Search results for: hybrid genetic algorithms

Authors: Adnan Kedir Jarso, Mesfin Megra Rorisa, Haftom Gebreslassie Gebregwergis, Frie Ayalew Yimam, Seada Hussen Adem

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A microgrid is a small-scale power grid that can operate independently or in conjunction with the main power grid. It is a promising solution for providing reliable and sustainable energy to remote areas. The integration of solar and vertical axis wind turbines (VAWTs) in a microgrid can provide a stable and efficient source of renewable energy. This paper provides a comprehensive overview of the integration of solar and VAWTs in a microgrid. The paper discusses the design, operation, and control of a microgrid that integrates solar and VAWTs. The paper also examines the performance of the microgrid in terms of efficiency, reliability, and cost-effectiveness. The paper highlights the advantages and disadvantages of using solar and VAWTs in a microgrid. The paper concludes that the integration of solar and VAWTs in a microgrid is a promising solution for providing reliable and sustainable energy to remote areas. The paper recommends further research to optimize the design and operation of a microgrid that integrates solar and VAWTs. The paper also recommends the development of policies and regulations that promote the use of microgrids that integrate solar and VAWTs. In conclusion, the integration of solar and VAWTs in a microgrid is a promising solution for providing reliable and sustainable energy to remote areas. The paper provides a comprehensive overview of the integration of solar and VAWTs in a microgrid and highlights the advantages and disadvantages of using solar and VAWTs in a microgrid. The paper recommends further research and the development of policies and regulations that promote the use of microgrids that integrate solar and VAWTs.

Keywords: hybrid generation, intermittent power, optimization, photovoltaic, vertical axis wind turbine

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Authors: Ding He, Ping Hu

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This article presents a “networking approach” as an alternative to the “layering model” in the issue of the historic urban landscape [HUL], based on research conducted in the historic city of Jingdezhen, the center of the porcelain industry in China. This study points out that the existing HUL concept, which can be traced back to the fundamental conceptual divisions set forth by western science, tends to analyze the various elements of urban heritage (composed of hybrid natural-cultural elements) by layers and ignore the nuanced connections and interweaving structure of various elements. Instead, the networking analysis approach can respond to the challenges of complex heritage networks and to the difficulties that are often faced when modern schemes of looking and thinking of landscape in the Eurocentric heritage model encounters local knowledge of Chinese settlement. The fieldwork in this paper examines the local language regarding place names and everyday uses of urban spaces, thereby highlighting heritage systems grounded in local life and indigenous knowledge. In the context of Chinese “Fengshui”, this paper demonstrates the local knowledge of nature and local intelligence of settlement location and design. This paper suggests that industrial elements (kilns, molding rooms, piers, etc.) and spiritual elements (temples for ceramic saints or water gods) are located in their intimate natural networks. Furthermore, the functional, spiritual, and natural elements are perceived as a whole and evolve as an interactive system. This paper proposes a local and cognitive approach in heritage, which was initially developed in European Landscape Convention and historic landscape characterization projects, and yet seeks a more tentative and nuanced model based on urban ethnography in a Chinese city.

Keywords: Chinese city, historic urban landscape, heritage conservation, network

Procedia PDF Downloads 130

Authors: Behnaz Moradijamei, Michael Higgins

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Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

Procedia PDF Downloads 134

Authors: Muhammad Cheema, Tahir Shah, Subhash Anand

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The cost of making apparel fabrics for garment manufacturing is very high because of their conventional manufacturing processes and new methods/processes are being constantly developed for making fabrics by unconventional methods. With the advancements in technology and the availability of the innovative fibres, durable nonwoven fabrics by using the hydroentanglement process that can compete with the woven fabrics in terms of their aesthetic and tensile properties are being developed. In the work reported here, the hydroentangled nonwoven fabrics were developed through a hybrid nonwoven manufacturing processes by using fibrillated Tencel® and bi-component (sheath/core) polyethylene/polyester (PE/PET) fibres, in which the initial nonwoven fabrics were prepared by the needle-punching method followed by hydroentanglement process carried out at optimal pressures of 50 to 250bars. The prepared fabrics were characterized according to the British Standards (BS 3356:1990, BS 9237:1995, BS 13934-1:1999) and the attained results were compared with those for a standard plain-weave cotton, polyester woven fabric and commercially available nonwoven fabric (Evolon®). The developed hydroentangled fabrics showed better drape properties owing to their flexural rigidity of 252 mg.cm in the machine direction, while the corresponding commercial hydroentangled fabric displayed a value of 1340 mg.cm in the machine direction. The tensile strength of the developed hydroentangled fabrics showed an approximately 200% increase than the commercial hydroentangled fabrics. Similarly, the developed hydroentangled fabrics showed higher properties in term of air permeability, such as the developed hydroentangled fabric exhibited 448 mm/sec and Evolon fabric exhibited 69 mm/sec at 100 Pa pressure. Thus for apparel fabrics, the work combining the existing methods of nonwoven production, provides additional benefits in terms of cost, time and also helps in reducing the carbon footprint for the apparel fabric manufacture.

