Search results for: performance properties

Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdelatif, Rabah Siham

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Camels play a vital role as multipurpose animals, providing milk meat and serving as a means of transportation. They serve as a financial reserve for pastoralists and hold significant cultural and social value. Camel milk, known for its exceptional nutritional properties, is considered a valuable substitute for human milk. However, udder infections, particularly mastitis, pose significant challenges to camel farming. Clinical and subclinical mastitis can lead to substantial economic losses. Mastitis, especially the subclinical form, is a persistent and prevalent condition affecting milk hygiene and quality in dairy camels. This review offers insights into the prevalence and risk factors associated with subclinical mastitis in camels. The prevalence of subclinical mastitis in dairy camels was found to range from 9.28% to 87.78%. Major pathogens responsible for camel mastitis include Staphylococcus aureus, Coagulase-negative Staphylococcus, Streptococcus agalactiae, Streptococcus dysgalactiae, Escherichia coli, Micrococcus spp, Pasteurella haemolytica and Corynebacterium spp. The study outlines key risk factors contributing to camel mastitis, emphasizing factors such as severe tick infestation, age, stage of lactation, parity, body condition score, skin lesion on the teats or udders, anti-suckling devices, previous history of the udder, conformation of the udder, breed, unhygienic milking practices, production system, amongst others have been reported to be important in the prevalence of subclinical mastitis. This comprehensive overview provides valuable insights into the multifaceted aspects of camel mastitis, encompassing prevalent bacterial pathogens and diverse risk factors. The findings underscore the importance of holistic management practices, emphasizing hygiene, health monitoring, and targeted interventions to ensure the well-being and productivity of camels in various agro-pastoral contexts.

Keywords: bacterial pathogens, camel, mastitis, risk factors

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Authors: Mahnaz Babaei Morad, Mojtaba Zargarzadeh, Behnaz Babaei Morad, Najmeh Salari Nasab

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Green roofs and walls are one of the key elements of sustainable design in ecology design of cities. Lack of open space and urban green at different scales from one neighborhood to district is as subject that has become challenge for urban management Use change from green space to other use is familiar for Iranian citizens. The high price of land in this area, it seems only justified reason for municipalities that reduce the green space per capita. In this paper, examines the rooftops of Iranian city as a fifth facade, as well as the opportunity to offset some of the capital's urban spaces that has been removed. Today green roof isn't a matter of taste in the world. Be proportional to the quantity and quality of the architecture become the first concern of urban professionals and ecological approaches such as "sustainable" and "green architecture" is checked. In this paper we review and present examples of green roofs have been executed in Iran over the past decade. Survey some of the urban management policies in leading province in this article constitutes the second dimension. The purpose of this paper is study example of green roof performance in different parts of Iran, along with criteria for sustainable urban development and achieves the policies and components collection of implementation sustainable development , specific of Iranian green roof and monitor the develops ways to it.

Keywords: sustainable development, green roofs, Iran, green architecture

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Authors: Ali Heidari

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This paper presents the principles for improving flood mitigation operation in multipurpose dams and maximizing reservoir performance during flood occurrence with a focus on the real-time operation of gated spillways. The criteria of operation include the safety of dams during flood management, minimizing the downstream flood risk by decreasing the flood hazard and fulfilling water supply and other purposes of the dam operation in mid and long terms horizons. The parameters deemed to be important include flood inflow, outlet capacity restrictions, downstream flood inundation damages, economic revenue of dam operation, and environmental and sedimentation restrictions. A simulation model was used to determine the real-time release of the Dez dam located in the Dez rivers in southwest Iran, considering the gate regulation curves for the gated spillway. The results of the simulation model show that there is a possibility to improve the current procedures used in the real-time operation of the dams, particularly using gate regulation curves and early flood forecasting system results. The Dez dam operation data shows that in one of the best flood control records, % 17 of the total active volume and flood control pool of the reservoir have not been used in decreasing the downstream flood hazard despite the availability of a flood forecasting system.

