Search results for: electrical network frequency stability

Authors: Priyanka Agrawal, Janou Koskamp, Amir Raoof, Mariette Wolthers

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Calcite is the main mineral found in carbonate rocks, which form significant hydrocarbon reservoirs and subsurface repositories for CO2 sequestration. The injected CO2 mixes with the reservoir fluid and disturbs the geochemical equilibrium, triggering calcite dissolution. Different combinations of fluid chemistry and injection rate may therefore result in different evolution of porosity, permeability and dissolution patterns. To model the changes in porosity and permeability Kozeny-Carman equation K∝〖(∅)〗^n is used, where K is permeability and ∅ is porosity. The value of n is mostly based on experimental data or pore network models. In pore network models, this derivation is based on accuracy of relation used for conductivity and pore volume change. In fact, at a single pore scale, this relationship is the result of the pore shape development due to dissolution. We have prepared a new reactive transport model for a single pore which simulates the complex chemical reaction of carbonic-acid induced calcite dissolution and subsequent pore-geometry evolution at a single pore scale. We use COMSOL Multiphysics package 5.3 for the simulation. COMSOL utilizes the arbitary-Lagrangian Eulerian (ALE) method for the free-moving domain boundary. We examined the effect of flow rate on the evolution of single pore shape profiles due to calcite dissolution. We used three flow rates to cover diffusion dominated and advection-dominated transport regimes. The fluid in diffusion dominated flow (Pe number 0.037 and 0.37) becomes less reactive along the pore length and thus produced non-uniform pore shapes. However, for the advection-dominated flow (Pe number 3.75), the fast velocity of the fluid keeps the fluid relatively more reactive towards the end of the pore length, thus yielding uniform pore shape. Different pore shapes in terms of inlet opening vs overall pore opening will have an impact on the relation between changing volumes and conductivity. We have related the shape of pore with the Pe number which controls the transport regimes. For every Pe number, we have derived the relation between conductivity and porosity. These relations will be used in the pore network model to get the porosity and permeability variation.

Keywords: single pore, reactive transport, calcite system, moving boundary

Procedia PDF Downloads 361

Authors: F.I. Adeosun, A.A. Idowu, D.O. Odulate,

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The aims of carrying out this experiment were to determine the water quality and to investigate if the various human and ecological activities around the river have any effect on the physico-chemical parameters of the river’s resources with a view to effectively utilizing these resources. Water samples were collected from two stations on the surface water of Lower Ogun River Akomoje biweekly for a period of 5 months (January to May, 2011). Results showed that temperature ranged between 24.0-30.7oC, transparency (0.53-1.00 m), depth (1.0-3.88 m), alkalinity (4.5-14.5 mg/l), nitrates (0.235-5.445 mg/l), electrical conductivity (140-190µS/cm), dissolved oxygen (4.12-5.32 mg/l), phosphates (0.02 mg/l-0.7 5 mg/l) and total dissolved solids (70-95).The parameters at the deep end (station A) accounted for the bulk of the highest values; there was however no significant differences between the stations at P˂0.05 with the exception of transparency, depth, total dissolved solids and electrical conductivity. The phosphate value was relatively low which accounted for the low productivity and high transparency. The results obtained from the physico-chemical parameters agreed with the limits set by both national and international bodies for drinking and fish growth. It was however observed that during the period of data collection, catch was low and this could be attributed to low level of primary productivity due to the quality of physico-chemical parameters of the water. It is recommended that the agencies involved in the management of the river should put the right policies in place that will effectively enhance proper exploitation of the water resources. More research should also be carried out on the physico-chemical parameters since this work only studied the water for five months.

Keywords: physical, chemical, parameters, water quality, Ogunriver

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Authors: Maher Z. Mohammed, Barry G. Clarke

