Search results for: speed hump detection

Authors: Shayan Mohajer Hamidi

Abstract:

Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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Authors: Nabil Shawkat, Jamil Saquer

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Social media has accelerated our ability to engage with others and eliminated many communication barriers. On the other hand, the widespread use of social media resulted in an increase in online hate speech. This has drastic impacts on vulnerable individuals and societies. Therefore, it is critical to detect hate speech to prevent innocent users and vulnerable communities from becoming victims of hate speech. We investigate the performance of different deep learning and machine learning algorithms on three different datasets. Our results show that the BERT model gives the best performance among all the models by achieving an F1-score of 90.6% on one of the datasets and F1-scores of 89.7% and 88.2% on the other two datasets.

Keywords: hate speech, machine learning, deep learning, abusive words, social media, text classification

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Authors: Debbarma Asis, Guha Chandan

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Tumor Protein-53 (P53) is one of the tumor suppressor proteins. P53 regulates the cell cycle that conserves stability by preventing genome mutation. It is named so as it runs as 53-kilodalton (kDa) protein on Polyacrylamide gel electrophoresis although the actual mass is 43.7 kDa. Experimental evidence has indicated that P53 cancer mutants loses tumor suppression activity and subsequently gain oncogenic activities to promote tumourigenesis. Tumor-specific DNA has recently been detected in the plasma of breast cancer patients. Detection of tumor-specific genetic materials in cancer patients may provide a unique and valuable tumor marker for diagnosis and prognosis. Commercially available MDA-468 breast cancer cell line was used for the proposed study.

Keywords: tumor protein (P53), cancer mutants, MDA-468, tumor suppressor gene

Procedia PDF Downloads 480

Authors: B. Y. Danjuma, A. Archibong-Eso, Aliyu M. Aliyu, H. Yeung

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In this experimental investigation, a new data for slugging frequency for high viscosity oil-gas flow are reported. Scale experiments were carried out using a mixture of air and mineral oil as the liquid phase in a 17 m long horizontal pipe with 0.0762 ID. The data set was acquired using two high-speed Gamma Densitometers at a data acquisition frequency of 250 Hz over a time interval of 30 seconds. For the range of flow conditions investigated, increase in liquid oil viscosity was observed to strongly influence the slug frequency. A comparison of the present data with prediction models available in the literature revealed huge discrepancies. A new correlation incorporating the effect of viscosity on slug frequency has been proposed for the horizontal flow, which represents the main contribution of this work.

Keywords: gamma densitometer, flow pattern, pressure gradient, slug frequency

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Authors: Rouhollah Torabi, Ashkan Chavoshi, Sheyda Almasi, Shima Almasi

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In this paper the effect of impeller trim on centrifugal pump performance is studied and the most important effect which is decreasing the flow rate, differential head and efficiency is analyzed. For this case a low specific speed centrifugal pump is simulated with CFD. Total flow inside the pump including the secondary flow in sidewall gap which form internal leakage is modeled simultaneously in CFX software. The flow field in different area of pumps such as inside impeller, volute, balance holes and leakage through wear rings are studied. To validate the results experimental tests are done for various impeller diameters. Results also compared with analytic equations which predict pump performance with trimmed impeller.

Keywords: centrifugal pump, CFD, impeller, trim

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Authors: Claire Williams

Abstract:

Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

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Authors: Robert Pellerin, Michel Gamache, Remi Trudeau, Nathalie Perrier

