Search results for: chemical identification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7252

Search results for: chemical identification

6862 Embedded Electrochemistry with Miniaturized, Drone-Based, Potentiostat System for Remote Detection Chemical Warfare Agents

Authors: Amer Dawoud, Jesy Motchaalangaram, Arati Biswakarma, Wujan Mio, Karl Wallace

Abstract:

The development of an embedded miniaturized drone-based system for remote detection of Chemical Warfare Agents (CWA) is proposed. The paper focuses on the software/hardware system design of the electrochemical Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) signal processing for future deployment on drones. The paper summarizes the progress made towards hardware and electrochemical signal processing for signature detection of CWA. Also, the miniature potentiostat signal is validated by comparing it with the high-end lab potentiostat signal.

Keywords: drone-based, remote detection chemical warfare agents, miniaturized, potentiostat

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6861 Scientific Investigation for an Ancient Egyptian Polychrome Wooden Stele

Authors: Ahmed Abdrabou, Medhat Abdalla

Abstract:

The studied stele dates back to Third Intermediate Period (1075-664) B.C in an ancient Egypt. It is made of wood and covered with painted gesso layers. This study aims to use a combination of multi spectral imaging {visible, infrared (IR), Visible-induced infrared luminescence (VIL), Visible-induced ultraviolet luminescence (UVL) and ultraviolet reflected (UVR)}, along with portable x-ray fluorescence in order to map and identify the pigments as well as to provide a deeper understanding of the painting techniques. Moreover; the authors were significantly interested in the identification of wood species. Multispectral imaging acquired in 3 spectral bands, ultraviolet (360-400 nm), visible (400-780 nm) and infrared (780-1100 nm) using (UV Ultraviolet-induced luminescence (UVL), UV Reflected (UVR), Visible (VIS), Visible-induced infrared luminescence (VIL) and Infrared photography. False color images are made by digitally editing the VIS with IR or UV images using Adobe Photoshop. Optical Microscopy (OM), potable X-ray fluorescence spectroscopy (p-XRF) and Fourier Transform Infrared Spectroscopy (FTIR) were used in this study. Mapping and imaging techniques provided useful information about the spatial distribution of pigments, in particular visible-induced luminescence (VIL) which allowed the spatial distribution of Egyptian blue pigment to be mapped and every region containing Egyptian blue, even down to single crystals in some instances, is clearly visible as a bright white area; however complete characterization of the pigments requires the use of p. XRF spectroscopy. Based on the elemental analysis found by P.XRF, we conclude that the artists used mixtures of the basic mineral pigments to achieve a wider palette of hues. Identification of wood species Microscopic identification indicated that the wood used was Sycamore Fig (Ficus sycomorus L.) which is recorded as being native to Egypt and was used to make wooden artifacts since at least the Fifth Dynasty.

Keywords: polychrome wooden stele, multispectral imaging, IR luminescence, Wood identification, Sycamore Fig, p-XRF

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6860 Comparing Russian and American Students’ Metaphorical Competence

Authors: Svetlana L. Mishlanova, Evgeniia V. Ermakova, Mariia E. Timirkina

Abstract:

The paper is concerned with the study of metaphor production in essays written by Russian and English native speakers in the framework of cognitive metaphor theory. It considers metaphorical competence as individual’s ability to recognize, understand and use metaphors in speech. The work analyzes the influence of visual metaphor on production and density of conventional and novel verbal metaphors. The main methods of research include experiment connected with image interpretation, metaphor identification procedure (MIPVU) and visual conventional metaphors identification procedure proposed by VisMet group. The research findings will be used in the project aimed at comparing metaphorical competence of native and non-native English speakers.

Keywords: metaphor, metaphorical competence, conventional, novel

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6859 Impact of Water Storage Structures on Groundwater Recharge in Jeloula Basin, Central Tunisia

Authors: I. Farid, K. Zouari

Abstract:

