach to bioavailability evaluation. Results demonstrated the effect of the use of different cooking procedures and seasoning on the toxin's bioavailability. Sparus aurata was chosen in this study for its large production in aquaculture and high consumption in Europe. Also, with the continued evolution of fish farming practices and more common usage of novel feed ingredients based on plants, there is a growing concern about less studied contaminants in aquaculture and their consequences for human health. In pair with greener advances in this industry, there is a convergence towards alternative research methods, such as in vitro applications. In the case of bioavailability studies, both in vitro digestion protocols and intestinal transport assessment are excellent alternatives to in vivo studies. These methods provide fast, reliable and comparable results without ethical restraints.

Keywords: AFB1, aquaculture, bioaccessibility, ENNB1, intestinal transport.

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Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Shunsuke Saito, Kazuho Yoshimoto, Shunichi Ohmori, Sirawadee Arunyanart

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In this paper, we suggest a mechanism of assessment that rater and Ratee (or employees) to convince. There are many problems exist in the personnel assessment. In particular, we were focusing on the three. (1) Raters are not sufficiently recognized assessment point. (2) Ratee are not convinced by the mechanism of assessment. (3) Raters (or Evaluators) and ratees have empathy. We suggest 1: Setting of "understanding of the assessment points." 2: Setting of "relative assessment ability." 3: Proposal of two-way assessment mechanism to solve these problems. As a prerequisite, it is assumed that there are multiple raters. This is because has been a growing importance of multi-faceted assessment. In this model, it determines the weight of each assessment point evaluators by the degree of understanding and assessment ability of raters and ratee. We used the ANP (Analytic Network Process) is a theory that an extension of the decision-making technique AHP (Analytic Hierarchy Process). ANP can be to address the problem of forming a network and assessment of Two-Way is possible. We apply this technique personnel assessment, the weights of rater of each point can be reasonably determined. We suggest absolute assessment for Two-Way assessment by ANP. We have verified that the consent of the two approaches is higher than conventional mechanism. Also, human resources consultant we got a comment about the application of the practice.

Keywords: personnel evaluation, pairwise comparison, analytic network process (ANP), two-ways

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Authors: Bilal Murtaza, Xiaoyu Li, Liming Dong, Muhammad Kashif Saleemi, Gen Li, Bowen Jin, Lili Wang, Yongping Xu

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Fusarium spp. produce numerous mycotoxins, such as zearalenone (ZEN), deoxynivalenol (DON), and its acetylated compounds, 3-acetyl-deoxynivalenol (3-ADON) and 15-acetyl-deoxynivalenol (15-ADON) (15-ADON). In a co-culture system, the soil-derived Escherichia marmotae strain degrades ZEN and DON into 3-keto-DON and DOM-1 via enzymatic deep-oxidation. When pure mycotoxins were subjected to Escherichia marmotae in culture flasks, degradation, and detoxification were also attained. DON and ZEN concentrations, ambient pH, incubation temperatures, bacterium concentrations, and the impact of acid treatment on degradation were all evaluated. The results of the ELISA and high-performance liquid chromatography-electrospray ionization-high resolution mass spectrometry (HPLC-ESI-HRMS) tests demonstrated that the concentration of mycotoxins exposed to Escherichia marmotae was significantly lower than the control. ZEN levels were reduced by 43.9%, while zearalenone sulfate ([M/z 397.1052 C18H21O8S1) was discovered as a derivative of ZEN converted by microbes to a less toxic molecule. Furthermore, Escherichia marmotae appeared to metabolize DON 35.10% into less toxic derivatives (DOM-1 at m/z 281 of [DON - O]+ and 3-keto-DON at m/z 295 of [DON - 2H]+). These results show that Escherichia marmotae can reduce Fusarium mycotoxins production, degrade pure mycotoxins, and convert them to less harmful compounds, opening up new possibilities for study and innovation in mycotoxin detoxification.

