Search results for: electrical network

Authors: Jonathan K. Hill

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The transportation networks throughout Africa remain the only transportation infrastructure system in the world that is attacked by terrorists at a high frequency, so the international community can learn from each attack. The targeting of transportation should be recognized as a direct attack against a civilian population, so the international community should work to better understand the types of attacks utilized, the types of improvised explosive device designs adapted to transportation targets, and the ways the various modes of transportation have been attacked throughout the continent. Some countries have seen grenade attacks that have resulted in only injuries, while some countries have experienced large vehicle bombings that have resulted in hundreds of injuries and numerous deaths. With insurgencies, explosive devices have been small, complex, and generally target an enemy of the insurgency. With terrorist bombings, the explosive devices have been large, brazen, and targeted at civilian populations. And, these civilian populations are easily targeted within the transportation system. The presentation provided by Assess Africa LLC is titled ‘Evolution of Bombings Against Transportation Infrastructure’ and covers improvised explosive device characteristics, how improvised explosive devices have been adapted to transportation targets in Africa, analyses recent incidents, and provides some advice for effective protective measures. A main component of the improvised explosive device characteristics portion of the presentation focuses on the link between explosive device components, the intelligence network, and the bomb-builder’s network. By understanding the components, how the use of various components can be linked to a terrorist group’s capabilities, and how the bomb-builder acquires materials, the analysis of improvised explosive device attacks takes on a new direction – one that focuses on defeating the network instead of merely reviewing incidents of the past.

Keywords: Africa, bombings, critical infrastructure protection, transportation security

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Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: electricity price, k-factor GARMA, LLWNN, G-GARCH, forecasting

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Authors: Yasin Polat, Yılmaz Dağdemir, Mehmet Arı

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Samarium (III) oxide and Ytterbium (III) oxide doped Bismuth trioxide solid solutions, the nano ceramic (Bi2O3)1-x-y(Sm2O3)x(Yb2O3)y ternary system were obtained with x=5, 20 mol %, and y=5, 20 mol % dopant concentrations have been synthesized in air atmosphere with solid state reaction. Temperature dependent electrical conductivity of the samples have been investigated by 4-point probe technique by heating and cooling process. Doped-Bi2O3 materials of solid electrolyte systems are good oxygen anions O2-conductors which have collected much attention as potential solid ceramic electrolytes for solid oxide fuel cells (SOFCs) because of their relatively high oxygen ionic conductivity at lower temperatures.(Bi2O3)-based electrolytes have also wide other technological applications in devices with high economical interest such as oxygen sensors, ceramic membranes for oxygen separation, oxygen pumps, catalyzing of some heterogeneous reactions, partial oxidation of the hydrocarbons, and additive material in paints. In recent years, many experimental researches have mostly focused on improving of the Bi-based electrolytes which have high oxide ionic conductivity at low temperatures and better performance as alternatives to traditional stabilized zirconia has taken place. Generally, these systems are much better solid electrolytes than well-known stabilized zirconia, because some of the bismuth trioxide phases exhibit higher ion conductivity than other oxide ionic conductors. Crystal structure of the Nano ceramic (Bi2O3)1-x-y(Sm2O3)x(Yb2O3)y has been determined by X-Ray powder diffractions (XRD) measurements before and after electrical conductivity measurements of the samples. Surface and grain structure properties of the samples were determined by SEM analysis. The samples which synthesized in this study can be used in industrial applications such as electrolytes of the solid oxide fuel cells (SOFC).

Keywords: 4-point probe technique, bismuth trioxide, solid state reaction, solid oxide fuel cell

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Authors: Goutam Kumar Ghorai, Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, G. Sarkar, Ashis K. Dhara

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Diabetes mellitus is one of the most common chronic diseases in all countries and continues to increase in numbers significantly. Diabetic retinopathy (DR) is damage to the retina that occurs with long-term diabetes. DR is a major cause of blindness in the Indian population. Therefore, its early diagnosis is of utmost importance towards preventing progression towards imminent irreversible loss of vision, particularly in the huge population across rural India. The barriers to eye examination of all diabetic patients are socioeconomic factors, lack of referrals, poor access to the healthcare system, lack of knowledge, insufficient number of ophthalmologists, and lack of networking between physicians, diabetologists and ophthalmologists. A few diabetic patients often visit a healthcare facility for their general checkup, but their eye condition remains largely undetected until the patient is symptomatic. This work aims to focus on the design and development of a fully automated intelligent decision system for screening retinal fundus images towards detection of the pathophysiology caused by microaneurysm in the early stage of the diseases. Automated detection of microaneurysm is a challenging problem due to the variation in color and the variation introduced by the field of view, inhomogeneous illumination, and pathological abnormalities. We have developed aconvolutional neural network for efficient detection of microaneurysm. A loss function is also developed to handle severe class imbalance due to very small size of microaneurysms compared to background. The network is able to locate the salient region containing microaneurysms in case of noisy images captured by non-mydriatic cameras. The ground truth of microaneurysms is created by expert ophthalmologists for MESSIDOR database as well as private database, collected from Indian patients. The network is trained from scratch using the fundus images of MESSIDOR database. The proposed method is evaluated on DIARETDB1 and the private database. The method is successful in detection of microaneurysms for dilated and non-dilated types of fundus images acquired from different medical centres. The proposed algorithm could be used for development of AI based affordable and accessible system, to provide service at grass root-level primary healthcare units spread across the country to cater to the need of the rural people unaware of the severe impact of DR.

