Search results for: processing parameters

Authors: Karan Sharma, Ajay Kumar

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Epileptic seizure is a type of disease due to which electrical charge in the brain flows abruptly resulting in abnormal activity by the subject. One percent of total world population gets epileptic seizure attacks.Due to abrupt flow of charge, EEG (Electroencephalogram) waveforms change. On the display appear a lot of spikes and sharp waves in the EEG signals. Detection of epileptic seizure by using conventional methods is time-consuming. Many methods have been evolved that detect it automatically. The initial part of this paper provides the review of techniques used to detect epileptic seizure automatically. The automatic detection is based on the feature extraction and classification patterns. For better accuracy decomposition of the signal is required before feature extraction. A number of parameters are calculated by the researchers using different techniques e.g. approximate entropy, sample entropy, Fuzzy approximate entropy, intrinsic mode function, cross-correlation etc. to discriminate between a normal signal & an epileptic seizure signal.The main objective of this review paper is to present the variations in the EEG signals at both stages (i) Interictal (recording between the epileptic seizure attacks). (ii) Ictal (recording during the epileptic seizure), using most appropriate methods of analysis to provide better healthcare diagnosis. This research paper then investigates the effects of a noninvasive healing therapy on the subjects by studying the EEG signals using latest signal processing techniques. The study has been conducted with Reiki as a healing technique, beneficial for restoring balance in cases of body mind alterations associated with an epileptic seizure. Reiki is practiced around the world and is recommended for different health services as a treatment approach. Reiki is an energy medicine, specifically a biofield therapy developed in Japan in the early 20th century. It is a system involving the laying on of hands, to stimulate the body’s natural energetic system. Earlier studies have shown an apparent connection between Reiki and the autonomous nervous system. The Reiki sessions are applied by an experienced therapist. EEG signals are measured at baseline, during session and post intervention to bring about effective epileptic seizure control or its elimination altogether.

Keywords: EEG signal, Reiki, time consuming, epileptic seizure

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Authors: Seyed-Ahmad Shahidi, Salemeh Kazemzadeh, Mehdi Sharifi Soltani, Azade Ghorbani-HasanSaraei

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The kinetics of colour changes of American Pokeweed extract, due to concentration by various heating methods was studied. Three different heating/evaporation processes were employed for production of American Pokeweed extract concentrate. The American Pokeweed extract was concentrated to a final 40 °Brix from an initial °Brix of 4 by microwave heating, rotary vacuum evaporator and evaporating at atmospheric pressure. The final American Pokeweed extract concentration of 40 °Brix was achieved in 188, 216 and 320 min by using microwave, rotary vacuum and atmospheric heating processes, respectively. The colour change during concentration processes was investigated. Total colour differences, Hunter L, a and b parameters were used to estimate the extent of colour loss. All Hunter colour parameters decreased with time. The zero-order, first-order and a combined kinetics model were applied to the changes in colour parameters. All models were found to describe the L, a and b-data adequately. Results indicated that variation in TCD followed both first-order and combined kinetics models. This model implied that the colour formation and pigment destruction occurred during concentration processes of American Pokeweed extract.

Keywords: American pokeweed, colour, concentration, kinetics

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Authors: Hyojin Lim, Cuong Nguyen Khac, Ho-Youl Jung

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In this paper, we propose moving object detection method which is helpful for driver to safely take his/her car out of parking lot. When moving objects such as motorbikes, pedestrians, the other cars and some obstacles are detected at the rear-side of host vehicle, the proposed algorithm can provide to driver warning. We assume that the host vehicle is just before departure. Gaussian Mixture Model (GMM) based background subtraction is basically applied. Pre-processing such as smoothing and post-processing as morphological filtering are added.We examine “which color space has better performance for detection of moving objects?” Three color spaces including RGB, YCbCr, and Y are applied and compared, in terms of detection rate. Through simulation, we prove that RGB space is more suitable for moving object detection based on background subtraction.

