Search results for: automated supply chain
Commenced in January 2007
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Edition: International
Paper Count: 4348

Search results for: automated supply chain

2728 Current Applications of Artificial Intelligence (AI) in Chest Radiology

Authors: Angelis P. Barlampas

Abstract:

Learning Objectives: The purpose of this study is to inform briefly the reader about the applications of AI in chest radiology. Background: Currently, there are 190 FDA-approved radiology AI applications, with 42 (22%) pertaining specifically to thoracic radiology. Imaging findings OR Procedure details Aids of AI in chest radiology1: Detects and segments pulmonary nodules. Subtracts bone to provide an unobstructed view of the underlying lung parenchyma and provides further information on nodule characteristics, such as nodule location, nodule two-dimensional size or three dimensional (3D) volume, change in nodule size over time, attenuation data (i.e., mean, minimum, and/or maximum Hounsfield units [HU]), morphological assessments, or combinations of the above. Reclassifies indeterminate pulmonary nodules into low or high risk with higher accuracy than conventional risk models. Detects pleural effusion . Differentiates tension pneumothorax from nontension pneumothorax. Detects cardiomegaly, calcification, consolidation, mediastinal widening, atelectasis, fibrosis and pneumoperitoneum. Localises automatically vertebrae segments, labels ribs and detects rib fractures. Measures the distance from the tube tip to the carina and localizes both endotracheal tubes and central vascular lines. Detects consolidation and progression of parenchymal diseases such as pulmonary fibrosis or chronic obstructive pulmonary disease (COPD).Can evaluate lobar volumes. Identifies and labels pulmonary bronchi and vasculature and quantifies air-trapping. Offers emphysema evaluation. Provides functional respiratory imaging, whereby high-resolution CT images are post-processed to quantify airflow by lung region and may be used to quantify key biomarkers such as airway resistance, air-trapping, ventilation mapping, lung and lobar volume, and blood vessel and airway volume. Assesses the lung parenchyma by way of density evaluation. Provides percentages of tissues within defined attenuation (HU) ranges besides furnishing automated lung segmentation and lung volume information. Improves image quality for noisy images with built-in denoising function. Detects emphysema, a common condition seen in patients with history of smoking and hyperdense or opacified regions, thereby aiding in the diagnosis of certain pathologies, such as COVID-19 pneumonia. It aids in cardiac segmentation and calcium detection, aorta segmentation and diameter measurements, and vertebral body segmentation and density measurements. Conclusion: The future is yet to come, but AI already is a helpful tool for the daily practice in radiology. It is assumed, that the continuing progression of the computerized systems and the improvements in software algorithms , will redder AI into the second hand of the radiologist.

Keywords: artificial intelligence, chest imaging, nodule detection, automated diagnoses

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2727 Cancer Stem Cell-Associated Serum Proteins Obtained by Maldi TOF/TOF Mass Spectrometry in Women with Triple-Negative Breast Cancer

Authors: Javier Enciso-Benavides, Fredy Fabian, Carlos Castaneda, Luis Alfaro, Alex Choque, Aparicio Aguilar, Javier Enciso

Abstract:

Background: The use of biomarkers in breast cancer diagnosis, therapy, and prognosis has gained increasing interest. Cancer stem cells (CSCs) are a subpopulation of tumor cells that can drive tumor initiation and may cause relapse. Therefore, due to the importance of diagnosis, therapy, and prognosis, several biomarkers that characterize CSCs have been identified; however, in treatment-naïve triple-negative breast tumors, there is an urgent need to identify new biomarkers and therapeutic targets. According to this, the aim of this study was to identify serum proteins associated with cancer stem cells and pluripotency in women with triple-negative breast tumors in order to subsequently identify a biomarker for this type of breast tumor. Material and Methods: Whole blood samples from 12 women with histopathologically diagnosed triple-negative breast tumors were used after obtaining informed consent from the patient. Blood serum was obtained by conventional procedure and frozen at -80ºC. Identification of cancer stem cell-associated proteins was performed by matrix-assisted laser desorption/ionisation-assisted laser desorption/ionisation mass spectrometry (MALDI-TOF MS), protein analysis was obtained using the AB Sciex TOF/TOF™ 5800 system (AB Sciex, USA). Sequences not aligned by ProteinPilot™ software were analyzed by Protein BLAST. Results: The following proteins related to pluripotency and cancer stem cells were identified by MALDI TOF/TOF mass spectrometry: A-chain, Serpin A12 [Homo sapiens], AIEBP [Homo sapiens], Alpha-one antitrypsin, AT {internal fragment} [human, partial peptide, 20 aa] [Homo sapiens], collagen alpha 1 chain precursor variant [Homo sapiens], retinoblastoma-associated protein variant [Homo sapiens], insulin receptor, CRA_c isoform [Homo sapiens], Hydroxyisourate hydrolase [Streptomyces scopuliridis], MUCIN-6 [Macaca mulatta], Alpha-actinin-3 [Chrysochloris asiatica], Polyprotein M, CRA_d isoform, partial [Homo sapiens], Transcription factor SOX-12 [Homo sapiens]. Recommendations: The serum proteins identified in this study should be investigated in the exosome of triple-negative breast cancer stem cells and in the blood serum of women without breast cancer. Subsequently, proteins found only in the blood serum of women with triple-negative breast cancer should be identified in situ in triple-negative breast cancer tissue in order to identify a biomarker to study the evolution of this type of cancer, or that could be a therapeutic target. Conclusions: Eleven cancer stem cell-related serum proteins were identified in 12 women with triple-negative breast cancer, of which MUCIN-6, retinoblastoma-associated protein variant, transcription factor SOX-12, and collagen alpha 1 chain are the most representative and have not been studied so far in this type of breast tumor. Acknowledgement: This work was supported by Proyecto CONCYTEC–Banco Mundial “Mejoramiento y Ampliacion de los Servicios del Sistema Nacional de Ciencia Tecnología e Innovacion Tecnologica” 8682-PE (104-2018-FONDECYT-BM-IADT-AV).