Keywords: retinal fundus image, deep convolutional neural network, early detection of microaneurysms, screening of diabetic retinopathy

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Authors: Farzan Gity, Lida Ansari, Ian M. Povey, Roger E. Nagle, James C. Greer

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Titanium nitride (TiN) films have been widely used in variety of fields, due to its unique electrical, chemical, physical and mechanical properties, including low electrical resistivity, chemical stability, and high thermal conductivity. In microelectronic devices, thin continuous TiN films are commonly used as diffusion barrier and metal gate material. However, as the film thickness decreases below a few nanometers, electrical properties of the film alter considerably. In this study, the physical and electrical characteristics of 1.5nm to 22nm thin films deposited by Plasma-Enhanced Atomic Layer Deposition (PE-ALD) using Tetrakis(dimethylamino)titanium(IV), (TDMAT) chemistry and Ar/N2 plasma on 80nm SiO2 capped in-situ by 2nm Al2O3 are investigated. ALD technique allows uniformly-thick films at monolayer level in a highly controlled manner. The chemistry incorporates low level of oxygen into the TiN films forming titanium oxynitride (TiON). Thickness of the films is characterized by Transmission Electron Microscopy (TEM) which confirms the uniformity of the films. Surface morphology of the films is investigated by Atomic Force Microscopy (AFM) indicating sub-nanometer surface roughness. Hall measurements are performed to determine the parameters such as carrier mobility, type and concentration, as well as resistivity. The >5nm-thick films exhibit metallic behavior; however, we have observed that thin film resistivity is modulated significantly by film thickness such that there are more than 5 orders of magnitude increment in the sheet resistance at room temperature when comparing 5nm and 1.5nm films. Scattering effects at interfaces and grain boundaries could play a role in thickness-dependent resistivity in addition to quantum confinement effect that could occur at ultra-thin films: based on our measurements the carrier concentration is decreased from 1.5E22 1/cm3 to 5.5E17 1/cm3, while the mobility is increased from < 0.1 cm2/V.s to ~4 cm2/V.s for the 5nm and 1.5nm films, respectively. Also, measurements at different temperatures indicate that the resistivity is relatively constant for the 5nm film, while for the 1.5nm film more than 2 orders of magnitude reduction has been observed over the range of 220K to 400K. The activation energy of the 2.5nm and 1.5nm films is 30meV and 125meV, respectively, indicating that the TiON ultra-thin films are exhibiting semiconducting behaviour attributing this effect to a metal-semiconductor transition. By the same token, the contact is no longer Ohmic for the thinnest film (i.e., 1.5nm-thick film); hence, a modified lift-off process was developed to selectively deposit thicker films allowing us to perform electrical measurements with low contact resistance on the raised contact regions. Our atomic scale simulations based on molecular dynamic-generated amorphous TiON structures with low oxygen content confirm our experimental observations indicating highly n-type thin films.

Keywords: activation energy, ALD, metal-semiconductor transition, resistivity, titanium oxynitride, ultra-thin film

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Authors: Mohammad Parvaresh, Mahdi Babaee, Bahareh Arghand, Roushanak Fahimi Hanzaee, Davood Nourmohammadi

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Today, the intelligent network of water and wastewater as one of the key steps in realizing the smart city in the world. Use of pressure relief valves in urban water networks in order to reduce the pressure is necessary in Tehran city. But use these pressure relief valves lead to waste water, more power consumption, and environmental pollution because Tehran Province Water and Wastewater Co. use a quarter of industry 's electricity. In this regard, Tehran Province Water and Wastewater Co. identified solutions to reduce direct and indirect costs in energy use in the process of production, transmission and distribution of water because this company has extensive facilities and high capacity to realize green economy and industry. The aim of this study is to analyze the new project in water and wastewater industry to reach sustainable development.

