Search results for: small cell networks.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3969

Search results for: small cell networks.

699 Effect of Gibberellic Acid and 2,4- Dichlorophenoxyacetic Acid on Fruit Development and Fruit Quality of Wax Apple

Authors: Nguyen Minh Tuan, Yen Chung–Ruey

Abstract:

This study was conducted to evaluate the effects of gibberellic acid and 2,4- dichlorophenoxyacetic acid on flower number, fruit growth and fruit quality of wax apple. GA3 and 2,4-D were applied at small bud and petal fall stage. Number of flower, fruit set, fruit drop, fruit crack, fruit growth and fruit quality were recorded. Results indicated that spraying with 10 ppm GA3 had the best results in number of flower. GA3 spray at 30 ppm gave the faster rate of fruit growth than the other treatments. Fruit set, fruit size as well as fruit weight markedly improved by spraying 30 ppm GA3, followed by 10 ppm GA3 compared to untreated control. Moreover, spray GA3 at 30 ppm was the most effective and increased total soluble solids, reduced titratable acidity and fruit drop. On the other hand, it was noticed that with 10 ppm 2,4-D application also enhanced the fruit growth rate, improved physiological and biochemical characters of fruit compared to untreated control. It was concluded that both GA3 and 2,4-D spray have positive effects on fruit development, reduced fruit drop, fruit crack and improved fruit quality of wax apple under field conditions.

Keywords: Wax apple, GA3, 2, 4-D, fruit growth, fruit quality.

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698 Weld Defect Detection in Industrial Radiography Based Digital Image Processing

Authors: N. Nacereddine, M. Zelmat, S. S. Belaïfa, M. Tridi

Abstract:

Industrial radiography is a famous technique for the identification and evaluation of discontinuities, or defects, such as cracks, porosity and foreign inclusions found in welded joints. Although this technique has been well developed, improving both the inspection process and operating time, it does suffer from several drawbacks. The poor quality of radiographic images is due to the physical nature of radiography as well as small size of the defects and their poor orientation relatively to the size and thickness of the evaluated parts. Digital image processing techniques allow the interpretation of the image to be automated, avoiding the presence of human operators making the inspection system more reliable, reproducible and faster. This paper describes our attempt to develop and implement digital image processing algorithms for the purpose of automatic defect detection in radiographic images. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of global and local preprocessing and segmentation methods must be appropriated.

Keywords: Digital image processing, global and localapproaches, radiographic film, weld defect.

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697 A Comparative Study of a Defective Superconductor/ Semiconductor-Dielectric Photonic Crystal

Authors: S. Sadegzadeh, A. Mousavi

Abstract:

Temperature-dependent tunable photonic crystals have attracted widespread interest in recent years. In this research, transmission characteristics of a one-dimensional photonic crystal structure with a single defect have been studied. Here, we assume two different defect layers: InSb as a semiconducting layer and HgBa2Ca2Cu3O10 as a high-temperature superconducting layer. Both the defect layers have temperature-dependent refractive indexes. Two different types of dielectric materials (Si as a high-refractive index dielectric and MgF2 as a low-refractive index dielectric) are used to construct the asymmetric structures (Si/MgF2)NInSb(Si/MgF2)N named S.I, and (Si/MgF2)NHgBa2Ca2Cu3O10(Si/MgF2)N named S.II. It is found that in response to the temperature changes, transmission peaks within the photonic band gap of the S.II structure, in contrast to S.I, show a small wavelength shift. Furthermore, the results show that under the same conditions, S.I structure generates an extra defect mode in the transmission spectra. Besides high efficiency transmission property of S.II structure, it can be concluded that the semiconductor-dielectric photonic crystals are more sensitive to temperature variation than superconductor types.

Keywords: Defect modes, photonic crystals, semiconductor, superconductor, transmission.

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696 Impact of Stack Caches: Locality Awareness and Cost Effectiveness

Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang

Abstract:

Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.

Keywords: Hit rate, Locality of program, Stack cache, and Stack data.