An attempt has been made to examine the effect of water storage structures on groundwater recharge in a semi-arid agroclimatic setting in Jeloula Basin (Central Tunisia). In this area, surface water in rivers is seasonal, and therefore groundwater is the perennial source of water supply for domestic and agricultural purposes. Three pumped storage water power plants (PSWPP) have been built to increase the overall water availability in the basin and support agricultural livelihoods of rural smallholders. The scale and geographical dispersion of these multiple lakes restrict the understanding of these coupled human-water systems and the identification of adequate strategies to support riparian farmers. In the present review, hydrochemistry and isotopic tools were combined to get an insight into the processes controlling mineralization and recharge conditions in the investigated aquifer system. This study showed a slight increase in the groundwater level, especially after the artificial recharge operations and a decline when the water volume moves down during drought periods. Chemical data indicate that the main sources of salinity in the waters are related to water-rock interactions. Data inferred from stable isotopes in groundwater samples indicated recharge with modern rainfall. The investigated surface water samples collected from the PSWPP are affected by a significant evaporation and reveal large seasonal variations, which could be controlled by the water volume changes in the open surface reservoirs and the meteorological conditions during evaporation, condensation, and precipitation. The geochemical information is comparable to the isotopic results and illustrates that the chemical and isotopic signatures of reservoir waters differ clearly from those of groundwaters. These data confirm that the contribution of the artificial recharge operations from the PSWPP is very limited.

Keywords: Jeloula basin, recharge, hydrochemistry, isotopes

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6858 Human Factors Integration of Chemical, Biological, Radiological and Nuclear Response: Systems and Technologies

Authors: Graham Hancox, Saydia Razak, Sue Hignett, Jo Barnes, Jyri Silmari, Florian Kading

Abstract:

In the event of a Chemical, Biological, Radiological and Nuclear (CBRN) incident rapidly gaining, situational awareness is of paramount importance and advanced technologies have an important role to play in improving detection, identification, monitoring (DIM) and patient tracking. Understanding how these advanced technologies can fit into current response systems is essential to ensure they are optimally designed, usable and meet end-users’ needs. For this reason, Human Factors (Ergonomics) methods have been used within an EU Horizon 2020 project (TOXI-Triage) to firstly describe (map) the hierarchical structure in a CBRN response with adapted Accident Map (AcciMap) methodology. Secondly, Hierarchical Task Analysis (HTA) has been used to describe and review the sequence of steps (sub-tasks) in a CBRN scenario response as a task system. HTA methodology was then used to map one advanced technology, ‘Tag and Trace’, which tags an element (people, sample and equipment) with a Near Field Communication (NFC) chip in the Hot Zone to allow tracing of (monitoring), for example casualty progress through the response. This HTA mapping of the Tag and Trace system showed how the provider envisaged the technology being used, allowing for review and fit with the current CBRN response systems. These methodologies have been found to be very effective in promoting and supporting a dialogue between end-users and technology providers. The Human Factors methods have given clear diagrammatic (visual) representations of how providers see their technology being used and how end users would actually use it in the field; allowing for a more user centered approach to the design process. For CBRN events usability is critical as sub-optimum design of technology could add to a responders’ workload in what is already a chaotic, ambiguous and safety critical environment.

Keywords: AcciMap, CBRN, ergonomics, hierarchical task analysis, human factors

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6857 Analyzing Concrete Structures by Using Laser Induced Breakdown Spectroscopy

Authors: Nina Sankat, Gerd Wilsch, Cassian Gottlieb, Steven Millar, Tobias Guenther

Abstract:

Laser-Induced Breakdown Spectroscopy (LIBS) is a combination of laser ablation and optical emission spectroscopy, which in principle can simultaneously analyze all elements on the periodic table. Materials can be analyzed in terms of chemical composition in a two-dimensional, time efficient and minor destructive manner. These advantages predestine LIBS as a monitoring technique in the field of civil engineering. The decreasing service life of concrete infrastructures is a continuously growing problematic. A variety of intruding, harmful substances can damage the reinforcement or the concrete itself. To insure a sufficient service life a regular monitoring of the structure is necessary. LIBS offers many applications to accomplish a successful examination of the conditions of concrete structures. A selection of those applications are the 2D-evaluation of chlorine-, sodium- and sulfur-concentration, the identification of carbonation depths and the representation of the heterogeneity of concrete. LIBS obtains this information by using a pulsed laser with a short pulse length (some mJ), which is focused on the surfaces of the analyzed specimen, for this only an optical access is needed. Because of the high power density (some GW/cm²) a minimal amount of material is vaporized and transformed into a plasma. This plasma emits light depending on the chemical composition of the vaporized material. By analyzing the emitted light, information for every measurement point is gained. The chemical composition of the scanned area is visualized in a 2D-map with spatial resolutions up to 0.1 mm x 0.1 mm. Those 2D-maps can be converted into classic depth profiles, as typically seen for the results of chloride concentration provided by chemical analysis like potentiometric titration. However, the 2D-visualization offers many advantages like illustrating chlorine carrying cracks, direct imaging of the carbonation depth and in general allowing the separation of the aggregates from the cement paste. By calibrating the LIBS-System, not only qualitative but quantitative results can be obtained. Those quantitative results can also be based on the cement paste, while excluding the aggregates. An additional advantage of LIBS is its mobility. By using the mobile system, located at BAM, onsite measurements are feasible. The mobile LIBS-system was already used to obtain chloride, sodium and sulfur concentrations onsite of parking decks, bridges and sewage treatment plants even under hard conditions like ongoing construction work or rough weather. All those prospects make LIBS a promising method to secure the integrity of infrastructures in a sustainable manner.