Keywords: Tehran Province Water and Wastewater Company, water network efficiency, sustainable development, International Environmental Law

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Authors: Y. Boudjadja, A. Amira, A. Saoudel, A. Varilci, S. P. Altintas, C. Terzioglu

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In this work, we report the effect of Y3+ doping on structural, mechanical and electrical properties of Bi-2202 phase. Samples of Bi2Sr1.9Ca0.1-xYxCu2O7+δ with x = 0, 0.025, 0.05, 0.075 and 0.1 are elaborated in air by conventional solid state reaction and characterized by X-Ray Diffraction (XRD), Scanning Electronic Microscopy (SEM) combined with EDS spectroscopy, density, Vickers micro-hardness and resistivity measurements. A good correlation between the variations of the bulk density and the Vickers micro-hardness with doping is obtained. The SEM photograph shows that the samples are composed of grains with a flat shape that characterizes the Bi-based cuprates. Quantitative EDS analysis confirms the reduction of Ca content and the increase of Y content when x is increased. The variation of resistivity with temperature shows that only samples with x = 0, 0.025 and 0.05 present an onset transition to the superconducting state. The higher onset transition temperature is obtained for x = 0.025 and is about 93.62 K. The transition is wide and is realized in two steps confirming then the presence of the low Tc Bi-2201 phase in the samples. For x = 0.075 and 0.1, a transition to a semiconducting state is seen at low temperatures. Some physical parameters are extracted from these curves and discussed.

Keywords: Bi-2202 phase, doping, structure, mechanical and electrical properties

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Authors: Yuan-Jye Tseng, Yi-Shiuan Chen

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In this paper, a new concept of closed-loop design model is presented. The closed-loop design model is developed by integrating forward design and reverse design. Based on this new concept, a closed-loop design model for sustainable manufacturing by integrated evaluation of forward design, reverse design, and green manufacturing using a fuzzy analytic network process is developed. In the design stage of a product, with a given product requirement and objective, there can be different ways to design the detailed components and specifications. Therefore, there can be different design cases to achieve the same product requirement and objective. Thus, in the design evaluation stage, it is required to analyze and evaluate the different design cases. The purpose of this research is to develop a model for evaluating the design cases by integrated evaluation of forward design, reverse design, and green manufacturing models. A fuzzy analytic network process model is presented for integrated evaluation of the criteria in the three models. The comparison matrices for evaluating the criteria in the three groups are established. The total relational values among the three groups represent the total relational effects. In application, a super matrix can be created and the total relational values can be used to evaluate the design cases for decision-making to select the final design case. An example product is demonstrated in this presentation. It shows that the model is useful for integrated evaluation of forward design, reverse design, and green manufacturing to achieve a closed-loop design for sustainable manufacturing objective.

Keywords: design evaluation, forward design, reverse design, closed-loop design, supply chain management, closed-loop supply chain, fuzzy analytic network process

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Authors: Yousra Hadj Hassen, Walid Ayedi, Tarek Ouni, Mohamed Jallouli

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To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply investigated this area of research. Most existing researches rely only on the spatial appearance information from either one or multiple person images. Actually, the real person re-id framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to choose the best samples to remain a challenging problem. In this work, an extensive comparison of descriptors of state of the art associated with the proposed frame selection method is studied. Specifically, we evaluate the samples selection approach using multiple proposed descriptors. We show the effectiveness and advantages of the proposed method by extensive comparisons with related state-of-the-art approaches using two standard datasets PRID2011 and iLIDS-VID.

Keywords: camera network, descriptor, model, multi-shot, person re-identification, selection

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Authors: Wanying Xie

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Under the background of the increasing Sino-US trade friction, the two nations pay more attention to the medias’ words. This paper mainly studies the causality, effectiveness, and influence of discourse construction between traditional media and social media. Based on the Network Agenda Setting theory, a kind of associative memory pattern in Psychology, who focuses on how media affect audiences’ cognition of issues and attributes, as well as the significance of the relation between people and matters. The date of the sample chosen in this paper ranges from March 23, 2018, to April 30, 2019. A total of 395 Tweets of Donald Trump are obtained, and 731 related reports are collected from the mainstream American newspapers including New York Times, the Washington Post and the Washington Street, by using Factiva and other databases. The sample data are processed by MAXQDA while the media discourses are analyzed by SPSS and Cite Space, with an aim to study: 1) whether the inter-media discourse construction exists; 2) which media (traditional media V.S. social media) is dominant; 3) the causality between two media. The results show: 1) the discourse construction between three American mainstream newspapers and Donald Trump's Twitter is proved in some periods; 2) the dominant position is extremely depended on the events; 3) the causality between two media is decided by many reasons. New media technology shortens the time of agenda-setting effect to one day or less. By comparing the specific relation between the three major American newspapers and Donald Trump’s Twitter, whose popularity and influence could be reflected. Hopefully, this paper could enable readers to have a more comprehensive understanding of the international media language and political environment.