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695 Characterization of the O.ul-mS952 Intron:A Potential Molecular Marker to Distinguish Between Ophiostoma Ulmi and Ophiostoma Novo-Ulmi Subsp. Americana

Authors: Mohamed Hafez, Georg Hausner

Abstract:

The full length mitochondrial small subunit ribosomal (mt-rns) gene has been characterized for Ophiostoma novo-ulmi subspecies americana. The gene was also characterized for Ophiostoma ulmi and a group II intron was noted in the mt-rns gene of O. ulmi. The insertion in the mt-rns gene is at position S952 and it is a group IIB1 intron that encodes a double motif LAGLIDADG homing endonuclease from an open reading frame located within a loop of domain III. Secondary structure models for the mt-rns RNA of O. novo-ulmi subsp. americana and O. ulmi were generated to place the intron within the context of the ribosomal RNA. The in vivo splicing of the O.ul-mS952 group II intron was confirmed with reverse transcription-PCR. A survey of 182 strains of Dutch Elm Diseases causing agents showed that the mS952 intron was absent in what is considered to be the more aggressive species O. novo-ulmi but present in strains of the less aggressive O. ulmi. This observation suggests that the O.ul-mS952 intron can be used as a PCR-based molecular marker to discriminate between O. ulmi and O. novo-ulmi subsp. americana.

Keywords: Dutch Elm Disease, group II introns, mtDNA, species identification

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694 Matching Farmer Competence and Farm Resources with the Transformation of Agri-Food Marketing Systems

Authors: Bhawat Chiamjinnawat

Abstract:

The agri-food market transformation has implied market growth for the fruit industry in Thailand. This article focuses on analysis of farmer competence and farm resources which affect market strategies used by fruit farmers in Chanthaburi province of Thailand. The survey data were collected through the use of face-to-face interviews with structured questionnaires. This study identified 14 drivers related to farmer competence and farm resources of which some had significant effect on the decision to use either high-value markets or traditional markets. The results suggest that farmers who used high-value markets were better educated and they had longer experience and larger sized business. Identifying the important factors that match with the market transformation provides policy with opportunities to support the fruit farmers to increase their market power. Policies that promote business expansion of agricultural cooperatives and knowledge sharing among farmers are recommended to reduce limitations due to limited knowledge, low experience, and small business sizes.

Keywords: Farmer competence, farm resources, fruit industry, high-value markets, Thailand.

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693 Virtual Routing Function Allocation Method for Minimizing Total Network Power Consumption

Authors: Kenichiro Hida, Shin-Ichi Kuribayashi

Abstract:

In a conventional network, most network devices, such as routers, are dedicated devices that do not have much variation in capacity. In recent years, a new concept of network functions virtualisation (NFV) has come into use. The intention is to implement a variety of network functions with software on general-purpose servers and this allows the network operator to select their capacities and locations without any constraints. This paper focuses on the allocation of NFV-based routing functions which are one of critical network functions, and presents the virtual routing function allocation algorithm that minimizes the total power consumption. In addition, this study presents the useful allocation policy of virtual routing functions, based on an evaluation with a ladder-shaped network model. This policy takes the ratio of the power consumption of a routing function to that of a circuit and traffic distribution between areas into consideration. Furthermore, the present paper shows that there are cases where the use of NFV-based routing functions makes it possible to reduce the total power consumption dramatically, in comparison to a conventional network, in which it is not economically viable to distribute small-capacity routing functions.

Keywords: Virtual routing function, NFV, resource allocation, minimum power consumption.

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692 Compressed Sensing of Fetal Electrocardiogram Signals Based on Joint Block Multi-Orthogonal Least Squares Algorithm

Authors: Xiang Jianhong, Wang Cong, Wang Linyu

Abstract:

With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal electrocardiogram, compressed sensing, joint sparse reconstruction, block sparse signal

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691 Investigation of a Hybrid Process: Multipoint Incremental Forming

Authors: Safa Boudhaouia, Mohamed Amen Gahbiche, Eliane Giraud, Wacef Ben Salem, Philippe Dal Santo

Abstract:

Multi-point forming (MPF) and asymmetric incremental forming (ISF) are two flexible processes for sheet metal manufacturing. To take advantages of these two techniques, a hybrid process has been developed: The Multipoint Incremental Forming (MPIF). This process accumulates at once the advantages of each of these last mentioned forming techniques, which makes it a very interesting and particularly an efficient process for single, small, and medium series production. In this paper, an experimental and a numerical investigation of this technique are presented. To highlight the flexibility of this process and its capacity to manufacture standard and complex shapes, several pieces were produced by using MPIF. The forming experiments are performed on a 3-axis CNC machine. Moreover, a numerical model of the MPIF process has been implemented in ABAQUS and the analysis showed a good agreement with experimental results in terms of deformed shape. Furthermore, the use of an elastomeric interpolator allows avoiding classical local defaults like dimples, which are generally caused by the asymmetric contact and also improves the distribution of residual strain. Future works will apply this approach to other alloys used in aeronautic or automotive applications.