Keywords: dam operation, flood control criteria, Dez dam, Iran

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Authors: Aleksandra BužArovska, Gordana Bogoeva Gaceva

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Biodegradable polymers have received significant scientific attention in tissue engineering (TE) application, in particular their composites consisting of inorganic nanoparticles. In the last 15 years, they are subject of intensive research by many groups, aiming to develop polymer scaffolds with defined biodegradability, porosity and adequate mechanical stability. The most important characteristic making these materials attractive for TE is their biodegradability, a process that could be time controlled and long enough to enable generation of a new tissue as a replacement for the degraded polymer scaffold. In this work poly(L-lactic acid) scaffolds, filled with TiO2 nanoparticles functionalized with oleic acid, have been prepared by thermally induced phase separation method (TIPS). The functionalization of TiO2 nanoparticles with oleic acid was performed in order to improve the nanoparticles dispersibility within the polymer matrix and at the same time to inhibit the cytotoxicity of the nanofiller. The oleic acid was chosen as amphiphilic molecule belonging to the fatty acid family because of its non-toxicity and possibility for mediation between the hydrophilic TiO2 nanoparticles and hydrophobic PLA matrix. The produced scaffolds were characterized with thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and mechanical compression measurements. The bioactivity for bone tissue engineering application was tested in supersaturated simulated body fluid. The degradation process was followed by Fourier transform infrared spectroscopy (FTIR). The results showed anisotropic morphology with elongated open pores (100 µm), high porosity (around 92%) and perfectly dispersed nanofiller. The compression moduli up to 10 MPa were identified independent on the nanofiller content. Functionalized TiO2 nanoparticles induced formation of hydroxyapatite clusters as much as unfunctionalized TiO2. The prepared scaffolds showed properties ideal for scaffold vascularization, cell attachment, growth and proliferation.

Keywords: biodegradation, bone tissue engineering, mineralization, PLA scaffolds

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Authors: Abdelaadim Bidaoui

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As one of the most important linguistic inquiries, the topic of the intertwined relationship between language, the mind, and the world has attracted many scholars. In the fifties, Sapir and Whorf advocated the hypothesis that language shapes our cultural realities as an early attempt to provide answers to this linguistic inquiry. Later, discursive psychology views the linguistic behavior as “a dynamic form of social practice which constructs the social world, individual selves and identity.” (Jorgensen & Phillips 2002, 118). Discursive psychology also considers discourse as a trigger of social action and change. Building on discursive psychology and motivation theory, this paper examines the impact of linguistic behavior of the Moroccan coach Walid Reggragui on the Moroccan team’s exceptional performance in Qatar 2022 Soccer World Cup. The data used in the research is based on interviews conducted by the Moroccan coach prior and during the World Cup. Using a discourse analysis of the linguistic behavior of Reggragui, this paper shows how the linguistic behavior of Reggragui provided support for the three psychological needs: sense of belonging, competence, and autonomy. As any CDA research, this paper uses a triangulated theoretical framework that includes language, cognition and society.

Keywords: critical discourse analysis, motivation theory, discursive psychology, linguistic behavior

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Authors: Liu Yi Hui, Lin Yu Fang, Chiu Fan Yun

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In preparation for the coming super-aged society in Taiwan, the Ministry of Labor announced the Middle-aged and Elderly Employment Promotion Act in 2019, dedicating a chapter to expressly prohibiting age discrimination. This study aimed to enhance understanding of workplace ageism by collecting data through in-depth interviews. The findings can be summarized as follows: 1. Elderly employment in Taiwan and its three underlying motivations: Mainly in economic, social, and psychological needs. Economically, elders opt to continue working beyond the traditional retirement age because of financial shocks, a lack of financial planning, and being the breadwinner of the family. Socially and psychologically, they continue working to have a more diversified retirement life and find a new purpose in life. 2. Ageism on the re-employment of elders: On the ground, senior workers may face the age-based stereotype that their work performance is inferior and a broader social environment that is ostensibly friendly but essentially hostile. 3. Possible ways to facilitate elderly employment in terms of empowerment: By developing and empowering seniors with new skills or abilities for re-employment and strengthening their problem-solving skills in the face of new things through training programs, we can not only build the confidence and substantial abilities of senior workers in the workplace but also flip the social stereotype about age.