Keywords: triple-negative breast cancer, MALDI TOF/TOF MS, serum proteins, cancer stem cells

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2726 Automated System: Managing the Production and Distribution of Radiopharmaceuticals

Authors: Shayma Mohammed, Adel Trabelsi

Abstract:

Radiopharmacy is the art of preparing high-quality, radioactive, medicinal products for use in diagnosis and therapy. Radiopharmaceuticals unlike normal medicines, this dual aspect (radioactive, medical) makes their management highly critical. One of the most convincing applications of modern technologies is the ability to delegate the execution of repetitive tasks to programming scripts. Automation has found its way to the most skilled jobs, to improve the company's overall performance by allowing human workers to focus on more important tasks than document filling. This project aims to contribute to implement a comprehensive system to insure rigorous management of radiopharmaceuticals through the use of a platform that links the Nuclear Medicine Service Management System to the Nuclear Radio-pharmacy Management System in accordance with the recommendations of World Health Organization (WHO) and International Atomic Energy Agency (IAEA). In this project we attempt to build a web application that targets radiopharmacies, the platform is built atop the inherently compatible web stack which allows it to work in virtually any environment. Different technologies are used in this project (PHP, Symfony, MySQL Workbench, Bootstrap, Angular 7, Visual Studio Code and TypeScript). The operating principle of the platform is mainly based on two parts: Radiopharmaceutical Backoffice for the Radiopharmacian, who is responsible for the realization of radiopharmaceutical preparations and their delivery and Medical Backoffice for the Doctor, who holds the authorization for the possession and use of radionuclides and he/she is responsible for ordering radioactive products. The application consists of sven modules: Production, Quality Control/Quality Assurance, Release, General Management, References, Transport and Stock Management. It allows 8 classes of users: The Production Manager (PM), Quality Control Manager (QCM), Stock Manager (SM), General Manager (GM), Client (Doctor), Parking and Transport Manager (PTM), Qualified Person (QP) and Technical and Production Staff. Digital platform bringing together all players involved in the use of radiopharmaceuticals and integrating the stages of preparation, production and distribution, Web technologies, in particular, promise to offer all the benefits of automation while requiring no more than a web browser to act as a user client, which is a strength because the web stack is by nature multi-platform. This platform will provide a traceability system for radiopharmaceuticals products to ensure the safety and radioprotection of actors and of patients. The new integrated platform is an alternative to write all the boilerplate paperwork manually, which is a tedious and error-prone task. It would minimize manual human manipulation, which has proven to be the main source of error in nuclear medicine. A codified electronic transfer of information from radiopharmaceutical preparation to delivery will further reduce the risk of maladministration.