Keywords: hydroentanglement, nonwoven apparel, durable nonwoven, wearable nonwoven

Procedia PDF Downloads 243

Authors: Sandra H. Fukurozaki, Andre L. N. Silva, Joao B. F. Neto, Fernando J. G. Landgraf

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Nowadays, the rare earth (RE) metals play an important role in emerging technologies that are crucial for the decarbonisation of the energy sector. Their unique properties have led to increasing clean energy applications, such as wind turbine generators, and hybrid and electric vehicles. Despite the substantial media coverage that has recently surrounded the mining and processing of rare earth metals, very little quantitative information is available concerning their subsequent life stages, especially related to the metallic production of didymium (Nd-Pr) in fluoride molten salt system. Here we investigate a gate to gate scale life cycle assessment (LCA) of the didymium electrolysis based on three different scenarios of operational conditions. The product system is modeled with SimaPro Analyst 8.0.2 software, and IMPACT 2002+ was applied as an impact assessment tool. In order to develop a life cycle inventories built in software databases, patents, and other published sources together with energy/mass balance were utilized. Analysis indicates that from the 14 midpoint impact categories evaluated, the global warming potential (GWP) is the main contributors to the total environmental burden, ranging from 2.7E2 to 3.2E2 kg CO2eq/kg Nd-Pr. At the damage step assessment, the results suggest that slight changes in materials flows associated with enhancement of current efficiency (between 2.5% and 5%), could lead a reduction up to 12% and 15% of human health and climate change damage, respectively. Additionally, this paper highlights the knowledge gaps and future research efforts needing to understand the environmental impacts of Nd-Pr electrolysis process from the life cycle perspective.

Keywords: didymium electrolysis, environmental impacts, life cycle assessment, rare earth metals

Procedia PDF Downloads 155

Authors: Benjamin Bonsu Bruce, Marian Dorcas Quain David Appiah-Kubi, Gertrude Osei-Diko, Harrison Kwame Dapaah

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Taro [Colocasia esculenta (L.) Schott] is a major staple food and remains a significant crop to many cultural and agricultural customs worldwide. In Ghana, taro is mostly propagated using vegetative material, which is conserved in field collection and recycled from their farms to establish new fields. However, this practice promotes the accumulation of systemic pathogens. Prior exposure to pests and subsequent expression of disease symptoms can also be a huge constraint to sustainable conservation and utilization of taro genetic resources. In vitro, slow growth is one of the most promising techniques to be utilized for conservation. The objective of this study was to find a medium-term in vitro conservation protocol for local and exotic taro genotypes. The medium-term conservation study was conducted using actively growing shoots obtained from in vitro cultures. Explants were cultured to full strength in complete Murashige and Skoog medium supplemented with Mannitol at different concentrations (0g/l, 20g/l, 25g/l, and 30g/l). Another medium that was tested as an additional treatment is the White’s medium. The highest number of shoots (6.33) and leaves (22.67) occurred on medium containing 20 and 25g/l mannitol in genotype SAO 006 as compared to other genotypes, whereas 30g/l mannitol was the best to restrict growth for the entire 6 months period in terms of shoot height (22.50cm). The study reveals that mannitol supplemented culture media could reduce the growth of Colocasia plantlets, especially in stem height. Culture growth following 6 months of conservation, showed that healthy shoot cultures of Taro were obtained after 6 months of storage in a medium containing 20gl⁻¹ and 25gl⁻¹ mannitol.

Keywords: complete murashige, skoog medium, culture conditions, mannitol, slow growth conservation

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Authors: Beenish Saba, Ann D. Christy

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Modern day municipal solid waste landfills are operated and controlled to protect the environment from contaminants during the biological stabilization and degradation of the solid waste. They are equipped with liners, caps, gas and leachate collection systems. Landfill gas is passively or actively collected and can be used as bio fuel after necessary purification, but leachate treatment is the more difficult challenge. Leachate, if not recirculated in a bioreactor landfill system, is typically transported to a local wastewater treatment plant for treatment. These plants are designed for sewage treatment, and often charge additional fees for higher strength wastewaters such as leachate if they accept them at all. Different biological, chemical, physical and integrated techniques can be used to treat the leachate. Treating that leachate with simultaneous power production using microbial fuel cells (MFC) technology has been a recent innovation, reported its application in its earliest starting phase. High chemical oxygen demand (COD), ionic strength and salt concentration are some of the characteristics which make leachate an excellent substrate for power production in MFCs. Different materials of electrodes, microbial communities, carbon co-substrates and temperature conditions are some factors that can be optimized to achieve simultaneous power production and treatment. The advantage of the MFC is its dual functionality but lower power production and high costs are the hurdles in its commercialization and more widespread application. The studies so far suggest that landfill leachate MFCs can produce 1.8 mW/m2 with 79% COD removal, while amendment with food leachate or domestic wastewater can increase performance up to 18W/m3 with 90% COD removal. The columbic efficiency is reported to vary between 2-60%. However efforts towards biofilm optimization, efficient electron transport system studies and use of genetic tools can increase the efficiency of the MFC and can determine its future potential in treating landfill leachate.