Keywords: gaussian mixture model, background subtraction, moving object detection, color space, morphological filtering

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Authors: Shrey Sharma, Gunjan Kumar Verma

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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: inversion, limitations, optimization, resistivity

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Authors: Sanjaykumar R. Patel, Parth R. Kayastha

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α-lactose monohydrate is widely used in the pharmaceutical industries as an inactive substance that acts as a vehicle or a medium for a drug or other active substance. It is a byproduct of dairy industries, and the recovery of lactose from whey not only boosts the improvement of the economics of whey utilization but also causes a reduction in pollution as lactose recovery can reduce the BOD of whey by more than 80%. In the present study, levels of process parameters were kept as initial lactose concentration (30-50% w/w), sonication amplitude (20-40%), sonication time (2-6 hours), and crystallization temperature (10-20 ^oC) for the recovery of lactose in ultrasound assisted cooling crystallization. In comparison with cooling crystallization, the use of ultrasound enhanced the lactose recovery by 39.17% (w/w). The parameters were optimized for the lactose recovery using Taguchi Method. The optimum conditions found were initial lactose concentration at level 3 (50% w/w), amplitude of sonication at level 2 (40%), the sonication time at level 3 (6 hours), and crystallization temperature at level 1 (10 °C). The maximum recovery was found to be 85.85% at the optimum conditions. Sonication time and the initial lactose concentration were found to be significant parameters for the lactose recovery.

Keywords: crystallization, lactose, Taguchi method, ultrasound

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Authors: Mst. Nilufa Sultana, Shatirah Akib, Muhammad Aqeel Ashraf, Mohamed Roseli Zainal Abidin

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Most people today are aware that global Climate change, is not just a scientific theory but also a fact with worldwide consequences. Global climate change is due to rapid urbanization, industrialization, high population growth and current vulnerability of the climatic condition. Water is becoming scarce as a result of global climate change. To mitigate the problem arising due to global climate change and its drought effect, harvesting rainwater from green roofs, an environmentally-friendly and versatile technology, is becoming one of the best assessment criteria and gaining attention in Malaysia. This paper addresses the sustainability of green roofs and examines the quality of water harvested from green roofs in comparison to rainwater. The factors that affect the quality of such water, taking into account, for example, roofing materials, climatic conditions, the frequency of rainfall frequency and the first flush. A green roof was installed on the Humid Tropic Centre (HTC) is a place of the study on monitoring program for urban Stormwater Management Manual for Malaysia (MSMA), Eco-Hydrological Project in Kualalumpur, and the rainwater was harvested and evaluated on the basis of four parameters i.e., conductivity, dissolved oxygen (DO), pH and temperature. These parameters were found to fall between Class I and Class III of the Interim National Water Quality Standards (INWQS) and the Water Quality Index (WQI). Some preliminary treatment such as disinfection and filtration could likely to improve the value of these parameters to class I. This review paper clearly indicates that there is a need for more research to address other microbiological and chemical quality parameters to ensure that the harvested water is suitable for use potable water for domestic purposes. The change in all physical, chemical and microbiological parameters with respect to storage time will be a major focus of future studies in this field.

Keywords: Green roofs, INWQS, MSMA-SME, rainwater harvesting, water treatment, water quality parameter, WQI

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Authors: Nur Atirah Hasmi, Nadia Nisha Musa, Hasnun Nita Ismail, Zulfadli Mahfodz

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The effect of water quality parameters on the abundance of aquatic insects has been studied in Batu Berangkai, Dipang, Kuala Woh and Lata Kinjang Rivers, Perak, northern peninsular Malaysia. The focuses are to compare the abundance of aquatic insects in each sampling areas and to investigate the physical and chemical factors (water temperature, depth of water, canopy, water velocity, pH value, and dissolved oxygen) on the abundance of aquatic insects. The samples and data were collected by using aquatic net and multi-probe parameter. Physical parameters; water velocity, water temperature, depth, canopy cover, and two chemical parameters; pH value and dissolved oxygen have been measured in situ and recorded. A total of 631 individuals classified into 6 orders and 18 families of aquatic insects were identified from four sampling sites. The largest percentage of samples collected is from order Plecoptera 35.8%, followed by Ephemeroptera 32.6%, Trichoptera 17.0%, Hemiptera 8.1%, Coleoptera 4.8%, and the least is Odonata 1.7%. The aquatic insects collected from Dipang River have the highest abundance of 273 individuals from 6 orders and 13 families and the least insects trapped at Lata Kinjang which only have 64 individuals from 5 orders and 6 families. There is significant association between different sampling areas and abundance of aquatic insects (p<0.05). High abundance of aquatic insects was found in higher water temperature, low water velocity, deeper water, low pH, high amount of dissolved oxygen, and the area that is not covered by canopy.