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As an alternative to stone column in fine grained soils, it is possible to create stiffened columns of soils using electroosmosis (electroosmotic piles). This program of this research is to establish the effectiveness and efficiency of the process in different soils. The aim of this study is to assess the capability of electroosmosis treatment in a range of composite soils. The combined electroosmotic and preloading equipment developed by Nizar and Clarke (2013) was used with an octagonal array of anodes surrounding a single cathode in a nominal 250mm diameter 300mm deep cylinder of soil and 80mm anode to cathode distance. Copper coiled springs were used as electrodes to allow the soil to consolidate either due to an external vertical applied load or electroosmosis. The equipment was modified to allow the temperature to be monitored during the test. Electroosmotic tests were performed on China Clay Grade E kaolin and calcium bentonite (Bentonex CB) mixed with sand fraction C (BS 1881 part 131) at different ratios by weight; (0, 23, 33, 50 and 67%) subjected to applied voltages (5, 10, 15 and 20). The soil slurry was prepared by mixing the dry soil with water to 1.5 times the liquid limit of the soil mixture. The mineralogical and geotechnical properties of the tested soils were measured before the electroosmosis treatment began. In the electroosmosis cell tests, the settlement, expelled water, variation of electrical current and applied voltage, and the generated heat was monitored during the test time for 24 osmotic tests. Water content was measured at the end of each test. The electroosmotic tests are divided into three phases. In Phase 1, 15 kPa was applied to simulate a working platform and produce a uniform soil which had been deposited as a slurry. 50 kPa was used in Phase 3 to simulate a surcharge load. The electroosmotic treatment was only performed during Phase 2 where a constant voltage was applied through the electrodes in addition to the 15 kPa pressure. This phase was stopped when no further water was expelled from the cell, indicating the electroosmotic process had stopped due to either the degradation of the anode or the flow due to the hydraulic gradient exactly balanced the electroosmotic flow resulting in no flow. Control tests for each soil mixture were carried out to assess the behaviour of the soil samples subjected to only an increase of vertical pressure, which is 15kPa in Phase 1 and 50kPa in Phase 3. Analysis of the experimental results from this study showed a significant dewatering effect on the soil slurries. The water discharged by the electroosmotic treatment process decreased as the sand content increased. Soil temperature increased significantly when electrical power was applied and drops when applied DC power turned off or when the electrode degraded. The highest increase in temperature was found in pure clays at higher applied voltage after about 8 hours of electroosmosis test.

Keywords: electrokinetic treatment, electrical conductivity, electroosmotic consolidation, electroosmosis permeability ratio

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Authors: Moustafa M. S. Sanad

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The worsening of energy supply crisis and the exacerbation of climate change by environmental pollution problems have become the greatest threat to human life. One of the ways to confront these problems is to rely on renewable energy and its storage systems. Nowadays, huge attention has been directed to the development of lithium-ion batteries (LIBs) as efficient tools for storing the clean energy produced by green sources like solar and wind energies. Accordingly, the demand for powerful electrode materials with excellent electrochemical characteristics has been progressively increased to meet fast and continuous growth in the market of energy storage systems. Therefore, the electronic and electrical properties of conversion anode materials for rechargeable lithium-ion batteries (LIBs) can be enhanced by introducing lattice defects and oxygen vacancies in the crystal structure. In this regard, the intended presentation will demonstrate new insights and effective ways for enhancing the electrical conductivity and improving the electrochemical performance of different anode materials such as MgFe₂O₄, CdFe₂O₄, Fe₃O₄, LiNbO₃ and Nb₂O₅. The changes in the physicochemical and morphological properties have been deeply investigated via structural and spectroscopic analyses (e.g., XRD, FESEM, HRTEM, and XPS). Moreover, the enhancement in the electrochemical properties of these anode materials will be discussed through Galvanostatic Cycling (GC), Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS) techniques.

Keywords: structure modification, cationic substitution, non-stoichiometric synthesis, plasma treatment, lithium-ion batteries

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Authors: F. Yılmaz, Y. Saylan, A. Derazshamshir, S. Atay, A. Denizli

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Quartz crystal microbalance (QCM), high-resolution mass-sensing technique, measures changes in mass on oscillating quartz crystal surface by measuring changes in oscillation frequency of crystal in real time. Protein adsorption techniques via hydrophobic interaction between protein and solid support, called hydrophobic interaction chromatography (HIC), can be favorable in many cases. Some nanoparticles can be effectively applied for HIC. HIC takes advantage of the hydrophobicity of proteins by promoting its separation on the basis of hydrophobic interactions between immobilized hydrophobic ligands and nonpolar regions on the surface of the proteins. Lysozyme is found in a variety of vertebrate cells and secretions, such as spleen, milk, tears, and egg white. Its common applications are as a cell-disrupting agent for extraction of bacterial intracellular products, as an antibacterial agent in ophthalmologic preparations, as a food additive in milk products and as a drug for treatment of ulcers and infections. Lysozyme has also been used in cancer chemotherapy. The aim of this study is the synthesis of hydrophobic nanoparticles for Lysozyme detection. For this purpose, methacryoyl-L-phenylalanine was chosen as a hydrophobic matrix. The hydrophobic nanoparticles were synthesized by micro-emulsion polymerization method. Then, hydrophobic QCM nanosensor was characterized by Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, atomic force microscopy (AFM) and zeta size analysis. Hydrophobic QCM nanosensor was tested for real-time detection of Lysozyme from aqueous solution. The kinetic and affinity studies were determined by using Lysozyme solutions with different concentrations. The responses related to a mass (Δm) and frequency (Δf) shifts were used to evaluate adsorption properties.