Keywords: senior-friendly workplaces, elderly employment, empowerment, ageism

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Authors: Dmitri Terzi

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The article presents the results of an algorithmic study of a special optimization problem of the transport type (traveling salesman problem): 1) To solve the problem, a new natural algorithm has been developed based on the decomposition of the initial data into convex hulls, which has a number of advantages; it is applicable for a fairly large dimension, does not require a large amount of memory, and has fairly good performance. The relevance of the algorithm lies in the fact that, in practice, programs for problems with the number of traversal points of no more than twenty are widely used. For large-scale problems, the availability of algorithms and programs of this kind is difficult. The proposed algorithm is natural because the optimal solution found by the exact algorithm is not always feasible due to the presence of many other factors that may require some additional restrictions. 2) Another inverse problem solved here is to describe a class of traveling salesman problems that have a predetermined optimal solution. The constructed algorithm 2 allows us to characterize the structure of traveling salesman problems, as well as construct test problems to evaluate the effectiveness of algorithms and other purposes. 3) The appendix presents a software implementation of Algorithm 1 (in MATLAB), which can be used to solve practical problems, as well as in the educational process on operations research and optimization methods.

Keywords: traveling salesman problem, solution construction algorithm, convex hulls, optimality verification

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Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

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With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation

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Authors: Masoud Ghaemi, MohammadJafar Hedayati, Faezeh Yousefzadeh, Hoseinali Heydarzadeh

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According to the statistics of the International Committee on Large Dams, internal erosion and piping (scour) are major causes of the destruction of earth-fill dams. If such dams are constructed in narrow valleys, the valley walls will increase the arching of the dam body due to the transfer of vertical and horizontal stresses, so the occurrence of hydraulic fracturing in these embankments is more likely. Roudbar Dam in Lorestan is a clay-core pebble earth-fill dam constructed in a relatively narrow valley in western Iran. Three years after the onset of impoundment, there has been a fall in dam behavior. Evaluation of the dam behavior based on the data recorded on the instruments installed inside the dam body and foundation confirms the occurrence of internal erosion in the lower and adjacent parts of the core on the left support (abutment). The phenomenon of hydraulic fracturing is one of the main causes of the onset of internal erosion in this dam. Accordingly, the main objective of this paper is to evaluate the validity of this hypothesis. To evaluate the validity of this hypothesis, the dam behavior during construction and impoundment has been first simulated with a three-dimensional numerical model. Then, using validated empirical equations, the safety factor of the occurrence of hydraulic fracturing phenomenon upstream of the dam score was calculated. Then, using the artificial neural network, the failure time of the given section was predicted based on the maximum stress trend created. The study results show that steep slopes of valley walls, sudden changes in coefficient, and differences in compressibility properties of dam body materials have caused considerable stress transfer from core to adjacent valley walls, especially at its lower levels. This has resulted in the coefficient of confidence of the occurrence of hydraulic fracturing in each of these areas being close to one in each of the empirical equations used.

