Search results for: automated container terminal

Authors: Masato Saeki

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Presented herein is a novel algorithms for calculating the damping performance of particle dampers. The particle damper is a passive vibration control technique and has many practical applications due to simple design. It consists of granular materials constrained to move between two ends in the cavity of a primary vibrating system. The damping effect results from the exchange of momentum during the impact of granular materials against the wall of the cavity. This damping has the advantage of being independent of the environment. Therefore, particle damping can be applied in extreme temperature environments, where most conventional dampers would fail. It was shown experimentally in many papers that the efficiency of the particle dampers is high in the case of resonant vibration. In order to use the particle dampers effectively, it is necessary to solve the equations of motion for each particle, considering the granularity. The discrete element method (DEM) has been found to be effective for revealing the dynamics of particle damping. In this method, individual particles are assumed as rigid body and interparticle collisions are modeled by mechanical elements as springs and dashpots. However, the computational cost is significant since the equation of motion for each particle must be solved at each time step. In order to improve the computational efficiency of the DEM, the new algorithms are needed. In this study, new algorithms are proposed for implementing the high performance DEM. On the assumption that behaviors of the granular particles in the each divided area of the damper container are the same, the contact force of the primary system with all particles can be considered to be equal to the product of the divided number of the damper area and the contact force of the primary system with granular materials per divided area. This convenience makes it possible to considerably reduce the calculation time. The validity of this calculation method was investigated and the calculated results were compared with the experimental ones. This paper also presents the results of experimental studies of the performance of particle dampers. It is shown that the particle radius affect the noise level. It is also shown that the particle size and the particle material influence the damper performance.

Keywords: particle damping, discrete element method (DEM), granular materials, numerical analysis, equivalent noise level

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Authors: Seung Yoon Hyun, Hyeong Seung An, Myeong Ho Choi, Sung Hwan Bae, Yu Jong Sim

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In 2015, the southern part of the Korean Peninsula has 8.6 million poles, 1.25 million km power lines, and 2 million transformers, etc. It is the massive amount of distribution equipments which could cover a round-trip distance from the earth to the moon and 11 turns around the earth. These distribution equipments are spread out like capillaries and supplying power to every corner of the Korean Peninsula. In order to manage these huge power facility efficiently, KEPCO use DAS (Distribution Automation System) to operate distribution power system since 1997. DAS is integrated system that enables to remotely supervise and control breakers and switches on distribution network. Using DAS, we can reduce outage time and power loss. KEPCO has about 160,000 switches, 50%(about 80,000) of switches are automated, and 41 distribution center monitoring&control these switches 24-hour 365 days to get the best efficiency of distribution networks. However, the rapid increasing renewable energy sources become the problem in the efficient operation of distributed power system. (currently 2,400 MW, 75,000 generators operate in distribution power system). In this paper, it suggests the way to interconnect between renewable energy source and distribution power system.

Keywords: distribution, renewable, connect, DAS (Distribution Automation System)

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Authors: Jahangir Ahmad Rather, Emad A. Khudaish, Ahsanulhaq Qurashi, Palanisamy Kannan

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Chemical modification and assembling of fullerenes are fundamentally important for the application of fullerenes as functional molecules and in molecular devices and organic electronic devices. We have synthesized fullerene nanorods C60NRs conjugate via liquid-liquid interface and the synthesized C60NRs was characterized by FTIR spectroscopy, field emission electron microscopy (FESEM) and X-ray diffraction techniques. The C60NRs were immobilized on glassy carbon electrode via surface bound diazonium salts as an impact strategy. This method involves electrografting of p–nitrophenyl to give GCE–Ph–NO2 and then the terminal nitro-group was chemically reduced to GCE–Ph–NH2 in a presence of sodium borohydride/gold–polyaniline nanocomposite (NaBH4/Au–PANI). The Au–PANI composite was synthesized and characterized by FTIR, UV-vis, SEM and EDX techniques. The C60NRs were immobilized on GCE–Ph–NH2 via amination reaction which involves N-H addition across a π-bond on [60] fullerene. The immobilized C60NRs/GCE was subjected to electrochemical reduction in 1.0 M KOH to yield ERC60NRs/GCE sensor. The developed sensor shows high electrocatalytic activity for the detection of ethylparaben (EP) over a concentration range from 0.01 to 0.52 µM with a detection limit (LOD) 3.8 nM. The amount of EP present in the nourishing repair cream (OlAY®) was determined by standard addition method at the developed ERC60NRs/GCE sensor. The total concentration of EP was found to be 0.011 µM (0.1%) and is within the permissible limit of 0.19 % EP in cosmetics according to the European scientific committee (SCCS) on consumer safety on 22 March 2011 (SCCS/1348/11).

