Search results for: zinc based metal matrix composites

Authors: Hafiz Awais Ahmad

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This paper aims to examine the root causes of gender-based violence (GBV) in Pakistan and proposes strategies to address this issue. Using a qualitative approach, this study analyzed data from various sources, including interviews with survivors of GBV and experts in the field. The findings revealed that GBV in Pakistan is deeply rooted in patriarchal attitudes and practices, economic insecurity, lack of education, and limited access to justice. The study recommends a multi-faceted approach to address GBV, including legislative reforms, awareness-raising campaigns, economic empowerment, and improved access to justice for survivors. Furthermore, the study highlights the importance of engaging men and boys in efforts to address GBV and promote gender equality. The findings of this study have important implications for policy-makers, practitioners, and researchers working towards ending GBV in Pakistan.

Keywords: gender-based violence, Pakistan, legislative reforms, advocacy

Procedia PDF Downloads 131

Authors: Fangyan Li, Lin Min Lee, Hui Zhu Peh, Shoet Harn Chan

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Advantame, a derivative of aspartame, is the latest addition to a family of low caloric and high potent dipeptide sweeteners which include aspartame, neotame and alitame. The use of advantame as a high-intensity sweetener in food was first accepted by Food Standards Australia New Zealand in 2011 and subsequently by US and EU food authorities in 2014, with the results from toxicity and exposure studies showing advantame poses no safety concern to the public at regulated levels. To our knowledge, currently there is barely any detailed information on the analytical method of advantame in food matrix, except for one report published in Japanese, stating a high performance liquid chromatography (HPLC) and liquid chromatography/ mass spectrometry (LC-MS) method with a detection limit at ppm level. However, the use of acid in sample preparation and instrumental analysis in the report raised doubt over the reliability of the method, as there is indication that stability of advantame is compromised under acidic conditions. Besides, the method may not be suitable for analyzing food matrices containing advantame at low ppm or sub-ppm level. In this presentation, a simple, specific and sensitive method for the determination of advantame in food is described. The method involved extraction with water and clean-up via solid phase extraction (SPE) followed by detection using liquid chromatography tandem mass spectrometry (LC-MS/MS) in negative electrospray ionization mode. No acid was used in the entire procedure. Single laboratory validation of the method was performed in terms of linearity, precision and accuracy. A low detection limit at ppb level was achieved. Satisfactory recoveries were obtained using spiked samples at three different concentration levels. This validated method could be used in the routine inspection of the advantame level in food.

Keywords: advantame, food, LC-MS/MS, sweetener

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Authors: Burak Yigit Katanalp, Murat Tastan, Perviz Ahmedzade, çIgdem Canbay Turkyilmaz, Emrah Turkyilmaz

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This study evaluated the mechanical and rheological performance of fly ash-based geopolymer at high temperatures. A series of laboratory tests were conducted on neat bitumen and three modified bitumen samples, which incorporated fly ash-based geopolymer at various percentages. Low-calcium fly ash was used as the alumina-silica source. The dynamic shear rheometer and rotational viscometer were employed to determine high-temperature properties, while conventional tests such as penetration and softening point were used to evaluate the physical properties of bitumen. The short-term aging resistance of the samples was assessed using the rolling thin film oven. The results show that geopolymer has a compromising effect on bitumen properties, with improved stiffness, enhanced mechanical strength, and increased thermal susceptibility of the asphalt binder.

Keywords: bitumen, geopolymer, modification, dynamic mechanical analysis

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Authors: Hossein Hassani, Ali Rezaei

