Search results for: machine capacity

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, José J. Hernández-Flores, Edith Olaco Garcia

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The Project Scheduling Problem (PSP) is a generic name given to a whole class of problems in which the best form, time, resources and costs for project scheduling are necessary. The PSP is an application area related to the project management. This paper aims at being a guide to understand PSP by presenting a survey of the general parameters of PSP: the Resources (those elements that realize the activities of a project), and the Activities (set of operations or own tasks of a person or organization); the mathematical models of the main variants of PSP and the algorithms used to solve the variants of the PSP. The project scheduling is an important task in project management. This paper contains mathematical models, resources, activities, and algorithms of project scheduling problems. The project scheduling problem has attracted researchers of the automotive industry, steel manufacturer, medical research, pharmaceutical research, telecommunication, industry, aviation industry, development of the software, manufacturing management, innovation and technology management, construction industry, government project management, financial services, machine scheduling, transportation management, and others. The project managers need to finish a project with the minimum cost and the maximum quality.

Keywords: PSP, Combinatorial Optimization Problems, Project Management; Manufacturing Management, Technology Management.

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Authors: Aneri Mehta, Krunal Mehta

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Administration is largely based on two sciences: ‘management science’ and ‘political science’. The approach of new public management is more inclined towards the management science. Era of ‘New Public Management’ has affected the developing countries very immensely. Public management reforms are needed to enhance the development of the countries. This reform mainly includes capacity building, control of corruption, political decentralization, debureaucratization and public empowerment. This gives the opportunity to create self-sustaining change in the governance. This paper includes the link of approach of new public management and their effect on building effective democratization in the country. This approach mainly focuses on rationality and effectiveness of governance system. These need to have deep efforts on technological, organizational, social and cultural fields. Bringing citizen participation in governance is main objective of NPM. The shift from traditional public management to new public management have low success rate of reforms. This research includes case study of RTI which is a big step of government towards citizen centric approach of governance. The aspect of ‘publicness’ in the democratic policy implementation is important for good governance in India.

Keywords: public management, development, public empowerment, governance

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Authors: Terence Tumolva, Johannes Kristoff Vito, Joanna Crystelle Ragasa, Renz Marion Dela Cruz

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Natural fiber reinforced polymer (NFRP) composites have been the focus of various research projects due to their advantages over synthetic fiber-reinforced composites. For this study, ana haw is used as the fiber source due to its abundance throughout the Philippines. A problem addressed in this study is the need for an environment-friendly method of fiber treatment. The use of sodium alginate to treat fibers was thus investigated. The fibers were immersed in a sodium alginate solution and then in a calcium chloride solution afterwards. The treated fibers were used to reinforce orthophthalic unsaturated polyester (ortho-UP) resin. The mechanical properties were tested using a universal testing machine (UTM), and the fracture surfaces were characterized using scanning electron microscope (SEM). Results showed that the sodium alginate treatment had increased the tensile and flexural strength of the composite. The increase in fiber load had also been found to increase the stiffness of the composite. However, sodium alginate treatment did not provide any significant improvement in the wet mechanical properties of the NFRP. The composite is comparable to some commercially available polymeric materials.

Keywords: NFRP, composite, alginate, anahaw, polymer

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Authors: Christopher Lama, Alix Rieser, Aleksandra Molchanova, Charles Thangaraj

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New technologies like Tesla’s Dojo have made high-performance embedded computing more available. Although automobile computing has developed and benefited enormously from these more recent technologies, the costs are still high, prohibitively high in some cases for broader adaptation, particularly for the after-market and enthusiast markets. This project aims to implement a Raspberry Pi-based low-power (under one hundred Watts) highly mobile computing cluster for a neural network. The computing cluster built from off-the-shelf components is more affordable and, therefore, makes wider adoption possible. The paper describes the design of the neural network, Raspberry Pi-based cluster, and applications the cluster will run. The neural network will use input data from sensors and cameras to project a live view of the road state as the user drives. The neural network will be trained to predict traffic behavior and generate warnings when potentially dangerous situations are predicted. The significant outcomes of this study will be two folds, firstly, to implement and test the low-cost cluster, and secondly, to ascertain the effectiveness of the predictive AI implemented on the cluster.