Keywords: diazonium salt reduction, ethylparaben (EP), endocrine disruptor, fullerene nanorods (C60NRs), gold–polyaniline nanocomposite (Au–PANI)

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: Tety Widyaningrum, Sapnah Rahmawati, Abdulmuluk Attim

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Space was a container that includes land space, sea space and air space, including space in the earth as a whole region, where humans and other living creatures, operate and maintain its survival. Whereas spatial planning was a form of the structure of space and spatial pattern. At this time, the arrangement of space became a matter of considerable concern because through spatial planning was what will determine how the future city hall, how the welfare of the population that is in it, and how space can be a comfortable space to live. This spatial arrangement became a subject that must be considered not only by the Government as policy makers but also of concern to the entire community in it. As a place to stay, this space should be able to ensure the safety and comfort of the whole community, even people with disabilities, though. For development and spatial planning in Indonesia. It was still very low which was still concerned about the disabled. The spatial arrangement made generalizations. This caused the right for disabled people was less fulfilled. In accordance with the Declaration on the Rights of Persons with Disabilities who explains that people with disabilities had the right to be able to facilitate their efforts to become self-sufficient or not depends on the other party. It was also strengthened by According to the Law of the Republic of Indonesia No. 4 of 1997 on Persons with Disabilities; disabilities were part of the Indonesian people who had the status, rights, obligations and the same role with other Indonesian community in all aspects of life and livelihood. As observed, during the disabled were still used as objects that hadn’t been involved in the formulation of development planning of space in Indonesia, so the infrastructure space was still very far from the concept of friendly to the disabled. As an example of a sidewalk in Indonesia were still in bad condition, potholes, and uneven and don’t meet the eligibility standards. In addition, there were sidewalks that abused become a trade causing run down and chaotic atmosphere. In addition, pedestrians are also disturbed because the sidewalks were often still used as a parking lot or flowers to decorate the layout of the city, so the legroom was becoming increasingly limited. The development of infrastructure for pedestrians was also still concerned with aspects of aesthetic than functional. Therefore, the participation of disabled people must be involved in spatial planning exist. It aims to achieve spatial and environmentally friendly to the disabled. These dream space activities carried out by giving questionnaires and the dream images to the disabled about how the layout of the space they want what they want and what development was also in line with the principle of their convenience. This then will be taken into consideration for government in planning layout that was friendly to the whole community.

Keywords: diffable, aspiration, spatial, planning

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Authors: D. Bhowmik, Y. Tian, Q. Yin, F. Zhu