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In recent years, the study of soil contamination problems surrounding mines and smelting plants has attracted some serious attention of the environmental experts. These elements due to the non- chemical disintegration and nature are counted as environmental stable and durable contaminants. Variability of these contaminants in the soil and the time and financial limitation for the favorable environmental application, in order to reduce the risk of their irreparable negative consequences on environment, caused to apply the favorable grading of these contaminant for the further success of the risk management processes. In this study, we use the contaminants factor risk indices, average concentration, enrichment factor and geoaccumulation indices for evaluating the metal contaminant of including Pb, Ni, Se, Mo and Zn in the soil of Sarcheshmeh copper mine area. For this purpose, 120 surface soil samples up to the depth of 30 cm have been provided from the study area. And the metals have been analyzed using ICP-MS method. Comparison of the heavy and potentially toxic elements concentration in the soil samples with the world average value of the uncontaminated soil and shale average indicates that the value of Zn, Pb, Ni, Se and Mo is higher than the world average value and only the Ni element shows the lower value than the shale average. Expert opinions on the relative importance of each indicators were used to assign a final weighting of the metals and the heavy metals were ranked using the TOPSIS approach. This allows us to carry out efficient environmental proceedings, leading to the reduction of environmental ricks form the contaminants. According to the results, Ni, Pb, Mo, Zn, and Se have the highest rate of risk contamination in the soil samples of the study area.

Keywords: contamination coefficient, geoaccumulation factor, TOPSIS techniques, Sarcheshmeh copper complex

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Authors: Amir Ali Fatoorchi

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Regardless of the advantage of LoT devices, they have limitations like storage, compute, and security problems. In recent years, a lot of Blockchain-based research in IoT published and presented. In this paper, we present the Security issues of LoT. IoT has three levels of security issues: Low-level, Intermediate-level, and High-level. We survey and compare blockchain-based solutions for high-level security issues and show how the underlying technology of bitcoin and Ethereum could solve IoT problems.

Keywords: Blockchain, security, data security, IoT

Procedia PDF Downloads 198

Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

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Authors: Jin Yue

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Fresh produces especially fruits, vegetables, meats and aquatic products have limited shelf life and are highly susceptible to deterioration. Essential oils (EOs) extracted from plants have excellent antioxidant and broad-spectrum antibacterial activities, and they can play as natural food preservatives. But EOs are volatile, water insoluble, pungent, and easily decomposing under light and heat. Many approaches have been developed to improve the solubility and stability of EOs such as polymeric film, coating, nanoparticles, nano-emulsions and nanofibers. Construction of active packaging film which can incorporate EOs with high loading efficiency and controlled release of EOs has received great attention. It is still difficult to achieve accurate release of antibacterial compounds at specific target locations in active packaging. In this research, a relative humidity-responsive packaging material was designed, employing the electrospinning technique to fabricate a nanofibrous film loaded with a 4-terpineol/β-cyclodextrin inclusion complexes (4-TA/β-CD ICs). Functioning as an innovative food packaging material, the film demonstrated commendable attributes including pleasing appearance, thermal stability, mechanical properties, and effective barrier properties. The incorporation of inclusion complexes greatly enhanced the antioxidant and antibacterial activity of the film, particularly against Shewanella putrefaciens, with an inhibitory efficiency of up to 65%. Crucially, the film realized controlled release of 4-TA under 98% high relative humidity conditions by inducing the plasticization of polymers caused by water molecules, swelling of polymer chains, and destruction of hydrogen bonds within the cyclodextrin inclusion complex. This film with a long-term antimicrobial effect successfully extended the shelf life of Litopenaeus vannamei shrimp to 7 days at 4 °C. To further improve the loading efficiency and long-acting release of EOs, we synthesized the γ-cyclodextrin-metal organic frameworks (γ-CD-MOFs), and then efficiently anchored γ-CD-MOFs on chitosan-cellulose (CS-CEL) composite film by in situ growth method for controlled releasing of carvacrol (CAR). We found that the growth efficiency of γ-CD-MOFs was the highest when the concentration of CEL dispersion was 5%. The anchoring of γ-CD-MOFs on CS-CEL film significantly improved the surface area of CS-CEL film from 1.0294 m2/g to 43.3458 m2/g. The molecular docking and 1H NMR spectra indicated that γ-CD-MOF has better complexing and stabilizing ability for CAR molecules than γ-CD. In addition, the release of CAR reached 99.71±0.22% on the 10th day, while under 22% RH, the release pattern of CAR was a plateau with 14.71 ± 4.46%. The inhibition rate of this film against E. coli, S. aureus and B. cinerea was more than 99%, and extended the shelf life of strawberries to 7 days. By incorporating the merits of natural biopolymers and MOFs, this active packaging offers great potential as a substitute for traditional packaging materials.