Keywords: nanosensor, HIC, lysozyme, QCM

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Authors: Fayad Ghawbar

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The significance of the Multiple Input Multiple Output (MIMO) system in the 5G wireless communication system is essential to enhance channel capacity and provide a high data rate resulting in a need for dual-polarization in vertical and horizontal. Furthermore, size reduction is critical in a MIMO system to deploy more antenna elements requiring a compact, low-profile design. A compact dual-band 4-MIMO antenna system has been presented in this paper with pattern and polarization diversity. The proposed single antenna structure has been designed using two antenna layers with a C shape in the front layer and a partial slot with a U-shaped cut in the ground to enhance isolation. The single antenna is printed on an FR4 dielectric substrate with an overall size of 18 mm×18 mm×1.6 mm. The 4-MIMO antenna elements were printed orthogonally on an FR4 substrate with a size dimension of 36 × 36 × 1.6 mm3 with zero edge-to-edge separation distance. The proposed compact 4-MIMO antenna elements resonate at 3.4-3.6 GHz and 4.8-5 GHz. The s-parameters measurement and simulation results agree, especially in the lower band with a slight frequency shift of the measurement results at the upper band due to fabrication imperfection. The proposed design shows isolation above -15 dB and -22 dB across the 4-MIMO elements. The MIMO diversity performance has been evaluated in terms of efficiency, ECC, DG, TARC, and CCL. The total and radiation efficiency were above 50 % across all parameters in both frequency bands. The ECC values were lower than 0.10, and the DG results were about 9.95 dB in all antenna elements. TARC results exhibited values lower than 0 dB with values lower than -25 dB in all MIMO elements at the dual-bands. Moreover, the channel capacity losses in the MIMO system were depicted using CCL with values lower than 0.4 Bits/s/Hz.

Keywords: compact antennas, MIMO antenna system, 5G communication, dual band, ECC, DG, TARC

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Authors: M. Draman, S. Z. Muhamad Yassin, M. S. Alias, Z. Lambak, M. I. Zulkifli, S. N. Padhi, K. N. Baharim, F. Maskuriy, A. I. A. Rahim

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The performance of Malay automatic speech recognition (ASR) system for the call centre environment is presented. The system utilizes Kaldi toolkit as the platform to the entire library and algorithm used in performing the ASR task. The acoustic model implemented in this system uses a deep neural network (DNN) method to model the acoustic signal and the standard (n-gram) model for language modelling. With 80 hours of training data from the call centre recordings, the ASR system can achieve 72% of accuracy that corresponds to 28% of word error rate (WER). The testing was done using 20 hours of audio data. Despite the implementation of DNN, the system shows a low accuracy owing to the varieties of noises, accent and dialect that typically occurs in Malaysian call centre environment. This significant variation of speakers is reflected by the large standard deviation of the average word error rate (WERav) (i.e., ~ 10%). It is observed that the lowest WER (13.8%) was obtained from recording sample with a standard Malay dialect (central Malaysia) of native speaker as compared to 49% of the sample with the highest WER that contains conversation of the speaker that uses non-standard Malay dialect.

Keywords: conversational speech recognition, deep neural network, Malay language, speech recognition

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Authors: Agnieszka Markowska-Radomska, Ewa Dluska

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Maintaining a bioactive substances dense diet is important for the elderly, especially to prevent diseases and to support healthy ageing. Adequate bioactive substances intake can reduce the risk of developing chronic diseases (e.g. cardiovascular, osteoporosis, neurodegenerative syndromes, diseases of the oral cavity, gastrointestinal (GI) disorders, diabetes, and cancer). This can be achieved by introducing a comprehensive supplementation of components necessary for the proper functioning of the ageing body. The paper proposes the multiple emulsions of the W1/O/W2 (water-in-oil-in-water) type as carriers for effective co-encapsulation and co-delivery of bioactive substances in supplementation of the elderly. Multiple emulsions are complex structured systems ("drops in drops"). The functional structure of the W1/O/W2 emulsion enables (i) incorporation of one or more bioactive components (lipophilic and hydrophilic); (ii) enhancement of stability and bioavailability of encapsulated substances; (iii) prevention of interactions between substances, as well as with the external environment, delivery to a specific location; and (iv) release in a controlled manner. The multiple emulsions were prepared by a one-step method in the Couette-Taylor flow (CTF) contactor in a continuous manner. In general, a two-step emulsification process is used to obtain multiple emulsions. The paper contains a proposal of emulsion functionalization by introducing pH-responsive biopolymer—carboxymethylcellulose sodium salt (CMC-Na) to the external phase, which made it possible to achieve a release of components controlled by the pH of the gastrointestinal environment. The membrane phase of emulsions was soybean oil. The W1/O/W2 emulsions were evaluated for their characteristics (drops size/drop size distribution, volume packing fraction), encapsulation efficiency and stability during storage (to 30 days) at 4ºC and 25ºC. Also, the in vitro multi-substance co-release process were investigated in a simulated gastrointestinal environment (different pH and composition of release medium). Three groups of stable multiple emulsions were obtained: emulsions I with co-encapsulated vitamins B12, B6 and resveratrol; emulsions II with vitamin A and β-carotene; and emulsions III with vitamins C, E and D3. The substances were encapsulated in the appropriate emulsion phases depending on the solubility. For all emulsions, high encapsulation efficience (over 95%) and high volume packing fraction of internal droplets (0.54-0.76) were reached. In addition, due to the presence of a polymer (CMC-Na) with adhesive properties, high encapsulation stability during emulsions storage were achieved. The co-release study of encapsulated bioactive substances confirmed the possibility to modify the release profiles. It was found that the releasing process can be controlled through the composition, structure, physicochemical parameters of emulsions and pH of the release medium. The results showed that the obtained multiple emulsions might be used as potential liquid complex carriers for controlled/modified/site-specific co-delivery of bioactive substances in dietary supplementation in the elderly.