Keywords: discourse construction, media language, network agenda-setting theory, sino-us trade friction

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Authors: Abrar Al-Hasan

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Web 2.0 has significantly increased the amount of information available to users not only about firms and their offerings, but also about the activities of other individuals in their networks and markets. It is widely acknowledged that this increased availability of ‘social’ information, particularly about other individuals, is likely to influence a user’s behavior and choices. However, there are very few systematic studies of how such increased information transparency on the behavior of other users in a focal users’ network influences a focal users’ behavior in the emerging marketplace of online language learning. This study seeks to examine the value and impact of ‘social activities’ – wherein, a user sees and interacts with the learning activities of her peers – on her language learning efficiency. An online experiment in a peer-to-peer language marketplace was conducted to compare the learning efficiency of users with ‘social’ information versus users with no ‘social’ information. The results of this study highlight the impact and importance of ‘social’ information within the language learning context. The study concludes by exploring how these insights may inspire new developments in online education.

Keywords: e-Learning, language learning marketplace, peer-to-peer, social network

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Authors: B. Thanasansomboon, S. Choemprayong, N. Parinyanitikul, U. Tanlamai

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Being diagnosed with metastatic breast cancer, the patients as well as their caretakers are affected physically and mentally. Although the medical systems in Thailand have been attempting to improve the quality and effectiveness of the treatment of the disease in terms of physical illness, the success of the treatment also depends on the quality of mental health. Metastatic breast cancer patients have found that social support is a key factor that helps them through this difficult time. It is recognized that social support in different dimensions, including emotional support, social network support, informational support, instrumental support and appraisal support, are contributing factors that positively affect the quality of life of patients in general, and it is undeniable that social support in various forms is important in promoting the quality of life of metastatic breast patients. However, previous studies have not been dedicated to investigating their quality of life concerning affective, cognitive, and behavioral outcomes. Therefore, this study aims to develop integrated social support through social networks to improve the quality of life of metastatic breast cancer patients in Thailand.

Keywords: social support, metastatic breath cancer, quality of life, social network

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Authors: Abbas Ahmadi, Bijan Raie, Mohammad Reza Neyshabouri, Mohammad Ali Ghorbani, Farrokh Asadzadeh

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In recent years, vast areas of Urmia Lake in Dasht-e-Tabriz has dried up leading to saline sediments exposure on the surface lake coastal areas being highly susceptible to wind erosion. This study was conducted to investigate wind erosion and its relevance to soil physicochemical properties and also modeling of wind erodibility (WE) using artificial intelligence techniques. For this purpose, 96 soil samples were collected from 0-5 cm depth in 414000 hectares using stratified random sampling method. To measure the WE, all samples (<8 mm) were exposed to 5 different wind velocities (9.5, 11, 12.5, 14.1 and 15 m s-1 at the height of 20 cm) in wind tunnel and its relationship with soil physicochemical properties was evaluated. According to the results, WE varied within the range of 76.69-9.98 (g m-2 min-1)/(m s-1) with a mean of 10.21 and coefficient of variation of 94.5% showing a relatively high variation in the studied area. WE was significantly (P<0.01) affected by soil physical properties, including mean weight diameter, erodible fraction (secondary particles smaller than 0.85 mm) and percentage of the secondary particle size classes 2-4.75, 1.7-2 and 0.1-0.25 mm. Results showed that the mean weight diameter, erodible fraction and percentage of size class 0.1-0.25 mm demonstrated stronger relationship with WE (coefficients of determination were 0.69, 0.67 and 0.68, respectively). This study also compared efficiency of multiple linear regression (MLR), gene expression programming (GEP), artificial neural network (MLP), artificial neural network based on genetic algorithm (MLP-GA) and artificial neural network based on whale optimization algorithm (MLP-WOA) in predicting of soil wind erodibility in Dasht-e-Tabriz. Among 32 measured soil variable, percentages of fine sand, size classes of 1.7-2.0 and 0.1-0.25 mm (secondary particles) and organic carbon were selected as the model inputs by step-wise regression. Findings showed MLP-WOA as the most powerful artificial intelligence techniques (R2=0.87, NSE=0.87, ME=0.11 and RMSE=2.9) to predict soil wind erodibility in the study area; followed by MLP-GA, MLP, GEP and MLR and the difference between these methods were significant according to the MGN test. Based on the above finding MLP-WOA may be used as a promising method to predict soil wind erodibility in the study area.

Keywords: wind erosion, erodible fraction, gene expression programming, artificial neural network

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Authors: Mohsen Sheikholeslami, Zahra Khalili, Ladan Momayez

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Impacts of environmental parameters and dust deposition on the efficiency of solar panel have been scrutinized in this article. To gain thermal output, trapezoidal cooling channel has been attached in the bottom of the panel incorporating ternary nanofluid. To produce working fluid, water has been mixed with Fe₃O₄-TiO₂-GO nanoparticles. Also, the arrangement of fins has been considered to grow the cooling rate of the silicon layer. The existence of a thermoelectric layer above the cooling channel leads to higher electrical output. Efficacy of ambient temperature (Ta), speed of wind (V𝓌ᵢₙ𝒹) and inlet temperature (Tᵢₙ) and velocity (Vin) of ternary nanofluid on performance of PVT has been assessed. As Tin increases, electrical efficiency declines about 3.63%. Increase of ambient temperature makes thermal performance enhance about 33.46%. The PVT efficiency decreases about 13.14% and 16.6% with augment of wind speed and dust deposition. CO₂ mitigation has been reduced about 15.49% in presence of dust while it increases about 17.38% with growth of ambient temperature.

