Search results for: speed hump detection

Authors: Clara Tramuta, Lucia Decastelli, Elisa Barcucci, Sandra Fragassi, Samantha Lupi, Enrico Arletti, Melissa Bizzarri, Daniela Manila Bianchi

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Introdution: Food allergies occurs, in the Western World, 2% of adults and up to 8% of children. The protection of allergic consumers is guaranted, in Eurrope, by Regulation (EU) No 1169/2011 of the European Parliament which governs the consumer's right to information and identifies 14 food allergens to be mandatory indicated on the label. Among these, mustard is a popular spice added to enhance the flavour and taste of foods. It is frequently present as an ingredient in spice blends, marinades, salad dressings, sausages, and other products. Hypersensitivity to mustard is a public health problem since the ingestion of even low amounts can trigger severe allergic reactions. In order to protect the allergic consumer, high performance methods are required for the detection of allergenic ingredients. Food safety laboratories rely on validated methods that detect hidden allergens in food to ensure the safety and health of allergic consumers. Here we present the test results for the validation and accreditation of a Real time PCR assay (RT-PCR: SPECIALfinder MC Mustard, Generon), for the detection of mustard traces in food. Materials and Methods. The method was tested on five classes of food matrices: bakery and pastry products (chocolate cookies), meats (ragù), ready-to-eat (mixed salad), dairy products (yogurt), grains, and milling products (rice and barley flour). Blank samples were spiked starting with the mustard samples (Sinapis Alba), lyophilized and stored at -18 °C, at a concentration of 1000 ppm. Serial dilutions were then prepared to a final concentration of 0.5 ppm, using the DNA extracted by ION Force FAST (Generon) from the blank samples. The Real Time PCR reaction was performed by RT-PCR SPECIALfinder MC Mustard (Generon), using CFX96 System (BioRad). Results. Real Time PCR showed a limit of detection (LOD) of 0.5 ppm in grains and milling products, ready-to-eat, meats, bakery, pastry products, and dairy products (range Ct 25-34). To determine the exclusivity parameter of the method, the ragù matrix was contaminated with Prunus dulcis (almonds), peanut (Arachis hypogaea), Glycine max (soy), Apium graveolens (celery), Allium cepa (onion), Pisum sativum (peas), Daucus carota (carrots), and Theobroma cacao (cocoa) and no cross-reactions were observed. Discussion. In terms of sensitivity, the Real Time PCR confirmed, even in complex matrix, a LOD of 0.5 ppm in five classes of food matrices tested; these values are compatible with the current regulatory situation that does not consider, at international level, to establish a quantitative criterion for the allergen considered in this study. The Real Time PCR SPECIALfinder kit for the detection of mustard proved to be easy to use and particularly appreciated for the rapid response times considering that the amplification and detection phase has a duration of less than 50 minutes. Method accuracy was rated satisfactory for sensitivity (100%) and specificity (100%) and was fully validated and accreditated. It was found adequate for the needs of the laboratory as it met the purpose for which it was applied. This study was funded in part within a project of the Italian Ministry of Health (IZS PLV 02/19 RC).

Keywords: allergens, food, mustard, real time PCR

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Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

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Authors: Md. Abdul Aziz

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Sulfide ion is water soluble, highly corrosive, toxic and harmful to the human beings. As a result, knowing the exact concentration of sulfide in water is very important. However, the existing detection and quantification methods have several shortcomings, such as high cost, low sensitivity, and massive instrumentation. Consequently, the development of novel sulfide sensor is relevant. Nevertheless, electrochemical methods gained enormous popularity due to a vast improvement in the technique and instrumentation, portability, low cost, rapid analysis and simplicity of design. Successful field application of electrochemical devices still requires vast improvement, which depends on the physical, chemical and electrochemical aspects of the working electrode. The working electrode made of bulk gold (Au) and platinum (Pt) are quite common, being very robust and endowed with good electrocatalytic properties. High cost, and electrode poisoning, however, have so far hindered their practical application in many industries. To overcome these obstacles, we developed a sulfide sensor based on an indium tin oxide nanoparticle (ITONP)-modified ITO electrode. To prepare ITONP-modified ITO, various methods were tested. Drop-drying of ITONPs (aq.) on aminopropyltrimethoxysilane-functionalized ITO (APTMS/ITO) was found to be the best method on the basis of voltammetric analysis of the sulfide ion. ITONP-modified APTMS/ITO (ITONP/APTMS/ITO) yielded much better electrocatalytic properties toward sulfide electro-οxidation than did bare or APTMS/ITO electrodes. The ITONPs and ITONP-modified ITO were also characterized using transmission electron microscopy and field emission scanning electron microscopy, respectively. Optimization of the type of inert electrolyte and pH yielded an ITONP/APTMS/ITO detector whose amperometrically and chronocoulοmetrically determined limits of detection for sulfide in aqueous solution were 3.0 µM and 0.90 µM, respectively. ITONP/APTMS/ITO electrodes which displayed reproducible performances were highly stable and were not susceptible to interference by common contaminants. Thus, the developed electrode can be considered as a promising tool for sensing sulfide.