Keywords: automated system, management, radiopharmacy, technical papers

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2725 Valorisation of Food Waste Residue into Sustainable Bioproducts

Authors: Krishmali N. Ekanayake, Brendan J. Holland, Colin J. Barrow, Rick Wood

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Globally, more than one-third of all food produced is lost or wasted, equating to 1.3 billion tonnes per year. Around 31.2 million tonnes of food waste are generated across the production, supply, and consumption chain in Australia. Generally, the food waste management processes adopt environmental-friendly and more sustainable approaches such as composting, anerobic digestion and energy implemented technologies. However, unavoidable, and non-recyclable food waste ends up as landfilling and incineration that involve many undesirable impacts and challenges on the environment. A biorefinery approach contributes to a waste-minimising circular economy by converting food and other organic biomass waste into valuable outputs, including feeds, nutrition, fertilisers, and biomaterials. As a solution, Green Eco Technologies has developed a food waste treatment process using WasteMaster system. The system uses charged oxygen and moderate temperatures to convert food waste, without bacteria, additives, or water, into a virtually odour-free, much reduced quantity of reusable residual material. In the context of a biorefinery, the WasteMaster dries and mills food waste into a form suitable for storage or downstream extraction/separation/concentration to create products. The focus of the study is to determine the nutritional composition of WasteMaster processed residue to potential develop aquafeed ingredients. The global aquafeed industry is projected to reach a high value market in future, which has shown high demand for the aquafeed products. Therefore, food waste can be utilized for aquaculture feed development by reducing landfill. This framework will lessen the requirement of raw crops cultivation for aquafeed development and reduce the aquaculture footprint. In the present study, the nutritional elements of processed residue are consistent with the input food waste type, which has shown that the WasteMaster is not affecting the expected nutritional distribution. The macronutrient retention values of protein, lipid, and nitrogen free extract (NFE) are detected >85%, >80%, and >95% respectively. The sensitive food components including omega 3 and omega 6 fatty acids, amino acids, and phenolic compounds have been found intact in each residue material. Preliminary analysis suggests a price comparability with current aquafeed ingredient cost making the economic feasibility. The results suggest high potentiality of aquafeed development as 5 to 10% of the ingredients to replace/partially substitute other less sustainable ingredients across biorefinery setting. Our aim is to improve the sustainability of aquaculture and reduce the environmental impacts of food waste.

Keywords: biorefinery, ffood waste residue, input, wasteMaster

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2724 Effective Medium Approximations for Modeling Ellipsometric Responses from Zinc Dialkyldithiophosphates (ZDDP) Tribofilms Formed on Sliding Surfaces

Authors: Maria Miranda-Medina, Sara Salopek, Andras Vernes, Martin Jech

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Sliding lubricated surfaces induce the formation of tribofilms that reduce friction, wear and prevent large-scale damage of contact parts. Engine oils and lubricants use antiwear and antioxidant additives such as zinc dialkyldithiophosphate (ZDDP) from where protective tribofilms are formed by degradation. The ZDDP tribofilms are described as a two-layer structure composed of inorganic polymer material. On the top surface, the long chain polyphosphate is a zinc phosphate and in the bulk, the short chain polyphosphate is a mixed Fe/Zn phosphate with a gradient concentration. The polyphosphate chains are partially adherent to steel surface through a sulfide and work as anti-wear pads. In this contribution, ZDDP tribofilms formed on gray cast iron surfaces are studied. The tribofilms were generated in a reciprocating sliding tribometer with a piston ring-cylinder liner configuration. Fully formulated oil of SAE grade 5W-30 was used as lubricant during two tests at 40Hz and 50Hz. For the estimation of the tribofilm thicknesses, spectroscopic ellipsometry was used due to its high accuracy and non-destructive nature. Ellipsometry works under an optical principle where the change in polarisation of light reflected by the surface, is associated with the refractive index of the surface material or to the thickness of the layer deposited on top. Ellipsometrical responses derived from tribofilms are modelled by effective medium approximation (EMA), which includes the refractive index of involved materials, homogeneity of the film and thickness. The materials composition was obtained from x-ray photoelectron spectroscopic studies, where the presence of ZDDP, O and C was confirmed. From EMA models it was concluded that tribofilms formed at 40 Hz are thicker and more homogeneous than the ones formed at 50 Hz. In addition, the refractive index of each material is mixed to derive an effective refractive index that describes the optical composition of the tribofilm and exhibits a maximum response in the UV range, being a characteristic of glassy semitransparent films.

Keywords: effective medium approximation, reciprocating sliding tribometer, spectroscopic ellipsometry, zinc dialkyldithiophosphate

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2723 Material Handling Equipment Selection Using Fuzzy AHP Approach