Keywords: CS pedagogy, student research, cluster computing, machine learning

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Authors: Leonardo C. Pacheco-Londoño, Nataly J. Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta, Elkin Navarro, Gustavo Aroca-Martínez, Karin Rondón-Payares, Samuel P. Hernández-Rivera

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In our Life Science Research Center of the University Simon Bolivar (LSRC), one of the focuses is the diagnosis and prognosis of different diseases; we have been implementing the use of gold nanoparticles (Au-NPs) for various biomedical applications. In this case, Au-NPs were used for Surface-Enhanced Raman Spectroscopy (SERS) in different diseases' diagnostics, such as Lupus Nephritis (LN), hypertension (H), preeclampsia (PC), and others. This methodology is proposed for the diagnosis of each disease. First, good signals of the different metabolites by SERS were obtained through a mixture of urine samples and Au-NPs. Second, PLS-DA models based on SERS spectra to discriminate each disease were able to differentiate between sick and healthy patients with different diseases. Finally, the sensibility and specificity for the different models were determined in the order of 0.9. On the other hand, a second methodology was developed using machine learning models from all data of the different diseases, and, as a result, a discriminant spectral map of the diseases was generated. These studies were possible thanks to joint research between two university research centers and two health sector entities, and the patient samples were treated with ethical rigor and their consent.

Keywords: SERS, Raman, PLS-DA, diseases

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Authors: Bienvenu Gael Fouda Mbanga, Zikhona Tywabi-Ngeva, Kriveshini Pillay

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This work highlighted a new method for preparing Nitrogen carbon nanoparticles fused on zinc oxide nanoparticle nanocomposite (N-CNPs/ZnONPsNC) to remove copper ions (Cu²+) from wastewater by sol-gel method and applying the metal-loaded adsorbent in latent fingerprint application. The N-CNPs/ZnONPsNC showed to be an effective sorbent for optimum Cu²+ sorption at pH 8 and 0.05 g dose. The Langmuir isotherm was found to best fit the process, with a maximum adsorption capacity of 285.71 mg/g, which was higher than most values found in other research for Cu²+ removal. Adsorption was spontaneous and endothermic at 25oC. In addition, the Cu²+-N-CNPs/ZnONPsNC was found to be sensitive and selective for latent fingerprint (LFP) recognition on a range of porous surfaces. As a result, in forensic research, it is an effective distinguishing chemical for latent fingerprint detection.

Keywords: latent fingerprint, nanocomposite, adsorption, copper ions, metal loaded adsorption, adsorbent

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: Harun Sepet, Necmettin Tarakcioglu

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The present study investigated the impact strength and fracture mechanism of nano-CaCO3 and nanoclay reinforced HDPE nanocomposites by using Charpy impact test. The nano-CaCO3 and nanoclay reinforced HDPE granules were prepared by the melt blending method using a compounder system, which consists of industrial banbury mixer, single screw extruder and granule cutting in industrial-scale. The nano-CaCO3 and nanoclay reinforced HDPE granules were molded using an injection-molding machine as plates, and then impact samples were cut by using punching die from the nanocomposite plates. As a result of impact experiments, nano-CaCO3 and nanoclay reinforced HDPE nanocomposites were determined to have lower impact energy level than neat HDPE. Also, the impact strength of HDPE further decreased by addition nanoclay compared to nano-CaCO3. The occurred fracture areas with the impact were detected by SEM examination. It is understood that fracture surface morphology changes when nano-CaCO3 and nanoclay ratio increases. The fracture surface changes were examined to determine the fracture mechanism of nano-CaCO3 and nanoclay reinforced HDPE nanocomposites.