Keywords: aquatic insect, physicochemical parameter, river, water quality

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Authors: Arnab Majumdar, Sanjoy Sadhukhan

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Although gun barrel steels are an important variety from defense view point, available literatures are very limited. In the present work, an IF grade Ni-Cr-Mo-V high strength low alloy steel is produced in Electric Earth Furnace-ESR Route. Ingot was hot forged to desired dimension with a reduction ratio of 70-75% followed by homogenization, hardening and tempering treatment. Sample chemistry, NMIR, macro and micro structural analyses were done. Mechanical properties which include tensile, impact, and fracture toughness were studied. Ultrasonic testing was done to identify internal flaws. The existing high strength low alloy Ni-Cr-Mo-V steel shows improved properties in modified processing route and heat treatment schedule in comparison to properties noted earlier for manufacturing of gun barrels. The improvement in properties seems to withstand higher explosive loads with the same amount of steel in gun barrel application.

Keywords: gun barrel steels, IF grade, chemistry, physical properties, thermal and mechanical processing, mechanical properties, ultrasonic testing

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Authors: Duy Nhat Tran, Van Tien Pham, Quang Trung Trinh, Tien Hai Tran, Van Cong Bui

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In recent years, artificial intelligence and the Internet of Things have experienced significant advancements. Collecting image data and real-time analysis and processing of tasks have become increasingly popular in various aspects of life. Optical scanning devices are widely used to observe and analyze different environments, whether fixed outdoors, mounted on mobile devices, or used in unmanned aerial vehicles. As a result, the interaction between the physical environment and these devices has become more critical in terms of safety. Two commonly used methods for addressing these challenges are active and passive approaches. Each method has its advantages and disadvantages, but combining both methods can lead to higher efficiency. One solution is to utilize direct-drive motors for position control and real-time feedback within the operational range to determine appropriate control parameters with high precision. If the maximum motor torque is smaller than the inertial torque and the rotor reaches the operational limit, the spring system absorbs the impact force. Numerous experiments have been conducted to demonstrate the effectiveness of device protection during operation.

Keywords: optical device, collision safety, collision absorption, precise mechanics

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Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

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Authors: Suwarsono, Ario S. Baskoro, Gandjar Kiswanto, Budiono

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Friction Stir Welding (FSW) is a relatively new technique for joining metal. In some cases on aluminum joining, FSW gives better results compared with the arc welding processes, including the quality of welds and produces less distortion.FSW welding process for a light structure and thin materials requires small forces as possible, to avoid structure deflection. The joining process on FSW occurs because of melting temperature and compressive forces, the temperature generation of caused by material deformation and friction between the cutting tool and material. In this research, High speed rotation of spindle was expected to reduce the force required for deformation. The welding material was Aluminum A1100, with thickness of 0.4 mm. The tool was made of HSS material which was shaped by micro grinding process. Tool shoulder diameter is 4 mm, and the length of pin was 0.6 mm (with pin diameter= 1.5 mm). The parameters that varied were the plunge speed (2 mm/min, 3 mm/min, 4 mm/min). The tool speed is fixed at 33,000 rpm. Responses of FSSW parameters to analyze were Axial Force (Z-Force), Temperature and the Shear Strength of welds. Research found the optimum µFSSW parameters, it can be concluded that the most important parameters in the μFSSW process was plunge speed. lowest plunge speed (2 mm / min) causing the lowest axial force (110.40 Newton). The increases of plunge speed will increase the axial force (maximum Z-Farce= 236.03 Newton), and decrease the shear strength of welds.