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The context of large engineering projects is particularly favorable to the appearance of engineering changes and contractual modifications. These elements are potential causes for claims. In this paper, we investigate one of the critical components of the claim management process: the calculation of the impacts of changes in terms of losses of productivity due to the need to accelerate some project activities. When project changes are initiated, delays can arise. Indeed, project activities are often executed in fast-tracking in an attempt to respect the completion date. But the acceleration of project execution and the resulting rework can entail important costs as well as induce productivity losses. In the past, numerous methods have been proposed to quantify the duration of delays, the gains achieved by project acceleration, and the loss of productivity. The calculation related to those changes can be divided into two categories: direct cost and indirect cost. The direct cost is easily quantifiable as opposed to indirect costs which are rarely taken into account during the calculation of the cost of an engineering change or contract modification despite several research projects have been made on this subject. However, proposed models have not been accepted by companies yet, nor they have been accepted in court. Those models require extensive data and are often seen as too specific to be used for all projects. These techniques are also ignoring the resource constraints and the interdependencies between the causes of delays and the delays themselves. To resolve this issue, this research proposes a simulation model that mimics how major engineering changes or contract modifications are handled in large construction projects. The model replicates the use of overtime in a reactive scheduling mode in order to simulate the loss of productivity present when a project change occurs. Multiple tests were conducted to compare the results of the proposed simulation model with statistical analysis conducted by other researchers. Different scenarios were also conducted in order to determine the impact the number of activities, the time of occurrence of the change, the availability of resources, and the type of project changes on productivity loss. Our results demonstrate that the number of activities in the project is a critical variable influencing the productivity of a project. When changes occur, the presence of a large number of activities leads to a much lower productivity loss than a small number of activities. The speed of reducing productivity for 30-job projects is about 25 percent faster than the reduction speed for 120-job projects. The moment of occurrence of a change also shows a significant impact on productivity. Indeed, the sooner the change occurs, the lower the productivity of the labor force. The availability of resources also impacts the productivity of a project when a change is implemented. There is a higher loss of productivity when the amount of resources is restricted.

Keywords: engineering changes, indirect costs overtime, productivity, scheduling, simulation

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Authors: Israel Ibarra Solis, Juan Carlos Rodriguez Sierra, Ma. del Carmen Salazar Hernandez, Isis Rodriguez Sanchez, David Perez Guerrero

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At the present paper we try to explain the analysis techniques use for the lubricating oil in a maintenance period of a city bus (Mercedes Benz Boxer 40), which is call ‘R-24 route’, line Coecillo Centro SA de CV in Leon Guanajuato, to estimate the optimal time for the oil change. Using devices such as the rotational viscometer and the atomic absorption spectrometer, they can detect the incipient form when the oil loses its lubricating properties and, therefore, cannot protect the mechanical components of diesel engines such these trucks. Timely detection of lost property in the oil, it allows us taking preventive plan maintenance for the fleet.

Keywords: atomic absorption spectrometry, maintenance, predictive velocity rate, lubricating oils

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Authors: Cao Bin, Yuan Yi, Wang Qiang, Amor Abdelkader, Ali Reza Kamali, Diogo Montalvão

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The study of the electrodynamic behavior of non-ferrous particles in time-varying magnetic fields is a promising area of research with wide applications, including recycling of non-ferrous metals, mechanical transmission, and space debris. The key technology for recovering non-ferrous metals is eddy current separation (ECS), which utilizes the eddy current force and torque to separate non-ferrous metals. ECS has several advantages, such as low energy consumption, large processing capacity, and no secondary pollution, making it suitable for processing various mixtures like electronic scrap, auto shredder residue, aluminum scrap, and incineration bottom ash. Improving the separation efficiency of mixtures with different particle sizes in ECS can create significant social and economic benefits. Our previous study investigated the influence of particle size on separation efficiency by combining numerical simulations and separation experiments. Pearson correlation analysis found a strong correlation between the eddy current force in simulations and the repulsion distance in experiments, which confirmed the effectiveness of our simulation model. The interaction effects between particle size and material type, rotational speed, and magnetic pole arrangement were examined. It offer valuable insights for the design and optimization of eddy current separators. The underlying mechanism behind the effect of particle size on separation efficiency was discovered by analyzing eddy current and field gradient. The results showed that the magnitude and distribution heterogeneity of eddy current and magnetic field gradient increased with particle size in eddy current separation. Based on this, we further found that increasing the curvature of magnetic field lines within particles could also increase the eddy current force, providing a optimized method to improving the separation efficiency of fine particles. By combining the results of the studies, a more systematic and comprehensive set of optimization guidelines can be proposed for mixtures with different particle size ranges. The separation efficiency of fine particles could be improved by increasing the rotational speed, curvature of magnetic field lines, and electrical conductivity/density of materials, as well as utilizing the eddy current torque. When designing an ECS, the particle size range of the target mixture should be investigated in advance, and the suitable parameters for separating the mixture can be fixed accordingly. In summary, these results can guide the design and optimization of ECS, and also expand the application areas for ECS.