Keywords: Incremental forming, numerical simulation, MPIF, multipoint forming.

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690 Embedding a Large Amount of Information Using High Secure Neural Based Steganography Algorithm

Authors: Nameer N. EL-Emam

Abstract:

In this paper, we construct and implement a new Steganography algorithm based on learning system to hide a large amount of information into color BMP image. We have used adaptive image filtering and adaptive non-uniform image segmentation with bits replacement on the appropriate pixels. These pixels are selected randomly rather than sequentially by using new concept defined by main cases with sub cases for each byte in one pixel. According to the steps of design, we have been concluded 16 main cases with their sub cases that covere all aspects of the input information into color bitmap image. High security layers have been proposed through four layers of security to make it difficult to break the encryption of the input information and confuse steganalysis too. Learning system has been introduces at the fourth layer of security through neural network. This layer is used to increase the difficulties of the statistical attacks. Our results against statistical and visual attacks are discussed before and after using the learning system and we make comparison with the previous Steganography algorithm. We show that our algorithm can embed efficiently a large amount of information that has been reached to 75% of the image size (replace 18 bits for each pixel as a maximum) with high quality of the output.

Keywords: Adaptive image segmentation, hiding with high capacity, hiding with high security, neural networks, Steganography.

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689 Prevalence and Fungicidal Activity of Endophytic Micromycetes of Plants in Kazakhstan

Authors: L. V. Ignatova, Y. V. Brazhnikova, T. D. Mukasheva, R. Zh. Berzhanova, A. A. Omirbekova

Abstract:

Endophytic microorganisms are presented in plants of different families growing in the foothills and piedmont plains of Trans-Ili Alatau. It was found that the maximum number of endophytic micromycetes is typical to the Fabaceae family. The number of microscopic fungi in the roots reached (145.9±5.9)×103 CFU/g of plant tissue; yeasts - (79.8±3.5)×102 CFU/g of plant tissue. Basically, endophytic microscopic fungi are typical for underground parts of plants. In contrast, yeasts more infected aboveground parts of plants. Small amount of micromycetes is typical to inflorescence and fruits. Antagonistic activity of selected micromycetes against Fusarium graminearum, Cladosporium sp., Phytophtora infestans and Botrytis cinerea phytopathogens was detected. Strains with a broad, narrow and limited range of action were identified. For further investigations Rh2 and T7 strains were selected, they are characterized by a broad spectrum of fungicidal activity and they formed the large inhibition zones against phytopathogens. Active antagonists are attributed to the Rhodotorula mucilaginosa and Beauveria bassiana species.

Keywords: Endophytic micromycetes, fungicidal activity, prevalence.

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688 Performance Evaluation of Intelligent Controllers for AGC in Thermal Systems

Authors: Muhammad Muhsin, Abhishek Mishra, Shreyansh Vishwakarma, K. Dasaratha Babu, Anudevi Samuel

Abstract:

In an interconnected power system, any sudden small load perturbation in any of the interconnected areas causes the deviation of the area frequencies, the tie line power and voltage deviation at the generator terminals. This paper deals with the study of performance of intelligent Fuzzy Logic controllers coupled with Conventional Controllers (PI and PID) for Load Frequency Control. For analysis, an isolated single area and interconnected two area thermal power systems with and without generation rate constraints (GRC) have been considered. The studies have been performed with conventional PI and PID controllers and their performance has been compared with intelligent fuzzy controllers. It can be demonstrated that these controllers can successfully bring back the excursions in area frequencies and tie line powers within acceptable limits in smaller time periods and with lesser transients as compared to the performance of conventional controllers under same load disturbance conditions. The simulations in MATLAB have been used for comparative studies.

Keywords: Area Control Error, Fuzzy Logic, Generation rate constraint, Load Frequency, Tie line Power.