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Cyclic GMP-AMP synthase (cGAS), recognises cytoplasmic double-stranded DNA (dsDNA), indicative of bacterial and viral infections, as well as the leakage of self DNA by cellular dysfunction and stresses, to elicit the host's immune responses. Viruses also have developed numerous strategies to antagonize the cGAS-STING pathway. Kaposi's sarcoma-associated herpesvirus (KSHV) is a human DNA tumor virus that is the causative agent of Kaposi’s sarcoma and several other malignancies. To persist in the host, consequently causing diseases, KSHV must overcome the host innate immune responses, including the cGAS-STING DNA sensing pathway. We already found that ORF52 or KicGAS (KSHV inhibitor of cGAS), an abundant and basic gamma herpesvirus-conserved tegument protein, directly inhibits cGAS enzymatic activity. To better understand the mechanism, we have performed the biochemical and structural characterization of full-length KicGAS and various mutants in regarding binding to DNA. We observed that KicGAS is capable of self-association and identified the critical residues involved in the oligomerization process. We also characterized the DNA-binding of KicGAS and found that KicGAS cooperatively oligomerizes along the length of the double stranded DNA, the highly conserved basic residues at the c-terminal disordered region are crucial for DNA recognition. Deficiency in oligomerization also affects DNA binding. Thus DNA binding by KicGAS sequesters DNA and prevents it from being detected by cGAS, consequently inhibiting cGAS activation. KicGAS homologues also inhibit cGAS efficiently, suggesting inhibition of cGAS is evolutionarily conserved mechanism among gamma herpesvirus. These results highlight the important viral strategy to evade this innate immune sensor.

Keywords: Kaposi's sarcoma-associated herpesvirus, KSHV, cGAS, DNA binding, inhibition

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Authors: Gopi Kandaswamy, P. Balamuralidhar

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Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: fault detection, health monitoring, unmanned aerial vehicles, vibration analysis

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Authors: Ntungamili Kenosi, Moatlhodi W. Letshwenyo

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Negative environmental impacts due to construction of large projects such as dams have become an important aspect of land degradation. This paper will review the previous literature on the previous researches or study in the same area of study in the other parts of the world. After dam has been constructed, the actual environmental impacts are investigated and compared to the predicted results of the carried out Environmental Impact Assessment. GIS and Remote Sensing, play an important role in generating automated spatial data sets and in establishing spatial relationships. Results from other sources shows that the normalized vegetation index (NDVI) analysis was used to detect the spatial and temporal change of vegetation biomass in the study area. The result indicated that the natural vegetation biomass is declining. This is mainly due to the expansion of agricultural land and escalating human made structures in the area. Urgent environmental conservation is necessary when adjoining projects site. Less study on the evaluation of EIA on dam has been conducted in Botswana hence there is a need for the same study to be conducted and then it will be easy to be compared to other studies around the world.

Keywords: Botswana, dam, environmental impact assessment, GIS, normalized vegetation index (NDVI), remote sensing

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Authors: Tokihiko Akita, Seiichi Mita

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A millimeter-wave radar is the most robust against adverse environments, making it an essential environment recognition sensor for automated driving. However, the reflection signal is sparse and unstable, so it is difficult to obtain the high recognition accuracy. Deep learning provides high accuracy even for them in recognition, but requires large scale datasets with ground truth. Specially, it takes a lot of cost to annotate for a millimeter-wave radar. For the solution, utilizing a simulator that can generate an annotated huge dataset is effective. Simulation of the radar is more difficult to match with real world data than camera image, and recognition by deep learning with higher-order features using the simulator causes further deviation. We have challenged to improve the accuracy of traffic participant classification by fusing simulator and real-world data with domain adaptation technique. Experimental results with the domain adaptation network created by us show that classification accuracy can be improved even with a few real-world data.

Keywords: millimeter-wave radar, object classification, deep learning, simulation, domain adaptation

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Authors: Ruilian Zhao, Shukai Zhang, Yan Wang, Weiwei Wang

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Repairing broken test cases is an expensive and challenging task in evolving software systems. Although an automated repair technique with intent preservation has been proposed, but it does not take into account the association between test repairs and assertions, leading to a large number of irrelevant candidates and decreasing the repair capability. This paper proposes an assertion-driven test repair approach. Furthermore, an intent-oriented priority criterion is raised to guide the repair candidate generation, making the repairs closer to the intent of the test. In more detail, repair targets are determined through post-dominance relations between assertions and the methods that directly cause compilation errors. Then, test repairs are generated from the target in a bottom-up way, guided by the intent-oriented priority criteria. Finally, the generated repair candidates are prioritized to match the original test intent. The approach is implemented and evaluated on the benchmark of 4 open-source programs and 91 broken test cases. The result shows that the approach can fix 89% (81/91) of broken test cases, which is more effective than the existing intentpreserved test repair approach, and our intent-oriented priority criteria work well.