Keywords: bioactive substance co-release, co-encapsulation, elderly supplementation, multiple emulsion

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Authors: A. Khan, H. Mahmood

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In Underwater Wireless Sensor Networks (UWSNs), sensor nodes close to water surface (final destination) are often preferred for selection as forwarders. However, their frequent selection makes them depleted of their limited battery power. In consequence, these nodes die during early stage of network operation and create energy holes where forwarders are not available for packets forwarding. These holes severely affect network throughput. As a result, system performance significantly degrades. In this paper, a routing protocol is proposed to avoid energy holes during packets forwarding. The proposed protocol does not require the conventional position information (localization) of holes to avoid them. Localization is cumbersome; energy is inefficient and difficult to achieve in underwater environment where sensor nodes change their positions with water currents. Forwarders with the lowest water pressure level and the maximum number of neighbors are preferred to forward packets. These two parameters together minimize packet drop by following the paths where maximum forwarders are available. To avoid interference along the paths with the maximum forwarders, a packet holding time is defined for each forwarder. Simulation results reveal superior performance of the proposed scheme than the counterpart technique.

Keywords: energy holes, interference, routing, underwater

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Authors: Solaine Hachem, Frédéric Bourquin, Dominique Siegert

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The brutal collapse of bridges is mainly due to scour. Indeed, the soil erosion in the riverbed around a pier modifies the embedding conditions of the structure, reduces its overall stiffness and threatens its stability. Hence, finding an efficient technique that allows early scour detection becomes mandatory. Vibration analysis is an indirect method for scour detection that relies on real-time monitoring of the bridge. It tends to indicate the presence of a scour based on its consequences on the stability of the structure and its dynamic response. Most of the research in this field has focused on the dynamic behavior of a single pile and has examined the depth of the scour. In this paper, a bridge is fully modeled with all piles and spans and the scour is represented by a reduction in the foundation's stiffnesses. This work aims to identify the vibration modes sensitive to the rigidity’s loss in the foundations so that their variations can be considered as a scour indicator: the decrease in soil-structure interaction rigidity leads to a decrease in the natural frequencies’ values. By using the first-order perturbation method, the expression of sensitivity, which depends only on the selected vibration modes, is established to determine the deficiency of foundations stiffnesses. The solutions are obtained by using the singular value decomposition method for the regularization of the inverse problem. The propagation of uncertainties is also calculated to verify the efficiency of the inverse problem method. Numerical simulations describing different scenarios of scour are investigated on a simplified model of a real composite steel-concrete bridge located in France. The results of the modal analysis show that the modes corresponding to in-plane and out-of-plane piers vibrations are sensitive to the loss of foundation stiffness. While the deck bending modes are not affected by this damage.

Keywords: bridge’s piers, inverse problems, modal sensitivity, scour detection, vibration analysis

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Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang

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One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.

Keywords: malware detection, network security, targeted attack, computational intelligence

Procedia PDF Downloads 249

Authors: Ting Pan, Jiacheng Wang, Pengcheng Lin, Ying Chen, Songping Mo

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Phase change materials (PCMs) are widely used in latent heat thermal energy storage because of their good properties such as high energy storage density and constant heat-storage/release temperature. Microencapsulation techniques can prevent PCMs from leaking during the liquid-solid phase transition and enhance thermal properties. This technique has been widely applied in architectural materials, thermo-regulated textiles, aerospace fields, etc. One of the most important processes during the synthesis of microcapsules is to form a stable emulsion of the PCM core and reactant solution for the formation of the shell of the microcapsules. The use of surfactants is usually necessary for the formation of a stable emulsion system because of the difference in hydrophilia/lipophilicity of the PCM and the solvent. Unfortunately, the use of surfactants may cause pollution to the environment. In this study, modified kaolinite was used as an emulsion stabilizer for the microencapsulation of octodecane as PCM. Microcapsules were synthesized by phase inversion emulsification method, and the shell of polymethyl methacrylate (PMMA) was formed through free radical polymerization. The morphologies, crystalloid phase, and crystallization properties of microcapsules were investigated using scanning electron microscopy (SEM), X-ray diffractometer (XRD), and Fourier transforms infrared spectrometer (FTIR). The thermal properties and thermal stability were investigated by a differential scanning calorimeter (DSC) and a thermogravimetric analyzer (TG). The FT-IR, XRD results showed that the octodecane was well encapsulated in the PMMA shell. The SEM results showed that the microcapsules were spheres with an average size of about 50-100nm. The DSC results indicated that the latent heat of the microcapsules was 152.64kJ/kg and 164.23kJ/kg. The TG results confirmed that the microcapsules had good thermal stability due to the PMMA shell. Based on the results, it can be concluded that the modified kaolinite can be used as an emulsifier for the synthesis of PCM microcapsules, which is valid for reducing part of the possible pollution caused by the utilization of surfactants.