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687 Solid Waste Management through Mushroom Cultivation – An Eco Friendly Approach

Authors: Mary Josephine

Abstract:

Waste of certain process can be the input source of  other sectors in order to reduce environmental pollution. Today there  are more and more solid wastes are generated, but only very small  amount of those are recycled. So, the threatening of environmental  pressure to public health is very serious. The methods considered for  the treatment of solid waste are biogas tanks or processing to make  animal feed and fertilizer, however, they did not perform well. An  alternative approach is growing mushrooms on waste residues. This  is regarded as an environmental friendly solution with potential  economical benefit. The substrate producers do their best to produce  quality substrate at low cost. Apart from other methods, this can be  achieved by employing biologically degradable wastes used as the  resource material component of the substrate. Mushroom growing is  a significant tool for the restoration, replenishment and remediation  of Earth’s overburdened ecosphere. One of the rational methods of  waste utilization involves locally available wastes. The present study  aims to find out the yield of mushroom grown on locally available  waste for free and to conserve our environment by recycling wastes.

 

Keywords: Biodegradable, environment, mushroom, remediation.

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686 Technological Environment - International Marketing Strategy Relationship

Authors: Suthawan Chirapanda

Abstract:

International trade involves both large and small firms engaged in business overseas. Possible drivers that force companies to enter international markets include increasing competition at the domestic market, maturing domestic markets, and limited domestic market opportunities. Technology is an important driving factor in shaping international marketing strategy as well as in driving force towards a more global marketplace, especially technology in communication. It includes telephones, the internet, computer systems and e-mail. There are three main marketing strategy choices, namely standardization approach, adaptation approach and middleof- the-road approach that companies implement to overseas markets. The decision depends on situations and factors facing the companies in the international markets. In this paper, the contingency concept is considered that no single strategy can be effective in all contexts. The effect of strategy on performance depends on specific situational variables. Strategic fit is employed to investigate export marketing strategy adaptation under certain environmental conditions, which in turn can lead to superior performance.

Keywords: Contingency approach, international marketing strategy, strategic fit, technological environment

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685 An Effective Decision-Making Strategy Based on Multi-Objective Optimization for Commercial Vehicles in Highway Scenarios

Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

Abstract:

Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: Decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle.

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684 Sleep Scheduling Schemes Based on Location of Mobile User in Sensor-Cloud

Authors: N. Mahendran, R. Priya

Abstract:

The mobile cloud computing (MCC) with wireless sensor networks (WSNs) technology gets more attraction by research scholars because its combines the sensors data gathering ability with the cloud data processing capacity. This approach overcomes the limitation of data storage capacity and computational ability of sensor nodes. Finally, the stored data are sent to the mobile users when the user sends the request. The most of the integrated sensor-cloud schemes fail to observe the following criteria: 1) The mobile users request the specific data to the cloud based on their present location. 2) Power consumption since most of them are equipped with non-rechargeable batteries. Mostly, the sensors are deployed in hazardous and remote areas. This paper focuses on above observations and introduces an approach known as collaborative location-based sleep scheduling (CLSS) scheme. Both awake and asleep status of each sensor node is dynamically devised by schedulers and the scheduling is done purely based on the of mobile users’ current location; in this manner, large amount of energy consumption is minimized at WSN. CLSS work depends on two different methods; CLSS1 scheme provides lower energy consumption and CLSS2 provides the scalability and robustness of the integrated WSN.

Keywords: Sleep scheduling, mobile cloud computing, wireless sensor network, integration, location, network lifetime.

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683 The Grey Relational Analysis of the Influence Factors of Profit in Cartoon-s Character Merchandising Rights

Authors: Min Li, Tao Li

Abstract:

This paper constructs a four factors theoretical model of Chinese small and medium enterprises based on the “cartoon characters- reputation - enterprise marketing and management capabilities – protection of the cartoon image - institutional environment" by literature research, case studies and investigation. The empirical study show that the greatest impact on current merchandising rights income is the institutional environment friendliness, followed by marketing and management capabilities, input of character image protection and Cartoon characters- reputation through the real-time grey relational analysis, and the greatest impact on post-merchandising rights profit is Cartoon characters reputation, followed by the institutional environment friendliness, then marketing and management ability and input of character image protection through the time-delay grey relational analysis.