Keywords: active packaging, antibacterial activity, controlled release, essential oils, food quality control

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Authors: Jaehong Yu, Seoung Bum Kim

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Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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Authors: Xue Xiao, Sun Hao, Liu Donghua

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E-commerce is experiencing rapid development and evolution, but traditional research methods are difficult to fully demonstrate the relationship between micro factors and macro evolution in the development process of e-commerce, which cannot provide accurate assessment for the existing strategies and predict the future evolution trends. To solve these problems, this paper presents the concept of e-commerce service ecosystem based on the characteristics of e-commerce and business ecosystem theory, describes e-commerce environment as a complex adaptive system from the perspective of ecology, constructs a e-commerce service ecosystem model by using Agent-based modeling method and Java language in RePast simulation platform and conduct experiment through the way of computational experiment, attempt to provide a suitable and effective researching method for the research on e-commerce evolution. By two experiments, it can be found that system model built in this paper is able to show the evolution process of e-commerce service ecosystem and the relationship between micro factors and macro emergence. Therefore, the system model constructed by Agent-based method and computational experiment provides proper means to study the evolution of e-commerce ecosystem.

Keywords: e-commerce service ecosystem, complex system, agent-based modeling, computational experiment

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Authors: William Li

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Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

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Authors: Indu Bhushan Sharma, Rashmi Saraswat

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The thermotolerant, solvent stable and alkalophilic lipase producing bacterial strain was isolated from the water sample of the foothills of Trikuta Mountain in Kakryal (Reasi district) in Jammu and Kashmir, India. The lipase-producing microorganisms were screened using tributyrin agar plates. The selected microbe was optimized for maximum lipase production by subjecting to various carbon and nitrogen sources, incubation period and inoculum size. The selected strain was identified as Bacillus subtilis strain kakrayal_1 (BSK_1) using 16S rRNA sequence analysis. Effect of pH, temperature, metal ions, detergents and organic solvents were studied on lipase activity. Lipase was found to be stable over a pH range of 6.0 to 9.0 and exhibited maximum activity at pH 8. Lipolytic activity was highest at 37°C and the enzyme activity remained at 60°C for 24hrs, hence, established as thermo-tolerant. Production of lipase was significantly induced by vegetable oil and the best nitrogen source was found to be peptone. The isolated Bacillus lipase was stimulated by pre-treatment with Mn2+, Ca2+, K+, Zn2+, and Fe2+. Lipase was stable in detergents such as triton X 100, tween 20 and Tween 80. The 100% ethyl acetate enhanced lipase activity whereas, lipase activity were found to be stable in Hexane. The optimization resulted in 4 fold increase in lipase production. Bacillus lipases are ‘generally recognized as safe’ (GRAS) and are industrially interesting. The inducible alkaline, thermo-tolerant lipase exhibited the ability to be stable in detergents and organic solvents. This could be further researched as a potential biocatalyst for industrial applications such as biotransformation, detergent formulation, bioremediation and organic synthesis.

Keywords: bacillus, lipase, thermotolerant, alkalophilic

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Authors: Raja Umer Sajjad, Chang Hee Lee