Keywords: kaolinite, microencapsulation, PCM, thermal energy storage

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Authors: Matt S. Van Deren, Michael Papenfus

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Seattle is one of the hundreds of cities in the United States that relies on a combined sewer system to collect and convey municipal wastewater. By design, these systems convey all wastewater, including industrial and commercial wastewater, human sewage, and stormwater runoff, through a single network of pipes. Serious problems arise for combined sewer systems during heavy precipitation events when treatment plants and storage facilities are unable to accommodate the influx of wastewater needing treatment, causing the sewer system to overflow into local waterways through sewer outfalls. CSOs (Combined Sewer Overflows) pose a serious threat to human and environmental health. Principal pollutants found in CSO discharge include microbial pathogens, comprising of bacteria, viruses, parasites, oxygen-depleting substances, suspended solids, chemicals or chemical mixtures, and excess nutrients, primarily nitrogen and phosphorus. While concentrations of these pollutants can vary between overflow events, CSOs have the potential to spread disease and waterborne illnesses, contaminate drinking water supplies, disrupt aquatic life, and effect a waterbody’s designated use. This paper estimates the economic impact of CSOs on residential property values. Using residential property sales data from Seattle, Washington, this paper employs a hedonic valuation model that controls for housing and neighborhood characteristics, as well as spatial and temporal effects, to predict a consumer’s willingness to pay for improved water quality near their homes. Initial results indicate that a 100,000-gallon decrease in the average annual overflow discharged from a sewer outfall within 300 meters of a home is associated with a 0.053% increase in the property’s sale price. For the average home in the sample, the price increase is estimated to be $18,860.23. These findings reveal some of the important economic benefits of improving water quality by reducing the frequency and severity of combined sewer overflows.

Keywords: benefits, hedonic, Seattle, sewer

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Authors: Abdelhadi Elharfi

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A problem of boundary feedback (exponential) stabilization of an overhead crane model represented by a PDE is considered. For any $r>0$, the exponential stability at the desired decay rate $r$ is solved in semi group setting by a collocated-type stabiliser of a target system combined with a term involving the solution of an appropriate PDE.

Keywords: feedback stabilization, semi group and generator, overhead crane system

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Authors: Ammar Said Ahmed, M. Reissmann, R. Bortfeldt, G. A. Brockmann

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Milk protein genetic variants are of interest for characterizing domesticated mammalian species and breeds, and for studying associations with economic traits. The aim of this work was to analyze milk protein genetic variation in the Sudanese native cattle breeds, which have been gradually declining in numbers over the last years due to the breed substitution, and indiscriminate crossbreeding. The genetic variation at three milk protein genes αS1-casein (CSN1S1), αS2-casein (CSN1S2) and ƙ-casein (CSN3) was investigated in 250 animals belonging to five Bos indicus cattle breeds of Sudan (Butana, Kenana, White-nile, Erashy and Elgash). Allele specific primers were designed for five SNPs determine the CSN1S1 variants B and C, the CSN1S2 variants A and B, the CSN3 variants A, B and H. Allele, haplotype frequencies and genetic distances (D) were calculated and the phylogenetic tree was constructed. All breeds were found to be polymorphic for the studied genes. The CSN1S1*C variant was found very frequently (>0.63) in all analyzed breeds with highest frequency (0.82) in White-nile cattle. The CSN1S2*A variant (0.77) and CSN3*A variant (0.79) had highest frequency in Kenana cattle. Eleven haplotypes in casein gene cluster were inferred. Six of all haplotypes occurred in all breeds with remarkably deferent frequencies. The estimated D ranged from 0.004 to 0.049. The most distant breeds were White-nile and Kenana (D 0.0479). The results presented contribute to the genetic knowledge of indigenous cattle and can be used for proper definition and classification of the Sudanese cattle breeds as well as breeding, utilization, and potential development of conservation strategies for local breeds.