Keywords: microbial fuel cell, landfill leachate, power generation, MFC

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Authors: Shaher Bano, Samia Fida, Asif Israr

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The continuous development and exploitation of materials and designs have diverted the attention of the world towards the use of robust composite materials known as fiber-metal laminates in many high-performance applications. The hybrid structure of fiber metal laminates makes them a material of choice for various applications such as aircraft skin panels, fuselage floorings, door panels and other load bearing applications. The synergistic effect of properties of metals and fibers reinforced laminates are responsible for their high damage tolerance as the metal element provides better fatigue and impact properties, while high stiffness and better corrosion properties are inherited from the fiber reinforced matrix systems. They are mostly used as a layered structure in different joint configurations such as lap and but joints. The FML layers are usually bonded with each other using either mechanical fasteners or adhesive bonds. This research work is also focused on modification of an adhesive bonded joint as a single lap joint of carbon fibers based CARALL FML has been modified to increase interlaminar shear strength and avoid delamination. For this purpose different joint modification techniques such as the introduction of spews and shoulder to modify the bond shape and use of nanofillers such as carbon nano-tubes as a reinforcement in the adhesive materials, have been utilized to improve shear strength of lap joint of the adhesively bonded FML layers. Both the simulation and experimental results showed that lap joint with spews and shoulders configuration have better properties due to stress distribution over a large area at the corner of the joint. The introduction of carbon nanotubes has also shown a positive effect on shear stress and joint strength as they act as reinforcement in the adhesive bond material.

Keywords: adhesive joint, Carbon Reinforced Aluminium Laminate (CARALL), fiber metal laminates, spews

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Authors: Philippe Larvet

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This paper presents the concept of an object-based programming language where tests (if... then... else) and control structures (while, repeat, for...) disappear and are replaced by conditions on data. According to the object paradigm, by using this concept, data are still embedded inside objects, as variable-value couples, but object methods are expressed into the form of logical propositions (‘conditions on data’ or COD).For instance : variable1 = value1 AND variable2 > value2 => variable3 = value3. Implementing this approach, a central inference engine turns and examines objects one after another, collecting all CODs of each object. CODs are considered as rules in a rule-based system: the left part of each proposition (left side of the ‘=>‘ sign) is the premise and the right part is the conclusion. So, premises are evaluated and conclusions are fired. Conclusions modify the variable-value couples of the object and the engine goes to examine the next object. The paper develops the principles of writing CODs instead of complex algorithms. Through samples, the paper also presents several hints for implementing a simple mechanism able to process this ‘COD language’. The proposed approach can be used within the context of simulation, process control, industrial systems validation, etc. By writing simple and rigorous conditions on data, instead of using classical and long-to-learn languages, engineers and specialists can easily simulate and validate the functioning of complex systems.

Keywords: conditions on data, logical proposition, programming without code, object-oriented programming, system simulation, system validation

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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Borosilicate-crown (BK7) glass has found broad application in the optic and automotive industries and the growing demands for nanometric surface finishes is becoming a necessity in such applications. Thus, it has become paramount to optimize the parameters influencing the surface roughness of this precision lens. The research was carried out on a 4-axes Nanoform 250 precision lathe machine with an ultra-high precision grinding spindle. The experiment varied the machining parameters of feed rate, wheel speed and depth of cut at three levels for different combinations using Box Behnken design of experiment and the resulting surface roughness values were measured using a Taylor Hobson Dimension XL optical profiler. Acoustic emission monitoring technique was applied at a high sampling rate to monitor the machining process while further signal processing and feature extraction methods were implemented to generate the input to a neural network algorithm. This paper highlights the training and development of a back propagation neural network prediction algorithm through careful selection of parameters and the result show a better classification accuracy when compared to a previously developed response surface model with very similar machining parameters. Hence artificial neural network algorithms provide better surface roughness prediction accuracy in the ultra-high precision grinding of BK7 glass.

Keywords: acoustic emission technique, artificial neural network, surface roughness, ultra-high precision grinding

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Authors: Christine Ysabelle G. Roman, Pauline Torres

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Background: Hypertrophic cardiomyopathy is a disease of marked heterogeneity. It is a genetically determined heart disease characterized by significant myocardium hypertrophy that results in diastolic dysfunction, left ventricular outflow tract obstruction, and an increased risk of arrhythmias. The primary treatment in patients with such conditions is negative inotropic drugs, such as beta-blockers, calcium channel antagonists, and disopyramide. However, for those who remain symptomatic and need septal reduction therapy, surgical septal myectomy or alcohol septal ablation are options. Case Summary: A 19 – year old female presented in the authors’ institution with easy fatigability. The consult was done a year prior, and 2D echocardiography was requested which showed concentric left ventricular hypertrophy, asymmetrically hypertrophied interventricular septum (IVS) with the largest diameter of 3.3cm & subaortic dynamic obstruction with a maximum gradient of 47 mmHg. A repeat echo a year later showed asymmetric septal hypertrophy (IVS measuring at 3cm) with the systolic anterior motion of anterior mitral valve leaflet and left ventricular outflow tract obstruction (peak gradient of 50mmHg). The patient then underwent alcohol septal ablation and was discharged stable after four days of admission. Conclusion: Hypertrophic obstructive cardiomyopathy, a cardiovascular genetic disease, results in various patterns of left ventricular hypertrophy and abnormality of mitral valve apparatus. The patient is managed medically initially. However, despite optimal drug therapy and significant left ventricular outflow tract obstruction, significant heart failure symptoms or syncope require invasive treatment.