Keywords: amperometry, chronocoulometry, electrocatalytic properties, ITO-nanoparticle-modified ITO, sulfide sensor

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Authors: Moftah BinHasan

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Induction motors (IM) are vital components in industrial processes whose failure may yield to an unexpected interruption at the industrial plant, with highly incurred consequences in costs, product quality, and safety. Among different detection approaches proposed in the literature, that based on stator current monitoring termed as Motor Current Signature Analysis (MCSA) is the most preferred. MCSA is advantageous due to its non-invasive properties. The popularity of motor current signature analysis comes from being that the current consists of motor harmonics, around the supply frequency, which show some properties related to different situations of healthy and faulty conditions. One of the techniques used with machine line current resorts to spectrum analysis. Besides discussing the fundamentals of MCSA and its applications in the condition monitoring arena, this paper shows a summary of the most frequent faults and their consequence signatures on the stator current spectrum of an induction motor. In addition, this article presents different case studies of induction motor fault diagnosis. These faults were seeded in the machine which was run for more than an hour for each test before the results were recorded for the faulty situations. These results are then compared with those for the healthy cases that were recorded earlier.

Keywords: induction motor, condition monitoring, fault diagnosis, MCSA, rotor, stator, bearing, eccentricity

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Authors: Zhiwen Pan, Jesus Pacheco, Salim Hariri, Yiqiang Chen, Bozhi Liu

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The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.

Keywords: Internet of Things, network security, context awareness, intrusion detection

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Authors: Jannes Quer, Amir Niknejad, Marcus Weber

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Computational Drug Design is often based on Molecular Dynamics simulations of molecular systems. Molecular Dynamics can be used to simulate, e.g., the binding and unbinding event of a small drug-like molecule with regard to the active site of an enzyme or a receptor. However, the time-scale of the overall binding event is many orders of magnitude longer than the time-scale of simulation. Thus, there is a need to speed-up molecular simulations. In order to speed up simulations, the molecular dynamics trajectories have to be ”steared” out of local minimizers of the potential energy surface – the so-called metastabilities – of the molecular system. Increasing the kinetic energy (temperature) is one possibility to accelerate simulated processes. However, with temperature the entropy of the molecular system increases, too. But this kind ”stearing” is not directed enough to stear the molecule out of the minimum toward the saddle point. In this article, we give a new mathematical idea, how a potential energy surface can be changed in such a way, that entropy is kept under control while the trajectories are still steared out of the metastabilities. In order to compute the unsteared transition behaviour based on a steared simulation, we propose to use extrapolation methods. In the end we mathematically show, that our method accelerates the simulations along the direction, in which the curvature of the potential energy surface changes the most, i.e., from local minimizers towards saddle points.

Keywords: extrapolation, Eyring-Kramers, metastability, multilevel sampling

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Authors: Ajay Sidana, Kulbir Singh Sandhu, Balwinder Singh Sidhu

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Joining of dissimilar non-ferrous alloys like aluminium and magnesium alloys becomes important in various automobile and aerospace applications due to their low density and good corrosion resistance. Friction Stir Welding (FSW), a solid state joining process, successfully welds difficult to weld similar and dissimilar aluminum and magnesium alloys. Two tool rotation speeds were selected by keeping the transverse speed constant to weld similar and dissimilar alloys. Similar(Al to Al) and Dissimilar(Al to Mg) weld joints were obtained by FSW. SEM scans revealed that higher tool rotation fragments the coarse grains of base material into fine grains in the weld zone. Also, there are less welding defects in weld joints obtained with higher tool rotation speed. The material of dissimilar alloys was mixed with each other forming recrystallised new intermetallics. There was decrease in hardness of similar weld joint however there is significant increase in hardness of weld zone in case of dissimilar weld joints due to stirring action of tool and formation of inter metallics. Tensile tests revealed that there was decrease in percentage elongation in both similar and dissimilar weld joints.

Keywords: aluminum alloys, magnesium alloys, friction stir welding, microstructure, mechanical properties

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Authors: Shakir H. Mohammed Al-Alwany, Saad Hasan M. Ali, Ibrahim Mohammed S. Shnawa

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The study was aimed to define the percentage of detection of high-oncogenic risk types of HPV and their genotyping in archival tissue specimens that ranged from apparently healthy tissue to invasive breast cancer by using one of the recent versions of In Situ Hybridization(ISH) 0.2. To find out rational significance of such genotypes as well as over expressed products of mutants P53 and RB genes on the severity of underlying breast cancers. The DNA of HPV was detected in 46.5 % of tissues from breast cancers while HPV DNA in the tissues from benign breast tumours was detected in 12.5%. No HPV positive–ISH reaction was detected in healthy breast tissues of the control group. HPV DNA of genotypes (16, 18, 31 and 33) was detected in malignant group in frequency of 25.6%, 27.1%, 30.2% and 12.4%, respectively. Over expression of p53 was detected by IHC in 51.2% breast cancer cases and in 50% benign breast tumour group, while none of control group showed P53- over expression. Retinoblastoma protein was detected by IHC test in 49.7% of malignant breast tumours, 54.2% of benign breast tumours but no signal was reported in the tissues of control group. The significance prevalence of expression of mutated p53 & Rb genes as well as detection of high-oncogenic HPV genotypes in patients with breast cancer supports the hypothesis of an etiologic role for the virus in breast cancer development.