Keywords: milk protein, genetic variation, casein haplotype, Bos indicus

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Authors: Martina Katalin Szabó, István Üveges

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In this paper, the usage of negative emotive words is examined on the basis of a large Hungarian twitter-database via NLP methods. The data is analysed from a gender point of view, as well as changes in language usage over time. The term negative emotive word refers to those words that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g. rohadt jó ’damn good’) or a sentiment expression with positive polarity despite their negative prior polarity (e.g. brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’. Based on the findings of several authors, the same phenomenon can be found in other languages, so it is probably a language-independent feature. For the recent analysis, 67783 tweets were collected: 37818 tweets (19580 tweets written by females and 18238 tweets written by males) in 2016 and 48344 (18379 tweets written by females and 29965 tweets written by males) in 2021. The goal of the research was to make up two datasets comparable from the viewpoint of semantic changes, as well as from gender specificities. An exhaustive lexicon of Hungarian negative emotive intensifiers was also compiled (containing 214 words). After basic preprocessing steps, tweets were processed by ‘magyarlanc’, a toolkit is written in JAVA for the linguistic processing of Hungarian texts. Then, the frequency and collocation features of all these words in our corpus were automatically analyzed (via the analysis of parts-of-speech and sentiment values of the co-occurring words). Finally, the results of all four subcorpora were compared. Here some of the main outcomes of our analyses are provided: There are almost four times fewer cases in the male corpus compared to the female corpus when the negative emotive intensifier modified a negative polarity word in the tweet (e.g., damn bad). At the same time, male authors used these intensifiers more frequently, modifying a positive polarity or a neutral word (e.g., damn good and damn big). Results also pointed out that, in contrast to female authors, male authors used these words much more frequently as a positive polarity word as well (e.g., brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’). We also observed that male authors use significantly fewer types of emotive intensifiers than female authors, and the frequency proportion of the words is more balanced in the female corpus. As for changes in language usage over time, some notable differences in the frequency and collocation features of the words examined were identified: some of the words collocate with more positive words in the 2nd subcorpora than in the 1st, which points to the semantic change of these words over time.

Keywords: gender differences, negative emotive words, semantic changes over time, twitter

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Authors: Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer

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Crowdsourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowdsourced data can be a valuable tool for improving road safety, particularly in urban areas where the majority of road crashes occur. This study is the first to develop safety performance functions using crowdsourced data by adopting a negative binomial structure model and Full Bayes model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: PCR method (adopted in the Highway Capacity Manual HCM) as well as a graphical method using GIS tools to compare and validate. Lastly, recommendations were suggested for policymakers to ensure safer roads.

Keywords: crowdsourced data, road crashes, safety performance functions, Full Bayes models, network screening

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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

Keywords: multiclass classification, convolution neural network, OpenCV

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Authors: Hamad Almohamadi, Nabeel Alharthi, Majed Alamoudi

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Biphasic electrodes featuring CuSx/NiSx electrodeposited on nickel foam have been investigated for their electrocatalytic activity in water splitting. The study investigates the impacts of an S-vacancy induced biphasic design on the overpotential and Tafel slope. According to the findings, the NiSx/CuSx/NF electrode with S-vacancy defects displays stronger oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) activity with lower overpotential and a steeper Tafel slope than the non-defect sample. NiSx/CuSx/NF exhibits the lowest overpotential value of 212 mV vs reversible hydrogen electrode (RHE) for OER and −109 mV vs RHE for HER at 10 mA cm−2. Tafel slope of 25.4 mV dec−1 for OER and −108 mV dec−1 for OER found of that electrode. The electrochemical surface area (ECSA) and diffusion impedance of the electrode is calculated. The maximum ECSA, lowest series resistance and lowest charge transfer resistance are found in the *NiSx/CuSx/NF sample with S-vacancy defects, showing increased electrical conductivity and quick charge transfer kinetics. The *NiSx/CuSx/NF electrode was found to be stable for 80 hours in pure water splitting and 20 hours in sea-water splitting. The investigation comes to the conclusion that the enhanced water splitting activity and electrical conductivity of the electrode are caused by S-vacancy defects resulting in improved water splitting performance.

Keywords: water splitting, electrocatalyst, biphasic design, electrodeposition

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Authors: Lin-Han Chiang Hsieh, Hsiao-Yi Lin