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Stormwater runoff is the leading contributor to pollution of receiving waters. In response, an efficient stormwater monitoring program is required to quantify and eventually reduce stormwater pollution. The overall goals of stormwater monitoring programs primarily include the identification of high-risk dischargers and the development of total maximum daily loads (TMDLs). The challenge in developing better monitoring program is to reduce the variability in flux estimates due to sampling errors; however, the success of monitoring program mainly depends on the accuracy of the estimates. Apart from sampling errors, manpower and budgetary constraints also influence the quality of the estimates. This study attempted to develop optimum stormwater monitoring design considering both cost and the quality of the estimated pollutants flux. Three years stormwater monitoring data (2012 – 2014) from a mix land use located within Geumhak watershed South Korea was evaluated. The regional climate is humid and precipitation is usually well distributed through the year. The investigation of a large number of water quality parameters is time-consuming and resource intensive. In order to identify a suite of easy-to-measure parameters to act as a surrogate, Principal Component Analysis (PCA) was applied. Means, standard deviations, coefficient of variation (CV) and other simple statistics were performed using multivariate statistical analysis software SPSS 22.0. The implication of sampling time on monitoring results, number of samples required during the storm event and impact of seasonal first flush were also identified. Based on the observations derived from the PCA biplot and the correlation matrix, total suspended solids (TSS) was identified as a potential surrogate for turbidity, total phosphorus and for heavy metals like lead, chromium, and copper whereas, Chemical Oxygen Demand (COD) was identified as surrogate for organic matter. The CV among different monitored water quality parameters were found higher (ranged from 3.8 to 15.5). It suggests that use of grab sampling design to estimate the mass emission rates in the study area can lead to errors due to large variability. TSS discharge load calculation error was found only 2 % with two different sample size approaches; i.e. 17 samples per storm event and equally distributed 6 samples per storm event. Both seasonal first flush and event first flush phenomena for most water quality parameters were observed in the study area. Samples taken at the initial stage of storm event generally overestimate the mass emissions; however, it was found that collecting a grab sample after initial hour of storm event more closely approximates the mean concentration of the event. It was concluded that site and regional climate specific interventions can be made to optimize the stormwater monitoring program in order to make it more effective and economical.

Keywords: first flush, pollutant load, stormwater monitoring, surrogate parameters

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Authors: H. Li, W. Qin, Ben Ye

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Friction Push Plug Welding (FPPW) is a solid phase welding suitable for repairing defective welds and filling self-reacting weld keyholes in Friction Stir Welds. In FPPW process, a tapered shaped plug is rotated at high speed and forced into a tapered hole in the substrate. The plug and substrate metal is softened by the increasing temperature generated by friction and material plastic deformation. This paper aims to investigate the effect of process parameters on the quality of the weld. Orthogonal design methods were employed to reduce the amount of experiment. Three values were selected for each process parameter, rotation speed (1500r/min, 2000r/min, 2500r/min), plunge depth (2mm, 3mm, 4mm) and plunge speed (60mm/min, 90mm/min, 120r/min). AA6061aluminum alloy plug and substrate plate was used in the experiment. In a trial test with the plunge depth of 1mm, a noticeable defect appeared due to the short plunge time and insufficient temperature. From the recorded temperature profiles, it was found that the peak temperature increased with the increase of the rotation speed, plunge speed and plunge depth. In the initial stage, the plunge speed was the main factor affecting heat generation, while in the steady state welding stage, the rotation speed played a more important role. The FPPW weld defect includes flash and incomplete penetration in the upper, middle and bottom interface with the substrate. To obtain defect free weld, the higher rotation speed and proper plunge depth were recommended.

Keywords: friction push plug welding, process parameter, weld defect, orthogonal design

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Authors: Anwar Beg, Sireetorn Kuharat, Rashid Mehmood, Rabil Tabassum, Meisam Babaie

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Nano-polymeric solar paints and sol-gels have emerged as a major new development in solar cell/collector coatings offering significant improvements in durability, anti-corrosion and thermal efficiency. They also exhibit substantial viscosity variation with temperature which can be exploited in solar collector designs. Modern manufacturing processes for such nano-rheological materials frequently employ stagnation flow dynamics under high temperature which invokes radiative heat transfer. Motivated by elaborating in further detail the nanoscale heat, mass and momentum characteristics of such sol gels, the present article presents a mathematical and computational study of the steady, two-dimensional, non-aligned thermo-fluid boundary layer transport of copper metal-doped water-based nano-polymeric sol gels under radiative heat flux. To simulate real nano-polymer boundary interface dynamics, thermal slip is analysed at the wall. A temperature-dependent viscosity is also considered. The Tiwari-Das nanofluid model is deployed which features a volume fraction for the nanoparticle concentration. This approach also features a Maxwell-Garnet model for the nanofluid thermal conductivity. The conservation equations for mass, normal and tangential momentum and energy (heat) are normalized via appropriate transformations to generate a multi-degree, ordinary differential, non-linear, coupled boundary value problem. Numerical solutions are obtained via the stable, efficient Runge-Kutta-Fehlberg scheme with shooting quadrature in MATLAB symbolic software. Validation of solutions is achieved with a Variational Iterative Method (VIM) utilizing Langrangian multipliers. The impact of key emerging dimensionless parameters i.e. obliqueness parameter, radiation-conduction Rosseland number (Rd), thermal slip parameter (α), viscosity parameter (m), nanoparticles volume fraction (ϕ) on non-dimensional normal and tangential velocity components, temperature, wall shear stress, local heat flux and streamline distributions is visualized graphically. Shear stress and temperature are boosted with increasing radiative effect whereas local heat flux is reduced. Increasing wall thermal slip parameter depletes temperatures. With greater volume fraction of copper nanoparticles temperature and thermal boundary layer thickness is elevated. Streamlines are found to be skewed markedly towards the left with positive obliqueness parameter.