Keywords: Cartoon characters, merchandising rights, influencefactors, grey relational analysis

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682 Nonlinear Propagation of Acoustic Soliton Waves in Dense Quantum Electron-Positron Magnetoplasma

Authors: A. Abdikian

Abstract:

Propagation of nonlinear acoustic wave in dense electron-positron (e-p) plasmas in the presence of an external magnetic field and stationary ions (to neutralize the plasma background) is studied. By means of the quantum hydrodynamics model and applying the reductive perturbation method, the Zakharov-Kuznetsov equation is derived. Using the bifurcation theory of planar dynamical systems, the compressive structure of electrostatic solitary wave and periodic travelling waves is found. The numerical results show how the ion density ratio, the ion cyclotron frequency, and the direction cosines of the wave vector affect the nonlinear electrostatic travelling waves. The obtained results may be useful to better understand the obliquely nonlinear electrostatic travelling wave of small amplitude localized structures in dense magnetized quantum e-p plasmas and may be applicable to study the particle and energy transport mechanism in compact stars such as the interior of massive white dwarfs etc.

Keywords: Bifurcation theory, magnetized electron-positron plasma, phase portrait, the Zakharov-Kuznetsov equation.

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681 Artificial Intelligent Approach for Machining Titanium Alloy in a Nonconventional Process

Authors: Md. Ashikur Rahman Khan, M. M. Rahman, K. Kadirgama

Abstract:

Artificial neural networks (ANN) are used in distinct researching fields and professions, and are prepared by cooperation of scientists in different fields such as computer engineering, electronic, structure, biology and so many different branches of science. Many models are built correlating the parameters and the outputs in electrical discharge machining (EDM) concern for different types of materials. Up till now model for Ti-5Al-2.5Sn alloy in the case of electrical discharge machining performance characteristics has not been developed. Therefore, in the present work, it is attempted to generate a model of material removal rate (MRR) for Ti-5Al-2.5Sn material by means of Artificial Neural Network. The experimentation is performed according to the design of experiment (DOE) of response surface methodology (RSM). To generate the DOE four parameters such as peak current, pulse on time, pulse off time and servo voltage and one output as MRR are considered. Ti-5Al-2.5Sn alloy is machined with positive polarity of copper electrode. Finally the developed model is tested with confirmation test. The confirmation test yields an error as within the agreeable limit. To investigate the effect of the parameters on performance sensitivity analysis is also carried out which reveals that the peak current having more effect on EDM performance.

Keywords: Ti-5Al-2.5Sn, material removal rate, copper tungsten, positive polarity, artificial neural network, multi-layer perceptron.

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680 Preliminary Study of Fermented Pickle of Tabah Bamboo Shoot (Gigantochloa nigrociliata (Buese) Kurz)

Authors: Luh Putu T. Darmayanti, A. A. Duwipayana, I Nengah K. Putra, Nyoman S. Antara

Abstract:

Processing tabah bamboo shoot as fermented pickle is one of the way to increase the shelf life of this bamboo shoot. The advantage of this shoot is low concentration of hydro cyanic acid (HCN) make it potential for functional food product. This study aimed to determine the characteristic of tabah bamboo shoot pickle such as total of lactic acid bacteria (LAB), pH, total acidity, and hydro cyanic acid (HCN) content, and also find the LAB’s type involved during fermentation, and organic acids’ profiles. The pickle was made by natural fermentation with 6% salt concentration and fermentation conducted for 13 days. The result showed during the fermentation time, in the 4th day LAB’s number was highest as much as 72 x 107 CFU/ml and the lowest pH was 3.09. We also found decreasing in HCN from 37.8 ppm at the beginning to 20.52 ppm at the end of fermentation process. The organic acids detected during the fermentation were lactic acid with the highest concentration was 0.0546 g/100 g and small amount of acetic acid. By using PCR method, the 18 of LABs which had rod shape were detected as member of Lactobacillus spp., in which 17 strains detected as L. plantarum.

Keywords: Fermentation, LAB, pickle, tabah bamboo shoot.

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679 Oil Extraction from Microalgae Dunalliela sp. by Polar and Non-Polar Solvents

Authors: A. Zonouzi, M. Auli, M. Javanmard Dakheli, M. A. Hejazi

Abstract:

Microalgae are tiny photosynthetic plants. Nowadays, microalgae are being used as nutrient-dense foods and sources of fine chemicals. They have significant amounts of lipid, carotenoids, vitamins, protein, minerals, chlorophyll, and pigments. Oil extraction from algae is a hotly debated topic currently because introducing an efficient method could decrease the process cost. This can determine the sustainability of algae-based foods. Scientific research works show that solvent extraction using chloroform/methanol (2:1) mixture is one of the efficient methods for oil extraction from algal cells, but both methanol and chloroform are toxic solvents, and therefore, the extracted oil will not be suitable for food application. In this paper, the effect of two food grade solvents (hexane and hexane/ isopropanol) on oil extraction yield from microalgae Dunaliella sp. was investigated and the results were compared with chloroform/methanol (2:1) extraction yield. It was observed that the oil extraction yield using hexane, hexane/isopropanol (3:2) and chloroform/methanol (2:1) mixture were 5.4, 13.93, and 17.5 (% w/w, dry basis), respectively. The fatty acid profile derived from GC illustrated that the palmitic (36.62%), oleic (18.62%), and stearic acids (19.08%) form the main portion of fatty acid composition of microalgae Dunalliela sp. oil. It was concluded that, the addition of isopropanol as polar solvent could increase the extraction yield significantly. Isopropanol solves cell wall phospholipids and enhances the release of intercellular lipids, which improves accessing of hexane to fatty acids.

Keywords: Fatty acid profile, Microalgae, Oil extraction, Polar solvent.

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678 Hand Gesture Interpretation Using Sensing Glove Integrated with Machine Learning Algorithms

Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

Abstract:

In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove.

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677 ANN Based Model Development for Material Removal Rate in Dry Turning in Indian Context

Authors: Mangesh R. Phate, V. H. Tatwawadi

Abstract:

This paper is intended to develop an artificial neural network (ANN) based model of material removal rate (MRR) in the turning of ferrous and nonferrous material in a Indian small-scale industry. MRR of the formulated model was proved with the testing data and artificial neural network (ANN) model was developed for the analysis and prediction of the relationship between inputs and output parameters during the turning of ferrous and nonferrous materials. The input parameters of this model are operator, work-piece, cutting process, cutting tool, machine and the environment.

The ANN model consists of a three layered feedforward back propagation neural network. The network is trained with pairs of independent/dependent datasets generated when machining ferrous and nonferrous material. A very good performance of the neural network, in terms of contract with experimental data, was achieved. The model may be used for the testing and forecast of the complex relationship between dependent and the independent parameters in turning operations.

Keywords: Field data based model, Artificial neural network, Simulation, Convectional Turning, Material removal rate.

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676 Fiber Optic Sensors for Hydrogen Peroxide Vapor Measurement

Authors: H. Akbari Khorami, P. Wild, N. Djilali

Abstract:

This paper reports on the response of a fiber-optic sensing probe to small concentrations of hydrogen peroxide (H2O2) vapor at room temperature. H2O2 has extensive applications in industrial and medical environments. Conversely, H2O2 can be a health hazard by itself. For example, H2O2 induces cellular damage in human cells and its presence can be used to diagnose illnesses such as asthma and human breast cancer. Hence, development of reliable H2O2 sensor is of vital importance to detect and measure this species. Ferric ferrocyanide, referred to as Prussian Blue (PB), was deposited on the tip of a multimode optical fiber through the single source precursor technique and served as an indicator of H2O2 in a spectroscopic manner. Sensing tests were performed in H2O2-H2O vapor mixtures with different concentrations of H2O2. The results of sensing tests show the sensor is able to detect H2O2 concentrations in the range of 50.6 ppm to 229.5 ppm. Furthermore, the sensor response to H2O2 concentrations is linear in a log-log scale with the adjacent R-square of 0.93. This sensing behavior allows us to detect and quantify the concentration of H2O2 in the vapor phase.

Keywords: Chemical deposition, fiber-optic sensors, hydrogen peroxide vapor, prussian blue.

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675 Methodology: A Review in Modelling and Predictability of Embankment in Soft Ground

Authors: Bhim Kumar Dahal

Abstract:

Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: Embankment, ground improvement, modelling, model prediction.

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674 Impact of GCSC on Measured Impedance by Distance Relay in the Presence of Single Phase to Earth Fault

Authors: M. Zellagui, A. Chaghi

Abstract:

This paper presents the impact study of GTO Controlled Series Capacitor (GCSC) parameters on measured impedance (Zseen) by MHO distance relays for single transmission line high voltage 220 kV in the presence of single phase to earth fault with fault resistance (RF). The study deals with a 220 kV single electrical transmission line of Eastern Algerian transmission networks at Group Sonelgaz (Algerian Company of Electrical and Gas) compensated by series Flexible AC Transmission System (FACTS) i.e. GCSC connected at midpoint of the transmission line. The transmitted active and reactive powers are controlled by three GCSC-s. The effects of maximum reactive power injected as well as injected maximum voltage by GCSC on distance relays measured impedance is treated. The simulations results investigate the effects of GCSC injected parameters: variable reactance (XGCSC), variable voltage (VGCSC) and reactive power injected (QGCSC) on measured resistance and reactance in the presence of earth fault with resistance fault varied between 5 to 50 Ω for three cases study.