Keywords: hypertrophic obstructive cardiomyopathy, left ventricular outflow tract obstruction, alcohol septal ablation, alcohol

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Authors: Berna Istegun, Erkan Celebi

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The main objective of this experimental study is to assess the shear strength and the crack behavior of the triplets built of perforated brickwork masonry elements. In order to observe the influence of shear resistance and energy dissipating before and after retrofitting applications by using the reinforcing system, static-cyclic shear tests were employed in the structural mechanics laboratory of Sakarya University. The reinforcing system is composed of hybrid multiaxial seismic fabric consisting of alkali resistant glass and polypropylene fibers. The plaster as bonding material used in the specimen’s retrofitting consists of expanded glass granular. In order to acquire exact measuring data about the failure behavior of the two mortar joints under shear stressing, vertical load-controlled cylinder having force capacity of 50 kN and loading rate of 1.5 mm/min. with an internal inductive displacement transducers is carried out perpendicular to the triplet specimens. In this study, a total of six triplet specimens with textile reinforcement were prepared for these shear bond tests. The three of them were produced as single-sided reinforced triplets with seismic fabric, while the others were strengthened on both sides. In addition, three triplet specimens without retrofitting and plaster were also tested as reference samples. The obtained test results were given in the manner of force-displacement relationships, ductility coefficients and shear strength parameters comparatively. It is concluded that two-side seismic textile applications on masonry elements with relevant plaster have considerably increased the sheer force resistance and the ductility capacity.

Keywords: expanded glass granular, perforated brickwork, retrofitting, seismic fabric, triplet shear tests

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Authors: Cristian Păuna

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After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: Alvaro Aguinaga, Carlos Avila, Edgar Cando

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This article proposes a n-layer architecture, with a web client as a front-end, for the development of a virtual platform for process simulation on CNC machines. This Open-Source platform includes a CAD-CAM interface drawing primitives, and then used to furnish a CNC program that triggers a touch-screen virtual simulator. The objectives of this project are twofold. First one is an educational component that fosters new alternatives for the CAD-CAM/CNC learning process in undergrad and grade schools and technical and technological institutes emphasizing in the development of critical skills, discussion and collaborative work. The second objective puts together a research and technological component that will take the state of the art in CAD-CAM integration to a new level with the development of optimal algorithms and virtual platforms, on-line availability, that will pave the way for the long-term goal of this project, that is, to have a visible and active graduate school in Ecuador and a world wide Open-Innovation community in the area of CAD-CAM integration and operation of CNC machinery. The virtual platform, developed as a part of this study: (1) delivers improved training process of students, (2) creates a multidisciplinary team and a collaborative work space that will push the new generation of students to face future technological challenges, (3) implements industry standards for CAD/CAM, (4) presents a platform for the development of industrial applications. A protoype of this system was developed and implemented in a network of universities and technological institutes in Ecuador.

Keywords: CAD-CAM integration, virtual platforms, CNC machines, multi-layer based architecture

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Authors: Rajarshi Motilal

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The birth of the Internet and the rise of social media marked an important chapter in the history of humankind. Often termed the fourth scientific revolution, the Internet has changed human lives and cognisance. The birth of Web 2.0, followed by the launch of social media and social networking sites, added another milestone to these technological advancements where connectivity and influx of information became dominant. With billions of individuals using the internet and social media sites in the 21st century, “users” became “consumers”, and orthodox marketing reshaped itself to digital marketing. Furthermore, organisations started using sophisticated algorithms to predict consumer purchase behaviour and manipulate it to sustain themselves in such a competitive environment. The rampant storage and analysis of individual data became the new normal, raising many questions about data privacy. The excessive usage of the Internet among individuals brought in other problems of them becoming addicted to it, scavenging for societal approval and instant gratification, subsequently leading to a collective dualism, isolation, and finally, depression. This study aims to determine the relationship between social media usage in the modern age and the rise of psychological and cognitive imbalances in human minds. The literature review is positioned timely as an addition to the existing work at a time when the world is constantly debating on whether social media resignation is the only way to protect user data and restore the decaying cognitive balance.

Keywords: social media, digital marketing, consumer behaviour, internet addiction, data privacy

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Authors: Pitigalage Chamath Chandira Peiris

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A widely researched domain in the field of image processing in recent times has been single image super-resolution, which tries to restore a high-resolution image from a single low-resolution image. Many more single image super-resolution efforts have been completed utilizing equally traditional and deep learning methodologies, as well as a variety of other methodologies. Deep learning-based super-resolution methods, in particular, have received significant interest. As of now, the most advanced image restoration approaches are based on convolutional neural networks; nevertheless, only a few efforts have been performed using Transformers, which have demonstrated excellent performance on high-level vision tasks. The effectiveness of CNN-based algorithms in image super-resolution has been impressive. However, these methods cannot completely capture the non-local features of the data. Enhancer is a simple yet powerful Transformer-based approach for enhancing the resolution of images. A method for single image super-resolution was developed in this study, which utilized an efficient and effective transformer design. This proposed architecture makes use of a locally enhanced window transformer block to alleviate the enormous computational load associated with non-overlapping window-based self-attention. Additionally, it incorporates depth-wise convolution in the feed-forward network to enhance its ability to capture local context. This study is assessed by comparing the results obtained for popular datasets to those obtained by other techniques in the domain.