Keywords: eddy current separation, particle size, numerical simulation, metal recovery

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Authors: Yujeong Shin, Seong Jin Cho, Jin Ho Kim

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In the textile-weaving machine, the reed is the core component to separate thousands of strands of yarn and to produce the fabric in a continuous high-speed movement. In addition, the reed affects the quality of the fiber. Therefore, the wire forming analysis of the main raw materials of the reed needs to be considered. Roll-forming is a key technology among the manufacturing process of reed wire using textile machine. A simulation of roll-forming line in accordance with the reduction rate is performed using LS-DYNA. The upper roller, fixed roller and reed wire are modeled by finite element. The roller is set to be rigid body and the wire of SUS430 is set to be flexible body. We predict the variation of the cross-sectional shape of the wire depending on the reduction ratio.

Keywords: textile machine, reed, rolling, reduction ratio, wire

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Authors: Alpana Saini, Sanghamitra Barman

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Investigations were carried out to determine whether low cost peanut hull as adsorbent hold promise in removal of thionine dyes in the biomedical industries. Pollution of water due to presence of colorants is a severe socio-environmental problem caused by the discharge of industrial wastewater. In view of their toxicity, non-biodegradability and persistent nature, their removal becomes an absolute necessity. For the removal of Thionine Dye using Peanut Hull, the 10mg/L concentration of dyes, 0.5g/l of adsorbent and 200 rpm agitation speed are found to be optimum for the adsorption studies. The Spectrophotometric technique was adopted for the measurement of concentration of dyes before and after adsorption at ʎmax 598nm. The adsorption data has been fitted well to Langmuir isotherm than to Freundlich adsorption isotherm. The adsorbent was characterized by Scanning Electron Microscopy (SEM).

Keywords: adsorption, langmuir isotherm, peanut hull, thionine

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Authors: Ece Cigdem Mutlu, Burak Alakent

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Maintaining the quality of manufactured products at a desired level depends on the stability of process dispersion and location parameters and detection of perturbations in these parameters as promptly as possible. Shewhart control chart is the most widely used technique in statistical process monitoring to monitor the quality of products and control process mean and variability. In the application of Xbar control charts, sample standard deviation and sample mean are known to be the most efficient conventional estimators in determining process dispersion and location parameters, respectively, based on the assumption of independent and normally distributed datasets. On the other hand, there is no guarantee that the real-world data would be normally distributed. In the cases of estimated process parameters from Phase I data clouded with outliers, efficiency of traditional estimators is significantly reduced, and performance of Xbar charts are undesirably low, e.g. occasional outliers in the rational subgroups in Phase I data set may considerably affect the sample mean and standard deviation, resulting a serious delay in detection of inferior products in Phase II. For more efficient application of control charts, it is required to use robust estimators against contaminations, which may exist in Phase I. In the current study, we present a simple approach to construct robust Xbar control charts using average distance to the median, Qn-estimator of scale, M-estimator of scale with logistic psi-function in the estimation of process dispersion parameter, and Harrell-Davis qth quantile estimator, Hodge-Lehmann estimator and M-estimator of location with Huber psi-function and logistic psi-function in the estimation of process location parameter. Phase I efficiency of proposed estimators and Phase II performance of Xbar charts constructed from these estimators are compared with the conventional mean and standard deviation statistics both under normality and against diffuse-localized and symmetric-asymmetric contaminations using 50,000 Monte Carlo simulations on MATLAB. Consequently, it is found that robust estimators yield parameter estimates with higher efficiency against all types of contaminations, and Xbar charts constructed using robust estimators have higher power in detecting disturbances, compared to conventional methods. Additionally, utilizing individuals charts to screen outlier subgroups and employing different combination of dispersion and location estimators on subgroups and individual observations are found to improve the performance of Xbar charts.