Keywords: charpy, HDPE, industrial scale nano-CaCO3, nanoclay, nanocomposite

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Authors: Shaghayegh Shajari, Mehdi Mahmoodi, Mahmood Rajabian, Uttandaraman Sundararaj, Les J. Sudak

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Although several strain sensors based on carbon nanotubes (CNTs) have been reported, the stretchability and sensitivity of these sensors have remained as a challenge. Highly stretchable and sensitive strain sensors are in great demand for human motion monitoring and human-machine interface. This paper reports the fabrication and characterization of a new type of strain sensors based on a stretchable fluoropolymer / CNT nanocomposite system made via melt-mixing technique. Electrical and mechanical characterizations were obtained. The results showed that this nanocomposite sensor has high stretchability up to 280% of strain at an optimum level of filler concentration. The piezoresistive properties and the strain sensing mechanism of the strain sensor were investigated using Electrochemical Impedance Spectroscopy (EIS). High sensitivity was obtained (gauge factor as large as 12000 under 120% applied strain) in particular at the concentrations above the percolation threshold. Due to the tunneling effect, a non- linear piezoresistivity was observed at high concentrations of CNT loading. The nanocomposites with good conductivity and lightweight could be a promising candidate for strain sensing applications.

Keywords: carbon nanotubes, fluoropolymer, piezoresistive, strain sensor

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Authors: Gwanghee Heo, Geonhyeok Bang, Chunggil Kim, Chinok Lee

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This paper attempts to develop a wireless feedback control system as a primary step eventually toward a bio-inspired structure system where inanimate structure behaves like a life form autonomously. It is a standalone wireless control system which is supposed to measure externally caused structural responses, analyze structural state from acquired data, and take its own action on the basis of the analysis with an embedded logic. For an experimental examination of its effectiveness, we applied it on a model of two-span bridge and performed a wireless control test. Experimental tests have been conducted for comparison on both the wireless and the wired system under the conditions of Un-control, Passive-off, Passive-on, and Lyapunov control algorithm. By proving the congruence of the test result of the wireless feedback control system with the wired control system, its control performance was proven to be effective. Besides, it was found to be economical in energy consumption and also autonomous by means of a command algorithm embedded into it, which proves its basic capacity as a bio-inspired system.

Keywords: structural vibration control, wireless system, MR damper, feedback control, embedded system

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Authors: Fernando G. Torres, Omar P. Troncoso

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Quercetin is a naturally occurring polyphenol found in many vegetables, such as onion, with antioxidant properties. It is a dietary component with a documented role in reducing different human cancers. However, its low bioavailability, poor water solubility, and chemical instability limit its applications. Different nano-delivery systems such as nanoparticles, micelles, and nanohydrogels have been studied in order to improve the bioavailability of quercetin. Nanoparticles based on natural polymers such as starch have the advantage of being biocompatible, biodegradable, and non-toxic. In this study, quercetin was loaded into starch nanoparticles using a nanoprecipitation method. Different routes, using sodium tripolyphosphate and Tween® 80 as tensioactive agents, were tested in order to obtain an optimized starch-based nano-delivery system. The characterization of the nanoparticles loaded with quercetin was assessed by Fourier Transform Infrared Spectroscopy, Dynamic Light Scattering, Zeta potential, and Differential scanning calorimetry. UV-vis spectrophotometry was used to evaluate the loading efficiency and capacity of the samples. The results showed that starch-based systems could be successfully used for the nano-delivery of quercetin.

Keywords: starch nanoparticles, nanoprecipitation, quercetin, biomedical applications

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Authors: Alan Bhekisisa Buthelezi

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The aim of this paper is to explore African management and leadership philosophies at secondary schools in post-apartheid South Africa. The research was conducted in the King Cetshwayo district of KwaZulu-Natal province in South Africa. Apart from the literature on participative management, the paper reports on a research in which an empirical investigation based on a quantitative research paradigm was used to collect data from secondary school principals. The literature findings revealed that secondary school principals need to rethink their management and leadership philosophies in the twenty-first century. The findings of this research further reveal that ubuntu (humanness) and lekgotla (Sesotho term for “an African participatory approach to decision-making”) should be embedded in the art of school management and leadership in the South African context. The paper concludes with the submission that ongoing capacity-building workshops should be fast-tracked on matters pertaining to management and leadership.