Keywords: arching, artificial neural network, FLAC3D, hydraulic fracturing, internal erosion, pore water pressure

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Authors: Luís Fernando Cusioli, Leticia Nishi, Lucas Bairros, Gabriel Xavier Jorge, Sandro Rogério Lautenschalager, Celso Varutu Nakamura, Rosângela Bergamasco

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Focusing on the elimination of nitrogen and phosphorus from sewage, the study proposes to face the challenges of eutrophication and to optimize the effectiveness of sewage treatment through biofilms and filling produced by a 3D printer, seeking to identify the most effective Polylactic Acid (PLA), Acrylonitrile Butadiene Styrene (ABS). The study also proposes to evaluate the nitrification process in a Submerged Aerated Biological Filter (FBAS) on a pilot plant scale, quantifying the removal of nitrogen and phosphorus. The experiment will consist of two distinct phases, namely, a bench stage and the implementation of a pilot plant. During the bench stage, samples will be collected at five points to characterize the microbiota. Samples will be collected, and the microbiota will be investigated using Fluorescence In Situ Hybridization (FISH), deepening the understanding of the performance of biofilms in the face of multiple variables. In this context, the study contributes to the search for effective solutions to mitigate eutrophication and, thus, strengthen initiatives to improve effluent treatment.

Keywords: eutrophication, sewage treatment, biofilms, nitrogen and phosphorus removal, 3d printer, environmental efficiency

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Authors: They Shao Peng

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Machine vision system for inspection is an automated technology that is normally utilized to analyze items on the production line for quality control purposes, it also can be known as an automated visual inspection (AVI) system. By applying automated visual inspection, the existence of items, defects, contaminants, flaws, and other irregularities in manufactured products can be easily detected in a short time and accurately. However, AVI systems are still inflexible and expensive due to their uniqueness for a specific task and consuming a lot of set-up time and space. With the rapid development of mobile devices, smartphones can be an alternative device for the visual system to solve the existing problems of AVI. Since the smartphone-based AVI system is still at a nascent stage, this led to the motivation to investigate the smartphone-based AVI system. This study is aimed to provide a low-cost AVI system with high efficiency and flexibility. In this project, the object detection models, which are You Only Look Once (YOLO) model and Single Shot MultiBox Detector (SSD) model, are trained, evaluated, and integrated with the smartphone and webcam devices. The performance of the smartphone-based AVI is compared with the webcam-based AVI according to the precision and inference time in this study. Additionally, a mobile application is developed which allows users to implement real-time object detection and object detection from image storage.

Keywords: automated visual inspection, deep learning, machine vision, mobile application

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Authors: Pankaj Verma, Gagandeep Singh Walia, Padma Devi, H. P. Singh

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Code Division Multiple Access 2000 operates on various RF channel bandwidths 1.2288 or 3.6864 Mcps. CDMA offers high bandwidth and wireless broadband services but the efficiency gets decreased because of many interfering factors like fading, interference, scattering, diffraction, refraction, reflection etc. To reduce the spectral bandwidth is one of the major concerns in modern day technology and this is achieved by pulse shaping filter. This paper investigates the effect of diversity (MRC), interpolation factor in Root Raised Cosine (RRC) filter for the QPSK and BPSK modulation schemes. It is made possible to send information with minimum inter symbol interference and within limited bandwidth with proper pulse shaping technique. Bit error rate (BER) performance is analyzed by applying diversity technique by varying the interpolation factor for Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK). Interpolation factor increases the original sampling rate of a sequence to a higher rate and reduces the interference and diversity reduces the fading.

Keywords: CDMA2000, root raised cosine, roll off factor, ISI, diversity, interference, fading

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Authors: Ali Emre Öztürk, Ergun Ercelebi

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Autonomous robotic systems needs an equipment like a human eye for their movement. Robotic camera systems, distance sensors and 3D laser scanners have been used in the literature. In this study a 3D laser scanner has been produced for those autonomous robotic systems. In general 3D laser scanners are using 2 dimension laser range finders that are moving on one-axis (1D) to generate the model. In this study, the model has been obtained by a one-dimensional laser range finder that is moving in two –axis (2D) and because of this the laser scanner has been produced cheaper. Furthermore for the laser scanner a motor driver, an embedded system control board has been used and at the same time a user interface card has been used to make the communication between those cards and computer. Due to this laser scanner, the density of the objects, the distance between the objects and the necessary path ways for the robot can be calculated. The data collected by the laser scanner system is converted in to cartesian coordinates to be modeled in AutoCAD program. This study shows also the synchronization between the computer user interface, AutoCAD and the embedded systems. As a result it makes the solution cheaper for such systems. The scanning results are enough for an autonomous robot but the scan cycle time should be developed. This study makes also contribution for further studies between the hardware and software needs since it has a powerful performance and a low cost.