Keywords: mycotoxins, zearalenone, deoxynivalenol, bacterial degradation

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Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

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Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530

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Authors: Luigi Iannacci

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This study critically explores how disability and disability are presently and problematically configured within education. As such, pedagogies, discourses, and practices that shape this configuration are examined to forward a reconceptualization of disability as it relates to education and the inclusion of students with special needs in mainstream classroom contexts. The study examines how the dominant medical/deficit model of disability positions students with special needs and advocates for a shift towards a social/critical model of disability as applied to education and classrooms. This is demonstrated through a critical look at how language, processes, and ‘interventions’ name and address deficits people who have a disability are presumed to have and, as such, conceptualize these deficits as inherent flaws that are in need of ‘fixing.’ The study will demonstrate the necessary shifts in thinking, language and practice required to forward a critical/social model of disability. The ultimate aim of this research is to offer a much-needed reconceptualization of inclusion that recognizes disability as epistemology, identity, and diversity through a critical exploration of dominant discourses that impact language, policy, instruction and ultimately, the experiences students with disabilities have within mainstream classrooms. The presentation seeks to explore disability as neurodiversity and therefore elucidate how people with disabilities can demonstrate these ways of knowing within inclusive education that avoids superficial approaches that are not responsive to their needs. This research is, therefore, of interest and use to educators teaching at the elementary, secondary, and in-service levels as well as graduate students and scholars working in the areas of inclusion, special education, and literacy. Ultimately the presentation attempts to foster a social justice and human rights-focused approach to inclusion that is responsive to students with disabilities and, as such ensures a reconceptualization of present language, understandings and practices that continue to configure disability in problematic ways.

Keywords: inclusion, disability, critical approach, social justice

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Authors: Nicola Rubino

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This paper presents an analysis of a group of commodity exporting countries' nominal exchange rate movements in relationship to the US dollar. Using a series of Unrestricted Self-exciting Threshold Autoregressive models (SETAR), we model and evaluate sixteen national CPI price differentials relative to the US dollar CPI. Out-of-sample forecast accuracy is evaluated through calculation of mean absolute error measures on the basis of two-hundred and fifty-three months rolling window forecasts and extended to three additional models, namely a logistic smooth transition regression (LSTAR), an additive non linear autoregressive model (AAR) and a simple linear Neural Network model (NNET). Our preliminary results confirm presence of some form of TAR non linearity in the majority of the countries analyzed, with a relatively higher goodness of fit, with respect to the linear AR(1) benchmark, in five countries out of sixteen considered. Although no model appears to statistically prevail over the other, our final out-of-sample forecast exercise shows that SETAR models tend to have quite poor relative forecasting performance, especially when compared to alternative non-linear specifications. Finally, by analyzing the implied half-lives of the > coefficients, our results confirms the presence, in the spirit of arbitrage band adjustment, of band convergence with an inner unit root behaviour in five of the sixteen countries analyzed.

Keywords: transition regression model, real exchange rate, nonlinearities, price differentials, PPP, commodity points

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Authors: P. G. Kaviya, B. Muthupandian, R. Ganesan

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On-chip routers typically have buffers are used input or output ports for temporarily storing packets. The buffers are consuming some router area and power. The multiple queues in parallel as in VC router. While running a traffic trace, not all input ports have incoming packets needed to be transferred. Therefore large numbers of queues are empty and others are busy in the network. So the time consumption should be high for the high traffic. Therefore using a RoShaQ, minimize the buffer area and time The RoShaQ architecture was send the input packets are travel through the shared queues at low traffic. At high load traffic the input packets are bypasses the shared queues. So the power and area consumption was reduced. A parallel cross bar architecture is proposed in this project in order to reduce the power consumption. Also a new adaptive weighted routing algorithm for 8-port router architecture is proposed in order to decrease the delay of the network on chip router. The proposed system is simulated using Modelsim and synthesized using Xilinx Project Navigator.

Keywords: buffer, RoShaQ architecture, shared queue, VC router, weighted routing algorithm

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Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

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Authors: Jun-Ho Park, Kwang-Woo Nam, Seung-Mo Hong, Tae-Heon Moon, Sang-Ho Lee, Youn-Taik Leem

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The aim of this study was to build ‘Ubi-Net’, a decision-making support system for systematic establishment in U-City planning. We have experienced various urban problems caused by high-density development and population concentrations in established urban areas. To address these problems, a U-Service contributes to the alleviation of urban problems by providing real-time information to citizens through network connections and related information. However, technology, devices, and information for consumers are required for systematic U-Service planning in towns and cities where there are many difficulties in this regard, and a lack of reference systems. Thus, this study suggests methods to support the establishment of sustainable planning by providing comprehensive information including IT technology, devices, news, and social networking services(SNS) to U-City planners through intelligent searches. In this study, we targeted Smart U-Parking Planning to solve parking problems in an ‘old’ city. Through this study, we sought to contribute to supporting advances in U-Space and the alleviation of urban problems.