Keywords: friction stir spot welding, aluminum A1100, plunge speed, axial force, shear strength

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Authors: Daianne Fernandes Diogenes

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Railway ballast aggregates’ shape properties and size distribution can be directly affected by several factors, such as traffic, fouling, and maintenance processes, which cause breakage and wearing, leading to the fine particles’ accumulation through the ballast layer. This research aims to analyze the influence of traffic, tamping process, and sleepers’ stiffness on aggregates' shape and mechanical properties, by using traditional and digital image processing (DIP) techniques and cyclic tests, like resilient modulus (RM) and permanent deformation (PD). Aggregates were collected in different phases of the railway service life: (i) right after the crushing process; (ii) after construction, for the aggregates positioned below the sleepers and (iii) after 5 years of operation. An increase in the percentage of cubic particles was observed for the materials (ii) and (iii), providing a better interlocking, increasing stiffness and reducing axial deformation after 5 years of service, when compared to the initial conditions.

Keywords: digital image processing, mechanical behavior, railway ballast, shape properties

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Authors: Roya Biabani, Mentore Vaccari, Piero Ferrari

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Accumulated microplastic (MPLs) in soil pose the risk of adsorbing and transporting polychlorinated biphenyls (PCBs) into the food chain or bodies. PCBs belong to a class of man-made hydrophobic organic chemicals (HOCs) that are classified as probable human carcinogens and a hazard to biota. Therefore, to take effective action and not aggravate the already recognized problems, the knowledge of PCB remediation in the presence of MPLs needs to be complete. Due to the high efficiency and little secondary pollution production, thermal desorption (TD) has been widely used for processing a variety of pollutants, especially for removing volatile and semi-volatile organic matter from contaminated solids and sediment. This study investigates the fate of PCB compounds during the thermal remediation method. For this, the PCB-contaminated soil was collected from the earth-canal downstream Caffaro S.p.A. chemical factory, which produced PCBs and PCB mixtures between 1930 and 1984. For MPL analysis, MPLs were separated by density separation and oxidation of organic matter. An operational range for the key parameters of thermal desorption processes was experimentally evaluated. Moreover, the temperature treatment characteristics of the PCBs-contaminated soil under anaerobic and aerobic conditions were studied using the Thermogravimetric Analysis (TGA).

Keywords: contaminated soils, microplastics, polychlorinated biphenyls, thermal desorption

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Authors: Onder Turkmen, Musa Seymen, Sali Fidan, Mustafa Paksoy

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There is a requirement for registered edible seed pumpkin suitable for eating in Turkey. A total of 81 genotypes collected from the researchers in 2005 originated from Eskisehir, Konya, Nevsehir, Tekirdag, Sakarya, Kayseri and Kirsehir provinces were utilized. The used genetic materials were brought to S5 generation by the research groups among 2006 and 2010 years. In this research, S5 stage reached in the genotype given some of the morphological features, and selection of promising genotypes generated scale were made. Results showed that the A-1 (420), A-7 (410), A-8 (420), A-32 (420), B-17 (410), B-24 (410), B-25 (420), B-33 (400), C-24 (420), C-25 (410), C-26 (410) and C-30 (420) genotypes are expected to be promising varieties.

Keywords: candidate cultivar, edible seed pumpkin, morphologic parameters, selection

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Authors: Varsha Singh, Kishan Fuse

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This paper presents a study of the grey-Taguchi method to optimize CNC milling parameters of AA6061 T6 aluminium alloy. Grey-Taguchi method combines Taguchi method based design of experiments (DOE) with grey relational analysis (GRA). Multi-response optimization of different quality characteristics as surface roughness, material removal rate, cutting forces is done using grey relational analysis (GRA). The milling parameters considered for experiments include cutting speed, feed per tooth, and depth of cut. Each parameter with three levels is selected. A grey relational grade is used to estimate overall quality characteristics performance. The Taguchi’s L9 orthogonal array is used for design of experiments. MINITAB 17 software is used for optimization. Analysis of variance (ANOVA) is used to identify most influencing parameter. The experimental results show that grey relational analysis is effective method for optimizing multi-response characteristics. Optimum results are finally validated by performing confirmation test.