Keywords: distributed leadership, team leadership, decentralization of power, transformational leadership

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Authors: Abisola Akinola, Akinsulere Femi

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The stock market has continually been a source of economic development in most developing countries. This study examined the relationship between investors’ ratio analysis and profitability of quoted companies in Nigeria using secondary data obtained from the annual reports of forty-two (42) companies. The study employed the multiple regression technique to analyze the relationship between investors’ ratio analysis (measured by dividend per share and earning per share) and profitability (measured by the return on equity). The results from the analysis show that investors’ ratio analysis, when measured by earnings per share, have a positive and significant impact on profitability. However, the study noted that investors’ ratio analysis, when measured by dividend per share, tend to have a positive impact on profitability but it is statistically insignificant. By implication, investors and other stakeholders that are interested in investing in stocks can predict the earning capacity of listed firms in the stock market.

Keywords: dividend per share, earnings per share, profitability, return on equity

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Authors: Vincent Otieno, Alfred Agwanda, Anne Khasakhala

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Among the neo-Malthusian adherents, it is believed that rapid population growth strain countries’ capacity and performance. Fertility have however decelerated in most of the countries in the recent past. Scholars have concentrated on wide range of factors associated with fertility majorly at the national scale with some opining that analysis of trends and differentials in the various fertility parameters have been discussed extensively. However, others believe that considerably less attention has been paid to the fertility preference- a pathway through which various variables act on fertility. The Sub-Saharan African countries’ disparities amid almost similarities in policies is a cause of concern to demographers. One would point at the meager synergies that have been focused on the fertility preference as well, especially at the macro scale. Using Bongaarts reformulation of Easterlin and Crimmins (1985) conceptual scheme, the understanding of the current transition based on the fertility preference in general would help to provide explanations to the observed latest dynamics. This study therefore is an attempt to explain the current fertility transition through women’s fertility preference. Results reveal that indeed fertility transition is on course in most of the sub-Saharan countries with huge disparities in fertility preferences and its implementation indices.

Keywords: fertility preference, the degree of implementation index, sub-Saharan Africa, transition

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: Sultan Daud, John P. Forth, Nikolaos Nikitas

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The current study aims to highlight the loading characteristics impact on the time evolution (focusing particularly on long term effects) of the deformation of realized reinforced concrete beams. Namely the tension stiffening code provisions (i.e. within Eurocode 2) are reviewed with a clear intention to reassess their operational value and predicting capacity. In what follows the experimental programme adopted along with some preliminary findings and numerical modelling attempts are presented. For a range of long slender reinforced concrete simply supported beams (4200 mm) constant static sustained and repeated cyclic loadings were applied mapping the time evolution of deformation. All experiments were carried out at the Heavy Structures Lab of the University of Leeds. During tests the mid-span deflection, creep coefficient and shrinkage strains were monitored for duration of 90 days. The obtained results are set against the values predicted by Eurocode 2 and the tools within an FE commercial package (i.e. Midas FEA) to yield that existing knowledge and practise is at times over-conservative.

Keywords: Eurocode2, midas fea, repeated, sustained loading.

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Authors: Noor Zainab Habib, Ibrahim Kamaruddin, Madzlan Napiah

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This paper present a part of research conducted to investigate the creep behavior of bituminous concrete mixture prepared with well graded using the dynamic creep test. The samples were prepared from unmodified control mix and Polypropylene modified bituminous mix. Unmodified or control mix was prepared with 80/100 grade bitumen while polypropylene modified mix was prepared using polypropylene PP polymer as modifier, blended with 80/100 Pen bitumen. The concentration of polymer in the blend was kept at 1%, 2%, and 3% by weight of bitumen content. For Dynamic Creep Test, Marshall Specimen were prepared at optimum bitumen content and then tested using IPC Global Universal Testing Machine (UTM), in order to investigate the creep stiffness of both modified and control mix. From the results obtained it was found that 1% and 2% PP modified bituminous mix offer better results in comparison to control and 3% PP modified mix samples. The results verify all the findings of empirical and viscosity test results which indicates that polymer modification induces stiffening effect in the binder. Enhanced viscous component of the binder was considered responsible for this change which eventually enhances the mechanical strength of the modified bituminous mixes.