Keywords: human papilloma virus, P53, RB, breast cancer

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Authors: Illyas Md Isa, Maryam Musfirah Che Sobry, Mohamad Syahrizal Ahmad, Nurashikin Abd Azis

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A single-walled carbon nanotube (SWCNT) that has been modified with magnesium layered hydroxide 3-(4-methoxyphenyl)propionic acid nanocomposite was proposed for the determination of uric acid and bisphenol A by square wave voltammetry. The results obtained denote that MLH-MPP nanocomposites enhance the sensitivity of the voltammetry detection responses. The best performance is shown by the modified carbon nanotube paste electrode (CNTPE) with the composition of single-walled carbon nanotube: magnesium layered hydroxide 3-(4-methoxyphenyl)propionic acid nanocomposite at 100:15 (% w/w). The linear range where the sensor works well is within the concentration 1.0 10-7 – 1.0 10-4 and 3.0 10-7 – 1.0 10-4 for uric acid and bisphenol A respectively with the limit of detection of 1.0 10-7 M for both organics. The interferences of uric acid and bisphenol A with other organic were studied and most of them did not interfere. The results shown for each experimental parameter on the proposed CNTPE showed that it has high sensitivity, good selectivity, repeatability and reproducibility. Therefore, the modified CNTPE can be used for the determination of uric acid and bisphenol A in real samples such as blood, plastic bottles and foods.

Keywords: bisphenol A, magnesium layered hydroxide 3-(4-methoxyphenyl)propionic acid nanocomposite, Nanocomposite, uric acid

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: Jiao Sun, Li Pan, Shijun Liu

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Recommender systems have been widely used in contemporary industry, and plenty of work has been done in this field to help users to identify items of interest. Collaborative Filtering (CF, for short) algorithm is an important technology in recommender systems. However, less work has been done in automobile recommendation system with the sharp increase of the amount of automobiles. What’s more, the computational speed is a major weakness for collaborative filtering technology. Therefore, using MapReduce framework to optimize the CF algorithm is a vital solution to this performance problem. In this paper, we present a recommendation of the users’ comment on industrial automobiles with various properties based on real world industrial datasets of user-automobile comment data collection, and provide recommendation for automobile providers and help them predict users’ comment on automobiles with new-coming property. Firstly, we solve the sparseness of matrix using previous construction of score matrix. Secondly, we solve the data normalization problem by removing dimensional effects from the raw data of automobiles, where different dimensions of automobile properties bring great error to the calculation of CF. Finally, we use the MapReduce framework to optimize the CF algorithm, and the computational speed has been improved times. UV decomposition used in this paper is an often used matrix factorization technology in CF algorithm, without calculating the interpolation weight of neighbors, which will be more convenient in industry.

Keywords: collaborative filtering, recommendation, data normalization, mapreduce

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Authors: Manqhai Kraai, Adrian M. Shrader, Peter F. Scogings

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For animals living in herds, competition between group members increases as herd size increases. The intensity of this competition is likely greater across poor quality landscapes and during the dry season. In contrast to wild herbivores, herd size in domestic livestock is determined by their owners. This then raises the question, how do domestic livestock, like goats, reduce competition for food within these defined herds? To explore this question, large-scale foraging behaviour of both small (12 to 28 individuals) and large (42 to 83 individuals) herds of free-ranging goats were recorded in Tugela Ferry, KwaZulu-Natal, South Africa. The study was conducted on three different landscapes that varied in both food quality and availability, during the wet and dry seasons of 2013-2014. The goats were housed in kraals overnight and let out in the mornings to forage unattended. Thus, foraging decisions were made by the goats and not by herders. The large-scale foraging behaviours focussed on included, (i) total distance travelled by goats while foraging, (ii) distance travelled before starting to feed, (iii) travel speed, and (iv) feeding duration. This was done using Garmin Foretrex 401 GPS devices harnessed to two goats per herd. Irrespective of season, there was no difference in the total distance travelled by the different sized herds across the different quality landscapes. However, both small and large herds started feeding farther from the kraal in the dry compared to the wet season. Despite this, there was no significant seasonal difference in total amount of time the herds spent feeding across the different landscapes. Finally, both small and large herds increased their travel speed across all the landscapes in the dry season, but large herds travelled faster than small herds. This increase was likely to maximise the time that large herds could spend feeding in good areas. Ultimately, these results indicate that both small and large herds were affected by declines in food quality and quantity during the dry season. However, as large herds made greater behavioural adjustments compared to smaller herds (i.e., feeding farther away from the kraal and travelling faster), it appeared that they were more affected by the seasonal increases in intra-herd competition.