Keywords: ANOVA, CNC milling, grey relational analysis, multi-response optimization

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Authors: Kuei-Yu Chien, Hsiu-Yu Chiu, Chia-Nan Chen, Shu-Chen Chen

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Background: Frailty is associated with decreased physical performances that affect mobility of the elderly. Time up and go test (TUG) was the common method to evaluate mobility in the community. The purpose of this study was to compare the parameters in different stages of Time up and go test (TUG) and physical performance between pre-frail elderly (PFE) and non-frail elderly (NFE). We also investigated the relationship between TUG parameters and physical performance. Methods: Ninety-two community-dwelling older adults were as participants in this study. Based on Canadian Study of Health and Aging Clinical Frailty Scale, 22 older adults were classified as PFE (71.77 ± 6.05 yrs.) and 70 were classified as NFE (71.2 ± 5.02 yrs.). We performed body composition and physical performance, including balance, muscular strength/endurance, mobility, cardiorespiratory endurance, and flexibility. Results: Pre-frail elderly took significantly longer time than NFE in TUG test (p=.004). Pre-frail elderly had lower turning average angular velocity (p = .017), turning peak angular velocity (p = .041) and turning-stand to sit peak angular velocity (p = .037) than NFE. The turning related parameters related to open-eye stand on right foot, 30-second chair stand test, back scratch, and 2-min step tests. Conclusions: Turning average angular velocity, turning peak angular velocity and turning-stand to sit peak angular velocity mainly affected the TUG performance. We suggested that static/dynamic balance, agility, flexibility, and muscle strengthening of lower limbs exercise were important to PFE.

Keywords: mobility, aglity, active ageing, functional fitness

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Authors: L. Masilionyte, S. Maiksteniene

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Alternative farming systems are used to cultivate high quality food products and retain the viability and fertility of soil. The field experiments of different farming systems were conducted at Joniškėlis Experimental Station of the Lithuanian Research Centre for Agriculture and Forestry in 2006–2013. The soil of the experimental site was Endocalcari-Endohypogleyic Cambisol (CMg-n-w-can). In different farming systems, farmyard manure, straw and green manure catch crops used for fertilization both in the soil low in humus and in the soil moderate in humus. In the 0–20 cm depth layer, it had a more significant effect on soil moisture than on other physical soil properties. In the agricultural systems, in which catch crops had been grown, soil physical characteristics did not differ significantly before their biomass incorporation, except for the moisture content, which was lower in rainy periods and higher in drier periods than in the soil without catch crops. Soil bulk density and porosity in the topsoil layer were more dependent on soil humus content than on agricultural measures used: in the soil moderate in humus content, compared with the soil low in humus, bulk density was by 1.4 % lower, and porosity by 1.8 % higher. The research findings create a possibility to make improvements in alternative cropping systems by choosing organic fertilizers and catch crops’ combinations that have the sustainable effect on soil and that maintain the sustainability of soil productivity parameters. Rational fertilization systems, securing the stability of soil productivity parameters and crop rotation productivity will promote a development of organic agriculture.

Keywords: agro-measures, soil physical parameters, organic farming, sustainable farming

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Authors: Yongxin Chen, Min Zhang

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As industrial enterprises are the primary source of national pollution, environmental information disclosure is a crucial way to demonstrate to stakeholders the work they have done in fulfilling their environmental responsibilities and accepting social supervision. In the era of the digital economy, many companies, actively embracing the opportunities that come with digital transformation, have begun to apply digital technology to information collection and disclosure within the enterprise. However, less is known about the relationship between digital transformation and environmental disclosure. This study investigates how enterprise digital transformation affects environmental disclosure in 643 Chinese industrial companies, according to information processing theory. What is intriguing is that the depth (size) and breadth (diversity) of environmental disclosure linearly increase with the rise in the collection, processing, and analytical capabilities in the digital transformation process. However, the volume of data will grow exponentially, leading to a marginal increase in the economic and environmental costs of utilizing, storing, and managing data. In our empirical findings, linearly increasing benefits and marginal costs create a unique inverted U-shaped relationship between the degree of digital transformation and environmental disclosure in the Chinese industrial sector. Besides, based on the upper echelons theory, we also propose that the top management team with high stability and managerial capabilities will invest more effort and expense into improving environmental disclosure quality, lowering the carbon footprint caused by digital technology, maintaining data security etc. In both these contexts, the increasing marginal cost curves would become steeper, weakening the inverted U-shaped slope between DT and ED.