Keywords: desigin and decision support system, smart u-parking planning, social network analysis, urban engineering

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Authors: Yasin Tadayonrad

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

Procedia PDF Downloads 91

Authors: J. van Soest, B. Bruneel, J. Smit, N. Williams, P. Swiegers

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Selenium (Se) is an essential trace mineral involved in reducing oxidative stress, enhancing immune status, improving reproduction, and regulating growth. During finishing period, selenium supplementation can be applied to improve meat quality. Dietary selenium can be provided in inorganic or organic forms. Specifically, L-selenomethionine (organic selenium) allows for selenium storage in animal protein which supports the animal during periods of high oxidative stress. The objective of this study was to investigate the effects of synthetically produced, single amino acid, L-selenomethionine (Excential Selenium 4000, Orffa Additives BV) on production parameters, health status, and meat quality of Bonsmara bull calves. 24 calves, 7 months of age, completed a 60-day initial growing period at a commercial feedlot, after which they were transported to research station Rumen-8 (Bethlehem, South-Africa). After a ten-day adaptation period, the bulls were allocated to a control (n=12) or treatment (n=12) group. Each group was divided over 3 pens based on weight. Both groups received Total Mixed Ration supplemented with 5.25 mg Se/head per day. The control group was supplemented with sodium selenite as Se source, whilst the treatment group was supplemented with L-selenomethionine (Excential Selenium 4000, Orffa Additives BV). Animals were limited to 10 kg feed intake per head per day to ensure similar Se intake. Treatment period lasted 1.5 months. A beta-adrenergic agonist was included in the feed for the last 30 days. During the treatment period, average daily gain, average daily feed intake, and feed conversion ratio were recorded. Blood parameters were measured at day 1, day 25, and before slaughter (day 47). After slaughter, carcass weight, dressing percentage, grading, and meat quality (pH, tenderness, colour, odour, purge, proximate analyses, acid detergent fibre, and neutral detergent fibre) were determined. No differences between groups were found in performance. A higher number of animals with cortisol levels below detection limit (27.6 nmol/l) was recorded for the treatment group. Other blood parameters showed no differences. No differences were found regarding carcass weight and dressing percentage. Important parameters of meat quality were significantly improved in the treatment group: instrumental tenderness at 14 days ageing was 2.8 and 3.4 for treatment and control respectively (P=0.010), and a 0.5% decrease in purge (of fresh samples) was shown, 1.5% and 2.0% for treatment group and control respectively (p=0.029). Besides, pH was shown to be numerically reduced in the treatment group. In summary, supplementation with L-selenomethionine as selenium source improved meat quality compared to sodium selenite. Lower instrumental tenderness (Warner Bratzler Shear Force, WBSF) was recorded for the treatment group. This indicates less tough meat and highest consumer satisfaction. Regarding purge, control was just below 2.0%, an important threshold for consumer acceptation. Treatment group scored 0.5% lower for purge than control, indicating higher consumer satisfaction. The lower pH in the treatment group could be an indication of higher glycogen reserves in muscle which could contribute to a reduced risk of Dark Firm Dry carcasses. More animals showed cortisol levels below detection limit in the treatment group, indicating lower levels of stress when animals receive L-selenomethionine.