Keywords: photovoltaic system, CO₂ mitigation, ternary nanofluid, thermoelectric generator, environmental parameters, trapezoidal cooling channel

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Authors: Zeinab Jafari A., Ali Sharifnezhad B., Mohammad Razi C., Mohammad Haghpanahi D., Arash Maghsoudi

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Background and Objective: Sports-related rupture of the anterior cruciate ligament (ACL) and following injuries have been associated with various disorders, such as long-lasting changes in muscle activation patterns in athletes, which might last after ACL reconstruction (ACLR). The rupture of the ACL might result in abnormal patterns of movement execution, extending the treatment period and delaying athletes’ return to sports (RTS). As ACL injury is especially prevalent among athletes, the lengthy treatment process and athletes’ absence from sports are of great concern to athletes and coaches. Thus, estimating safe time of RTS is of crucial importance. Therefore, using a deep neural network (DNN) to classify the health levels of ACL in injured athletes, this study aimed to estimate the safe time for athletes to return to competitions. Methods: Ten athletes with ACLR and fourteen healthy controls participated in this study. Three health levels of ACL were defined: healthy, six-month post-ACLR surgery and nine-month post-ACLR surgery. Athletes with ACLR were tested six and nine months after the ACLR surgery. During the course of this study, surface electromyography (sEMG) signals were recorded from five knee muscles, namely Rectus Femoris (RF), Vastus Lateralis (VL), Vastus Medialis (VM), Biceps Femoris (BF), Semitendinosus (ST), during single-leg drop landing (SLDL) and forward hopping (SLFH) tasks. The Pseudo-Wigner-Ville distribution (PWVD) was used to produce three-dimensional (3-D) images of the energy distribution patterns of sEMG signals. Then, these 3-D images were converted to two-dimensional (2-D) images implementing the heat mapping technique, which were then fed to a deep convolutional neural network (DCNN). Results: In this study, we estimated the safe time of RTS by designing a DCNN classifier with an accuracy of 90 %, which could classify ACL into three health levels. Discussion: The findings of this study demonstrate the potential of the DCNN classification technique using sEMG signals in estimating RTS time, which will assist in evaluating the recovery process of ACLR in athletes.

Keywords: anterior cruciate ligament reconstruction, return to sports, surface electromyography, deep convolutional neural network

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Authors: T. D. Ibragimov, A. R. Imamaliyev, G. M. Bayramov

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The polymer network liquid crystals based on the liquid crystals Н37 and 5CB with polymethylvinilpirydine (PMVP) and polyethylene glycol (PEG) have been developed. Mesogene substance 4-n-heptyoxibenzoic acid (HOBA) is served for stabilization of obtaining composites. Kinetics of network formation is investigated by methods of polarization microscopy and integrated small-angle scattering. It is shown that gel-like states of the composite H-37 + PMVP + HOBA and 5CB+PEG+HOBA are formed at polymer concentration above 7 % and 9 %, correspondingly. At slow cooling, the system separates into a liquid crystal –rich phase and a liquid crystal-poor phase. At this case, transition of these phases in the H-37 + PMVP + HOBA (87 % + 12 % + 1 %) composite to an anisotropic state occurs at 49 оС and и 41 оС, accordingly, while the composite 5CB+PEG+HOBA (85% +13 % +2%) passes to anisotropic state at 36 оС corresponding to the isotropic-nematic transition of pure 5CB. The basic electro-optic parameters of the obtained composites are determined at room temperature. It is shown that the threshold voltage of the composite H-37 + PMVP + HOBA increase in comparison with pure H-37 and, accordingly, there is a shift of voltage dependence of rise times to the high voltage region. The contrast ratio worsens while decay time improves in comparison with the pure liquid crystal at all applied voltage. The switching times of the composite 5CB + PEG + HOBA (85% +13 % +2%) show anomalous behavior connected with incompleteness of the transition to an anisotropic state. Experimental results are explained by phase separation of the system, diminution of a working area of electro-optical effects and influence of areas with the high polymer concentration on areas with their low concentration.