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This study aims to determine the impact of the disclosure of flood potential map on housing prices. The disclosure is supposed to mitigate the market failure by reducing information asymmetry. On the other hand, opponents argue that the official disclosure of simulated results will only create unnecessary disturbances on the housing market. This study identifies the impact of the disclosure of the flood potential map by comparing the hedonic price of flood potential before and after the disclosure. The flood potential map used in this study is published by Taipei municipal government in 2015, which is a result of a comprehensive simulation based on geographical, hydrological, and meteorological factors. The residential property sales data of 2013 to 2016 is used in this study, which is collected from the actual sales price registration system by the Department of Land Administration (DLA). The result shows that the impact of flood potential on residential real estate market is statistically significant both before and after the disclosure. But the trend is clearer after the disclosure, suggesting that the disclosure does have an impact on the market. Also, the result shows that the impact of flood potential differs by the severity and frequency of precipitation. The negative impact for a relatively mild, high frequency flood potential is stronger than that for a heavy, low possibility flood potential. The result indicates that home buyers are of more concern to the frequency, than the intensity of flood. Another contribution of this study is in the methodological perspective. The classic hedonic price analysis with OLS regression suffers from two spatial problems: the endogeneity problem caused by omitted spatial-related variables, and the heterogeneity concern to the presumption that regression coefficients are spatially constant. These two problems are seldom considered in a single model. This study tries to deal with the endogeneity and heterogeneity problem together by combining the spatial fixed-effect model and geographically weighted regression (GWR). A series of literature indicates that the hedonic price of certain environmental assets varies spatially by applying GWR. Since the endogeneity problem is usually not considered in typical GWR models, it is arguable that the omitted spatial-related variables might bias the result of GWR models. By combing the spatial fixed-effect model and GWR, this study concludes that the effect of flood potential map is highly sensitive by location, even after controlling for the spatial autocorrelation at the same time. The main policy application of this result is that it is improper to determine the potential benefit of flood prevention policy by simply multiplying the hedonic price of flood risk by the number of houses. The effect of flood prevention might vary dramatically by location.

Keywords: flood potential, hedonic price analysis, endogeneity, heterogeneity, geographically-weighted regression

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Authors: Madhawa Basnayaka, Jouni Paltakari

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Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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Authors: Shirin jalili, Hadi Shirzad, Mahasti Modarresi, Samaneh Nabavi, Somayeh Khanjani

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Identifying the source tissue of biological material found at crime scenes can be very informative in a number of cases. Despite their usefulness, current visual, catalytic, enzymatic, and immunologic tests for presumptive and confirmatory tissue identification are applicable only to a subset of samples, might suffer limitations such as low specificity, lack of sensitivity, and are substantially impacted by environmental insults. In addition their results are operator-dependent. Recently the possibility of discriminating body fluids using mRNA expression differences in tissues has been described but lack of long term stability of that Molecule and the need to normalize samples for each individual are limiting factors. The use of DNA should solve these issues because of its long term stability and specificity to each body fluid. Cells in the human body have a unique epigenome, which includes differences in DNA methylation in the promoter of genes. DNA methylation, which occurs at the 5′-position of the cytosine in CpG dinucleotides, has great potential for forensic identification of body fluids, because tissue-specific patterns of DNA methylation have been demonstrated, and DNA is less prone to degradation than proteins or RNA. Previous studies have reported several body fluid-specific DNA methylation markers.The presence or absence of a methyl group on the 5’ carbon of the cytosine pyridine ring in CpG dinucleotide regions called ‘CpG islands’ dictates whether the gene is expressed or silenced in the particular body fluid. Were described methylation patterns at tissue specific differentially methylated regions (tDMRs) to be stable and specific, making them excellent markers for tissue identification. The results demonstrate that methylation-based tissue identification is more than a proof-of-concept. The methodology holds promise as another viable forensic DNA analysis tool for characterization of biological materials.

Keywords: DNA methylation, forensic science, epigenome, tDMRs

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Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani

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Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.

Keywords: Escherichia coli, gene regulation, network, time-series

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Authors: Clotilde Guyon, Nada Jmari, Yen-Chin Li, Jean Denoyel, Noriyuki Fujikado, Christophe Blanchet, David Root, Matthieu Giraud

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Aire induces ectopic expression of a large repertoire of tissue-specific antigen (TSA) genes in thymic medullary epithelial cells (MECs), driving immunological self-tolerance in maturing T cells. Although important mechanisms of Aire-induced transcription have recently been disclosed through the identification and the study of Aire’s partners, the fine transcriptional functions underlied by a number of them and conferred to Aire are still unknown. Alternative cleavage and polyadenylation (APA) is an essential mRNA processing step regulated by the termination complex consisting of 85 proteins, 10 of them have been related to Aire. We evaluated APA in MECs in vivo by microarray analysis with mRNA-spanning probes and RNA deep sequencing. We uncovered the preference of Aire-dependent transcripts for short-3’UTR isoforms and for proximal poly(A) site selection marked by the increased binding of the cleavage factor Cstf-64. RNA interference of the 10 Aire-related proteins revealed that Clp1, a member of the core termination complex, exerts a profound effect on short 3’UTR isoform preference. Clp1 is also significantly upregulated in the MECs compared to 25 mouse tissues in which we found that TSA expression is associated with longer 3’UTR isoforms. Aire-dependent transcripts escape a global 3’UTR lengthening associated with MEC differentiation, thereby potentiating the repressive effect of microRNAs that are globally upregulated in mature MECs. Consistent with these findings, RNA deep sequencing of actinomycinD-treated MECs revealed the increased stability of short 3’UTR Aire-induced transcripts, resulting in TSA transcripts accumulation and contributing for their enrichment in the MECs.