Keywords: non-orthogonal stagnation-point heat transfer, solar nano-polymer coating, MATLAB numerical quadrature, Variational Iterative Method (VIM)

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Authors: Ankur Jain, W. Wilfred Godfrey

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Embedded systems are usually microcontroller-based systems that represent a class of reliable and dependable dedicated computer systems designed for specific purposes. Micro-controllers are used in most electronic devices in an endless variety of ways. Some micro-controller-based embedded systems are required to respond to external events in the shortest possible time and such systems are known as real-time embedded systems. So in multitasking system there is a need of task Scheduling,there are various scheduling algorithms like Fixed priority Scheduling(FPS),Earliest deadline first(EDF), Rate Monotonic(RM), Deadline Monotonic(DM),etc have been researched. In this Report various conventional algorithms have been reviewed and analyzed, these algorithms consists of single shape task, A new Multishape scheduling algorithms has been proposed and implemented and analyzed.

Keywords: dm, edf, embedded systems, fixed priority, microcontroller, rtos, rm, scheduling algorithms

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Authors: H. Benaldjia, N. Habib, F. Djefaflia, A. Nait-Merzoug, A. Harat, J. El-Haskouri, O. Guellati

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Currently, the technology has attracted knowledge of energy storage sources similar to batteries, capacitors and super-capacitors because of its very different applications in many fields with major social and economic challenges. Moreover, hydroxides have attracted much attention as a promising and active material choice in large-scale applications such as molecular adsorption/storage and separation for the environment, ion exchange, nanotechnology, supercapacitor for energy storage and conversion, electro-biosensing, and catalysts, due to their unique properties which are strongly influenced by their composition, microstructure, and synthesis method. In this context, we report in this study the synthesis of hydroxide-based nanomaterials precisely based on Ni and Fe using a simple hydrothermal method with mono and bi precursors at optimized growth conditions (6h-120°C). The obtained products were characterized using different techniques, such as XRD, FTIR, FESEM and BET, as well as electrochemical measurements.

Keywords: energy storage, Supercapacitors, nanocomposites, nanohybride, electro-active materials.

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Authors: Ramandeep Kaur, Makula Ajitha

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Fluvastatin has been reported for increasing bone mineral density in osteoporosis since last decade. Systemically administered drug undergoes extensive hepatic first-pass metabolism, thus very small amount of drug reaches the bone tissue which is highly insignificant. The present study aims to deliver fluvastatin in the form of nanoemulsion (NE) gel directly to the bone tissue through transdermal route thereby bypassing hepatic first pass metabolism. The NE formulation consisted of isopropyl myristate as oil, tween 80 as surfactant, transcutol as co-surfactant and water as the aqueous phase. Pseudoternary phase diagrams were constructed using aqueous titration method and NE’s obtained were subjected to thermodynamic-kinetic stability studies. The stable NE formulations were evaluated for their droplet size, zeta potential, and transmission electron microscopy (TEM). The nano-sized formulations were incorporated into 0.5% carbopol 934 gel matrix. Ex-vivo permeation behaviour of selected formulations through rat skin was investigated and compared with the conventional formulations (suspension and emulsion). Further, in-vivo pharmacokinetic study was carried using male Wistar rats. The optimized NE formulations mean droplet size was 11.66±3.2 nm with polydispersity index of 0.117. Permeation flux of NE gel formulations was found significantly higher than the conventional formulations i.e. suspension and emulsion. In vivo pharmacokinetic study showed significant increase in bioavailability (1.25 fold) of fluvastatin than oral formulation. Thus, it can be concluded that NE gel was successfully developed for transdermal delivery of fluvastatin for the treatment of osteoporosis.