Keywords: distance, feeding duration, food availability, food quality, travel speed

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Authors: Ilana Margalith, Adaya Meirowitz, Sigalit Cohavi

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Violence against health professionals by patients and their families have recently become a disturbing phenomenon worldwide, exacting psychological as well as economic tolls. Health workplaces in Israel (e.g. hospitals and H.M.O clinics) provide workshops for their employees, supplying them with coping strategies. However, these workshops do not focus on nursing students, who are also subjected to this violence. Their learning environment is no longer as protective as it used to be. Furthermore, coping with violence was not part of the curriculum for Israeli nursing students. Thus, based on human aggression theories which depict the pivotal role of the professional's correct response in preventing the onset of an aggressive response or the escalation of violence, a workshop was developed for undergraduate nursing students at the Clalit Nursing Academy, Rabin Campus (Dina), Israel. The workshop aimed at reducing students' anxiety vis a vis the aggressive patient or family in addition to strengthening their ability to cope with such situations. The students practiced interpersonal skills, especially relevant to early detection of potential violence, as well as ‘a correct response’ reaction to the violence, thus developing the necessary steps to be implemented when encountering violence in the workplace. In order to assess the efficiency of the workshop, the participants filled out a questionnaire comprising knowledge and self-efficacy scales. Moreover, the replies of the 23 participants in this workshop were compared with those of 24 students who attended a standard course on interpersonal communication. Students' self-efficacy and knowledge were measured in both groups before and after the course. A statistically significant interaction was found between group (workshop/standard course) and time (before/after) as to the influence on students' self-efficacy (p=0.004) and knowledge (p=0.007). Nursing students, who participated in this ‘coping with workplace violence’ workshop, gained knowledge, confidence and a sense of self-efficacy with regard to workplace violence. Early detection of signs of imminent violence amongst patients or families and the prevention of its escalation, as well as the ability to manage the threatening situation when occurring, are acquired skills. Encouraging nursing students to learn and practice these skills may enhance their ability to cope with these unfortunate occurrences.

Keywords: early detection of violence, nursing students, patient aggression, self-efficacy, workplace violence

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Authors: Surendra Choudhary, Sapan Tiwari

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The driver has two fundamental duties i) controlling the position of the vehicle along the longitudinal and lateral direction of movement ii) roadway width. Both of these duties are interdependent and are concurrently referred to as two-dimensional driver behavior. One of the main problems facing driver behavior modeling is to identify the parameters for describing the exemplary driving conduct and car maneuver under distinct traffic circumstances. Still, to date, there is no well-accepted theory that can comprehensively model the 2-D driver conduct (longitudinal and lateral). The primary objective of this research is to explore the vehicle's lateral longitudinal behavior in the heterogeneous condition of traffic on horizontal curves as well as the effect of road geometry on dynamic traffic parameters, i.e., car velocity and lateral placement. In this research, with their interrelationship, a thorough assessment of dynamic car parameters, i.e., speed, lateral acceleration, and turn radius. Also, horizontal curve road parameters, i.e., curvature radius, pavement friction, are performed. The dynamic parameters of the various types of car drivers are gathered using a VBOX GPS-based tool with high precision. The connection between dynamic car parameters and curve geometry is created after the removal of noise from the GPS trajectories. The major findings of the research are that car maneuvers with higher than the design limits of speed, acceleration, and lateral deviation on the studied curves of the highway. It can become lethal if the weather changes from dry to wet.

Keywords: geometry, maneuverability, terrain, trajectory, VBOX

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Authors: Tohid Rahimi, Yahya Naderi, Babak Yousefi, Seyed Hossein Hoseini

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Today’s modern interconnected power system is highly complex in nature. In this, one of the most important requirements during the operation of the electric power system is the reliability and security. Power and frequency oscillation damping mechanism improve the reliability. Because of power system stabilizer (PSS) low speed response against of major fault such as three phase short circuit, FACTs devise that can control the network condition in very fast time, are becoming popular. However, FACTs capability can be seen in a major fault present when nonlinear models of FACTs devise and power system equipment are applied. To realize this aim, the model of multi-machine power system with FACTs controller is developed in MATLAB/SIMULINK using Sim Power System (SPS) blockiest. Among the FACTs device, Static synchronous series compensator (SSSC) due to high speed changes its reactance characteristic inductive to capacitive, is effective power flow controller. Tuning process of controller parameter can be performed using different method. However, Genetic Algorithm (GA) ability tends to use it in controller parameter tuning process. In this paper, firstly POD controller is used to power oscillation damping. But in this station, frequency oscillation dos not has proper damping situation. Therefore, FOD controller that is tuned using GA is using that cause to damp out frequency oscillation properly and power oscillation damping has suitable situation.

Keywords: power oscillation damping (POD), frequency oscillation damping (FOD), Static synchronous series compensator (SSSC), Genetic Algorithm (GA)

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Authors: Jose Daniel Hoyos Giraldo, Jesus Hernan Jimenez Giraldo, Juan Pablo Alvarado Perilla