Keywords: Aire, central tolerance, miRNAs, transcription termination

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Authors: Ha Phuong Tran, Feng Wang, Jo Dewulf, Hai Trung Huynh, Thomas Schaubroeck

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The fast increase and complex components have made waste of electrical and electronic equipment (or e-waste) one of the most problematic waste streams worldwide. Precise information on its size on national, regional and global level has therefore been highlighted as prerequisite to obtain a proper management system. However, this is a very challenging task, especially in developing countries where both formal e-waste management system and necessary statistical data for e-waste estimation, i.e. data on the production, sale and trade of electrical and electronic equipment (EEE), are often lacking. Moreover, there is an inflow of non-registered electronic and electric equipment, which ‘invisibly’ enters the EEE domestic market and then is used for domestic consumption. The non-registration/invisibility and (in most of the case) illicit nature of this flow make it difficult or even impossible to be captured in any statistical system. The e-waste generated from it is thus often uncounted in current e-waste estimation based on statistical market data. Therefore, this study focuses on enhancing e-waste estimation in developing countries and proposing a calculation pathway to quantify the magnitude of the non-registered EEE inflow. An advanced Input-Out Analysis model (i.e. the Sale–Stock–Lifespan model) has been integrated in the calculation procedure. In general, Sale-Stock-Lifespan model assists to improve the quality of input data for modeling (i.e. perform data consolidation to create more accurate lifespan profile, model dynamic lifespan to take into account its changes over time), via which the quality of e-waste estimation can be improved. To demonstrate the above objectives, a case study on televisions (TVs) in Vietnam has been employed. The results show that the amount of waste TVs in Vietnam has increased four times since 2000 till now. This upward trend is expected to continue in the future. In 2035, a total of 9.51 million TVs are predicted to be discarded. Moreover, estimation of non-registered TV inflow shows that it might on average contribute about 15% to the total TVs sold on the Vietnamese market during the whole period of 2002 to 2013. To tackle potential uncertainties associated with estimation models and input data, sensitivity analysis has been applied. The results show that both estimations of waste and non-registered inflow depend on two parameters i.e. number of TVs used in household and the lifespan. Particularly, with a 1% increase in the TV in-use rate, the average market share of non-register inflow in the period 2002-2013 increases 0.95%. However, it decreases from 27% to 15% when the constant unadjusted lifespan is replaced by the dynamic adjusted lifespan. The effect of these two parameters on the amount of waste TV generation for each year is more complex and non-linear over time. To conclude, despite of remaining uncertainty, this study is the first attempt to apply the Sale-Stock-Lifespan model to improve the e-waste estimation in developing countries and to quantify the non-registered EEE inflow to domestic consumption. It therefore can be further improved in future with more knowledge and data.

Keywords: e-waste, non-registered electrical and electronic equipment, TVs, Vietnam

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: R. S. Komartin, B. Balanuca, R. Stan

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the last decades, studies about the use of polymeric materials of plant origin, considering environmental concerns, have captured the interest of researchers because these represent an alternative to petroleum-derived materials. Vegetable oils are one of the preferred alternatives for petroleum-based raw materials having long aliphatic chains similar to hydrocarbons which means that can be processed using conventional chemistry. Epoxidized vegetable oils (EVO) are among the most interesting products derived from oil both for their high reactivity (epoxy group) and for the potential to react with compounds from various classes. As in the case of epoxy resins starting from petrochemical raw materials, those obtained from EVO can be crosslinked with different agents to build polymeric networks and can also be reinforced with various additives to improve their thermal and mechanical performances. Among the multitude of known EVO, the most common in industrial practice are epoxidized linseed oils (ELO) and epoxidized soybean oils (ESO), the first with an iodine index over 180, the second having a lower iodine index but being cheaper. On the other hand, lignin (Ln) is the second natural organic material as a spread, whose use has long been hampered because of the high costs associated with its isolation and purification. In this context, our goal was to obtain new composite materials with satisfactory intermediate properties in terms of stiffness and elasticity using the characteristics of ELO and Ln and choosing the proper curing procedure. In the present study linseed oil (LO) epoxidation was performed using peracetic acid generated in situ. The obtained bio-based epoxy resin derived from linseed oil was used further to produce the new composites byloading Ln in various mass ratios. The resulted ELO-Ln blends were subjected to a dual-curing protocol, namely photochemical and thermal. The new ELO-Ln composites were investigated by FTIR spectrometry, thermal stability, water affinity, and morphology. The positive effect of lignin regarding the thermal stability of the composites could be proved. The results highlight again the still largely unexplored potential of lignin in industrial applications.

Keywords: composite materials, dual curing, epoxidized linseed oil, lignin

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Authors: J. Ritonja, B. Grcar

Abstract:

For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.

Keywords: eigenvalue analysis, mathematical model, power system stability, synchronous generator

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