Keywords: polymer modified bitumen, stiffness, creep, viscosity

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Authors: Neziha Jaouedi, Noureddine Boujnah, Mohamed Salim Bouhlel

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In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression). It’s worth noting that many information is hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. These models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human activity. Each modality is used to recognize a human action using wavelets of derived beta distributions approach. The proposed approach has been validated successfully on a subset of KTH and UCF sports database.

Keywords: feautures extraction, human action classifier, wavelet neural network, beta wavelet

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Authors: Farrah Putri Salmanida, Mei-Li Wu, Rika Wahyuningtyas, Wen-Bin Chung, Hso-Chi Chaung, Ko-Tung Chang

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Within the field of immunotherapy, oncolytic virotherapy (OVT) employs dual approaches that directly eliminate tumor cells while preserving healthy ones and indirectly reprogram the tumor microenvironment (TME) to elicit antitumor responses. Within the TME, tumor associated macrophages (TAMs) manifest characteristics akin to those of anti-inflammatory M2 macrophages, thus earning the designation of M2-like TAMs. In prior research, two antigens denoted as A1 (g6Ld10T) and A3 (ORF6L5), derived from a complete sequence of ORF5 with partial sequence of ORF6 in Porcine Reproductive and Respiratory Syndrome Virus Genotype 2 (PRRSV-2), demonstrated the capacity to repolarize M2-type porcine alveolar macrophages (PAMs) into M1 phenotypes. In this study, we sought for utilizing OVT strategies by introducing A1 or A3 on TAMs to endow them with the anti-tumor traits of M1 macrophages while retaining their capacity to target cancer cells. Upon exposing human THP-1-derived M2 macrophages to a cross-species test with 2 µg/ml of either A1 or A3 for 24 hours, real time PCR revealed that A3, but not A1, treated cells exhibited upregulated gene expressions of M1 markers (CCR7, IL-1ß, CCL2, Cox2, CD80). These cells reacted to virus-derived antigen, as evidenced by increased expression of pattern-recognition receptors TLR3, TLR7, and TLR9, subsequently providing feedback in the form of type I interferon responses like IFNAR1, IFN-ß, IRF3, IRF7, OAS1, Mx1, and ISG15. Through an MTT assay, only after 15 µg/ml of A3 treatment could the cell viability decrease, with a predicted IC50 of 16.96 µg/ml. Interestingly, A3 caused dose-dependent toxicity to a rat C6 glial cancer cell line even at doses as low as 2.5 µg/ml and reached its IC50 at 9.419 µg/ml. Using Annexin V/7AAD staining and PCR test, we deduced that a significant proportion of C6 cells were undergoing the early apoptosis phase predominantly through the intrinsic apoptosis cascade involving Bcl-2 family proteins. Following this stage, we conducted a test on A3’s repolarization ability, which revealed a significant rise in M1 gene expression markers, such as TNF, CD80, and IL-1ß, in M2-like TAMs generated in vitro from murine RAW264.7 macrophages grown with conditioned medium of 4T1 breast cancer cells. This was corroborated by the results of transcriptome analysis, which revealed that the primary subset among the top 10 to top 30 significantly upregulated differentially expressed genes (DEGs) dominantly consisted of M1 macrophages profiles, including Ccl3, Ccl4, Csf3, TNF, Bcl6b, Stc1, and Dusp2. Our findings unveiled the remarkable potential of the PRRSV-derived antigen A3 to repolarize macrophages while also being capable of selectively inducing apoptosis in cancerous cells. While further in vivo study is needed for A3, it holds promise as an adjuvant by its dual effects in cancer therapy modalities.

Keywords: cancer cell apoptosis, interferon responses, macrophage repolarization, recombinant protein

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

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With the development of virtualization technologies, a new type of service named cloud computing service is produced. Cloud users usually encounter the problem of how to use the virtualized platform easily over the web without requiring the plug-in or installation of special software. The object of this paper is to develop a system and a method enabling process interfacing within an automation scenario for accessing remote application by using the web browser. To meet this challenge, we have devised a web-based interface that system has allowed to shift the GUI application from the traditional local environment to the cloud platform, which is stored on the remote virtual machine. We designed the sketch of web interface following the cloud virtualization concept that sought to enable communication and collaboration among users. We describe the design requirements of remote application technology and present implementation details of the web application and its associated components. We conclude that this effort has the potential to provide an elastic and resilience environment for several application services. Users no longer have to burden the system maintenances and reduce the overall cost of software licenses and hardware. Moreover, this remote application service represents the next step to the mobile workplace, and it lets user to use the remote application virtually from anywhere.