Keywords: calves, meat quality, nutrition, selenium

Procedia PDF Downloads 181

Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

Procedia PDF Downloads 246

Authors: Sihem Salmi Laouar, Khoudair Chabane, Rabah Laouar, Adrian J. Boyce et Anthony E. Fallick

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The solid mass of Essouabaa belongs paléogéography to the field téthysian and belonged to the area of the Mounts of Mellègue. This area was not saved by the oceanic-2 event anoxic (EAO-2) which was announced, over one short period, around the limit cénomanian-turonian. In the solid mass of Essouabba, the dominant sediments, pertaining to this period, are generally fine, dark, laminated and sometimes rolled deposits. They contain a rather rich planktonic microfaune, pyrite, and grains of phosphate, thus translating an environment rather deep and reducing rather deep and reducing. For targeting well the passage Cénomanian-Turonian (C-T) in the solid mass of Essouabaa, of the studies lithological and biostratigraphic were combined with the data of the isotopic analyses carbon and oxygen like with the contents of CaCO3. The got results indicate that this passage is marked by a biological event translated by the appearance of the "filaments" like by a positive excursion of the δ13C and δ18O. The cénomanian-turonian passage in the solid mass of Essouabaa represents a good example where during the oceanic event anoxic a facies with organic matter with contents of COT which can reach 1.36%. C E massive presents biostratigraphic and isotopic similarities with those obtained as well in the areas bordering (ex: Tunisia and Morocco) that throughout the world.

Keywords: limit cénomanian-turonian (C-T), COT, filaments, event anoxic 2 (EAO-2), stable isotopes, mounts of Mellègue, Algeria

Procedia PDF Downloads 515

Authors: Samia Dardouri, Ridha Bouallegue

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Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, multimedia flows, scheduling algorithms, mobile computing

Procedia PDF Downloads 383

Authors: Moses C. Siame, Kazutoshi Haga, Atsushi Shibayama

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This study investigates the removal of silica, alumina and phosphorus as impurities from Sanje iron ore using wet high-intensity magnetic separation (WHIMS). Sanje iron ore contains low-grade hematite ore found in Nampundwe area of Zambia from which iron is to be used as the feed in the steelmaking process. The chemical composition analysis using X-ray Florence spectrometer showed that Sanje low-grade ore contains 48.90 mass% of hematite (Fe₂O₃) with 34.18 mass% as an iron grade. The ore also contains silica (SiO₂) and alumina (Al₂O₃) of 31.10 mass% and 7.65 mass% respectively. The mineralogical analysis using X-ray diffraction spectrometer showed hematite and silica as the major mineral components of the ore while magnetite and alumina exist as minor mineral components. Mineral particle distribution analysis was done using scanning electron microscope with an X-ray energy dispersion spectrometry (SEM-EDS) and images showed that the average mineral size distribution of alumina-silicate gangue particles is in order of 100 μm and exists as iron-bearing interlocked particles. Magnetic separation was done using series L model 4 Magnetic Separator. The effect of various magnetic separation parameters such as magnetic flux density, particle size, and pulp density of the feed was studied during magnetic separation experiments. The ore with average particle size of 25 µm and pulp density of 2.5% was concentrated using pulp flow of 7 L/min. The results showed that 10 T was optimal magnetic flux density which enhanced the recovery of 93.08% of iron with 53.22 mass% grade. The gangue mineral particles containing 12 mass% silica and 3.94 mass% alumna remained in the concentrate, therefore the concentrate was further treated in the second stage WHIMS using the same parameters from the first stage. The second stage process recovered 83.41% of iron with 67.07 mass% grade. Silica was reduced to 2.14 mass% and alumina to 1.30 mass%. Accordingly, phosphorus was also reduced to 0.02 mass%. Therefore, the two stage magnetic separation process was established using these results.