Keywords: 3D laser scanner, embedded system, 1D laser range finder, 3D model

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Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: Andres F. Ramirez, Carlos F. Valencia

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The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

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Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi

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Incorporating Home eNodeB (HeNB) in cellular networks, e.g. Long Term Evolution Advanced (LTE-A), is beneficial for extending coverage and enhancing capacity at low price especially within the non-line-of sight (NLOS) environments such as homes. HeNB or femtocell is a small low powered base station which provides radio coverage to the mobile users in an indoor environment. This deployment results in a heterogeneous network where the available spectrum becomes shared between two layers. Therefore, a problem of Inter Cell Interference (ICI) appears. This issue is the main challenge in LTE-A. To deal with this challenge, various techniques based on frequency, time and power control are proposed. This paper deals with the impact of carrier aggregation and higher order MIMO (Multiple Input Multiple Output) schemes on the LTE-Advanced performance. Simulation results show the advantages of these schemes on the system capacity (4.10⁹ b/s/Hz when bandwidth B=100 MHz and when applying MIMO 8x8 for SINR=30 dB), maximum theoretical peak data rate (more than 4 Gbps for B=100 MHz and when MIMO 8x8 is used) and spectral efficiency (15 b/s/Hz and 30b/s/Hz when MIMO 4x4 and MIMO 8x8 are applying respectively for SINR=30 dB).

Keywords: capacity, carrier aggregation, LTE-Advanced, MIMO (Multiple Input Multiple Output), peak data rate, spectral efficiency

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Authors: Ana-Marija Stjepić, Luka Sušac, Dalia Suša Vugec

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In the last few years, examples from scientific literature and business practices show that the adoption of technological innovations increases enterprises' performance. Recently, when it comes to the field of information technology innovation, business intelligence systems (BISs) have drawn a significant amount of attention of the scientific circles. BISs can be understood as a form of technological innovation which can bring certain benefits to the organizations that are adopting it. Therefore, the aim of this paper is twofold: (1) to define determinants of successful BISs adoption in small and medium enterprises and thus contribute to this neglected research area and (2) to present the current state of BISs adoption in small and medium-sized companies. In order to do so, determinants are defined and classified into three dimensions, according to the Technology – Organization – Environment (TOE) theoretical framework that describes the impact of each dimension on technological innovations adoption. Moreover, paper brings a case study presenting the adoption of BISs in practice within an organization from tertiary (service) industry sector. Based on the results of the study, guidelines for more efficient, faster and easier BISs adoption are presented.

Keywords: adoption, business intelligence, business intelligence systems, case study, TOE framework

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Authors: Michael Shandalov, Tzvi Templeman, Michael Schmidt, Itzhak Kelson, Eyal Yahel