Keywords: test repair, test intent, software test, test case evolution

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Authors: Jungkyun Im

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Nonsteroidal anti-inflammatory drugs (NSAIDs) are effective for relieving pain and reducing inflammation. They are nonselective inhibitors of two isoforms of COX, cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2), and thereby inhibiting the production of hormone-like lipid compounds such as, prostaglandins and thromboxanes which cause inflammation, pain, fever, platelet aggregation, etc. In addition, recently there are many research articles reporting the neuroprotective effect of NSAIDs in neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). However, the clinical use of NSAIDs in these diseases is limited by low brain distribution. Therefore, in order to assist the in-depth investigation on the pharmaceutical mechanism of flurbiprofen in neuroprotection and to make flurbiprofen a more potent drug to prevent or alleviate neurodegenerative diseases, delivery of flurbiprofen to brain should be effective and sufficient amount of flurbiprofen must penetrate the BBB thus gaining access into the patient’s brain. We have recently developed several types of guanidine-rich molecular carriers with high molecular weights and good water solubility that readily cross the blood-brain barrier (BBB) and display efficient distributions in the mouse brain. The G8 (having eight guanidine groups) molecular carrier based on D-sorbitol was found to be very effective in delivering anticancer drugs to a mouse brain. In the present study, employing the same molecular carrier, we prepared the flurbiprofen conjugate and studied its BBB permeation by mouse tissue distribution study. Flurbiprofen was attached to a molecular carrier with a fluorescein probe and multiple terminal guanidiniums. The conjugate was found to internalize into live cells and readily cross the BBB to enter the mouse brain. Our novel synthetic flurbiprofen conjugate will hopefully delivery NSAIDs into brain, and is therefore applicable to the neurodegenerative diseases treatment or prevention.

Keywords: flurbiprofen, drug delivery, molecular carrier, organic synthesis

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Authors: Itulelo Matiyabu Imaja, Patrick Ndayizigamiye, Manoj Maharaj

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There are many catalysts of corruption. These include amongst others, lack of effective control measures to deter or detect corrupt behaviour. Literature suggests that ICT could assist in curbing corruption through the implementation of automated systems, citizens engagement through e-government and online media to name a few. In the Democratic Republic of Congo, lack of transparency and accountability in public funds collection and allocation contribute to corruption in funds mismanagement. Using the accountability theory and available literature, this paper analyses how Democratic Republic of Congo (DRC) institutions could be strengthened through ICT in order to deter instances of corruption. Findings reveal that DRC lacks reliable control, monitoring and evaluation mechanisms that could identify potentially corrupt behavior. In addition, citizens and civil society organizations who are meant to hold the institutions accountable are not given secure platform to express their views and potentially flag any corrupt behavior. Hence, the paper presents a preliminary conceptual framework that depicts how ICT could be used to strengthen current institutions to potentially deter corrupt behavior in public funds management in Congo.

Keywords: corruption, ICT adoption, transparency, DR Congo

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Authors: Engineer Dilnawaz Shah

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Solid Waste Management (SWM) is perhaps one of the most important elements constituting the environmental health and sanitation of the urban developing sector. The management system has several components that are integrated as well as interdependent; thus, the efficiency and effectiveness of the entire system are affected when any of its functional components fails or does not perform up to the level mark of operation. Sindh Solid Waste Management Board (SSWMB) is responsible for the management of solid waste in the entire city. There is a need to adopt the engineered approach in the redesigning of the existing system. In most towns, street sweeping operations have been mechanized and done by machinery operated by vehicles. Construction of Garbage Transfer Stations (GTS) at a number of locations within the city will cut the cost of transportation of waste to disposal sites. Material processing, recovery of recyclables, compaction, volume reduction, and increase in density will enable transportation of waste to disposal sites/landfills via long vehicles (bulk transport), minimizing transport/traffic and environmental pollution-related issues. Development of disposal sites into proper sanitary landfill sites is mandatory. The transportation mechanism is through garbage vehicles using either hauled or fixed container systems employing crew for mechanical or manual loading. The number of garbage vehicles is inadequate, and due to comparatively long haulage to disposal sites, there are certain problems of frequent vehicular maintenance and high fuel costs. Foreign investors have shown interest in enterprising improvement schemes and proposed operating a solid waste management system in Karachi. The waste to Energy option is being considered to provide a practical answer to be adopted to generate power and reduce waste load – a two-pronged solution for the increasing environmental problem. The paper presents results and analysis of a recent study into waste generation and characterization probing into waste-to-energy options for Karachi City.