Keywords: Sanje iron ore, magnetic separation, silica, alumina, recovery

Procedia PDF Downloads 258

Authors: Swapnil Kumar Singh

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Gamma-ray bursts (GRB's), short and intense pulses of low-energy γ rays, have fascinated astronomers and astrophysicists since their unexpected discovery in the late sixties. GRB'sare accompanied by long-lasting afterglows, and they are associated with core-collapse supernovae. The detection of delayed emission in X-ray, optical, and radio wavelength, or "afterglow," following a γ-ray burst can be described as the emission of a relativistic shell decelerating upon collision with the interstellar medium. While it is fair to say that there is strong diversity amongst the afterglow population, probably reflecting diversity in the energy, luminosity, shock efficiency, baryon loading, progenitor properties, circumstellar medium, and more, the afterglows of GRBs do appear more similar than the bursts themselves, and it is possible to identify common features within afterglows that lead to some canonical expectations. After an initial flash of gamma rays, a longer-lived "afterglow" is usually emitted at longer wavelengths (X-ray, ultraviolet, optical, infrared, microwave, and radio). It is a slowly fading emission at longer wavelengths created by collisions between the burst ejecta and interstellar gas. In X-ray wavelengths, the GRB afterglow fades quickly at first, then transitions to a less-steep drop-off (it does other stuff after that, but we'll ignore that for now). During these early phases, the X-ray afterglow has a spectrum that looks like a power law: flux F∝ E^β, where E is energy and beta is some number called the spectral index. This kind of spectrum is characteristic of synchrotron emission, which is produced when charged particles spiral around magnetic field lines at close to the speed of light. In addition to the outgoing forward shock that ploughs into the interstellar medium, there is also a so-called reverse shock, which propagates backward through the ejecta. In many ways," reverse" shock can be misleading; this shock is still moving outward from the restframe of the star at relativistic velocity but is ploughing backward through the ejecta in their frame and is slowing the expansion. This reverse shock can be dynamically important, as it can carry comparable energy to the forward shock. The early phases of the GRB afterglow still provide a good description even if the GRB is highly collimated since the individual emitting regions of the outflow are not in causal contact at large angles and so behave as though they are expanding isotropically. The majority of afterglows, at times typically observed, fall in the slow cooling regime, and the cooling break lies between the optical and the X-ray. Numerous observations support this broad picture for afterglows in the spectral energy distribution of the afterglow of the very bright GRB. The bluer light (optical and X-ray) appears to follow a typical synchrotron forward shock expectation (note that the apparent features in the X-ray and optical spectrum are due to the presence of dust within the host galaxy). We need more research in GRB and Particle Physics in order to unfold the mysteries of afterglow.

Keywords: GRB, synchrotron, X-ray, isotropic energy

Procedia PDF Downloads 88

Authors: Chothmal

Abstract:

In this paper, we present a route discovery process which uses the signal strength on a link as a parameter of its inclusion in the route discovery method. The proposed signal-to-interference and noise ratio (SINR) based multipath reactive routing protocol is named as SINR-MP protocol. The proposed SINR-MP routing protocols has two following two features: a) SINR-MP protocol selects routes based on the SINR of the links during the route discovery process therefore it select the routes which has long lifetime and low frame error rate for data transmission, and b) SINR-MP protocols route discovery process is multipath which discovers more than one SINR based route between a given source destination pair. The multiple routes selected by our SINR-MP protocol are node-disjoint in nature which increases their robustness against link failures, as failure of one route will not affect the other route. The secondary route is very useful in situations where the primary route is broken because we can now use the secondary route without causing a new route discovery process. Due to this, the network overhead caused by a route discovery process is avoided. This increases the network performance greatly. The proposed SINR-MP routing protocol is implemented in the trail version of network simulator called Qualnet.

Keywords: ad hoc networks, quality of service, video streaming, H.264/SVC, multiple routes, video traces

Procedia PDF Downloads 249

Authors: Senay Yitmen

Abstract:

This research investigated individual’s support and helping intentions towards Syrian refugees in Turkey. This is examined in relation to perceived threat and negative emotions, and also to the perceptions of whether one’s intimate social network (family and friends) considers Syrians a threat (descriptive network norm) and whether this network morally supports Syrian refugees (injunctive norms). A questionnaire study was conducted among Turkish participants (n= 565) and the results showed that perception of threat was associated with negative emotions which, in turn, were related to less support of Syrian refugees. Additionally, descriptive norms moderated the relationship between perceived threat and negative emotions towards Syrian refugees. Furthermore, injunctive norms moderated the relationship between negative emotions and support to Syrian refugees. Specifically, the findings indicate that perceived threat is associated with less support of Syrian refugees through negative emotions when descriptive norms are weak and injunctive norms are strong. Injunctive norms appear to trigger a dilemma over the decision to conform or not to conform: when one has negative emotions as a result of perceived threat, it becomes more difficult to conform to the moral obligation of injunctive norms which is associated with less support of Syrian refugees. Hence, these findings demonstrate that both descriptive and injunctive norms are important and play different roles in individual’s support of Syrian refugees.

Keywords: descriptive norms, emotions, injunctive norms, the perception of threat

Procedia PDF Downloads 189