Keywords: average run length, M-estimators, quality control, robust estimators

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Authors: Ravi Kumar, Dhrubajit Barman, Nomi Baruah

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Software Cloning has grown an active area in software engineering research community yielding numerous techniques, various tools and other methods for clone detection and removal. The copying, modifying a block of code is identified as cloning as it is the most basic means of software reuse. Agile Software Development is an approach which is currently being used in various software projects, so that it helps to respond the unpredictability of building software through incremental, iterative, work cadences. Software Cloning has been introduced to Agile Environment and many Agile Software Development approaches are using the concept of Software Cloning. This paper discusses the various Agile Software Development approaches. It also discusses the degree to which the Software Cloning concept is being introduced in the Agile Software Development approaches.

Keywords: agile environment, refactoring, reuse, software cloning

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Authors: Benalia Nadia, Bensiali Nadia, Zezouri Noura

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This paper studies the effects of voltage sags, both symmetrical and unsymmetrical, on the three-phase Synchronous Machine (SM) when powering an isolate load or infinite bus bar. The vast majority of the electrical power generation systems in the world is consist of synchronous generators coupled to the electrical network though a transformer. Voltage sags on SM cause speed variations, current and torque peaks and hence may cause tripping and equipment damage. The consequences of voltage sags in the machine behavior depends on different factors such as its magnitude (or depth), duration , the parameters of the machine and also the size of load. In this study, we consider the machine feeds an infinite bus bar in the first and the isolate load using symmetric and asymmetric defaults to see the behavior of the machine in both case the simulation have been used on SIMULINK MATLAB.

Keywords: power quality, voltage sag, synchronous generator, infinite system

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Authors: A. Elsariti, T. Evans

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An understanding of the interaction between acoustic waves and cancellous bone is needed in order to realize the full clinical potential of ultrasonic bone measurements. Scattering is likely to be of central importance but has received little attention to date. Few theoretical approaches have been described to explain scattering of ultrasound from bone. In this study, a scattering model based on velocity and density fluctuations in a binary mixture (marrow fat and cortical matrix) was used to estimate the ultrasonic attenuation in cancellous bone as a function of volume fraction. Predicted attenuation and backscatter coefficient were obtained for a range of porosities and scatterer size. At 600 kHZ and for different scatterer size the effect of velocity and density fluctuations in the predicted attenuation was approximately 60% higher than velocity fluctuations.

Keywords: ultrasound scattering, sound speed, density fluctuations, attenuation coefficient

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Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

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Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

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Authors: Nanditha Rajamani, Anirudhaa R. Rao, Divya Sriram

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One of the greatest difficulties in treating patients with pain is the highly subjective nature of pain sensation. The measurement of pain intensity is primarily dependent on the patient’s report, often with little physical evidence to provide objective corroboration. This is also complicated by the fact that there are only few and expensive existing technologies (Functional Magnetic Resonance Imaging-fMRI). The need is thus clear and urgent for a reliable, non-invasive, non-painful, objective, readily adoptable, and coefficient diagnostic platform that provides additional diagnostic information to supplement its current regime with more information to assist doctors in diagnosing these patients. Thus, our idea of developing a pain detector was conceived to take a step further the detection and diagnosis of chronic and acute pain.

Keywords: pain sensor, microwave radiometery, pain sensation, fMRI

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Authors: Steve H. Y. Lee, Jeremy P. E. Spencer

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The aim of the present study was to explore the feasibility of enriching polyphenols in cow milk via addition of flavanone-rich citrus pulp to existing animal feed. 8 Holstein lactating cows were enrolled onto the 4 week feeding study. 4 cows were fed the standard farm diet (control group), with another 4 (treatment group) which are fed a standard farm diet mixed with citrus pulp diet. Milk was collected twice a day, 3 times a week. The resulting milk yield and its macronutrient composition as well as lactose content were measured. The milk phenolic compounds were analysed using electrochemical detection (ECD).

Keywords: milk, polyphenol, animal feeding, lactating cows

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Authors: Bachir Chemani, Rachid Halfaoui

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The aim of work is to define the distribution density of winding yarn on cylindrical and conical bobbins. It is known that parallel winding gives greater density and more regular distribution, but the unwinding of yarn is much more difficult for following process. The conical spool has an enormous advantage during unwinding and may contain a large amount of yarns, but the density distribution is not regular because of difference in diameters. The variation of specific density over the reel height is explained generally by the sudden change of winding speed due to direction movement variation of yarn. We determined the conditions of uniform winding and developed a calculate model to the change of the specific density of winding wire over entire spool height.