Keywords: fluvastatin, nanoemulsion gel, osteoporosis, transdermal

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Bilge Kaan Tekelioglu, Mehmet Celik, Mahmut Ali Gokce, Ladine Celik, Yusuf Uzun

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A male mature barn owl (Tyto alba) was brought to Cukurova University Ceyhan Veterinary Medicine Faculty at the beginning of January 2017. The bird was found at a local state elementary school’s garden where had been terribly damaged by metal wires. On the clinical examination, the animal was in shock and atonic position at arrival and seems to have feather problems and severe injuries. The ears, eyes, claws and wounded areas were checked and no signs of viral, microbial or ecto-parasitic infection were observed. The bird has been declared by U.S. wild life Office as endangered species. At first, the owl was kept in silent, warm and darkened cabinet against shock and warmed fluid replacement was started by % 5 dextrose solution per orally. On the second day, we started per oral forced feeding with chicken flesh meat dipped into the dextrose solution. On the third day, the bird was continued to be fed with fresh meat. At the fourth day, the owl was started to be fed with chicks during the next 3 days died by natural means which has been supplied by a local breeder. At the first 3 days 1 chick per day and the following days 2 chicks per day has been given per orally. The tenth day we started flying exercises in a small and non-windowed room safely. The saved owl was kept in this room for 10 more days. Finally, the owl was released at the habitation where it had been found injured. This study has one more time proved that, if you save one, you can save more. Wild life is in danger all over the world. Every living creature has right and deserves a chance to live.

Keywords: wild life, barn owl, Tyto alba, rescue, life support, feeding

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Authors: Sangeeta Palekar, Mahima Rana, Jayu Kalambe

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In this paper, a microfluidic-based platform for the quantification of contaminants in the water is proposed. The proposed system uses microfluidic channels with an embedded environment for contaminants detection in water. Microfluidics-based platforms present an evident stage of innovation for fluid analysis, with different applications advancing minimal efforts and simplicity of fabrication. Polydimethylsiloxane (PDMS)-based microfluidics channel is fabricated using a soft lithography technique. Vertical and horizontal connections for fluid dispensing with the microfluidic channel are explored. The principle of colorimetry, which incorporates the use of Griess reagent for the detection of nitrite, has been adopted. Nitrite has high water solubility and water retention, due to which it has a greater potential to stay in groundwater, endangering aquatic life along with human health, hence taken as a case study in this work. The developed platform also compares the detection methodology, containing photodetectors for measuring absorbance and image sensors for measuring color change for quantification of contaminants like nitrite in water. The utilization of image processing techniques offers the advantage of operational flexibility, as the same system can be used to identify other contaminants present in water by introducing minor software changes.

Keywords: colorimetric, fluid contaminants, nitrite detection, microfluidics

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Authors: Sahar Essa, Hussain A. Safar, Raj Raghupathy