Keywords: waste to energy option, integrated approach, solid waste management, physical and chemical composition of waste in Karachi

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Authors: C. Rajalakshmi, Vibin Ipe Thomas

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Sonogashira coupling reactions are widely employed in the synthesis of molecules of biological and pharmaceutical importance. Copper catalyzed Sonogashira coupling reactions are gaining importance owing to the low cost and less toxicity of copper as compared to the palladium catalyst. In the present work, a detailed computational study has been carried out on the Sonogashira coupling reaction between aryl halides and terminal alkynes catalyzed by Copper (I) species with trans-1, 2 Diaminocyclohexane as ligand. All calculations are performed at Density Functional Theory (DFT) level, using the hybrid Becke3LYP functional. Cu and I atoms are described using an effective core potential (LANL2DZ) for the inner electrons and its associated double-ζ basis set for the outer electrons. For all other atoms, 6-311G+* basis set is used. We have identified that the active catalyst species is a neutral 3-coordinate trans-1,2 diaminocyclohexane ligated Cu (I) alkyne complex and found that the oxidative addition and reductive elimination occurs in a single step proceeding through one transition state. This is owing to the ease of reductive elimination involving coupling of Csp2-Csp carbon atoms and the less stable Cu (III) intermediate. This shows the mechanism of copper catalyzed Sonogashira coupling reactions are quite different from those catalyzed by palladium. To gain further insights into the mechanism, substrates containing various functional groups are considered in our study to traverse their effect on the feasibility of the reaction. We have also explored the effect of ligand on the catalytic cycle of the coupling reaction. The theoretical results obtained are in good agreement with the experimental observation. This shows the relevance of a combined theoretical and experimental approach for rationally improving the cross-coupling reaction mechanisms.

Keywords: copper catalysed, density functional theory, reaction mechanism, Sonogashira coupling

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Authors: Anu Paul, Varghese Paul

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The focal aspire of e-Government (eGovt) is to offer citizen-centered service delivery. Accordingly, the citizenry consumes services from multiple government agencies through national portal. Thus, eGovt is an enterprise with the primary business motive of transparent, efficient and effective public services to its citizenry and its logical structure is the eGovernment Enterprise Architecture (eGEA). Since eGovt is IT oriented multifaceted service-centric system, EA doesn’t do much on an automated enterprise other than the business artifacts. Service-Oriented Architecture (SOA) manifestation led some governments to pertain this in their eGovts, but it limits the source of business artifacts. The concurrent use of EA and SOA in eGovt executes interoperability and integration and leads to Service-Oriented e-Government Enterprise (SOeGE). Consequently, agile eGovt system becomes a reality. As an IT perspective eGovt comprises of centralized public service artifacts with the existing application logics belong to various departments at central, state and local level. The eGovt is renovating to SOeGE by apply the Service-Orientation (SO) principles in the entire system. This paper explores IT perspective of SOeGE in India which encompasses the public service models and illustrated with a case study the Passport service of India.