Keywords: single image super resolution, computer vision, vision transformers, image restoration

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: Sahar Javadi-Novashnagh, Mohammad Moradi-Shahrbabak, Mostafa Sadeghi, Katarzyna Ropka-Molik, Hossein Moradi-Shahrbabak, Maria Consuelo Mura

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The objective of this study was to investigate two single nucleotide polymorphisms located in exon 2 (g.939A > G) and intron 3 (g.4349A > G) of fatty acid binding protein 3 (FABP3) gene in two Iranian sheep breeds, Lori-Bakhtiari and Zel, using polymerase chain reaction -restriction fragment length polymorphism (PCR-RFLP) approach. The association of the polymorphisms with growth traits and blood parameters was also examined. Results revealed a g.939A > G SNP (single nucleotide polymorphism) in the exon 2 exhibiting three genotypes: AA, AG, and GG. Statistical analysis indicated that this polymorphism significantly influenced blood triglyceride (P < 0.05) and cholesterol (P < 0.08) levels as well as weaning weight (P < 0.05). Animals with AG genotype had the highest blood triglyceride level and weaning weight while the highest amount of blood cholesterol was observed in animals with GG genotype. On the other hand, no significant effect was observed on birth and fat-tail weight traits. The intron 3 (g.4349A > G) was monomorphic across the studied samples. Lori-Bakhtiari breed showed significantly higher blood triglyceride and cholesterol levels, as also birth and weaning weight compared to Zel breed (P < 0.01). Considering that the literature is bereft of any report on the association study between FABP3 SNPs and sheep growth traits and blood parameters, our findings suggest that the investigated polymorphism might be one of the main genetic factors affecting growth and physiological traits in sheep.

Keywords: FABP3 gene, fatness, weaning weight, blood triglyceride, cholesterol, Zel, Lori-Bakhtiari

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Authors: K. Sanjayani, C. Saraswathy, S. Sreenivasan, S. Sudhahar, D. Suganya, K. S. Neelukumari, N. Vijayarangan

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Double Base Number System (DBNS) is an imminent system of representing a number using two bases namely 2 and 3, which has its application in Elliptic Curve Cryptography (ECC) and Digital Signature Algorithm (DSA).The previous binary method representation included only base 2. DBNS uses an approximation algorithm namely, Greedy Algorithm. By using this algorithm, the number of digits required to represent a larger number is less when compared to the standard binary method that uses base 2 algorithms. Hence, the computational speed is increased and time being reduced. The standard binary method uses binary digits 0 and 1 to represent a number whereas the DBNS method uses binary digit 1 alone to represent any number (canonical form). The greedy algorithm uses two ways to represent the number, one is by using only the positive summands and the other is by using both positive and negative summands. In this paper, arithmetic operations are used for elliptic curve cryptography. Elliptic curve discrete logarithm problem is the foundation for most of the day to day elliptic curve cryptography. This appears to be a momentous hard slog compared to digital logarithm problem. In elliptic curve digital signature algorithm, the key generation requires 160 bit of data by usage of standard binary representation. Whereas, the number of bits required generating the key can be reduced with the help of double base number representation. In this paper, a new technique is proposed to generate key during encryption and extraction of key in decryption.

Keywords: cryptography, double base number system, elliptic curve cryptography, elliptic curve digital signature algorithm

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Authors: Esraa Mohamed El-Fawal

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A facile solvothermal procedure was applied to fabricate zinc ferrite nanoparticles (ZnFe₂O₄ NPs). Activated carbon (AC) derived from peanut shells is synthesized using a microwave through the chemical activation method. The ZnFe₂O₄-AC composite is then mixed with a cerium-based metal-organic framework (CeMOF) by solid-state adding to formulate ZnFe₂O₄-AC/CeMOF composite. The synthesized photo materials were tested by scanning/transmission electron microscope (SEM/TEM), Photoluminescence (PL), (XRD) X-Ray diffraction, (FTIR) Fourier transform infrared, (UV-Vis/DRS) ultraviolet-visible/diffuse reflectance spectroscopy. The prepared ZnFe₂O₄-AC/CeMOFphotomaterial shows significantly boosted efficiency for photodegradation of methyl orange /methylene blue (MO/MB) compared with the pristine ZnFe₂O₄ and ZnFe₂O₄-AC composite under the irradiation of visible-light. The favorable ZnFe₂O₄-AC/CeMOFphotocatalyst displays the highest photocatalytic degradation efficiency of MB/MO (R: 91.5-88.6%, consecutively) compared with the other as-prepared materials after 30 min of visible-light irradiation. The apparent reaction rate K: 1.94-1.31 min-1 is also calculated. The boosted photocatalytic proficiency is ascribed to the heterojunction at the interface of prepared photo material that assists the separation of the charge carriers. To reach optimization, statistical analysis using response surface methodology was applied. The effect of independent parameters (such as A (pH), B (irradiation time), and (c) initial pollutants concentration on the response function (%)photodegradation of MB/MO dyes (as examples of azodyes) was investigated via using central composite design. At the optimum condition, the photodegradation efficiency (%) of the MB/MO is 99.8-97.8%, respectively. ZnFe2O₄-AC/CeMOF hybrid reveals good stability over four consecutive cycles.