Keywords: concrete, damage assessment, harmful substances, LIBS

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6856 Chemical Stability of Ceramic Crucibles to Molten Titanium

Authors: Jong-Min Park, Hyung-Ki Park, Seok Hong Min, Tae Kwon Ha

Abstract:

Titanium is widely used due to its high specific strength, good biocompatibility, and excellent corrosion resistance. In order to produce titanium powders, it is necessary to melt titanium, and generally it is conducted by an induction heating method using Al₂O₃ ceramic crucible. However, since titanium reacts chemically with Al₂O₃, it is difficult to melt titanium by the induction heating method using Al₂O₃ crucible. To avoid this problem, we studied the chemical stability of the various crucibles such as Al₂O₃, MgO, ZrO₂, and Y₂O₃ crucibles to molten titanium. After titanium lumps (Grade 2, O(oxygen)<0.25wt%) were placed in each crucible, they were heated to 1800℃ with a heating rate of 5 ℃/min, held at 1800℃ for 30 min, and finally cooled to room temperature with a cooling rate of 5 ℃/min. All heat treatments were carried out in high purity Ar atmosphere. To evaluate the chemical stability, thermodynamic data such as Ellingham diagram were utilized, and also Vickers hardness test, microstructure analysis, and EPMA quantitative analysis were performed. As a result, Al₂O₃, MgO and ZrO₂ crucibles chemically reacted with molten titanium, but Y₂O₃ crucible rarely reacted with it.

Keywords: titanium, induction melting, crucible, chemical stability

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6855 The Marker Active Compound Identification of Calotropis gigantea Roots Extract as an Anticancer

Authors: Roihatul Mutiah, Sukardiman, Aty Widyawaruyanti

Abstract:

Calotropis gigantiea (L.) R. Br (Apocynaceae) commonly called as “Biduri” or “giant milk weed” is a well-known weed to many cultures for treating various disorders. Several studies reported that C.gigantea roots has anticancer activity. The main aim of this research was to isolate and identify an active marker compound of C.gigantea roots for quality control purpose of its extract in the development as anticancer natural product. The isolation methods was bioactivity guided column chromatography, TLC, and HPLC. Evaluated anticancer activity of there substances using MTT assay methods. Identification structure active compound by UV, 1HNMR, 13CNMR, HMBC, HMQC spectral and other references. The result showed that the marker active compound was identical as Calotropin.

Keywords: calotropin, Calotropis gigantea, anticancer, marker active

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6854 Optical Characterization of Lead Sulphide Thin Films Grown by Chemical Bath Deposition

Authors: Ekpekpo Arthur

Abstract:

Thin films can either be conductive or dielectric (non-conductive). It is formed through atom/molecules state or formed after decomposing the materials into atomic/molecular scale by physical or chemical processes. In this study, thin films of Lead Sulphide were deposited on glass substrate prepared from lead acetate and thiourea solution using chemical bath deposition (CBD). The glass slides were subjected to the pretreatment by soaking them in a solution of 50% sulphuric acid and 50% nitric acid. Lead sulphide was deposited at different parameters such as deposition time and temperature. The optical properties of the thin films were determined from spectroscopy measurements of absorbance and reflectance. Optical studies show that the band gap of lead sulphide ranges between 0.41 eV to 300K.

Keywords: lead sulphide, spectroscopy, absorbance, reflectance

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6853 Hydro-Chemical Characterization of Glacial Melt Waters Draining from Shaune Garang Glacier, Himachal Himalaya

Authors: Ramesh Kumar, Rajesh Kumar, Shaktiman Singh, Atar Singh, Anshuman Bhardwaj, Ravindra Kumar Sinha, Anupma Kumari

Abstract:

A detailed study of the ion chemistry of the Shaune Garnag glacier meltwater has been carried out to assess the role of active glacier in the chemical denudation rate. The chemical compositions of various ions in meltwater of the Shaune Garang glacier were analyzed during the melting period 2015 and 2016. Total 112 of melt water samples twice in a day were collected during ablation season of 2015 and 2016. To identify various factors controlling the dissolved ionic strength of Shaune Garang Glacier meltwater statistical analysis such as correlation matrix, Principle Component Analysis (PCA) and factor analysis were applied to deduce the result. Cation concentration for Ca²⁺ > Mg²⁺ > Na⁺ > K⁺ in the meltwater for both the years can be arranged in the order as Ca²⁺ > Mg²⁺ > Na⁺ > K⁺. Study showed that Ca²⁺ and HCO₃⁻ found to be dominant on the both melting period. Carbonate weathering identified as the dominant process controlling the dissolved ion chemistry of meltwater due to the high ratios of (Ca²⁺ + Mg²⁺) versus TZ+ and (Ca²⁺ + Mg²⁺) versus (Na⁺ + K⁺) in the study area. The cation denudation rate of the Shaune Garnag catchment is 3412.2 m⁻² a⁻¹, i.e. higher than the other glacierised catchment in the Himalaya, indicating intense chemical erosion in this catchment.

Keywords: Shaune Garang glacier, Hydrochemistry, chemical composition, cation denudation rate, carbonate weathering

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6852 Hydrogen Production from Solid Waste of Sago Processing Industries in Indonesia: Effect of Chemical and Biological Pretreatment

Authors: Pratikno Hidayat, Khamdan Cahyari

Abstract:

Hydrogen is the ultimate choice of energy carriers in future. It contents high energy density (42 kJ/g), emits only water vapor during combustion and has high energy conversion up to 50% in fuel cell application. One of the promising methods to produce hydrogen is from organic waste through dark fermentation method. It utilizes sugar-rich organic waste as substrate and hydrogen-producing microorganisms to generate the hydrogen. Solid waste of sago processing industries in Indonesia is one of the promising raw materials for both producing biofuel hydrogen and mitigating the environmental impact due to the waste disposal. This research was meant to investigate the effect of chemical and biological pretreatment i.e. acid treatment and mushroom cultivation toward lignocellulosic waste of these sago industries. Chemical pretreatment was conducted through exposing the waste into acid condition using sulfuric acid (H2SO4) (various molar i.e. 0.2, 0.3, and 0.4 M and various duration of exposure i.e. 30, 60 and 90 minutes). Meanwhile, biological treatment was conducted through utilization of the solid waste as growth media of mushroom (Oyster and Ling-zhi) for 3 months. Dark fermentation was conducted at pH 5.0, temperature 27℃ and atmospheric pressure. It was noticed that chemical and biological pretreatment could improve hydrogen yield with the highest yield at 3.8 ml/g VS (31%v H2). The hydrogen production was successfully performed to generate high percentage of hydrogen, although the yield was still low. This result indicated that the explosion of acid chemical and biological method might need to be extended to improve degradability of the solid waste. However, high percentage of hydrogen was resulted from proper pretreatment of residual sludge of biogas plant to generate hydrogen-producing inoculum.

Keywords: hydrogen, sago waste, chemical, biological, dark fermentation, Indonesia

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6851 Natural and Construction/Demolition Waste Aggregates: A Comparative Study

Authors: Debora C. Mendes, Matthias Eckert, Claudia S. Moço, Helio Martins, Jean-Pierre Gonçalves, Miguel Oliveira, Jose P. Da Silva

Abstract:

Disposal of construction and demolition waste (C&DW) in embankments in the periphery of cities causes both environmental and social problems. To achieve the management of C&DW, a detailed analysis of the properties of these materials should be done. In this work we report a comparative study of the physical, chemical and environmental properties of natural and C&DW aggregates from 25 different origins. Assays were performed according to European Standards. Analysis of heavy metals and organic compounds, namely polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs), were performed. Finally, properties of concrete prepared with C&DW aggregates are reported. Physical analyses of C&DW aggregates indicated lower quality properties than natural aggregates, particularly for concrete preparation and unbound layers of road pavements. Chemical properties showed that most samples (80%) meet the values required by European regulations for concrete and unbound layers of road pavements. Analyses of heavy metals Cd, Cr, Cu, Pb, Ni, Mo and Zn in the C&DW leachates showed levels below the limits established by the Council Decision of 19 December 2002. Identification and quantification of PCBs and PAHs indicated that few samples shows the presence of these compounds. The measured levels of PCBs and PAHs are also below the limits. Other compounds identified in the C&DW leachates include phthalates and diphenylmethanol. The characterized C&DW aggregates show lower quality properties than natural aggregates but most samples showed to be environmentally safe. A continuous monitoring of the presence of heavy metals and organic compounds should be made to trial safe C&DW aggregates. C&DW aggregates provide a good economic and environmental alternative to natural aggregates.