Keywords: enterprise architecture, service-oriented e-Government enterprise, service interface layer, service model

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Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

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Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

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Authors: Mohammad Mokhtari, Gires Usup, Zaidi Che Cob

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Bacteria communities as mediators of the biogeochemical process are the main component of the mangrove ecosystems. Crab burrows by increasing oxic-anoxic interfaces and facilitating the flux rate between sediment and tidal water affect biogeochemical properties of sediments. The effect of fiddler crab burrows on the density and diversity of bacteria were investigated to elucidate the effect of burrow on bacterial distribution. Samples collected from the burrow walls of three species of fiddler crabs including Uca paradussumieri, Uca rosea, and Uca forcipata. Sediment properties including grain size, temperature, Redox potential, pH, chlorophyll, water and organic content were measured from the burrow walls to assess the correlation between environmental variables and bacterial communities. Bacteria were enumerated with epifluorescence microscopy after staining with SYBR green. Bacterial DNA extracted from sediment samples and the community profiles of bacteria were determined with Terminal Restriction Fragment Length Polymorphism (T-RFLP). High endemism was observed among bacterial communities. Among the 152 observed OTU’s, 22 were found only in crab burrows. The highest bacterial density and diversity were recorded in burrow wall. The results of ANOSIM indicated a significant difference between the bacterial communities from the three species of fiddler crab burrows. Only 3% of explained bacteria variability in the constrained ordination model of CCA was contributed to depth, while much of the bacteria’s variability was attributed to coarse sand, pH, and chlorophyll content. Our findings suggest that crab burrows by affecting sediment properties such as redox potential, pH, water, and chlorophyll content induce significant effects on the bacterial communities.

Keywords: bioturbation, canonical corresponding analysis, fiddler crab, microbial ecology

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Authors: Latha Subbiah, Dhanalakshmi Samiappan

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In this paper, we propose denoising Common Carotid Artery (CCA) B mode ultrasound images by a decomposition approach to curvelet thresholding and automatic segmentation of the intima media thickness and adventitia boundary. By decomposition, the local geometry of the image, its direction of gradients are well preserved. The components are combined into a single vector valued function, thus removes noise patches. Double threshold is applied to inherently remove speckle noise in the image. The denoised image is segmented by active contour without specifying seed points. Combined with level set theory, they provide sub regions with continuous boundaries. The deformable contours match to the shapes and motion of objects in the images. A curve or a surface under constraints is developed from the image with the goal that it is pulled into the necessary features of the image. Region based and boundary based information are integrated to achieve the contour. The method treats the multiplicative speckle noise in objective and subjective quality measurements and thus leads to better-segmented results. The proposed denoising method gives better performance metrics compared with other state of art denoising algorithms.

Keywords: curvelet, decomposition, levelset, ultrasound

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Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

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Authors: Haruna Karamba, Nafisa Muhammad Danyaro

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The study describe the action of natural latex (extract) of two sub-aquatic macrophytes plants i.e., Cassia occidentalis and Physalis angulata which were tested against two water snail species; Bulinus globusus and Lymnaea natalensis, the intermediate host of Bilharziasis (chistosomiasis) in the tropical countries. Bilherziasis is a disease prevalent and endermic to tropical Africa, seriously undermining health status of Nigerian youth. The easiest way to eradicate the disease is to eliminate the secondary host of the pathogen, chistosoma species. Therefore we carried out a research to investigate the molluscicidal effect of the leaf extract of C. occidentalis and P. angulata on mortality rate of B. globusus and L. natalensis water snails using pond water in the laboratory of science laboratory department of Kano State Polytechnic, Nigeria. One hundred and fifty juveniles’ snails were collected from Jakara Dam in the Northeastern part of Kano, Nigeria. The snails were put inside a plastic container and transported immediately to the laboratory where they were transferred into reservoir tank containing pond water and kept for 48 hours to get acclimatized with laboratory environment. Twelve water bathes 2/3 filled with pond water were prepared and kept in the laboratory. Leaf extract of the plants were obtained by blending and homogenizing the leaf tissue from which the extract were obtained and prepared in 10, 20, 30, 40 and 50 ppm, in addition to 0 ppm, which served as control. Ten snails were placed in each of the twelve water bathes. Six water bathes for the species of C. accidentalis extract and other six for P. angulata. The treatment combinations were maintained for 2 days after which the number of living snails present in each water bathes were counted and subsequently at 2 days intervals. The result indicated that extracts from both plants were lethal to the snails as concentration of the extract increases particularly mortality rate was highest at 40 and 50 ppm. Conclusively the toxicity of the extracts from these plants proven lethal to snails and hence can be used as molluscicides for cheap and easy method of eliminating water snails and therefore reducing the incidence of Bilharziasis.