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Range and endurance are the main limitations of electric aircraft due to the nature of its source of power. The improvement of efficiency on this kind of systems is extremely meaningful to encourage the aircraft operation with less environmental impact. The propeller efficiency highly affects the overall efficiency of the propulsion system; hence its optimization can have an outstanding effect on the aircraft performance. An optimization method is applied to an aircraft propeller in order to maximize its range and endurance by estimating the best combination of geometrical parameters such as diameter and airfoil, chord and pitch distribution for a specific aircraft design at a certain cruise speed, then the rotational speed at which the propeller operates at minimum current consumption is estimated. The optimization is based on the Blade Element Momentum (BEM) method, additionally corrected to account for tip and hub losses, Mach number and rotational effects; furthermore an airfoil lift and drag coefficients approximation is implemented from Computational Fluid Dynamics (CFD) simulations supported by preliminary studies of grid independence and suitability of different turbulence models, to feed the BEM method, with the aim of achieve more reliable results. Additionally, Vortex Theory is employed to find the optimum pitch and chord distribution to achieve a minimum induced loss propeller design. Moreover, the optimization takes into account the well-known brushless motor model, thrust constraints for take-off runway limitations, maximum allowable propeller diameter due to aircraft height and maximum motor power. The BEM-CFD method is validated by comparing its predictions for a known APC propeller with both available experimental tests and APC reported performance curves which are based on Vortex Theory fed with the NASA Transonic Airfoil code, showing a adequate fitting with experimental data even more than reported APC data. Optimal propeller predictions are validated by wind tunnel tests, CFD propeller simulations and a study of how the propeller will perform if it replaces the one of on known aircraft. Some tendency charts relating a wide range of parameters such as diameter, voltage, pitch, rotational speed, current, propeller and electric efficiencies are obtained and discussed. The implementation of CFD tools shows an improvement in the accuracy of BEM predictions. Results also showed how a propeller has higher efficiency peaks when it operates at high rotational speed due to the higher Reynolds at which airfoils present lower drag. On the other hand, the behavior of the current consumption related to the propulsive efficiency shows counterintuitive results, the best range and endurance is not necessary achieved in an efficiency peak.

Keywords: BEM, blade design, CFD, electric aircraft, endurance, optimization, range

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Authors: Nusrat Praween, Krishna Thej Pammi Guru, Palash Kumar Basu

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Designing non-invasive biosensors for cancer diagnosis is essential for developing an affordable and specific tool to measure cancer-related exosome biomarkers. Exosomes, released by healthy as well as cancer cells, contain valuable information about the biomarkers of various diseases, including cancer. Despite the availability of various isolation techniques, ultracentrifugation is the standard technique that is being employed. Post isolation, exosomes are traditionally exposed to detergents for extracting their proteins, which can often lead to protein degradation. Further to this, it is very essential to develop a sensing platform for the quantification of clinically relevant proteins in a wider range to ensure practicality. In this study, exosomes were immobilized on the Au Screen Printed Electrode (SPE) using EDC/NHS chemistry to facilitate binding. After immobilizing the exosomes on the screen-printed electrode (SPE), we investigated the impact of the electric field by applying various voltages to induce exosome lysis and release their contents. The lysed solution was used for sensing TSG101, a crucial biomarker associated with various cancers, using both faradaic and non-faradaic electrochemical impedance spectroscopy (EIS) methods. The results of non-faradaic and faradaic EIS were comparable and showed good consistency, indicating that non-faradaic sensing can be a reliable alternative. Hence, the non-faradaic sensing technique was used for label-free quantification of the TSG101 biomarker. The results were validated using ELISA. Our electrochemical immunosensor demonstrated a consistent response of TSG101 from 125 pg/mL to 8000 pg/mL, with a detection limit of 0.125 pg/mL at room temperature. Additionally, since non-faradic sensing is label-free, the ease of usage and cost of the final sensor developed can be reduced. The proposed immunosensor is capable of detecting the TSG101 protein at low levels in healthy serum with good sensitivity and specificity, making it a promising platform for biomarker detection.

Keywords: biosensor, exosomes isolation on SPE, electric field lysis of exosome, EIS sensing of TSG101

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Authors: M. Akhlaque Ahmed, Sidra A. Shaikh, Maliha A. Siddiqui, Adeel Tahir

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Global and diffuse solar radiation on horizontal surface of southern sindh namely Karachi, Hyderabad, Nawabshah were carried out using sunshine hour data of the area to asses the feasibility of solar Energy utilization at Sindh province for power generation. From the observation, result is derived which shows a drastic variation in the diffuse and direct component of solar radiation for summer and winter for Southern Sindh that is both contributes 50% for Karachi and Hyderabad. In Nawabshah area, the contribution of diffuse solar radiation is low in monsoon months, July and August. The Kᴛ value of Nawabshah indicates a clear sky almost throughout the year. The percentage of diffuse radiation does not exceed more than 20%. In Nawabshah, the appearance of cloud is rare even in monsoon months. The estimated values indicate that Nawabshah has high solar potential whereas Karachi and Hyderabad has low solar potential. During the monsoon months, the southern part of Sind can utilize the hybrid system with wind power. Near Karachi and Hyderabad, the wind speed ranges between 6.2 to 6.9 m/sec. There exist a wind corridor near Karachi, Hyderabad, Gharo, Keti Bander and Shah Bander. The short fall of solar can be compensated by wind because in monsoon months July and August the wind speed are higher in the southern region of Sindh.

Keywords: hybrid power system, power generation, solar and wind energy potential, southern Sindh

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Authors: Sahib Dino Naseerani

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The presented scientific text discusses the concept of imaginary pressure and its role in different relative motions. It explores how imaginary pressure, which is the combined effect of external atmospheric pressure and real pressure, affects various substances and their physical properties. The study aims to understand the impact of imaginary pressure and its potential applications in different contexts, such as spaceflight. The main objective of this study is to investigate the role of imaginary pressure on different relative motions. Specifically, the researchers aim to examine how imaginary pressure affects the contraction and mass variation of a body when it is in motion at the speed of light. The study seeks to provide insights into the behavior and consequences of imaginary pressure in various scenarios. The data was collected using three research papers. This research contributes to a better understanding of the theoretical implications of imaginary pressure. It elucidates how imaginary pressure is responsible for the contraction and mass variation of a body in motion, particularly at the speed of light. The findings shed light on the behavior of substances under the influence of imaginary pressure, providing valuable insights for future scientific studies. The study addresses the question of how imaginary pressure influences various relative motions and their associated physical properties. It aims to understand the role of imaginary pressure in the contraction and mass variation of a body, particularly at high speeds. By examining different substances in liquid and solid forms, the research explores the consequences of imaginary pressure on their volume, length, and mass.