Keywords: concrete preparation, construction and demolition waste, heavy metals, organic pollutants

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6850 Fault Location Identification in High Voltage Transmission Lines

Authors: Khaled M. El Naggar

Abstract:

This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.

Keywords: optimization, estimation, faults, measurement, high voltage, simulated annealing

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6849 Mid-Temperature Methane-Based Chemical Looping Reforming for Hydrogen Production via Iron-Based Oxygen Carrier Particles

Authors: Yang Li, Mingkai Liu, Qiong Rao, Zhongrui Gai, Ying Pan, Hongguang Jin

Abstract:

Hydrogen is an ideal and potential energy carrier due to its high energy efficiency and low pollution. An alternative and promising approach to hydrogen generation is the chemical looping steam reforming of methane (CL-SRM) over iron-based oxygen carriers. However, the process faces challenges such as high reaction temperature (>850 ℃) and low methane conversion. We demonstrate that Ni-mixed Fe-based oxygen carrier particles have significantly improved the methane conversion and hydrogen production rate in the range of 450-600 ℃ under atmospheric pressure. The effect on the reaction reactivity of oxygen carrier particles mixed with different Ni-based particle mass ratios has been determined in the continuous unit. More than 85% of methane conversion has been achieved at 600 ℃, and hydrogen can be produced in both reduction and oxidation steps. Moreover, the iron-based oxygen carrier particles exhibited good cyclic performance during 150 consecutive redox cycles at 600 ℃. The mid-temperature iron-based oxygen carrier particles, integrated with a moving-bed chemical looping system, might provide a powerful approach toward more efficient and scalable hydrogen production.

Keywords: chemical looping, hydrogen production, mid-temperature, oxygen carrier particles

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6848 Agriculture Water Quality Evaluation in Minig Basin

Authors: Ben Salah Nahla

Abstract:

The problem of water in Tunisia affects the quality and quantity. Tunisia is in a situation of water shortage. It was estimated that 4.6 Mm3/an. Moreover, the quality of water in Tunisia is also mediocre. In fact, 50% of the water has a high salinity (> 1.5g/l). There are several parameters which affect water quality such as sodium, fluoride. An excess of this parameter may induce some human health. Furthermore, the mining basin area has a problem of industrial waste. This problem may affect the water quality of the groundwater. Therefore, the purpose of this work is to assess the water quality in Basin Mining and the impact of fluorine. For this research, some water samples were done in the field and specific water analysis was implemented in the laboratory. Sampling is carried out on eight drilling in the area of the mining region. In the following, we will look at water view composition, physical and chemical quality. A physical-chemical analysis of water from a survey of the Mining area of Tunisia was performed and showed an excess for the following items: fluorine, sodium, sulfate. So many chemicals may be present in water. However, only a small number of them immediately concern in terms of health in all circumstances. Fluorine (F) is one particular chemical that is considered both necessary for the human body, but an excess of the rate of this chemical causes serious diseases. Sodium fluoride and sodium silicofluoride are more soluble and may spread in animals and plants where their toxicity largest organizations. The more complex particles such as cryolite and fluorite, almost insoluble, are more stable and less toxic. Thereafter, we will study the problem of excess fluorine in the water. The latter intended for human consumption must always comply with the limits for microbiological quality parameters and physical-chemical parameters defined by European standards (1.5 mg/l) and Tunisian (2 mg/l).

Keywords: water, minier basin, fluorine, silicofluoride

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6847 Safeners, Tools for Artificial Manipulation of Herbicide Selectivity: A Zea mays Case Study

Authors: Sara Franco Ortega, Alina Goldberg Cavalleri, Nawaporn Onkokesung, Richard Dale, Melissa Brazier-Hicks, Robert Edwards

Abstract:

Safeners are agrochemicals that enhance the selective chemical control of wild grasses by increasing the ability of the crop to metabolise the herbicide. Although these compounds are widely used, their mode of action is not well understood. It is known that safeners enhance the metabolism of herbicides, by up-regulating the associated detoxification system we have termed the xenome. The xenome proteins involved in herbicide metabolism have been previously divided into four different phases, with cytochrome P450s (CYPs) playing a key role in phase I metabolism by catalysing hydroxylation and dealkylation reactions. Subsequently, glutathione S-transferases (GSTs) and UDP-glucosyltransferases lead to the formation of Phase II conjugates prior to their transport into the vacuole by ABCs transporters (Phase III). Maize (Zea mays), was been treated with different safeners to explore the selective induction of xenome proteins, with a special interest in the regulation of the CYP superfamily. Transcriptome analysis enabled the identification of key safener-inducible CYPs that were then functionally assessed to determine their role in herbicide detoxification. In order to do that, CYP’s were codon optimised, synthesised and inserted into the yeast expression vector pYES3 using in-fusion cloning. CYP’s expressed as recombinant proteins in a strain of yeast engineered to contain the P450 co-enzyme (cytochrome P450 reductase) from Arabidopsis. Microsomes were extracted and treated with herbicides of different chemical classes in the presence of the cofactor NADPH. The reaction products were then analysed by LCMS to identify any herbicide metabolites. The results of these studies will be presented with the key CYPs identified in maize used as the starting point to find orthologs in other crops and weeds to better understand their roles in herbicide selectivity and safening.

Keywords: CYPs, herbicide detoxification, LCMS, RNA-Seq, safeners

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6846 Identification of Wiener Model Using Iterative Schemes

Authors: Vikram Saini, Lillie Dewan

Abstract:

This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

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6845 A Convolutional Neural Network Based Vehicle Theft Detection, Location, and Reporting System

Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

Abstract:

One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

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6844 Assessment of the Physical and Chemical Characteristics of Ugbogui River, Edo State, Nigeria

Authors: Iyagbaye O. Rich, Omoigberale O. Michael, Iyagbaye A. Louis

Abstract:

The physical, chemical parameters and some trace contents of Ugbogui in Edo State, Nigeria were investigated from August 2015 to April 2016. Four stations were studied from upstream to downstream using standard methods. A total of thirty-three (33) physical and chemical characteristics and trace metal contents were examined; Air and water temperatures, depth, transparency, colour, turbidity, flow velocity, pH, total alkalinity, conductivity and dissolved solids etc. Other includes dissolved oxygen, oxygen saturation, biochemical oxygen demand, chloride, phosphate, sodium, nitrate, sulphate, potassium, calcium, magnesium, iron, lead, copper, zinc, nickel, cadmium, vanadium and chromium. Eleven (11) parameters exhibited clear seasonal variations. However, there were high significant differences (p < 0.01) in the values of depth, colour, total suspended solid, biochemical oxygen demand, chemical oxygen demand, chloride, bicarbonate, phosphate, sulphate, iron, manganese, zinc, copper, chromium and cadmium among the stations. The anthropogenic activities had negatively impacted at station 3 of the river, although most of the recorded values were still within permissible limits.

Keywords: anthropogenic activities, Nigeria, permissible limits, physical and chemical parameters, trace metal, water quality

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6843 Measuring Multi-Class Linear Classifier for Image Classification

Authors: Fatma Susilawati Mohamad, Azizah Abdul Manaf, Fadhillah Ahmad, Zarina Mohamad, Wan Suryani Wan Awang

Abstract:

A simple and robust multi-class linear classifier is proposed and implemented. For a pair of classes of the linear boundary, a collection of segments of hyper planes created as perpendicular bisectors of line segments linking centroids of the classes or part of classes. Nearest Neighbor and Linear Discriminant Analysis are compared in the experiments to see the performances of each classifier in discriminating ripeness of oil palm. This paper proposes a multi-class linear classifier using Linear Discriminant Analysis (LDA) for image identification. Result proves that LDA is well capable in separating multi-class features for ripeness identification.

Keywords: multi-class, linear classifier, nearest neighbor, linear discriminant analysis

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6842 Using Structural Equation Modeling to Analyze the Impact of Remote Work on Job Satisfaction

Authors: Florian Pfeffel, Valentin Nickolai, Christian Louis Kühner

Abstract:

Digitalization has disrupted the traditional workplace environment by allowing many employees to work from anywhere at any time. This trend of working from home was further accelerated due to the COVID-19 crisis, which forced companies to rethink their workplace models. While in many companies, this shift happened out of pure necessity; many employees were left more satisfied with their job due to the opportunity to work from home. This study focuses on employees’ job satisfaction in the service sector in dependence on the different work models, which are defined as a “work from home” model, the traditional “work in office” model, and a hybrid model. Using structural equation modeling (SEM), these three work models have been analyzed based on 13 influencing factors on job satisfaction that have been further summarized in the three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, a survey has been conducted with n = 684 employees in the service sector. Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. Additionally, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that employees who work entirely remotely or have a hybrid work model are significantly more satisfied with their job, with a job satisfaction score of 5.0 respectively on a scale from 1 (very dissatisfied) to 7 (very satisfied), than employees do not have the option to work from home with a score of 4.6. This comes as a result of the lower identification with the work in the model without any remote working. Furthermore, the responses indicate that it is important to consider the individual preferences of each employee when it comes to the work model to achieve overall higher job satisfaction. Thus, it can be argued that companies can profit off of more motivation and higher productivity by considering the individual work model preferences, therefore, increasing the identification with the respective work.