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Human cytomegalovirus (CMV) continues to be a source of severe complications in immunologically immature and immunocompromised hosts. Effective CMV vaccines that help diminish CMV disease in transplant patients and avoid congenital infection are of great importance. Though the exact roles of defense mechanisms are unidentified, viral-specific antibodies and cytokine responses are known to be involved in controlling CMV infections. CMV envelope glycoprotein B (UL55/gB), matrix proteins (UL83/pp65, UL99/pp28, UL32/pp150), and assembly protein UL80a/pp38 are known to be targets of antiviral immune responses. We immunized mice intraperitoneally with these five CMV-related proteins (commercial) for their ability to induce specific antibody responses (in-house immunoassay) and cytokine production (commercial assay) in a mouse model. We observed a significant CMV-antigen-specific antibody response to pp38 and pp65 (E/C ˃2.0, p˂0.001). Mice immunized with pp38 had significantly higher concentrations of GM-CSF, IFN-α, IL-2 IL-4, IL-5, and IL-17A (p˂0.05). Mice immunized with pp65 showed significantly higher concentrations of GM-CSF, IFN-γ, IL-2 IL-4, IL-10, IL-12, IL-17A, and TNF-α. Th1 to Th2 cytokines ratios revealed a Th1 cytokine bias in mice immunized with pp38, pp65, pp150, and gB. We suggest that stimulation with multiple CMV-related proteins, which include pp38, pp65, and gB antigens, will allow both humoral and cellular immune responses to be efficiently activated, thus serving as appropriate CMV antigens for future vaccines.

Keywords: cytomegalovirus, UL99/pp28, UL80a/pp38, UL83/pp65, UL32/pp150, UL55/gB, CMV-antigen-specific antibody, CMV antigen-specific cytokine responses

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Authors: Husam Kaid, Abdulrahman Al-Ahmari, Zhiwu Li

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This paper develops a robust deadlock control technique for shared and unreliable resources in automated manufacturing systems (AMSs) based on structural analysis and colored Petri nets, which consists of three steps. The first step involves using strict minimal siphon control to create a live (deadlock-free) system that does not consider resource failure. The second step uses an approach based on colored Petri net, in which all monitors designed in the first step are merged into a single monitor. The third step addresses the deadlock control problems caused by resource failures. For all resource failures in the Petri net model a common recovery subnet based on colored petri net is proposed. The common recovery subnet is added to the obtained system at the second step to make the system reliable. The proposed approach is evaluated using an AMS from the literature. The results show that the proposed approach can be applied to an unreliable complex Petri net model, has a simpler structure and less computational complexity, and can obtain one common recovery subnet to model all resource failures.

Keywords: automated manufacturing system, colored Petri net, deadlocks, siphon

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Authors: Hirokatsu Kawashima

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One important element of teaching/learning listening is intensive listening such as listening for precise sounds, words, grammatical, and semantic units. Several classroom-based investigations have been conducted to explore the usefulness of auditory recognition of phonological, grammatical and semantic errors in such a context. The current study reports the results of one such investigation, which targeted auditory recognition of phonological, grammatical, and semantic errors at the sentence level. 56 Japanese EFL learners participated in this investigation, in which their recognition performance of phonological, grammatical and semantic errors was measured on a 9-point scale by learners’ self-evaluation from the perspective of 1) two types of similar English sound (vowel and consonant minimal pair words), 2) two types of sentence word order (verb phrase-based and noun phrase-based word orders), and 3) two types of semantic consistency (verb-purpose and verb-place agreements), respectively, and their general listening proficiency was examined using standardized tests. A number of findings have been made about the interactive relationships between the three types of auditory error recognition and general listening proficiency. Analyses based on the OPLS (Orthogonal Projections to Latent Structure) regression model have disclosed, for example, that the three types of auditory error recognition are linked in a non-linear way: the highest explanatory power for general listening proficiency may be attained when quadratic interactions between auditory recognition of errors related to vowel minimal pair words and that of errors related to noun phrase-based word order are embraced (R2=.33, p=.01).

Keywords: auditory error recognition, intensive listening, interaction, investigation

Procedia PDF Downloads 499

Authors: A. Kavya Sri, K. Sai Vineela, R. Vanitha, S. Rohith

Abstract:

Large pieces of ice that break from the glaciers are known as icebergs. The threat that icebergs pose to navigation, production of offshore oil and gas services, and underwater pipelines makes their detection crucial. In this project, an automated iceberg tracking method using deep learning techniques and satellite images of icebergs is to be developed. With a temporal resolution of 12 days and a spatial resolution of 20 m, Sentinel-1 (SAR) images can be used to track iceberg drift over the Southern Ocean. In contrast to multispectral images, SAR images are used for analysis in meteorological conditions. This project develops a web-based graphical user interface to detect and track icebergs using sentinel-1 images. To track the movement of the icebergs by using temporal images based on their latitude and longitude values and by comparing the center and area of all detected icebergs. Testing the accuracy is done by precision and recall measures.