Keywords: digital transformation, environmental disclosure, the top management team, information processing theory, upper echelon theory

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Authors: Amandeep Singh, Niraj Bala

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In the last decades, light-weight materials such as magnesium matrix composites have become hot topic for material research due to their excellent mechanical and physical properties. However, relatively very less work has been done related to the wear behavior of these composites. Magnesium matrix composites have wide applications in automobile and aerospace sector. In this review, attempt has been done to collect the literature related to wear behavior of magnesium matrix composites fabricated through various processing techniques such as stir casting, powder metallurgy, friction stir processing etc. Effect of different reinforcements, reinforcement content, reinforcement size, wear load, sliding speed and time have been studied by different researchers in detail. Wear mechanism under different experimental condition has been reviewed in detail. The wear resistance of magnesium and its alloys can be enhanced with the addition of different reinforcements. Wear resistance can further be enhanced by increasing the percentage of added reinforcements. Increase in applied load during wear test leads to increase in wear rate of magnesium composites.

Keywords: hardness, magnesium matrix composites, reinforcement, wear

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Authors: Anaam H. Al-ShaikhAli, Mansour A. Al-Herz

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The research leverages the proven HS-FCC technology to directly crack crude oils into petrochemical building blocks. Crude oils were subjected to an optimized hydro-processing process where metal contaminants and sulfur were reduced to an acceptable level for feeding the crudes into the HS-FCC technology. The hydro-processing is achieved through a fixed-bed reactor which is composed of 3 layers of catalysts. The crude oil is passed through a dementalization catalyst followed by a desulfurization catalyst and finally a de-aromatization catalyst. The hydroprocessing was conducted at an optimized liquid hourly space velocity (LHSV), temperature, and pressure for an optimal reduction of metals and sulfur from the crudes. The hydro-processed crudes were then fed into a micro activity testing (MAT) unit to simulate the HS-FCC technology. The catalytic cracking of crude oils was conducted over tailored catalyst formulations under an optimized catalyst/oil ratio and cracking temperature for optimal production of total light olefins.

Keywords: petrochemical, catalytic cracking, catalyst synthesis, HS-FCC technology

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Authors: F. Bendahma, S. Bentata, S. Cherid, A. Zitouni, S. Terkhi, T. Lantri, Y. Sefir, Z. F. Meghoufel

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We examine the electronic transport properties in Al_xGa_1-xAs/GaAs superlattices. Using the transfer-matrix technique and the exact Airy function formalism, we investigate theoretically the effect of structural parameters on the electronic energy spectra of trimer thickness barrier (TTB). Our numerical calculations showed that the localization length of the states becomes more extended when the disorder is correlated (trimer case). We have also found that the resonant tunneling time (RTT) is of the order of several femtoseconds.

Keywords: electronic transport properties, structural parameters, superlattices, transfer-matrix technique

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

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

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

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Authors: Katerina Nerantzaki, Panayiota Metallidou, Anastasia Efklides

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The aim of the study was to investigate: (a) changes in the intensity of various epistemic emotions during cognitive processing in a decision-making task and (b) their associations with metacognitive feelings of difficulty and confidence. One hundred and fifty-two undergraduate university students were asked individually to read in the e-prime environment decision-making scenarios about moral dilemmas concerning self-driving cars, which differed in the level of conflict they produced, and then to make a choice between two options. Further, the participants were asked to rate on a four-point scale four epistemic emotions (surprise, curiosity, confusion, and wonder) and two metacognitive feelings (feeling of difficulty and feeling of confidence) after making their choice in each scenario. Changes in cognitive processing due to the level of conflict affected differently the intensity of the specific epistemic emotions. Further, there were interrelations of epistemic emotions with metacognitive feelings.