Keywords: schistosomiasis, bilharziasis, Bulinus globusus, Lymnea natalensis, Physalis angulata, Cassia occidentalis, Kano

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

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Authors: T. Wanyama, B. Far

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Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: community water usage, fuzzy logic, irrigation, multi-agent system

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Authors: Sara Arafeh, Kovriguine Evguine

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Cytochromes P450 are enzymes that require a supply of electrons to catalyze the synthesis of steroid hormones, fatty acids, and prostaglandin hormone. Cytochrome P450 Oxidoreductase (CYPOR), a membrane bound enzyme, provides these electrons in its open conformation. CYPOR has two cytosolic domains (FAD domain and FMN domain) and an N-terminal in the membrane. In its open conformation, electrons flow from NADPH, FAD, and finally to FMN where cytochrome P450 picks up these electrons. In the closed conformation, cytochrome P450 does not bind to the FMN domain to take the electrons. It was found that when the cytosolic domains are isolated, CYPOR could not bind to cytochrome P450. This suggested that the membrane environment is important for CYPOR function. This project takes the initiative to better understand the dynamics of CYPOR in its full length. Here, we determine the distance between specific sites in the FAD and FMN binding domains in CYPOR by Forster Resonance Energy Transfer (FRET) and Ultrafast TA spectroscopy with and without NADPH. The approach to determine these distances will rely on labeling these sites with red and infrared fluorophores. Mimic membrane attachment is done by inserting CYPOR in lipid nanodiscs. By determining the distances between the donor-acceptor sites in these domains, we can observe the open/closed conformations upon reducing CYPOR in the presence and absence of cytochrome P450. Such study is important to better understand CYPOR mechanism of action in various endosomal membranes including hepatic CYPOR which is vital in plasma cholesterol homeostasis. By investigating the conformational cycles of CYPOR, we can synthesize drugs that would be more efficient in affecting the steroid hormonal levels and metabolism of toxins catalyzed by Cytochrome P450.

Keywords: conformational cycle of CYPOR, cytochrome P450, cytochrome P450 oxidoreductase, FAD domain, FMN domain, FRET, Ultrafast TA Spectroscopy

Procedia PDF Downloads 258

Authors: U. S. N. Raju, Kothuri Sai Kiran, Meena G. Kamal, Vinay Nikhil Pabba, Suresh Kanaparthi

Abstract:

There is huge amount of lecture video data available for public use, and many more lecture videos are being created and uploaded every day. Searching for videos on required topics from this huge database is a challenging task. Therefore, an efficient method for video retrieval is needed. An approach for automated video indexing and video search in large lecture video archives is presented. As the amount of video lecture data is huge, it is very inefficient to do the processing in a centralized computation framework. Hence, Hadoop Framework for distributed computing for Big Video Data is used. First, step in the process is automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. In the next step, we extract textual metadata by applying video Optical Character Recognition (OCR) technology on key-frames. The OCR and detected slide text line types are adopted for keyword extraction, by which both video- and segment-level keywords are extracted for content-based video browsing and search. The performance of the indexing process can be improved for a large database by using distributed computing on Hadoop framework.