Keywords: azo-dyes, photo-catalysis, zinc ferrite, response surface methodology

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Basanti Ekka, Talis Juhna

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Dairy industrial effluents originated by the typical processing activities are composed of various organic and inorganic constituents, and these include proteins, fats, inorganic salts, antibiotics, detergents, sanitizers, pathogenic viruses, bacteria, etc. These contaminants are harmful to not only human beings but also aquatic flora and fauna. Because consisting of large classes of contaminants, the specific targeted removal methods available in the literature are not viable solutions on the industrial scale. Therefore, in this on-going research, a series of coagulation, electrochemical, and catalytic methods will be employed. The bulk coagulation and electrochemical methods can wash off most of the contaminants, but some of the harmful chemicals may slip in; therefore, specific catalysts designed and synthesized will be employed for the removal of targeted chemicals. In the context of Latvian dairy industries, presently, work is under progress on the characterization of dairy effluents by total organic carbon (TOC), Inductively Coupled Plasma Mass Spectrometry (ICP-MS)/ Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), High-Performance Liquid Chromatography (HPLC), Gas Chromatography-Mass Spectrometry (GC-MS), and Mass Spectrometry. After careful evaluation of the dairy effluents, a cost-effective natural coagulant will be employed prior to advanced electrochemical technology such as electrocoagulation and electro-oxidation as a secondary treatment process. Finally, graphene oxide (GO) based hybrid materials will be used for post-treatment of dairy wastewater as graphene oxide has been widely applied in various fields such as environmental remediation and energy production due to the presence of various oxygen-containing groups. Modified GO will be used as a catalyst for the removal of remaining contaminants after the electrochemical process.

Keywords: catalysis, dairy wastewater, electrochemical method, graphene oxide

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Authors: Azar Heidarizadi, Mahdieh Salimi, Hossein Mozdarani

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Introduction: As a complex disease, breast cancer results from several genetic and epigenetic changes. Lactoferrin, a member of the transferrin family, is reported to have a number of biological functions, including DNA synthesis, immune responses, iron transport, etc., any of which could play a role in tumor progression. The aim of this study was to investigate the bioinformatics data and experimental assay to find the pattern of promoter methylation and gene expression of LTF in breast cancer in order to study its potential role in cancer management. Material and Methods: In order to evaluate the methylation status of the LTF promoter, we studied the MS-PCR and Real-Time PCR on samples from patients with breast cancer and normal cases. 67 patient samples were conducted for this study, including tumoral, plasma, and normal tissue adjacent samples, as well as 30 plasma from normal cases and 10 tissue breast reduction cases. Subsequently, bioinformatics analyses such as cBioPortal databases, string, and genomatix were conducted to disclose the prognostic value of LTF in breast cancer progression. Results: The analysis of LTF expression showed an inverse relationship between the expression level of LTF and the stages of tissues of breast cancer patients (p<0.01). In fact, stages 1 and 2 had a high expression in LTF, while, in stages 3 and 4, a significant reduction was observable (p < 0.0001). LTF expression frequently alters with a decrease in the expression in ER⁺, PR⁺, and HER2⁺ patients (P < 0.01) and an increase in the expression in the TNBC, LN¯, ER¯, and PR- patients (P < 0.001). Also, LTF expression is significantly associated with metastasis and lymph node involvement factors (P < 0.0001). The sensitivity and specificity of LTF were detected, respectively. A negative correlation was detected between the results of level expression and methylation of the LTF promoter. Conclusions: The altered expression of LTF observed in breast cancer patients could be considered as a promotion in cell proliferation and metastasis even in the early stages of cancer.

Keywords: LTF, expression, methylation, breast cancer

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Authors: Sara ElElimy, Samir Moustafa

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Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

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Authors: Bremmy Laksono, Riksa Parikrama, Nur A. Rosyada, Willyanti Soewondo, Dadang S. H. Effendi, Eriska Rianti, Arlette S. Setiawan, Ine Sasmita, Risti S. Primanti, Erna Kurnikasari, Yunia Sribudiani

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Down syndrome (DS) is a chromosomal abnormality characterised by complete 21 chromosome trisomy (classical or non-disjunction), or partial 21 chromosome trisomy (mosaicism), or chromosome rearrangement involving chromosome 21 (translocation). This study was carried out to describe the frequency of DS patients in a research institution in the city of Bandung, Indonesia. This descriptive study also provides a picture of the residential location and surrounding area of their dwellings. This study involved people with DS in various age whose chromosome were evaluated by conventional karyotyping method and FISH. Data were collected from 60 patients with DS from a total 150 patients during the period of September 2015 to August 2016 who were referred to Cell Culture and Cytogenetics Laboratory, Faculty of Medicine Universitas Padjadjaran, Indonesia. Results showed that the most common type of DS was non-disjunction (93%), followed by mosaicism (5%), no patient with translocation DS (0%), and a very rare type of tetrasomy 21 (2%). There were 39 males (65%) and 21 females (35%) of DS patient. Most of them live in suburban area beyond Bandung city (55%) while the rest live inside urban area of Bandung city (45%). They live mostly in dense area of greater Bandung area (65%) and only a few live in mid-density area (25%) and the least live in sparse populated area (10%). Their houses are mostly located in residential estate area (55%), nearby industrial area (37%), and around agricultural area (8%). Based on the study, it could be concluded that non-disjunction DS is the most common type. DS patients referred to the laboratory mostly came from dense residential zone in suburban area outside Bandung city. The low number of DS patients referred to the laboratory for chromosome analysis was the highlight to improve health service for people with genetic disorder. This study offered several information regarding area of DS patients’ residence and the condition of neighbourhood in Bandung city where they live as well.