Keywords: confusion, curiosity, epistemic emotions, metacognitive experiences, surprise

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Authors: Badreddine Chemali, Boualem Tiliouine

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This article presents the main results of a numerical investigation on the uncertainty of dynamic response of structures with statistically correlated random damping Gamma distributed. A computational method based on a Linear Statistical Model (LSM) is implemented to predict second order statistics for the response of a typical industrial building structure. The significance of random damping with correlated parameters and its implications on the sensitivity of structural peak response in the neighborhood of a resonant frequency are discussed in light of considerable ranges of damping uncertainties and correlation coefficients. The results are compared to those generated using Monte Carlo simulation techniques. The numerical results obtained show the importance of damping uncertainty and statistical correlation of damping coefficients when obtaining accurate probabilistic estimates of dynamic response of structures. Furthermore, the effectiveness of the LSM model to efficiently predict uncertainty propagation for structural dynamic problems with correlated damping parameters is demonstrated.

Keywords: correlated random damping, linear statistical model, Monte Carlo simulation, uncertainty of dynamic response

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Authors: Y. de Smet, J. Hubinont

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PROMETHEE and GAIA are well-known Multiple Criteria Decision Aid methods. Given an evaluation table and preference parameters they allow to rank the alternatives, to visualize the problem, to perform sensitivity and robustness analysis, etc. Unfortunately, it is often hard for the Decision Maker (DM) to estimate the precise values of these parameters. Therefore an alternative option is to give ranges of potential values in order to apply Stochastic Multicriteria Acceptability Analysis. This has been recently studied in the context of the SMAA-PROMETHEE method. The aim of this contribution is to propose an SMAA extension of GAIA. We show how this tool can be useful and provide complementary information to SMAA-PROMETHEE. This is illustrated on a pedagogical example.

Keywords: multiple criteria decision making, PROMETHEE, GAIA, SMAA

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Chin-Yuan Hsieh, Wei-Chun Lu, Yu-Hong Zeng

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The situation of a group of fish die is frequently found due to the fish disease caused by the deterioration of aquaculture water quality. The toxic ammonia is produced by animals as a byproduct of protein. The system is designed by the smart sensor technology and developed by the mathematical model to monitor the water parameters 24 hours a day and predict the relationship among twelve water quality parameters for monitoring the water quality in aquaculture. All data measured are stored in cloud server. In productive ponds, the daytime pH may be high enough to be lethal to the fish. The sudden change of the aquaculture conditions often results in the increase of PH value of water, lack of oxygen dissolving content, water quality deterioration and yield reduction. From the real measurement, the system can send the message to user’s smartphone successfully on the bad conditions of water quality. From the data comparisons between measurement and model simulation in fish aquaculture site, the difference of parameters is less than 2% and the correlation coefficient is at least 98.34%. The solubility rate of oxygen decreases exponentially with the elevation of water temperature. The correlation coefficient is 98.98%.

Keywords: aquaculture, sensor, ammonia, dissolved oxygen

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Authors: Hamza Javar Magnier, Robin Curtis

Abstract:

There have been rapid advances in the upstream processing of protein therapeutics, which has shifted the bottleneck to downstream purification and formulation. Finding liquid formulations with shelf lives of up to two years is increasingly difficult for some of the newer therapeutics, which have been engineered for activity, but their formulations are often viscous, can phase separate, and have a high propensity for irreversible aggregation1. We explore means to develop improved predictive ability from a better understanding of how protein-protein interactions on formulation conditions (pH, ionic strength, buffer type, presence of excipients) and how these impact upon the initial steps in protein self-association and aggregation. In this work, we study the initial steps in the aggregation pathways using a minimal protein model based on square-well potentials and discontinuous molecular dynamics. The effect of model parameters, including range of interaction, stiffness, chain length, and chain sequence, implies that protein models fold according to various pathways. By reducing the range of interactions, the folding- and collapse- transition come together, and follow a single-step folding pathway from the denatured to the native state2. After parameterizing the model interaction-parameters, we developed an understanding of low-temperature conformational properties and fluctuations, and the correlation to the folding transition of proteins in isolation. The model fluctuations increase with temperature. We observe a low-temperature point, below which large fluctuations are frozen out. This implies that fluctuations at low-temperature can be correlated to the folding transition at the melting temperature. Because proteins “breath” at low temperatures, defining a native-state as a single structure with conserved contacts and a fixed three-dimensional structure is misleading. Rather, we introduce a new definition of a native-state ensemble based on our understanding of the core conservation, which takes into account the native fluctuations at low temperatures. This approach permits the study of a large range of length and time scales needed to link the molecular interactions to the macroscopically observed behaviour. In addition, these models studied are parameterized by fitting to experimentally observed protein-protein interactions characterized in terms of osmotic second virial coefficients.