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We present a new method to produce a model system for the study of radiation damage in non-radioactive materials. The method is based on homogeneously incorporating 228Th ions in PbS thin films using a small volume chemical bath deposition (CBD) technique. The common way to alloy metals with radioactive elements is by melting pure elements, which requires considerable amounts of radioactive material with its safety consequences such as high sample activity. Controlled doping of the thin films with (very) small amounts (100-200ppm) of radioactive elements such as thorium is expected to provide a unique path for studying radiation damage in materials due to decay processes without the need of sealed enclosure. As a first stage, we developed CBD process for controlled doping of PbS thin films (~100 nm thick) with the stable isotope (t1/2~106 years), 232Th. Next, we developed CBD process for controlled doping of PbS thin films with active 228Th isotope. This was achieved by altering deposition parameters such as temperature, pH, reagent concentrations and time. The 228Th-doped films were characterized using X-ray diffraction, which indicated a single phase material. Film morphology and thickness were determined using scanning electron microscopy (SEM). Energy dispersive spectroscopy (EDS) mapping in the analytical transmission electron microscope (A-TEM), X-ray photoelectron spectroscopy (XPS) depth profiles and autoradiography indicated that the Th ions were homogeneously distributed throughout the films, suggesting Pb substitution by Th ions in the crystal lattice. The properties of the PbS (228Th) film activity were investigated by using alpha-spectroscopy and gamma spectroscopy. The resulting films are applicable for isochronal annealing of resistivity measurements and currently under investigation. This work shows promise as a model system for the analysis of dilute defect systems in semiconductor thin films.

Keywords: thin films, doping, radiation damage, chemical bath deposition

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Authors: Ali Yasin, Ali Kamran, Muhammad Safdar

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In order to reduce the hefty cost involved in terms of time and project cost, the development and application of advanced numerical tools to address the burn-back analysis problem in solid rocket motor design and development is the need of time. Several advanced numerical schemes have been developed in recent times, but their usage in the design of propellant grain of solid rocket motors is very rare. In this paper, an advanced numerical technique named the Level-Set method has been utilized for the burn-back analysis of star grain to study the effect of geometrical parameters on ballistic performance indicators such as solid loading, neutrality, and sliver percentage. In the level set technique, simple finite difference methods may fail quickly and require more sophisticated non-oscillatory schemes for feasible long-time simulation. For internal ballistic calculations, a simplified equilibrium pressure method is utilized. Preliminary results of the operative conditions, for all the combustion time, of star grain burn-back using level set techniques are compared with published results using CAD technique to test the developed numerical model.

Keywords: solid rocket motor, internal ballistic, level-set technique, star grain

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Authors: Khaled Alkadamani

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Using the simultaneous equations model, this paper examines the impact of capital requirements on bank risk-taking during the recent financial crisis. It also explores the relationship between capital and risk decisions and the impact of economic instability on this relationship. By analyzing the data of 20 Islamic commercial banks between 2004 and 2014 from four Middle East countries, the study concludes a positive effect of regulatory pressure on bank capital in Saudi Arabia and UAE and a negative effect in Jordan and Kuwait. Moreover, the results show a negative impact of regulatory pressure on bank risk taking in Saudi Arabia, Jordan and UAE. The findings reveal also that banks close to the minimum regulatory capital requirements improve their capital adequacy by increasing their capital and decreasing their risk taking. Furthermore, the results show that economic crisis negatively affects bank risk changes, suggesting that banks react to the impact of uncertainty by reducing their risk taking. Finally, the estimations show a negative correlation between banks profitability and capital adequacy ratio (CAR), implying that as more capital is set aside as a buffer for banks safety; it affects the performance of Islamic banks.

Keywords: bank capital, bank regulation, crisis, Islamic banks, risk taking

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Authors: Muhanad Al-Jubouri

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A local scour is the most important of the several scours impacting bridge performance and security. Even though scour is widespread in bridges, especially during flood seasons, the experimental tests could not be applied to many standard highway bridges. A computational fluid dynamics numerical model was used to solve the problem of calculating local scouring and deposition for non-cohesive silt and clear water conditions near single and double cylindrical piers with the effect of floating debris. When FLOW-3D software is employed with the Rang turbulence model, the Nilsson bed-load transfer equation and fine mesh size are considered. The numerical findings of single cylindrical piers correspond pretty well with the physical model's results. Furthermore, after parameter effectiveness investigates the range of outcomes based on predicted user inputs such as the bed-load equation, mesh cell size, and turbulence model, the final numerical predictions are compared to experimental data. When the findings are compared, the error rate for the deepest point of the scour is equivalent to 3.8% for the single pier example.