Keywords: liquid crystals, polymers, small-angle scattering, optical properties

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Authors: Chularat Leewuttanakul, Khanitta Ruttarattanamongkol, Sasivimon Chittrakorn

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Rice during grain development stage is a rich source of many bioactive compounds. Dough stage rice contains high amounts of photochemical and can be used for rice milling industries. However, rice grain at dough stage had low milling quality due to high moisture content. Thermal processing can be applied to rice grain for improving milled rice yield. This experiment was conducted to study the chemical and physic properties of dough stage rice grain after roasting treatment. Rice were roasted with two different methods including traditional pan roasting at 140 °C for 60 minutes and using the electrical roasting machine at 140 °C for 30, 40, and 50 minutes. The chemical, physical properties, and bioactive compounds of brown rice and milled rice were evaluated. The result of this experiment showed that moisture content of brown and milled rice was less than 10 % and amylose contents were in the range of 26-28 %. Rice grains roasting for 30 min using electrical roasting machine had high head rice yield and length and breadth of grain after milling were close to traditional pan roasting (p > 0.05). The lightness (L*) of rice did not affect by roasting treatment (p > 0.05) and the a* indicated the yellowness of milled rice was lower than brown rice. The bioactive compounds of brown and milled rice significantly decreased with increasing of drying time. Brown rice roasted for 30 minutes had the highest of total phenolic content, antioxidant activity, α-tocopherol, and ɤ-oryzanol content. Volume expansion and elongation of cooked rice decreased as roasting time increased and quality of cooked rice roasted for 30 min was comparable to traditional pan roasting. Hardness of cooked rice as measured by texture analyzer increased with increasing roasting time. The results indicated that rice grains at dough stage, containing a high amount of bioactive compounds, have a great potential for rice milling industries and the electrical roasting machine can be used as an alternative to pan roasting which decreases processing time and labor costs.

Keywords: bioactive compounds, cooked rice, dough stage rice grain, grain development, roasting

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Authors: Adeolu O. Dairo

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Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

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Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

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Authors: Pankhuri Bansal, Sanjeev Kumar

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We examined the exotic role of electrical poling of layered BCZT-NZFO bulk composite for sustainable advancement of magnetoelectric (ME) technology. Practically, it seems quite difficult to access the full potential of ME composites due to their weak ME coupling performances. Using a standard poling protocol, we successfully deployed the coupling performance of laminated ME composite, comprised of a ferroelectric (FE) layer of BCZT and a ferrite layer of NZFO. However, the ME coupling constant of laminated composite is optimized by lowering the volume fraction of the FE component to strengthen the mechanical strain in the piezoelectric layer while fixing the thickness of the magnetostrictive ferrite layer. Here, we employed systematic zero field cooled (ZFC) and field cooled (FC) electrical poling protocol on morphotropic phase boundary (MPB) based BCZT composition, well-appreciated for it’s remarkable electromechanical activity. We report a record augmentation in magnetoelectric coupling as a consequence of a prudent field-cooled poling mechanism. On the basis of our findings, we emphasize that the degree of magnetoelectricity may be significantly improved for the miniaturization of efficient devices via proper execution of the poling technique.

Keywords: magnetoelectric, lead-free, ferroelctric, ferromagnetic, energy harvesting

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Authors: Mohamed A. Mohamed-Ali, Jannis Simos, Khalid M. Kheiralla

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The Ingessana hills in the southern Blue Nile of Sudan are part of the southern sector of the NE-SW trending ophiolithic belt of the Arab-Nubian Shield with mid-neoproterozoic age. The rocks are mainly serpentinized and in parts highly silicified dunites especially towards the contact with the intruding Bau granite. A promising chromite mineralization zones in the area tend to be generally associated with NE-SW trending shear-zones. A detailed geophysical survey employing electrical resistivity tomography (ERT) at 34 lines were carried out over a zone of a known chromite mineralization to test feasibility of detecting and delineating the ore (if exist) and accordingly facilitate the positioning of exploratory drill holes. ERT sections were inverted with smooth constraints inversion code where the contacts between the granite and the ultramafics are showing up clearly. The continuity of mineralization along the contact is not well confirmed. However, the low-resistivity anomalies are probably recognized as potential chromite mineralization zones. These anomalies represent prime targets for further exploration by drilling, trenching or shallow pits. If the results of the drilling or excavations are positive, small open pit exploitations may produce important tonnages of chromite.

Keywords: chromite exploration, ERT, Ingessana Hills, inversion

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Authors: Xi Xiao, Chunhui Chen, Xinyu Liu, Guangwu Hu, Yong Jiang

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Location sharing is a fundamental service in mobile Online Social Networks (mOSNs), which raises significant privacy concerns in recent years. Now, most location-based service applications adopt client/server architecture. In this paper, a location sharing system, named CSLocShare, is presented to provide flexible privacy-preserving location sharing with client/server architecture in mOSNs. CSLocShare enables location sharing between both trusted social friends and untrusted strangers without the third-party server. In CSLocShare, Location-Storing Social Network Server (LSSNS) provides location-based services but do not know the users’ real locations. The thorough analysis indicates that the users’ location privacy is protected. Meanwhile, the storage and the communication cost are saved. CSLocShare is more suitable and effective in reality.