Keywords: chromosome, descriptive, Down syndrome, prevalence

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Authors: Saboor Saeed, Chunming Jiang

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Eosinophilic Granulomatosis with polyangiitis (EGPA), formerly known as Churg-Strauss syndrome, is a rare systemic vasculitis of small and medium-sized vessels that primarily develops in middle-aged individuals. It is characterized by asthma, blood eosinophilia, and extra pulmonary manifestations. In childhood, EGPA is extremely rare. Pulmonary and cardiac involvement is predominant in pediatric EGPA, and mortality is substantial. Generally, EGPA will develop in three stages: a) The allergic phase is commonly associated with asthma, allergic rhinitis, and sinusitis, b) the eosinophilic phase, in which the main pathology is related to the infiltration of eosinophilic organs, i.e., lung, heart, and gastrointestinal system, c) vasculitis phase involved purpura, peripheral neuropathy, and some constitutional symptoms. The key to the treatment of EGPA lies in the early diagnosis of the disease. Early application of glucocorticoids and immunosuppressants can improve symptoms and the overall prognosis of EGPA. Case Description: We presented a case of an 8-year-old boy with a history of short asthma, marked eosinophilia, and multi-organ involvement. The extremely high eosinophil level in the blood (72.50%) prompted the examination of eosinophilic leukemia before EGPA diagnosis was made. Subsequently, this disease was successfully treated. This case report shows a typical case of CSS in childhood because of the extreme eosinophilia. It emphasizes the importance of EGPA is a life-threatening cause of children's eosinophilia. Conclusion: EGPA in children has unique clinical, imaging, and histological characteristics different from those of adults. In pediatric patients, the development and diagnosis of systemic symptoms are often delayed, mainly occurring in the eosinophilic phase, which will lead to specific manifestations. At the same time, we cannot detect a genetic relationship related to EGPA.

Keywords: Churg Strauss syndrome, asthma, vasculitis, hypereosinophilia, eosinophilic granulomatosis polyangiitis

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Authors: Yu. Mateyshina, A. Ulihin, N. Uvarov

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Supercapacitors are one of the most promising devices for energy storage applications as they can provide higher power density than batteries and higher energy density than conventional dielectric capacitors. Carbon materials with various microtextures are considered as main candidates for supercapacitors in terms of high surface area, interconnected pore structure, controlled pore size, high electrical conductivity and environmental friendliness. The specific capacitance (C) of the electrode material of the Electrochemical Double Layer Capacitors (EDLC) is known to depend on the specific surface area (Ss) and the pore structure. Activated carbons are most commonly used in supercapacitors because of their high surface area (Ss ≥ 1000 m2/g), good adhesion to electrolytes and low cost. In this work, electrochemical properties of new microporous and mesoporous carbon electrode materials were studied. The aim of the work was to investigate the relationship between the specific capacitance and specific surface area in a series of materials prepared from different organic precursors.. As supporting matrixes different carbon samples with Ss = 100-2000 m2/g were used. The materials were modified by treatment in acids (H2SO4, HNO3, acetic acid) in order to enable surface hydrophilicity. Then nanoparticles of transition metal oxides (for example NiO) were deposited on the carbon surfaces using methods of salts impregnation, mechanical treatment in ball mills and the precursors decomposition. The electrochemical characteristics of electrode hybrid materials were investigated in a symmetrical two-electrode cell using an impedance spectroscopy, voltammetry in both potentiodynamic and galvanostatic modes. It was shown that the value of C for the materials under study strongly depended on the preparation method of the electrode and the type of electrolyte (1 M H2SO4, 6 M KOH, 1 M LiClO4 in acetonitryl). Specific capacity may be increased by the introduction of nanoparticles from 50-100 F/g for initial carbon materials to 150-300 F/g for nanocomposites which may be used in supercapacitors. The work is supported by the по SC-14.604.21.0013.