Keywords: home-office, identification with work, job satisfaction, new work, remote work, structural equation modeling

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6841 The Impact of the Number of Neurons in the Hidden Layer on the Performance of MLP Neural Network: Application to the Fast Identification of Toxics Gases

Authors: Slimane Ouhmad, Abdellah Halimi

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In this work, we have applied neural networks method MLP type to a database from an array of six sensors for the detection of three toxic gases. As the choice of the number of hidden layers and the weight values has a great influence on the convergence of the learning algorithm, we proposed, in this article, a mathematical formulation to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases on the one hand, and optimize the computation time on the other hand, the comparison to other results achieved in this case.

Keywords: MLP Neural Network, back-propagation, number of neurons in the hidden layer, identification, computing time

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6840 Development of Partial Discharge Defect Recognition and Status Diagnosis System with Adaptive Deep Learning

Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

Abstract:

This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

Procedia PDF Downloads 78
6839 Multimodal Employee Attendance Management System

Authors: Khaled Mohammed

Abstract:

This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

Procedia PDF Downloads 155
6838 Chemical Modification of Jute Fibers with Oxidative Agents for Usability as Reinforcement in Polymeric Composites

Authors: Yasemin Seki, Aysun Akşit

Abstract:

The goal of this research is to modify the surface characterization of jute yarns with different chemical agents to improve the compatibility with a non-polar polymer, polypropylene, when used as reinforcement. A literature review provided no knowledge on surface treatment of jute fibers with sodium perborate trihydrate. This study also aims to compare the efficiency of sodium perborate trihydrate on jute fiber treatment with other commonly used chemical agents. Accordingly, jute yarns were treated with 0.02% potassium dichromate (PD), potassium permanganate (PM) and sodium perborate trihydrate (SP) aqueous solutions in order to enhance interfacial compatibility with polypropylene in this study. The effect of treatments on surface topography, surface chemistry and interfacial shear strength of jute yarns with polypropylene were investigated. XPS results revealed that surface treatments enhanced surface hydrophobicity by increasing C/O ratios of fiber surface. Surface roughness values increased with the treatments. The highest interfacial adhesion with polypropylene was achieved after SP treatment by providing the highest surface roughness values and hydrophobic character of jute fiber.

Keywords: jute, chemical modification, sodium perborate, polypropylene

Procedia PDF Downloads 508
6837 Characteristic Matrix Faults for Flight Control System

Authors: Thanh Nga Thai

Abstract:

A major issue in air transportation is in flight safety. Recent developments in control engineering have an attractive potential for resolving new issues related to guidance, navigation, and control of flying vehicles. Many future atmospheric missions will require increased on board autonomy including fault diagnosis and the subsequent control and guidance recovery actions. To improve designing system diagnostic, an efficient FDI- fault detection and identification- methodology is necessary to achieve. Contribute to characteristic of different faults in sensor and actuator in the view of mathematics brings a lot of profit in some condition changes in the system. This research finds some profit to reduce a trade-off to achieve between fault detection and performance of the closed loop system and cost and calculated in simulation.

Keywords: fault detection and identification, sensor faults, actuator faults, flight control system

Procedia PDF Downloads 422
6836 Re-identification Risk and Mitigation in Federated Learning: Human Activity Recognition Use Case

Authors: Besma Khalfoun

Abstract:

In many current Human Activity Recognition (HAR) applications, users' data is frequently shared and centrally stored by third parties, posing a significant privacy risk. This practice makes these entities attractive targets for extracting sensitive information about users, including their identity, health status, and location, thereby directly violating users' privacy. To tackle the issue of centralized data storage, a relatively recent paradigm known as federated learning has emerged. In this approach, users' raw data remains on their smartphones, where they train the HAR model locally. However, users still share updates of their local models originating from raw data. These updates are vulnerable to several attacks designed to extract sensitive information, such as determining whether a data sample is used in the training process, recovering the training data with inversion attacks, or inferring a specific attribute or property from the training data. In this paper, we first introduce PUR-Attack, a parameter-based user re-identification attack developed for HAR applications within a federated learning setting. It involves associating anonymous model updates (i.e., local models' weights or parameters) with the originating user's identity using background knowledge. PUR-Attack relies on a simple yet effective machine learning classifier and produces promising results. Specifically, we have found that by considering the weights of a given layer in a HAR model, we can uniquely re-identify users with an attack success rate of almost 100%. This result holds when considering a small attack training set and various data splitting strategies in the HAR model training. Thus, it is crucial to investigate protection methods to mitigate this privacy threat. Along this path, we propose SAFER, a privacy-preserving mechanism based on adaptive local differential privacy. Before sharing the model updates with the FL server, SAFER adds the optimal noise based on the re-identification risk assessment. Our approach can achieve a promising tradeoff between privacy, in terms of reducing re-identification risk, and utility, in terms of maintaining acceptable accuracy for the HAR model.

Keywords: federated learning, privacy risk assessment, re-identification risk, privacy preserving mechanisms, local differential privacy, human activity recognition

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6835 Modelling and Simulation of Biomass Pyrolysis

Authors: P. Ahuja, K. S. S. Sai Krishna

Abstract:

There is a concern over the energy shortage in the modern societies as it is one of the primary necessities. Renewable energy, mainly biomass, is found to be one feasible solution as it is inexhaustible and clean energy source all over the world. Out of various methods, thermo chemical conversion is considered to be the most common and convenient method to extract energy from biomass. The thermo-chemical methods that are employed are gasification, liquefaction and combustion. On gasification biomass yields biogas, on liquefaction biomass yields bio-oil and on combustion biomass yields bio-char. Any attempt to biomass gasification, liquefaction or combustion calls for a good understanding of biomass pyrolysis. So, Irrespective of the method used the first step towards the thermo-chemical treatment of biomass is pyrolysis. Pyrolysis mainly converts the solid mass into liquid with gas and residual char as the byproducts. Liquid is used for the production of heat, power and many other chemicals whereas the gas and char can be used as fuels to generate heat.

Keywords: biomass, fluidisation, pyrolysis, simulation

Procedia PDF Downloads 342
6834 Impact of Chemical Flooding on Displacement Efficiency in Shallow Carbonate Marine Reservoir (Case Study)

Authors: Tarek Duzan, Walid Eddib

Abstract:

The marine shallow carbonate reservoir (G- Eocene) is one of the biggest mature water drive reservoir of Waha Oil Company. The cumulative oil produced up to date is about to eighty percent of the booked original oil in place at ninety five percent of Water cut. However, the company believes that there is a good amount of remaining oil left need to be recovered. Many laboratory studies have been conducted to see the possibility drain the commercial oil left behind using two types of gases, namely, carbone dioxide and enriched hydrocarbon gas injection. The conclusions of those cases were inconclusive Technically and Economically. Therefore, the company has decided to verify another Tertiary Recovery (EOR) technique that may be applied to the interested reservoir. A global screening criteria and quick Laboratory chemical tests have been conducted by using many types of chemical injection into real rock samples. The outcomes were unique economically and provide a significant increase in the commercial oil left. Finally, the company has started conducting a sector pilot plan before proceeding with a full plan. There are many wellbores available to use in a potential field Enhanced Oil Recovery.

Keywords: chemical lab. test, ASP, rock types, oil samples, and global screening criteria

Procedia PDF Downloads 138
6833 Stress Corrosion Crack Identification with Direct Assessment Method in Pipeline Downstream from a Compressor Station

Authors: H. Gholami, M. Jalali Azizpour

Abstract:

Stress Corrosion Crack (SCC) in pipeline is a type of environmentally assisted cracking (EAC), since its discovery in 1965 as a possible cause of failure in pipeline, SCC has caused, on average, one of two failures per year in the U.S, According to the NACE SCC DA a pipe line segment is considered susceptible to SCC if all of the following factors are met: The operating stress exceeds 60% of specified minimum yield strength (SMYS), the operating temperature exceeds 38°C, the segment is less than 32 km downstream from a compressor station, the age of the pipeline is greater than 10 years and the coating type is other than Fusion Bonded Epoxy(FBE). In this paper as a practical experience in NISOC, Direct Assessment (DA) Method is used for identification SCC defect in unpiggable pipeline located downstream of compressor station.

Keywords: stress corrosion crack, direct assessment, disbondment, transgranular SCC, compressor station

Procedia PDF Downloads 386