Keywords: virtualization technology, virtualized platform, web interface, remote application

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Authors: Ning Xue, Srinivas Merugu, Ignacio Delgado Martinez, Tao Sun, John Tsang, Shih-Cheng Yen

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We have developed a polyimide based neural interface electrode to record nerve signals from the sciatic nerve of a rat. The neural interface electrode has a split-ring shape, with four protruding gold electrodes for recording, and two reference gold electrodes around the split-ring. The split-ring electrode can be opened up to encircle the sciatic nerve. The four electrodes can be bent to sit on top of the nerve and hold the device in position, while the split-ring frame remains flat. In comparison, while traditional cuff electrodes can only fit certain sizes of the nerve, the developed device can fit a variety of rat sciatic nerve dimensions from 0.6 mm to 1.0 mm, and adapt to the chronic changes in the nerve as the electrode tips are bendable. The electrochemical impedance spectroscopy measurement was conducted. The gold electrode impedance is on the order of 10 kΩ, showing excellent charge injection capacity to record neural signals.

Keywords: impedance, neural interface, split-ring electrode, neural signal recording

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Authors: K. Rattawan, W. Intagun, W. Kanoksilapatham

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Objective of this research is to study effect of coffee grounds on physical and heating value properties of sugarcane bagasse pellets. The coffee grounds were tested as an additive for pelletizing process of bagasse pellets. Pelletizing was performed using a Flat–die pellet mill machine. Moisture content of raw materials was controlled at 10-13%. Die temperature range during the process was 75-80 ^oC. Physical characteristics (bulk density and durability) of the bagasse pellet and pellets with 1-5% coffee ground were determined following the standard assigned by the Pellet Fuel Institute (PFI). The results revealed increasing values of 648±3.4, 659 ± 3.1, 679 ± 3.3 and 685 ± 3.1 kg/m³ (for pellet bulk density); and 98.7 ± 0.11, 99.2 ± 0.26, 99.3 ± 0.19 and 99.4 ± 0.07% (for pellet durability), respectively. In addition, the heating values of the coffee ground supplemented pellets (15.9 ± 1.16, 17.0 ± 1.23 and 18.8 ± 1.34 MJ/kg) were improved comparing to the non-supplemented control (14.9 ± 1.14 MJ/kg), respectively. The results indicated that both the bulk density and durability values of the bagasse pellets were increased with the increasing proportion of the coffee ground additive.

Keywords: bagasse, coffee grounds, pelletizing, heating value, sugar cane bagasse

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Authors: Ahmed Al-Saadi, Ali Hassanpour, Tariq Mahmud

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The main objective of this study is to investigate ways to reduce the aerodynamic drag coefficient and to increase the stability of the full-size Sport Utility Vehicle using three-dimensional Computational Fluid Dynamics (CFD) simulation. The baseline model in the simulation was the Land Rover Discovery 4. Many aerodynamic devices and external design modifications were used in this study. These reduction aerodynamic techniques were tested individually or in combination to get the best design. All new models have the same capacity and comfort of the baseline model. Uniform freestream velocity of the air at inlet ranging from 28 m/s to 40 m/s was used. ANSYS Fluent software (version 16.0) was used to simulate all models. The drag coefficient obtained from the ANSYS Fluent for the baseline model was validated with experimental data. It is found that the use of modern aerodynamic add-on devices and modifications has a significant effect in reducing the aerodynamic drag coefficient.