Keywords: imaginary pressure, contraction, variation, relative motion

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Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

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Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

Procedia PDF Downloads 88

Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

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Authors: Luís F. da Silva, Ariadne C. Catto, Osmando F. Lopes, Khalifa Aguir, Valmor R. Mastelaro, Caue Ribeiro, Elson Longo

Abstract:

Gas detection is important for controlling industrial, and vehicle emissions, agricultural residues, and environmental control. In last decades, several semiconducting oxides have been used to detect dangerous or toxic gases. The excellent gas-sensing performance of these devices have been observed at high temperatures (~250 °C), which forbids the use for the detection of flammable and explosive gases. In this way, ultraviolet light activated gas sensors have been a simple and promising alternative to achieve room temperature sensitivity. Among the semiconductor oxides which exhibit a good performance as gas sensor, the zinc oxide (ZnO) and tin oxide (SnO2) have been highlighted. Nevertheless, their poor selectivity is the main disadvantage for application as gas sensor devices. Recently, heterostructures combining these two semiconductors (ZnO-SnO2) have been studied as an alternative way to enhance the gas sensor performance (sensitivity, selectivity, and stability). In this work, we investigated the influence of mass ratio Zn:Sn on the properties of ZnO-SnO2 nanocomposites prepared by hydrothermal treatment for 4 hours at 200 °C. The crystalline phase, surface, and morphological features were characterized by X-ray diffraction (XRD), high-resolution transmission electron (HR-TEM), and X-ray photoelectron spectroscopy (XPS) measurements. The gas sensor measurements were carried out at room-temperature under ultraviolet (UV) light irradiation using different ozone levels (0.06 to 0.61 ppm). The XRD measurements indicate the presence of ZnO and SnO2 crystalline phases, without the evidence of solid solution formation. HR-TEM analysis revealed that a good contact between the SnO2 nanoparticles and the ZnO nanorods, which are very important since interface characteristics between nanostructures are considered as challenge to development new and efficient heterostructures. Electrical measurements proved that the best ozone gas-sensing performance is obtained for ZnO:SnO2 (50:50) nanocomposite under UV light irradiation. Its sensitivity was around 6 times higher when compared to SnO2 pure, a traditional ozone gas sensor. These results demonstrate the potential of ZnO-SnO2 heterojunctions for the detection of ozone gas at room-temperature when irradiated with UV light irradiation.

Keywords: hydrothermal, zno-sno2, ozone sensor, uv-activation, room-temperature

Procedia PDF Downloads 275

Authors: Tanwarat Kajsongkram, Saowalux Rotamporn, Sirinat Limbunruang, Sirinan Thubthimthed.

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High-Performance Liquid Chromatography (HPLC) method was developed and validated for simultaneous estimation of 6-Gingerol(6G) and 6-Shogaol(6S) in joint pain relief gel containing ginger extract. The chromatographic separation was achieved by using C18 column, 150 x 4.6mm i.d., 5μ Luna, mobile phase containing acetonitrile and water (gradient elution). The flow rate was 1.0 ml/min and the absorbance was monitored at 282 nm. The proposed method was validated in terms of the analytical parameters such as specificity, accuracy, precision, linearity, range, limit of detection (LOD), limit of quantification (LOQ), and determined based on the International Conference on Harmonization (ICH) guidelines. The linearity ranges of 6G and 6S were obtained over 20-60 and 6-18 µg/ml respectively. Good linearity was observed over the above-mentioned range with linear regression equation Y= 11016x- 23778 for 6G and Y = 19276x-19604 for 6S (x is concentration of analytes in μg/ml and Y is peak area). The value of correlation coefficient was found to be 0.9994 for both markers. The limit of detection (LOD) and limit of quantification (LOQ) for 6G were 0.8567 and 2.8555 µg/ml and for 6S were 0.3672 and 1.2238 µg/ml respectively. The recovery range for 6G and 6S were found to be 91.57 to 102.36 % and 84.73 to 92.85 % for all three spiked levels. The RSD values from repeated extractions for 6G and 6S were 3.43 and 3.09% respectively. The validation of developed method on precision, accuracy, specificity, linearity, and range were also performed with well-accepted results.