Keywords: local scouring, non-cohesive, clear water, computational fluid dynamics, turbulence model, bed-load equation, debris

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Authors: Angela Meyer

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The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines.

Keywords: anomaly detection, decision support, machine learning, monitoring, performance optimization, wind turbines

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Authors: Sambit Supriya Dash, Rahul Ravi R, Vikram Ramanan, Vinayak Malhotra

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Combustion in itself is a complex phenomenon that involves the interaction and interplay of multiple phenomena, the combined effect of which gives rise to the common flame that we see and use in our daily life applications from cooking to propelling our vehicles to space. The most important thing that goes unnoticed about these flames is the effect of the various phenomena from its surrounding environment that affects its behavior and properties. These phenomena cause a variety of energy interactions that lead to various types of energy transformations which in turn affect the flame behavior. This paper focuses on experimentally investigating the effect of one such phenomenon, which is the acoustics or sound energy on diffusion flames. The subject in itself is extensively studied upon as thermo-acoustics globally, whereas the current work focuses on studying its effect on soot formation on diffusion flames. The said effect is studied in this research work by the use of a butane as fuel, fitted with a nozzle that houses 3 arrays consisting of 4 holes each that are placed equidistant to each other and the resulting flame impinged with sound from two independent and similar sound sources that are placed equidistant from the centre of the flame. The entire process is systematically video graphed using a 60 fps regular CCD and analysed for variation in flame heights and flickering frequencies where the fuel mass flow rate is maintained constant and the configuration of entrainment holes and frequency of sound are varied, whilst maintaining constant ambient atmospheric conditions. The current work establishes significant outcomes on the effect of acoustics on soot formation; it is noteworthy that soot formation is the main cause of pollution and a major cause of inefficiency of current propulsion systems. This work is one of its kinds, and its outcomes are widely applicable to commercial and domestic appliances that utilize combustion for energy generation or propulsion and help us understand them better, so that we can increase their efficiency and decrease pollution.

Keywords: thermoacoustics, entrainment, propulsion system, efficiency, pollution

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Authors: Orhun Aydin, Mark V. Janikas, Rodrigo Alves, Renato Assuncao

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In this paper, a tree-based perturbation methodology for regionalization inference is presented. Regionalization is a constrained optimization problem that aims to create groups with similar attributes while satisfying spatial contiguity constraints. Similar to any constrained optimization problem, the spatial constraint may hinder convergence to some global minima, resulting in spatially contiguous members of a group with dissimilar attributes. This paper presents a general methodology for rigorously perturbing spatial constraints through the use of random spanning trees. The general framework presented can be used to quantify the effect of the spatial constraints in the overall regionalization result. We compare several types of stochastic spanning trees used in inference problems such as fuzzy regionalization and determining the number of regions. Performance of stochastic spanning trees is juxtaposed against the traditional permutation-based hypothesis testing frequently used in spatial statistics. Inference results for fuzzy regionalization and determining the number of regions is presented on the Local Area Personal Incomes for Texas Counties provided by the Bureau of Economic Analysis.

Keywords: regionalization, constrained clustering, probabilistic inference, fuzzy clustering

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Authors: Ahmet Kayabasi, Ali Akdagli

Abstract:

In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: Md. Alauddin, Md. Ruhul Amin, Md. Omar Faruque, Muhammad Ali Siddiquee, Zakir Hossain Howlader, Mohammad Asaduzzaman

Abstract:

Diabetes and hypertension are the major lifestyle related diseases. The α-amylase and angiotensin converting enzymes (ACE) are the key enzymes that regulate diabetes and hypertension. The aim was to develop a drug for the treatment of diabetes and hypertension. The Rice Bran (RB) sample (Oryza sativa; BRRI-Dhan-84) was collected from the Bangladesh Rice Research Institute (BRRI), and rice bran proteins were isolated and hydrolyzed by hydrolyzing enzyme alcalase and trypsin. In vivo experiment suggested that rice bran bioactives has an effect on regulating the expression of several key gluconeogenesis and lipogenesis-regulating genes, such as glucose-6-phosphatase, phosphoenolpyruvate carboxykinase, and fatty acid synthase. The above genes have a connection of regulating the glucose level, lipids profile as well as act as an anti-inflammatory agent. A molecular docking, bioinformatics and in vitro experiments were performed. We found rice bran protein hydrolysates significantly (<0.05) influence the peptide concentration in the case of trypsin, alcalase, and (trypsin + alcalase) digestion. The in vitro analysis found that protein hydrolysate significantly (<0.05) reduced diabetic and hypertension as well as oxidative stress. A molecular docking study showed that the YY and IP peptide have a significantly strong binding affinity to the active site of the ACE enzyme and α-amylase with -7.8Kcal/mol and -6.2Kcal/mol, respectively. The Molecular dynamics (MD) simulation and Swiss ADME data analysis showed that less toxicity risk, good physicochemical properties, pharmacokinetics, and drug-likeness with drug scores 0.45 and 0.55 of YY and IP peptides, respectively. Thus, rice bran bioactive could be a good candidate for the treatment of diabetes and hypertension.

Keywords: anti-hypertensive and anti-hyperglycemic, anti-oxidative, bioinformatics, in vitro study, rice bran proteins and peptides

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Authors: Rufus Temidayo Akinnubi, M. O. Adeniyi

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Existing diurnal air temperature models simulate night time air temperature over Nigeria with high biases. An improved parameterization is presented for modeling the diurnal pattern of air temperature (Ta) which is applicable in the calculation of turbulent heat fluxes in Global climate models, based on Nigeria Micrometeorological Experimental site (NIMEX) surface layer observations. Five diurnal Ta models for estimating hourly Ta from daily maximum, daily minimum, and daily mean air temperature were validated using root-mean-square error (RMSE), Mean Error Bias (MBE) and scatter graphs. The original Fourier series model showed better performance for unstable air temperature parameterizations while the stable Ta was strongly overestimated with a large error. The model was improved with the inclusion of the atmospheric cooling rate that accounts for the temperature inversion that occurs during the nocturnal boundary layer condition. The MBE and RMSE estimated by the modified Fourier series model reduced by 4.45 oC and 3.12 oC during the transitional period from dry to wet stable atmospheric conditions. The modified Fourier series model gave good estimation of the diurnal weather patterns of Ta when compared with other existing models for a tropical environment.

Keywords: air temperature, mean bias error, Fourier series analysis, surface energy balance,

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Authors: Ben-Caleb Egbide, Iyoha Francis, Egharevba Mathew, Oduntan Emmanuel

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The prosperity of any nation is determined not just by the availability of resources, but also by the discipline exercised in the management of those resources. This paper examines the functional association between adherence to budgetary estimates or budget discipline (BDISC) and national prosperity proxied by Real Gross Domestic Product (RGDP) and Relative Poverty Index (RPI)/Human Development Index (HDI). Adopting a longitudinal retrospective research strategy, time series data relating to both the endogenous and exogenous variables were extracted from official government publications for 36 years’ (1980-2015 in the case of RGDP and RPI), and for 26 years (1990-2015 in the case of HDI). Ordinary Least Square (OLS), as well as cointegration regressions, were employed to gauge both the short term and long term impact of BDISC on RPI/HDI and RGDP. The results indicated that BDISC is directly related with RGDP but indirectly related with RPI. The implication is that while adherence to budgetary estimate can enhance economic growth, it has the capacity to slow down the rate of poverty in the long run. The paper, therefore, recommend stricter adherence to budgets as a way out of economic under performance in Nigeria and engender the process of promoting human development and national prosperity.

Keywords: budget discipline, human development index, national prosperity, Nigeria

Procedia PDF Downloads 231