Keywords: aerodynamics, RANS, sport utility vehicle, turbulent flow

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: Sunil Chaudhary, Rajendra Bahadur Thapa, Eleni Berki, Marko Helenius

Abstract:

The increasing number of Internet and mobile phone users, and essentially those, who use these electronic media to perform online transactions makes Nepal lucrative for phishing attacks. It is one of the reasons behind escalating phishing attacks in the country. Therefore, in this paper we examine various phishing attempts and real scenarios in Nepal to determine the seriousness of the problem. We also want to find out how prepared are the Internet and mobile phone users and how well-equipped are the private sector and government authorities responsible to handle cybercrime in the country. We considered five areas of research study, i.e., legal measures, technical and procedural measures, organizational structure, capacity building and international cooperation. These constitute important factors in cyber security and are recommended by the Global Cyber security Agenda (GCA). On the basis of our findings, we provide essential suggestions to make anti-phishing measures more appropriate to Nepalese State and society.

Keywords: internet banking, mobile banking, e-commerce, phishing, anti-phishing, Nepal

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Authors: Surinder Deswal, Mahesh Pal

Abstract:

The paper investigates the potential of support vector machines based regression approach to model the mass transfer capacity of multiple plunging jets, both vertical (θ = 90°) and inclined (θ = 60°). The data set used in this study consists of four input parameters with a total of eighty eight cases. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 (root mean square error values of 0.0025 and 0.0020) were achieved by using polynomial and radial basis kernel functions based support vector regression respectively. Results suggest an improved performance by radial basis function in comparison to polynomial kernel based support vector machines. The estimated overall mass transfer coefficient, by both the kernel functions, is in good agreement with actual experimental values (within a scatter of ±15 %); thereby suggesting the utility of support vector machines based regression approach.

Keywords: mass transfer, multiple plunging jets, support vector machines, ecological sciences

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Authors: Raied, Badr Al-Fulaiti, E. I. El-Shafey

Abstract:

Cyclodextrin (CD) derivatives (αCD, βCD, ϒCD and hp-βCD) were successfully immobilized on silica gel surface via epichlorohydrin as a cross linker. The ratio of silica to CD was optimized in preliminary experiments based on best performance of iodine adsorption capacity. Selected adsorbents with ratios of silica to CD derivatives, in this study, include Si-αCD (3:2), Si-βCD (4:1), Si-ϒCD (4:1) and Si-hp-βCD (4:1). The adsorption of iodine (I2/KI) solution was investigated in terms of initial pH, contact time, iodine concentration and temperature. No significant variations was noticed for iodine adsorption at different pH values, thus, initial pH 6 was selected for further studies. Equilibrium adsorption was reached faster on Si-hp-βCD than other adsorbents with kinetic adsorption data fitting well pseudo second order model. Activation energy (Ea) was found to be in the range of 12.7 - 23.4 kJ/mol. Equilibrium adsorption data were found to fit well the Langmuir adsorption model with lower uptake as temperature rises. Iodine uptake follows the order: Si-hp-βCD (714 mg/g) >Si-αCD (625 mg/g) >Si-βCD (555.6 mg/g)> Si-ϒCD (435 mg/g). Thermodynamic study showed that iodine adsorption is exothermic and spontaneous. Adsorbents reuse exhibited excellent performance for iodine adsorption with a decrease in iodine uptake of ~ 2- 4 % in the third adsorption cycle.

Keywords: adsorption, iodine, silica, cyclodextrin, functionalization, epichlorohydrin

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Authors: Getachew Demeissie Ayalew, Yongtao Sun, Yang Yang

Abstract:

The spiral welded pipe manufacturing industry requires strict production standards for automated grinders for welding seams. However, traditional grinding machines in this sector are insufficient due to a lack of quality control protocols and inconsistent performance. This research aims to improve the quality of spiral welded pipes by developing intelligent automated abrasive belt grinding equipment. The system has equipped with six degrees of freedom (6 DOF) KUKA KR360 industrial robots, enabling concurrent grinding operations on both internal and external welds. The grinding robot control system is designed with a PLC, and a human-machine interface (HMI) system is employed for operations. The system includes an electric speed controller, data connection card, DC driver, analog amplifier, and HMI for input data. This control system enables the grinding of spiral welded pipe. It ensures consistent production quality and cost-effectiveness by reducing the product life cycle and minimizing risks in the working environment.

Keywords: Intelligent Systems, Spiral Welded Pipe, Grinding, Industrial Robot, End-Effector, PLC Controller System, 3D Laser Sensor, HMI.

Procedia PDF Downloads 281