Keywords: GCSC Parameters, Transmission line, Earth fault, Symmetrical components, Distance protection, Measured impedance.

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673 Understanding Innovation by Analyzing the Pillars of the Global Competitiveness Index

Authors: Ujjwala Bhand, Mridula Goel

Abstract:

Global Competitiveness Index (GCI) prepared by World Economic Forum has become a benchmark in studying the competitiveness of countries and for understanding the factors that enable competitiveness. Innovation is a key pillar in competitiveness and has the unique property of enabling exponential economic growth. This paper attempts to analyze how the pillars comprising the Global Competitiveness Index affect innovation and whether GDP growth can directly affect innovation outcomes for a country. The key objective of the study is to identify areas on which governments of developing countries can focus policies and programs to improve their country’s innovativeness. We have compiled a panel data set for top innovating countries and large emerging economies called BRICS from 2007-08 to 2014-15 in order to find the significant factors that affect innovation. The results of the regression analysis suggest that government should make policies to improve labor market efficiency, establish sophisticated business networks, provide basic health and primary education to its people and strengthen the quality of higher education and training services in the economy. The achievements of smaller economies on innovation suggest that concerted efforts by governments can counter any size related disadvantage, and in fact can provide greater flexibility and speed in encouraging innovation.

Keywords: Innovation, Global Competitiveness Index, BRICS, economic growth.

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672 Harris Extraction and SIFT Matching for Correlation of Two Tablets

Authors: Ali Alzaabi, Georges Alquié, Hussain Tassadaq, Ali Seba

Abstract:

This article presents the developments of efficient algorithms for tablet copies comparison. Image recognition has specialized use in digital systems such as medical imaging, computer vision, defense, communication etc. Comparison between two images that look indistinguishable is a formidable task. Two images taken from different sources might look identical but due to different digitizing properties they are not. Whereas small variation in image information such as cropping, rotation, and slight photometric alteration are unsuitable for based matching techniques. In this paper we introduce different matching algorithms designed to facilitate, for art centers, identifying real painting images from fake ones. Different vision algorithms for local image features are implemented using MATLAB. In this framework a Table Comparison Computer Tool “TCCT" is designed to facilitate our research. The TCCT is a Graphical Unit Interface (GUI) tool used to identify images by its shapes and objects. Parameter of vision system is fully accessible to user through this graphical unit interface. And then for matching, it applies different description technique that can identify exact figures of objects.

Keywords: Harris Extraction and SIFT Matching

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671 Study of Compost Maturity during Humification Process using UV-Spectroscopy

Authors: N. Sanmanee, K. Panishkan, K. Obsuwan, S. Dharmvanij

Abstract:

The increments of aromatic structures are widely used to monitor the degree of humification. Compost derived from mix manures mixed with agricultural wastes was studied. The compost collected at day 0, 7, 14, 21, 28, 35, 49, 77, 91, 105, and 119 was divided into 3 stages, initial stage at day 0, thermophilic stage during day 1-48, and mature stage during day 49-119. The change of highest absorptions at wavelength range between 210-235 nm during day 0- 49 implied that small molecules such as nitrates and carboxylic occurred faster than the aromatic molecules that were found at wavelength around 280 nm. The ratio of electron-transfer band at wavelength 253 nm by the benzonoid band at wavelength 230 nm (E253/E230) also gradually increased during the fermenting period indicating the presence of O-containing functional groups. This was in agreement with the shift change from aliphatic to aromatic structures as shown by the relationship with C/N and H/C ratios (r = - 0.631 and -0.717, p< 0.05) since both were decreasing. Although the amounts of humic acid (HA) were not different much during the humification process, the UV spectral deconvolution showed better qualitative characteristics to help in determining the compost quality. From this study, the compost should be used at day 49 and should not be kept longer than 3 months otherwise the quality of HA would decline regardless of the amounts of HA that might be rising. This implied that other processes, such as mineralization had an influence on the humification process changing HA-s structure and its qualities.

Keywords: Compost maturity, UV spectroscopy, humification, humic acid

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670 Intelligent Transport System: Classification of Traffic Signs Using Deep Neural Networks in Real Time

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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