Keywords: mobile online social networks, client/server architecture, location sharing, privacy-preserving

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Authors: Alok Tiwari, Ming Show Wong

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Lanthanum (La) doped Barium Tin Oxide (BaSnO₃) film is an excellent alternative for expensive Transparent Conducting Oxides (TCOs) film such as Indium Tin Oxide (ITO). However single crystal film of La-doped BaSnO₃ has been reported with a good amount of conductivity and transparency but in order to improve its reachability, it is important to grow doped BaSO₃ films on an inexpensive substrate. La-doped BaSnO₃ thin films have been grown on quartz substrate by Radio Frequency (RF) sputtering at a different substrate temperature (from 200⁰C to 750⁰C). The thickness of the film measured was varying from 360nm to 380nm with varying substrate temperature. Structure, optical and electrical properties have been studied. The carrier concentration is seen to be decreasing as we enhance the substrate temperature while mobility found to be increased up to 9.3 cm²/V-S. At low substrate temperature resistivity found was lower (< 3x10⁻³ ohm-cm) while sudden enhancement was seen as substrate temperature raises and the trend continues further with increasing substrate temperature. Optical transmittance is getting better with higher substrate temperature from 70% at 200⁰C to > 80% at 750⁰C. Overall, understanding of changes in microstructure, electrical and optical properties of a thin film by varying substrate temperature has been reported successfully.

Keywords: conductivity, perovskite, mobility, TCO film

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Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

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Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness

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Authors: Lourena M. Veríssimo, Lucas A. Machado, Renata Rutckeviski, Francisco H. Xavier Júnior, Éverton N. Alencar, Andreza R. V. Morais, Teresa R. F. Dantas, Christian M. Oliveira, Arnóbio A. Silva Júnior, Eryvaldo S. T. Egito

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This study aimed to obtain emulsion systems based on bullfrog oil (BO). The BO was extracted at 80ºC and analyzed by Gas Chromatography-Mass Spectrometry (GC/MS). The critical Hydrophilic-Lipophilic Balance (HLBc) Assay of the BO was performed through BO, Tween® 20, Span® 80 and deionized water mixtures using an Ultra-Turrax® and determined using dynamic light scattering, pH, electrical conductivity and creaming rate. Then, a pseudoternary phase diagram (PPD) was constructed by water titration. The GC/MS analysis of BO suggested Methyl Oleate (9.26%) as major compound. The HLBc was 12.1, wherein the correspondent emulsion showed a pH of 4.83±1.29, electrical conductivity of 103.65 µS, creaming rate of 2.51±0.54%, droplet size of 207.07±8.31 nm and polydispersity index of 0.212±0.005. The PPD showed different formulations characterized as O/W emulsions. Thus, the PPD proved to be a useful tool to produce BO emulsions, in which their constituents may vary within the range of the desired system.

Keywords: bullfrog (Rana catesbeiana Shaw) oil, emulsion production, hydrophilic-lipophilic balance, gas chromatography/mass spectrometry analysis

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Authors: William Ho, Agus Wicaksana

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Anecdotal evidence in the last decade shows that the occurrence of disruptive events and uncertainties in the supply chain is increasing. The coupling of these events with the nature of an increasingly complex and interdependent business environment leads to devastating impacts that quickly propagate within and across organizations. For example, the recent COVID-19 pandemic increased the global supply chain disruption frequency by at least 20% in 2020 and is projected to have an accumulative cost of $13.8 trillion by 2024. This crisis raises attention to organizational resilience to weather business uncertainty. However, the concept has been criticized for being vague and lacking a consistent definition, thus reducing the significance of the concept for practice and research. This study is intended to solve that issue by providing a comprehensive review of the conceptualization, measurement, and antecedents of operational resilience that have been discussed in the supply chain risk management literature (SCRM). We performed a Scholarly Network Analysis, combining citation-based and text-based approaches, on 252 articles published from 2000 to 2021 in top-tier journals based on three parameters: AJG ranking and ABS ranking, UT Dallas and FT50 list, and editorial board review. We utilized a hybrid scholarly network analysis by combining citation-based and text-based approaches to understand the conceptualization, measurement, and antecedents of operational resilience in the SCRM literature. Specifically, we employed a Bibliographic Coupling Analysis in the research cluster formation stage and a Co-words Analysis in the research cluster interpretation and analysis stage. Our analysis reveals three major research clusters of resilience research in the SCRM literature, namely (1) supply chain network design and optimization, (2) organizational capabilities, and (3) digital technologies. We portray the research process in the last two decades in terms of the exemplar studies, problems studied, commonly used approaches and theories, and solutions provided in each cluster. We then provide a conceptual framework on the conceptualization and antecedents of resilience based on studies in these clusters and highlight potential areas that need to be studied further. Finally, we leverage the concept of abnormal operating performance to propose a new measurement strategy for resilience. This measurement overcomes the limitation of most current measurements that are event-dependent and focus on the resistance or recovery stage - without capturing the growth stage. In conclusion, this study provides a robust literature review through a scholarly network analysis that increases the completeness and accuracy of research cluster identification and analysis to understand conceptualization, antecedents, and measurement of resilience. It also enables us to perform a comprehensive review of resilience research in SCRM literature by including research articles published during the pandemic and connects this development with a plethora of articles published in the last two decades. From the managerial perspective, this study provides practitioners with clarity on the conceptualization and critical success factors of firm resilience from the SCRM perspective.