Keywords: ginger, 6-gingerol, HPLC, 6-shogaol

Procedia PDF Downloads 429

Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

Procedia PDF Downloads 61

Authors: Alae Lamtai, Said Elkoun, Hniya Kharmoudi, Mathieu Robert, Carl Diez

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This study applies Taguchi's design of experiment methodology and grey relational analysis (GRA) for multi objective optimization of an industrial recycling line. This last is composed mainly of a mono and twin-screw extruder and a filtration system. Experiments were performed according to L₁₆ standard orthogonal array based on five process parameters, namely: mono screw design, screw speed of the mono and twin-screw extruder, melt pump pressure, and filter mesh size. The objective of this optimization is to improve the durability of the Polyethylene (PE) blend by decreasing the loss of Stress Crack resistance (SCR) using Notched Crack Ligament Stress (NCLS) test and Unnotched Crack Ligament Stress (UCLS) in parallel with increasing the gain of Izod impact strength of the Polyethylene (PE) blend before and after recycling. Based on Grey Relational Analysis (GRA), the optimal setting of process parameters was identified, and the results indicated that the mono-screw design and screw speed of both mono and twin-screw extruder impact significantly the mechanical properties of recycled Polyethylene (PE) blend.

Keywords: Taguchi, recycling line, polyethylene, stress crack resistance, Izod impact strength, grey relational analysis

Procedia PDF Downloads 63

Authors: Pujan Sarkar

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Frictional behavior of glass epoxy and Al particulate glass-epoxy composites sliding against mild steel are investigated experimentally at normal atmospheric condition. Glass epoxy (0 wt% Al) and 5, 10 and 15 wt% Al particulate filled glass-epoxy composites are fabricated in conventional hand lay-up technique followed by light compression moulding process. A pin on disc type friction apparatus is used under dry sliding conditions. Experiments are carried out at a normal load of 5-50 N, and sliding speeds of 0.5-5.0 m/s for a fixed duration. Variations of friction coefficient with sliding time at different loads and speeds for all the samples are considered. Results show that the friction coefficient is influenced by sliding time, normal loads, sliding speeds, and wt% of Al content. In general, with respect to time, friction coefficient increases initially with a lot of fluctuations for a certain duration. After that, it becomes stable for the rest of the experimental time. With the increase of normal load, friction coefficient decreases at all speed levels and for all the samples whereas, friction coefficient increases with the increase of sliding speed at all normal loads for glass epoxy and 5 wt% Al content glass-epoxy composites. But for 10 and 15 wt%, Al content composites at all loads, reverse trend of friction coefficient has been recorded. Under different tribological conditions, the suitability of composites in respect of wt% of Al content is noted, and 5 wt% Al content glass-epoxy composite reports as the lowest frictional material at all loads compared to other samples.

Keywords: Al powder, composite, epoxy, friction, glass fiber

Procedia PDF Downloads 117

Authors: Yi Zhang, Yuan Tian, Jiehua Chen, Sihong Gu

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Chip-scale spin-exchange relaxation free (SERF) atomic magnetometer makes use of millimeter-scale vapor cells micro-fabricated by Micro-electromechanical Systems (MEMS) technique and SERF mechanism, resulting in the characteristics of high spatial resolution and high sensitivity. It is useful for biomagnetic imaging including magnetoencephalography and magnetocardiography. In a prevailing scheme, circularly polarized on-resonance laser beam is adapted for both pumping and probing the atomic polarization. And the magnetic-field-sensitive signal is extracted by transmission laser intensity enhancement as a result of atomic polarization increase on zero field level crossing resonance. The scheme is very suitable for integration, however, the laser amplitude modulation (AM) noise and laser frequency modulation to amplitude modulation (FM-AM) noise is superimposed on the photon shot noise reducing the signal to noise ratio (SNR). To suppress AM and FM-AM noise the paper puts forward a novel scheme which adopts circularly polarized on-resonance light pumping and linearly polarized frequency-detuning laser probing. The transmission beam is divided into transmission and reflection beams by a polarization analyzer, the angle between the analyzer's transmission polarization axis and frequency-detuning laser polarization direction is set to 45°. The magnetic-field-sensitive signal is extracted by polarization rotation enhancement of frequency-detuning laser which induces two beams intensity difference increase as the atomic polarization increases. Therefore, AM and FM-AM noise in two beams are common-mode and can be almost entirely canceled by differential detection. We have carried out an experiment to study our scheme. The experiment reveals that the noise in the differential signal is obviously smaller than that in each beam. The scheme is promising to be applied for developing more sensitive chip-scale magnetometer.

Keywords: atomic magnetometer, chip scale, differential detection, spin-exchange relaxation free

Procedia PDF Downloads 161

Authors: K. Frahtia, I. Mihoubi, S. Picot

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Leishmaniasis is a group of parasitic disease with a varied clinical expression caused by flagellate protozoa of the Leishmania genus. These diseases are transmitted to humans and animals by the sting of a vector insect, the female sandfly. Among the groups of dipteral disease vectors, Phlebotominae occupy a prime position and play a significant role in human pathology, such as leishmaniasis that affects nearly 350 million people worldwide. The vector control operation launched by health services throughout the country proves to be effective since despite the prevalence of the disease remains high especially in rural areas, leishmaniasis appears to be declining in Algeria. In this context, this study mainly concerns molecular detection of Leishmania from the vector. Furthermore, a molecular diagnosis has also been made on skin samples taken from patients in the region of Constantine, located in the North-East of Algeria. Concerning the vector, 5858 sandflies were captured, including 4360 males and 1498 females. Male specimens were identified based on their morphological. The morphological identification highlighted the presence of the Phlebotomus genus with a prevalence of 93% against 7% represented by the Sergentomyia genus. About the identified species, P. perniciosus is the most abundant with 59.4% of the male identified population followed by P. longicuspis with 24.7% of the workforce. P. perfiliewi is poorly represented by 6.7% of specimens followed by P. papatasi with 2.2% and 1.5% S. dreyfussi. Concerning skin samples, 45/79 (56.96%) collected samples were found positive by real-time PCR. This rate appears to be in sharp decline compared to previous years (alert peak of 30,227 cases in 2005). Concerning the detection of Leishmania from sandflies by RT-PCR, the results show that 3/60 PCR performed genus are positive with melting temperatures corresponding to that of the reference strain (84.1 +/- 0.4 ° C for L. infantum). This proves that the vectors were parasitized. On the other side, identification by RT-PCR species did not give any results. This could be explained by the presence of an insufficient amount of leishmanian DNA in the vector, and therefore support the hypothesis of the regression of leishmaniasis in Constantine.