Keywords: supercapacitors, carbon electrode, mesoporous carbon, electrochemistry

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Authors: Karl Kingsley

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Many mechanisms are involved in the control of cellular differentiation and growth, which are often dysregulated in many cancers. Many distinct pathways are involved in these mechanisms of control, including deoxyribonuclease (DNA) methyltransferase and histone deacetylase (HDAC) activation that controls both genetic and epigenetic modifications and micro ribonucleic acid (RNA) expression. Less is known about the expression of DNA methyltransferase (DNMT) and HDAC in oral cancers and the effect on microRNA expression. The primary objective of this study was to evaluate the expression of DNMT and HDAC family members in oral cancer and the concomitant expression of cancer-associated microRNAs. Using commercially available oral cancers, including squamous cell carcinoma (SCC)-4, SCC-9, SCC-15, and SCC-25, RNA was extracted and screened for DNMT, HDAC, and microRNA expression using highly-specific primers and quantitative polymerase chain reaction (qPCR). These data revealed low or absent expression of DNMT-1, which is associated with cellular differentiation but increased expression of DNMT-3a and DNMT-3b in all SCC cell lines compared with normal non-cancerous cell controls. In addition, no expression of HDAC1 and HDAC2 expression was found among the normal, non-cancerous cells but was highly expressed in each of the SCC cell lines examined. Differential expression of oncogenic and cancer-associated microRNAs was also observed among the SCC cell lines, including miR-21, miR-133, miR-149, miR-155, miR-365, and miR-720. These findings also appeared to vary according to observed growth rates among these cells. These data may be the first to demonstrate the expression and association between HDAC and DNMT3 family members among oral cancers. In addition, the differential expression of these epigenetic modifiers may be associated with the expression of specific microRNAs in these cancers, which have not previously been observed to the best of the author's knowledge. In addition, some associations and relationships may exist between the expression of these biomarkers and the rates of growth and proliferation, which may suggest that these expression patterns might represent potentially useful biomarkers to determine tumor aggressiveness and other phenotypic behaviors among oral cancers.

Keywords: oral cancer, DNA methyltransferase, histone deacetylase, microRNA

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Authors: Ali Elshabrawy

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Cloud computing is expected to be important for e Government in near future. Governments need it for solving some of its e Government, financial, infrastructure, legacy systems and integration problems. It reduces information technology (IT) infrastructure needs and support costs, and offers on-demand infrastructure and computational power, improved collaboration capabilities, which are important for e Government projects start up and sustainability. Budget pressures will continue to drive more and more government IT to hybrid and even public clouds, and more cooperation between cloud service providers and governmental agencies are expected, Or developing governmental private, community clouds. Motivation to convince governments to use cloud computing services, will create a pressure on cloud service providers to cope with government's requirements for interoperability, security standards, open data and integration between their cloud systems There will be significant legal action arising out of governmental uses of cloud computing, and legislation addressing both IT and business needs and consumer fears and protections. Cloud computing is a considered a revolution for IT and E business in general and e commerce, e Government in particular. As governments faces increasing challenges regarding IT infrastructure required for e Government projects implementation. As a result of Lack of required financial resources allocated for e Government projects in developed and developing countries. Cloud computing can play a major role to solve some of e Government projects challenges such as, lack of financial resources, IT infrastructure, Human resources trained to manage e Government applications, interoperability, cost efficiency challenges. If we could solve some security issues related to cloud computing usage which considered critical for e Government projects. Pretty sure it’s Just a matter of time before cloud service providers will find out solutions to attract governments as major customers for their business.

Keywords: cloud computing, e-government, adoption, supply side barriers, e-government requirements, challenges

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Authors: Laila Salah Seada, Ashraf Ibrahim, Fawaz Al Rashid, Ihab Abdo, Hassan Kasim, Waleed Al Mansi, Saud Al Shabli

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Background and Objectives: Colorectal carcinoma is increasing among both men and women worldwide. It has a multifactorial etiology including genetic factors, environmental factors and inflammatory conditions of the digestive tract. A clinicopathologic assessment of colorectal carcinoma in Hail region is done, considering any changing patterns in two 5-year periods from 2005-2009 (A) and from 2012 to 2017 (B). All data had been retrieved from histopathology files of King Khalid Hospital, Hail. Results: During period (A), 75 cases were diagnosed as colorectal carcinoma. Male patients comprised 56/75 (74.7%) of the study, with a mean age of 58.4 (36-97), while females were 19/75 (25.3%) with a mean age of 50.3(30-85) and the difference was significant (p = 0.05). M:F ratio was 2.9:1. Most common histological type was adenocarcioma in 68/75 (90.7%) patients mostly well differentiated in 44/68 (64.7%). Mucinous neoplasms comprised only 7/75 (9.3%) of cases and tended to have a higher stage (p = 0.04). During period (B), 115 cases were diagnosed with an increase of 53.3% in number of cases than period (A). Male to female ratio also decreased to 1.35:1, females being 44.83% more affected. Adenocarcinoma remained the prevalent type (93.9%), while mucinous type was still rare (5.2%). No distal metastases found at time of presentation. Localization of tumors was rectosigmoid in group (A) in 41.4%, which increased to 56.6% in group (B), with an increase of 15.2%. Iliocecal location also decreased from 8% to 3.5%, being 56.25% less. Other proximal areas of the colon were decreased by 25.75%, from 53.9% in group (A) to 40% in group (B). Conclusion: Colorectal carcinoma in Hail region has increased by 53.3% in the past 5 years, with more females being diagnosed. Localization has also shifted distally by 15.2%. These findings are different from Western world patterns which experienced a decrease in incidence and proximal shift of the colon cancer localization. This might be due to better diagnostic tools, population awareness of the disease, as well as changing of life style and/or food habits in the region.

Keywords: colorectal cancer, Hail Region, changing pattern, distal shift

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