Keywords: textile, cylindrical bobbins, conical bobbins, parallel winding, cross winding

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Authors: C. Rattanakawin, S. Vasailor

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Acid leaching of flotation concentrate of oxide copper ore containing mainly of malachite was performed in a standard agitation tank with various parameters. The effects of solid to liquid ratio, sulfuric acid concentration, agitation speed, leaching temperature and time were examined to get proper conditions. The best conditions are 1:8 solid to liquid ratio, 10% concentration by weight, 250 rev/min, 30 ^oC and 5-min leaching time in respect. About 20% Cu grade assayed by atomic absorption technique with 98% copper recovery was obtained from these combined optimum conditions. Dissolution kinetics of the concentrate was approximated as a logarithmic function. As a result, the first-order reaction rate is suggested from this leaching study.

Keywords: agitation leaching, dissolution kinetics, flotation concentrate, oxide copper ore, sulfuric acid

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Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

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The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

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Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

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Authors: Linta Rose, Prasad K. Bhaskaran

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Water-level information along the coast is very important for disaster management, navigation, planning shoreline management, coastal engineering and protection works, port and harbour activities, and for a better understanding of near-shore ocean dynamics. The water-level variation along a coast attributes from various factors like astronomical tides, meteorological and hydrological forcing. The study area is the Head Bay of Bengal which is highly vulnerable to flooding events caused by monsoons, cyclones and sea-level rise. The study aims to explore the extent to which wind and surface pressure can influence water-level elevation, in view of the low-lying topography of the coastal zones in the region. The ADCIRC hydrodynamic model has been customized for the Head Bay of Bengal, discretized using flexible finite elements and validated against tide gauge observations. Monthly mean climatological wind and mean sea level pressure fields of ERA Interim reanalysis data was used as input forcing to simulate water-level variation in the Head Bay of Bengal, in addition to tidal forcing. The output water-level was compared against that produced using tidal forcing alone, so as to quantify the contribution of meteorological forcing to water-level. The average contribution of meteorological fields to water-level in January is 5.5% at a deep-water location and 13.3% at a coastal location. During the month of July, when the monsoon winds are strongest in this region, this increases to 10.7% and 43.1% respectively at the deep-water and coastal locations. The model output was tested by varying the input conditions of the meteorological fields in an attempt to quantify the relative significance of wind speed and wind direction on water-level. Under uniform wind conditions, the results showed a higher contribution of meteorological fields for south-west winds than north-east winds, when the wind speed was higher. A comparison of the spectral characteristics of output water-level with that generated due to tidal forcing alone showed additional modes with seasonal and annual signatures. Moreover, non-linear monthly mode was found to be weaker than during tidal simulation, all of which point out that meteorological fields do not cause much effect on the water-level at periods less than a day and that it induces non-linear interactions between existing modes of oscillations. The study signifies the role of meteorological forcing under fair weather conditions and points out that a combination of multiple forcing fields including tides, wind, atmospheric pressure, waves, precipitation and river discharge is essential for efficient and effective forecast modelling, especially during extreme weather events.

Keywords: ADCIRC, head Bay of Bengal, mean sea level pressure, meteorological forcing, water-level, wind

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Authors: Nagaratna Rajur, J. D. Mallapur, Y. B. Kirankumar

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The security in mobile communication is very different from the internet or telecommunication, because of its poor user interface and limited processing capacity, as well as combination of complex network protocols. Hence, it poses a challenge for less memory usage and low computation speed based security system. Security involves all the activities that are undertaken to protect the value and on-going usability of assets and the integrity and continuity of operations. An effective network security strategies requires identifying threats and then choosing the most effective set of tools to combat them. Cryptography is a simple and efficient way to provide security in communication. RSA is an asymmetric key approach that is highly reliable and widely used in internet communication. However, it has not been efficiently implemented in mobile communication due its computational complexity and large memory utilization. The proposed algorithm modifies the current RSA to be useful in mobile communication by reducing its computational complexity and memory utilization.