Keywords: protein folding, native-ensemble, conformational fluctuation, aggregation

Procedia PDF Downloads 348

Authors: Assia Amri, Naima Layachi, Ali Ladjama

Abstract:

The characterization of some Algerian honey was carried out on the basis of their physico-chemical properties: moisture,hydroxy methyl furfural, diastase activity, pH,free, total and lactonic acidity, electrical conductivity, minerals and proline content. Studied samples are found to be low in moisture and therefore safe from fermentation, low in HMF level and high in diastase activity. Additionally the diastase activity and the HMF content are widely recognized parameters indicating the freshness of honey. Phenolic compounds present in honey are classified into two groups - simple phenols and polyphenols. The simple phenols in honey are various phenol acids, but polyphenols are various flavonoids and flavonides. The aim of our work was to determine antioxidant properties of various Algerian honey samples–the total phenol content, total flavonoids content, as well as honey anti radical activity.The quality of honey samples differs on account of various factors such as season, packaging and processing conditions, floral source, geographical origin and storage period. It is important that precautions should be taken to ensure standardization and rationalization of beekeeping techniques, manufacturing procedures and storing processes to improve honey quality.

Keywords: honey, physico-chemical characterization, phenolic coumpound, HMF, diastase activity

Procedia PDF Downloads 400

Authors: Cangir Uyarlar, E. Eren Gultepe, I. Sadi Cetingul, Ismail Bayram

Abstract:

This study was conducted to investigate the effect of humic acid (Potassium Humate) at different levels on rations on the effects of both maternal and offspring health, metabolic parameters and immunity levels in transition dairy cows. For this purpose, 50 Holstein dairy cows divided 5 trial groups. Experimental groups were designed as follows: A) Control (0% Humas); B) 0.5 Humas (0,5% in concentrated diet); C) 1 Humas (1% in concentrated diet), D) 1,5 Humas (1,5% in concentrated diet), E) 2 Humas (2% in concentrated diet), respectively. The study lasted from the first day of the dry period to postpartum 30th day. Diets were prepared as isocaloric and isonitrogenic. In the experiment, the day on which the animals gave birth was accepted as ‘0 (zero)’ and blood was taken from tail vein (v. coccygea) at -60, -53, -46, -39, -32, -25, -18, -11, -4, 0, ; Colostrum samples were taken on days 0, 1 and 2; Blood samples were taken on days 0, 1, 2, 15 and 30 from the juguler vein (v. jugularis) of the new born calves. Total blood leukocyte, Lymphocyte, Monocyte, granulocytes, Hemoglobin, Hematocrit, MCV, MCH, MWC, RDW, PLT, MPV, PDW, PCT, NEFA, BHBA, Glucose, Total Cholesterol , Triglyceride, LDL, HDL, VLDL, ALT, AST, ALP, GGT and Total IgG levels and colostrum IgG levels were determined in this experiment. The results suggest that although the supplementation of humic acid at 2% level adversely affected to production parameters, the addition of humic acid (potassium humate) to the concentrate mix during the dry period (particularly 0.5 and 1% levels) may provide an increasing on mother and the offspring immunity, some improving on serum metabolism parameters and enhancing the milk production.

Keywords: humic acid, dairy cow, calf, immunity

Procedia PDF Downloads 190