Keywords: video lectures, big video data, video retrieval, hadoop

Procedia PDF Downloads 510

Authors: Meghan Biallas, Amanda Hoffman, Tamara Miller, Kimmy Schnibben, Janaina Siegler

Abstract:

This paper assesses Walmart’s supply chain resiliency amidst continuous supply chain disruptions. It aims to evaluate how Walmart can use supply chain resiliency theory to retain its status as a global supply chain leader. The Bloomberg terminal was used to organize Walmart’s 754 Tier-1 suppliers by the size of their relationship to Walmart. Additional data from IBISWorld and Statista was also used in the analysis. This research focused on the top ten Tier-1 suppliers, with the greatest percentage of their revenue attributed to Walmart. This paper also applied the firm’s information to the Supply Chain Resilience Assessment and Management (SCRAM) framework for supply chain resiliency to evaluate the firm’s capabilities, vulnerabilities, and gaps. A rubric was created to quantify Walmart’s risks using four pillars: flexibility, velocity, visibility, and collaboration. Information and examples were reported from Walmart’s 10k filing. For each example, a rating of 1 indicated “high” resiliency, 0 indicated “medium” resiliency, and -1 indicated “low” resiliency. Findings from this study include the following: (1) Walmart has maintained its leadership through its ability to remain resilient with regard to visibility, efficiency, capacity, and collaboration. (2) Walmart is experiencing increases in supply chain costs due to internal factors affecting the company and external factors affecting its suppliers. (3) There are a number of emerging supply chain risks with Walmart’s suppliers, which could cause issues for Walmart to remain a supply chain leader in the future. Using the SCRAM framework, this paper assesses how Walmart measures up to the Supply Chain Resiliency Theory, identifying areas of strength as well as areas where Walmart can improve in order to remain a global supply chain leader.

Keywords: supply chain resiliency, zone of balanced resilience, supply chain resilience assessment and management, supply chain theory.

Procedia PDF Downloads 95

Authors: Ryan B. Escorial, Elmer A. Maravillas, Chris Jordan G. Aliac

Abstract:

This study presents a small-scale water pumping system utilizing a fuzzy logic inference system attached to a renewable energy source. The fuzzy logic controller was designed and simulated in MATLAB fuzzy logic toolbox to examine the properties and characteristics of the input and output variables. The result of the simulation was implemented in a microcontroller, together with sensors, modules, and photovoltaic cells. The study used a grand rapid variety of lettuce, organic substrates, and foliar for observation of the capability of the device to irrigate crops. Two plant boxes intended for manual and automated irrigation were prepared with each box having 48 heads of lettuce. The observation of the system took 22-31 days, which is one harvest period of the crop. Results showed a 22.55% increase in agricultural productivity compared to manual irrigation. Aside from reducing human effort, and time, the smart irrigation system could help lessen some of the shortcomings of manual irrigations. It could facilitate the economical utilization of water, reducing consumption by 25%. The use of renewable energy could also help farmers reduce the cost of production by minimizing the use of diesel and gasoline.

Keywords: fuzzy logic, intelligent system, precision agriculture, renewable energy

Procedia PDF Downloads 108

Authors: Edwin Hidayat, Redi Yulianto, Disi Hanafiah

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On the one hand, parameters which are used for determining the number of lane on the new road construction are average annual average daily traffic (AADT) and peak hour factor (K-factor). On the other hand, the value of K-factor listed in the guidelines and manual for road planning in Indonesia is a value of adoption or adaptation from foreign guidelines or manuals. Thus, the value is less suitable for Indonesian condition due to differences in road conditions, vehicle type, and driving behavior. The purpose of this study is to provide an example on how to determine k-factor values at a road segment with particular conditions in north coast road, West Java. The methodology is started with collecting traffic volume data for 24 hours over 365 days using PLATO (Automated Traffic Counter) with the approach of video image processing. Then, the traffic volume data is divided into per hour and analyzed by comparing the peak traffic volume in the 30th hour (or other) with the AADT in the same year. The analysis has resulted that for the 30th peak hour the K-factor is 0.97. This value can be used for planning road geometry or evaluating the road capacity performance for the 4/2D interurban road.

Keywords: road geometry, K-factor, annual average daily traffic, north coast road

Procedia PDF Downloads 146

Authors: Fan Ye

Abstract:

Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.

Keywords: RWIS, visibility distance, low visibility, adverse weather

Procedia PDF Downloads 235

Authors: Michael Stewart

Abstract:

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

Procedia PDF Downloads 176