Keywords: supply chain risk management, organizational resilience, scholarly network analysis, systematic literature review

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Authors: Shi-Bo Feng, Sheng-Jie Zhang, Jin Zhou

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The relationship between microbial diversity and algal bloom has received considerable attention for decades. Microbes undoubtedly affect annual bloom events and impact the physiology of both partners, as well as shape ecosystem diversity. However, knowledge about interactions and network correlations among broader-spectrum microbes that lead to the dynamics in a complete bloom cycle are limited. In this study, pyrosequencing and network approaches simultaneously assessed the associate patterns among bacteria, archaea, and microeukaryotes in surface water and sediments in response to a natural dinoflagellate (Alexandrium sp.) bloom. In surface water, among the bacterial community, Gamma-Proteobacteria and Bacteroidetes dominated in the initial bloom stage, while Alpha-Proteobacteria, Cyanobacteria, and Actinobacteria become the most abundant taxa during the post-stage. In the archaea biosphere, it clustered predominantly with Methanogenic members in the early pre-bloom period while the majority of species identified in the later-bloom stage were ammonia-oxidizing archaea and Halobacteriales. In eukaryotes, dinoflagellate (Alexandrium sp.) was dominated in the onset stage, whereas multiply species (such as microzooplankton, diatom, green algae, and rotifera) coexistence in bloom collapse stag. In sediments, the microbial species biomass and richness are much higher than the water body. Only Flavobacteriales and Rhodobacterales showed a slight response to bloom stages. Unlike the bacteria, there are small fluctuations of archaeal and eukaryotic structure in the sediment. The network analyses among the inter-specific associations show that bacteria (Alteromonadaceae, Oceanospirillaceae, Cryomorphaceae, and Piscirickettsiaceae) and some zooplankton (Mediophyceae, Mamiellophyceae, Dictyochophyceae and Trebouxiophyceae) have a stronger impact on the structuring of phytoplankton communities than archaeal effects. The changes in population were also significantly shaped by water temperature and substrate availability (N & P resources). The results suggest that clades are specialized at different time-periods and that the pre-bloom succession was mainly a bottom-up controlled, and late-bloom period was controlled by top-down patterns. Additionally, phytoplankton and prokaryotic communities correlated better with each other, which indicate interactions among microorganisms are critical in controlling plankton dynamics and fates. Our results supplied a wider view (temporal and spatial scales) to understand the microbial ecological responses and their network association during algal blooming. It gives us a potential multidisciplinary explanation for algal-microbe interaction and helps us beyond the traditional view linked to patterns of algal bloom initiation, development, decline, and biogeochemistry.

Keywords: microbial community, harmful algal bloom, ecological process, network

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Authors: Antonella D'Alessandro, Filippo Ubertini, Annibale Luigi Materazzi

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The progress of nanotechnology resulted in the development of new instruments in the field of civil engineering. In particular, the introduction of carbon nanofillers into construction materials can enhance their mechanical and electrical properties. In construction, concrete is among the most used materials. Due to the characteristics of its components and its structure, concrete is suitable for modification, at the nanometer level too. Moreover, to guarantee structural safety, it is desirable to achieve a widespread monitoring of structures. The ideal thing would be to realize structures able to identify their behavior modifications, states of incipient damage or conditions of possible risk for people. This paper presents a research work about novel cementitious composites with conductive carbon nanoinclusions able of monitoring their state of deformation, with particular attention to concrete. The self-sensing ability is achieved through the correlation between the variation of stress or strain and that of electrical resistance. Carbon nanofillers appear particularly suitable for such applications. Nanomodified concretes with different carbon nanofillers has been tested. The samples have been subjected to cyclic and dynamic loads. The experimental campaign shows the potentialities of this new type of sensors made of nanomodified concrete for diffuse Structural Health Monitoring.

Keywords: carbon nanofillers, cementitious nanocomposites, smart sensors, structural health monitoring.

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Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

Procedia PDF Downloads 103