Keywords: Algeria, molecular diagnostic, phlebotomus, real time PCR

Procedia PDF Downloads 261

Authors: Khlood F. Salman, Richard Zoucha, Hani Nawafleh

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Introduction: Jordan ranks the fourth highest breast cancer prevalence after Lebanon, Bahrain, and Kuwait. Considerable evidence showed that cultural, ethnic, and economic differences influence a woman’s practice to early detection and prevention of breast cancer. Objectives: To understand women’s health beliefs and values in relation to early detection of breast cancer; and to explore the impact of these beliefs on their decisions regarding reluctance or acceptance of early detection measures such as mammogram screening. Design: A qualitative focused ethnography was used to collect data for this study. Settings: The study was conducted in the second largest city surrounded by a large rural area in Ma’an- Jordan. Participants: A total of twenty seven women, with no history of breast cancer, between the ages of 18 and older, who had prior health experience with health providers, and were willing to share elements of personal health beliefs related to breast health within the larger cultural context. The participants were recruited using the snowball method and words of mouth. Data collection and analysis: A short questionnaire was designed to collect data related to socio demographic status (SDQ) from all participants. A Semi-structured interviews guide was used to elicit data through interviews with the informants. Nvivo10 a data manager was utilized to assist with data analysis. Leininger’s four phases of qualitative data analysis was used as a guide for the data analysis. The phases used to analyze the data included: 1) Collecting and documenting raw data, 2) Identifying of descriptors and categories according to the domains of inquiry and research questions. Emic and etic data is coded for similarities and differences, 3) Identifying patterns and contextual analysis, discover saturation of ideas and recurrent patterns, and 4) Identifying themes and theoretical formulations and recommendations. Findings: Three major themes were emerged within the cultural and religious context; 1. Fear, denial, embarrassment and lack of knowledge were common perceptions of Ma’anis’ women regarding breast health and screening mammography, 2. Health care professionals in Jordan were not quick to offer information and education about breast cancer and screening, and 3. Willingness to learn about breast health and cancer prevention. Conclusion: The study indicated the disparities between the infrastructure and resourcing in rural and urban areas of Jordan, knowledge deficit related to breast cancer, and lack of education about breast health may impact women’s decision to go for a mammogram screening. Cultural beliefs, fear, embarrassments as well as providers lack of focus on breast health were significant contributors against practicing breast health. Health providers and policy makers should provide resources for the establishment health education programs regarding breast cancer early detection and mammography screening. Nurses should play a major role in delivering health education about breast health in general and breast cancer in particular. A culturally appropriate health awareness messages can be used in creating educational programs which can be employed at the national levels.

Keywords: breast health, beliefs, cultural context, ethnography, mammogram screening

Procedia PDF Downloads 280

Authors: Pawasuth Saengdee, Chamras Promptmas, Ting Zeng, Silke Leimkühler, Ulla Wollenberger

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Sulfite has been used as a versatile preservative to limit the microbial growth and to control the taste in some food and beverage. However, it has been reported to cause a wide spectrum of severe adverse reactions. Therefore, it is important to determine the amount of sulfite in food and beverage to ensure consumer safety. An efficient electrocatalytic biosensor for sulfite detection was developed by immobilizing of human sulfite oxidase (hSO) on 3-aminoproplytriethoxysilane (APTES) modified indium tin oxide (ITO) electrode. Cyclic voltammetry was employed to investigate the electrochemical characteristics of the hSO modified ITO electrode for various pretreatment and binding conditions. Amperometry was also utilized to demonstrate the current responses of the sulfite sensor toward sodium sulfite in an aqueous solution at a potential of 0 V (vs. Ag/AgCl 1 M KCl). The proposed sulfite sensor has a linear range between 0.5 to 2 mM with a correlation coefficient 0.972. Then, the additional polymer layer of PVA was introduced to extend the linear range of sulfite sensor and protect the enzyme. The linear range of sulfite sensor with 5% coverage increases from 2.8 to 20 mM at a correlation coefficient of 0.983. In addition, the stability of sulfite sensor with 5% PVA coverage increases until 14 days when kept in 0.5 mM Tris-buffer, pH 7.0 at 4 8C. Therefore, this sensor could be applied for the detection of sulfite in the real sample, especially in food and beverage.

Keywords: sulfite oxidase, bioelectrocatalytsis, indium tin oxide, direct electrochemistry, sulfite sensor

Procedia PDF Downloads 219