Keywords: synthetic aperture radar (SAR), icebergs, deep learning, spatial resolution, temporal resolution

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Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

Abstract:

Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

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Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, features extraction, offline signature verification, voting-based classifier

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Authors: Mahmut Yildirim

Abstract:

This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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Authors: Ahmed A. Alghamdi

Abstract:

Single-walled carbon nanotubes (SWCNTs) are an outstanding material for applications in thermoelectric power generation, nanoelectronics, electrochemical energy storage, photovoltaics, and light emission. They are ultra-lightweight and possess electrical as well as thermal conductivity, flexibility, and mechanical strength. SWCNT is applicable in water treatment, brine desalination, removal of heavy metal ions associated with pollutants, and oil-water separation. Carbon nanotube (CNT) is believed to tackle the trade-off issue between permeability, selectivity, and fouling issues in membrane filtration applications. Studying these CNT structures, as well as their interconnection in nanotechnology, assists in finding the precise position to be placed for water desalination. Reverse osmosis (RO) has been used globally for desalination, resulting in purified water. Thin film composite (TFC) membranes were utilized in the RO process for desalination. The sheet thickness increases the salt rejection and decreases the water flux when CNT is utilized as a support layer to this membrane. Thus, through a temperature-induced phase separation technique (TIPS), axially aligned SWCNT (AASWCNT) is fabricated, and its use enhances the salt rejection and water flux at short reaction times with a modified procedure. An evaluation was conducted and analogized with prior works in the literature, which exhibited that the prepared TFC membrane showed a better outcome.

Keywords: single-walled carbon nanotubes, thin film composite, axially aligned swcnt, temperature induced phase separation technique, reverse osmosis

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Authors: Hussein M. Etmimi, Peter E. Mallon

Abstract:

Electrospinning uses an electrical charge to draw very fine fibers (typically on the micro or nano scale) from a liquid or molten precursor. Over the years, this method has become a widely used and a successful technique to process polymer materials and their composites into nanofibers. The main focus of this work is to study the electrospinning of multi-phase amphiphilic copolymers and their nanocomposites, which contain graphene as the nanofiller material. In such amphiphilic materials, the constituents segments are incompatible and thus the solid state morphology will be determined by the composition of the various constituents as well as the method of preparation. In this study, amphiphilic block copolymers of poly(dimethyl siloxane) and poly(methyl methacrylate) (PDMS-b-PMMA) with well-defined structures were synthesized and the solution electrospinning of these materials and their properties were investigated. Atom transfer radical polymerization (ATRP) was used to obtain the controlled block copolymers with relatively high molar masses and narrow dispersity. First, PDMS macroinitiators with different chain length of 1000, 5000 and 10000 g/mol were synthesized by the reaction of monocarbinol terminated PDMS with α-bromoisobutyryl bromide initiator. The obtained macroinitiators were used for the polymerization of methyl methacrylate monomer to obtain the desired block copolymers using the ATRP process. Graphene oxide (GO) of different loading was then added to the copolymer solution and the resultant nanocomposites were successfully electrospun into nanofibers. The electrospinning was achieved using dimethylformamide/chloroform mixture (60:40 vl%) as electrospinning solution medium. Scanning electron microscopy (SEM) showed the successful formation of the electrospun fibers with dimensions in the nanometer range. X-ray diffraction indicated that the GO nanosheets were of an exfoliated structure, irrespective of the filler loading. Thermogravimetric analysis also showed that the thermal stability of the nanofibers was improved in the presence of GO, which was not a function of the filler loading. Differential scanning calorimetry also showed that the mechanical properties (measured as glass transition temperature) of the nanofibers was improved significantly in the presence of GO, which was a function of the filler loading.

Keywords: elctrospinning, graphene oxide, nanofibers, polymethyl methacrylate (PMMA)

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Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

Abstract:

Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

Procedia PDF Downloads 861