Keywords: M-RSA, sensor networks, sensor applications, security

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Authors: Rajeev Jain, Nimisha Jadon, Kshiti Singh

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Titanium oxide nanoparticles and 1-butyl-2,3-dimethylimidazolium bis (trifluoromethane- sulfonyl) imide modified glassy carbon electrode (TiO2/IL/GCE) has been fabricated for electrochemical sensing of flunarizine dihydrochloride (FRH). The electrochemical properties and morphology of the prepared nanocomposite were studied by electrochemical impedance spectroscopy (EIS) and transmission electron microscopy (TEM). The response of the electrochemical sensor was found to be proportional to the concentrations of FRH in the range from 0.5 µg mL-1 to 16 µg mL-1. The detection limit obtained was 0.03 µg mL-1. The proposed method was also applied to the determination of FRH in pharmaceutical formulation and human serum with good recoveries.

Keywords: flunarizine dihydrochloride, ionic liquid, nanoparticles, voltammetry, human serum

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Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.

Keywords: machine learning, pattern clustering, pooling, classification

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Authors: V. Prasannavenkadesan, A. Elango, S. Chockalingam

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During machining process, chatter is an unavoidable phenomenon. Boring bars possess the cantilever shape and due to this, it is subjected to chatter. The adverse effect of chatter includes the increase in temperature which will leads to excess tool wear. To overcome these problems, in this investigation, Cartridge brass (Cu – 70% and Zn – 30%) is passively fixed on the boring bar and also clearance is provided in order to reduce the displacement, tool wear and cutting temperature. A conventional all geared lathe is attached with vibrometer and pyrometer is used to measure the displacement and temperature. The influence of input parameters such as cutting speed, depth of cut and clearance on temperature, tool wear and displacement are investigated for various cutting conditions. From the result, the optimum conditions to obtain better damping in boring process for chatter reduction is identified.

Keywords: boring, chatter, mass damping, passive damping

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Authors: Francisco Toledo-Castillo, María Josefa Sospedra-Baeza, Sergio Hidalgo-Fuentes

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Motorcycles constitute about 9% of all motorized vehicles in Spain and are generally overrepresented in traffic accidents, accounting for 21% of total accidents. Six years of motorcycle accident data were obtained through the national accident database of Spain (Dirección General de Tráfico). Some of the studied factors are age, gender, helmet wearing, alcohol consumption, speeding, subject’s driving license and for how long it has been held, the trip purpose, and the presence of a passenger on the vehicle. Key findings show helmet use, unsafe speed, the trip purpose, weather, distraction, collision type and other variables play significant roles in crash-injury outcomes. Finally, we examine evolution of mortality and severity from 2006 to 2011.

Keywords: motorcycle accidents, risk factors, statistics, Spain

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Authors: Yamileth P. Herrera, Ronald R. Gutierrez, Carlos, Pacheco-Bustos

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This research aims at the numerical modeling of a rectangular contact tank in order to improve the hydrodynamic behavior and the retention time of the water to be treated with the disinfecting agent. The methodology to be followed includes a hydraulic analysis of the tank to observe the fluid velocities, which will allow evidence of low-speed areas that may generate pathogenic agent incubation or high-velocity areas, which may decrease the optimal contact time between the disinfecting agent and the microorganisms to be eliminated. Based on the results of the numerical model, the efficiency of the tank under the geometric and hydraulic conditions considered will be analyzed. This would allow the performance of the tank to be improved before starting a construction process, thus avoiding unnecessary costs.

Keywords: contact tank, numerical models, hydrodynamic modeling, residence time

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Authors: Mehdi Fuladipanah

Abstract:

Stepped spillway includes several steps from the crest to the toe. The steps of stepped spillway could cause to decrease the energy with making energy distribution in the longitude mode and also to reduce the outcome speed. The aim of this study was to stimulate the stepped spillway combined with stilling basin-step using Fluent model and the turbulent superficial flow using RNG, K-ε. The free surface of the flow was monitored by VOF model. The velocity and the depth of the flow were measured by tail water depth by the numerical model and then the dissipated energy was calculated along the spillway. The results indicated that the stilling basin-step complex may cause energy dissipation increment in the stepped spillway. Also, the numerical model was suggested as an effective method to predict the circular and complicated flows in the stepped spillways.

Keywords: stepped spillway, fluent model, VOF model, K-ε model, energy distribution

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