Authors: Priyanka Verma, Vijaya Dixit, Rishabh Bajpai

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This research paper is aimed at selecting appropriate material handling equipment among the given choices so that the automation level in material handling can be enhanced. This work is a practical case scenario of material handling systems in consumer electronic appliances manufacturing organization. The choices of material handling equipment among which the decision has to be made are Automated Guided Vehicle’s (AGV), Autonomous Mobile Robots (AMR), Overhead Conveyer’s (OC) and Battery Operated Trucks/Vehicle’s (BOT). There is a need of attaining a certain level of automation in order to reduce human interventions in the organization. This requirement of achieving certain degree of automation can be attained by material handling equipment’s mentioned above. The main motive for selecting above equipment’s for study was solely based on corporate financial strategy of investment and return obtained through that investment made in stipulated time framework. Since the low cost automation with respect to material handling devices has to be achieved hence these equipment’s were selected. Investment to be done on each unit of this equipment is less than 20 lakh rupees (INR) and the recovery period is less than that of five years. Fuzzy analytic hierarchic process (FAHP) is applied here for selecting equipment where the four choices are evaluated on basis of four major criteria’s and 13 sub criteria’s, and are prioritized on the basis of weight obtained. The FAHP used here make use of triangular fuzzy numbers (TFN). The inability of the traditional AHP in order to deal with the subjectiveness and impreciseness in the pair-wise comparison process has been improved in the FAHP. The range of values for general rating purposes for all decision making parameters is kept between 0 and 1 on the basis of expert opinions captured on shop floor. These experts were familiar with operating environment and shop floor activity control. Instead of generating exact value the FAHP generates the ranges of values to accommodate the uncertainty in decision-making process. The four major criteria’s selected for the evaluation of choices of material handling equipment’s available are materials, technical capabilities, cost and other features. The thirteen sub criteria’s listed under these following four major criteria’s are weighing capacity, load per hour, material compatibility, capital cost, operating cost and maintenance cost, speed, distance moved, space required, frequency of trips, control required, safety and reliability issues. The key finding shows that among the four major criteria selected, cost is emerged as the most important criteria and is one of the key decision making aspect on the basis of which material equipment selection is based on. While further evaluating the choices of equipment available for each sub criteria it is found that AGV scores the highest weight in most of the sub-criteria’s. On carrying out complete analysis the research shows that AGV is the best material handling equipment suiting all decision criteria’s selected in FAHP and therefore it is beneficial for the organization to carry out automated material handling in the facility using AGV’s.

Keywords: fuzzy analytic hierarchy process (FAHP), material handling equipment, subjectiveness, triangular fuzzy number (TFN)

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2722 A Quantitative Evaluation of Text Feature Selection Methods

Authors: B. S. Harish, M. B. Revanasiddappa

Abstract:

Due to rapid growth of text documents in digital form, automated text classification has become an important research in the last two decades. The major challenge of text document representations are high dimension, sparsity, volume and semantics. Since the terms are only features that can be found in documents, selection of good terms (features) plays an very important role. In text classification, feature selection is a strategy that can be used to improve classification effectiveness, computational efficiency and accuracy. In this paper, we present a quantitative analysis of most widely used feature selection (FS) methods, viz. Term Frequency-Inverse Document Frequency (tfidf ), Mutual Information (MI), Information Gain (IG), CHISquare (x2), Term Frequency-Relevance Frequency (tfrf ), Term Strength (TS), Ambiguity Measure (AM) and Symbolic Feature Selection (SFS) to classify text documents. We evaluated all the feature selection methods on standard datasets like 20 Newsgroups, 4 University dataset and Reuters-21578.

Keywords: classifiers, feature selection, text classification

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2721 Revolutionizing Accounting: Unleashing the Power of Artificial Intelligence

Authors: Sogand Barghi

Abstract:

The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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2720 Combination of Unmanned Aerial Vehicle and Terrestrial Laser Scanner Data for Citrus Yield Estimation

Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

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Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

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2719 Growth Pattern, Condition Factor and Relative Condition Factor of Twenty Important Demersal Marine Fish Species in Nigerian Coastal Water

Authors: Omogoriola Hannah Omoloye

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Fish is a key ingredient on the global menu, a vital factor in the global environment and an important basis for livelihood worldwide1. The length – weight relationships (LWRs) is of great importance in fishery assessment2,3. Its importance is pronounced in estimated the average weight at a given length group4 and in assessing the relative well being of a fish population5. Length and weight measurement in conjunction with age data can give information on the stock composition, age at maturity, life span, mortality, growth and production4,5,6,7. In addition, the data on length and weight can also provides important clues to climatic and environmental changes and the change in human consumption practices8,9. However, the size attained by the individual fish may also vary because of variation in food supply, and these in turn may reflect variation in climatic parameters and in the supply of nutrient or in the degree of competition for food. Environment deterioration, for example, may reduce growth rates and will cause a decrease in the average age of the fish. The condition factor and the relative condition factor10 are the quantitative parameters of the well being state of the fish and reflect recent feeding condition of the fish. It is based on the hypothesis that heavier fish of a given length are in better condition11. This factor varies according to influences of physiological factors, fluctuating according to different stages of the development. Condition factor has been used as an index of growth and feeding intensity12. Condition factor decrease with increase in length 12,13 and also influences the reproductive cycle in fish14. The objective here is to determine the length-weight relationships and condition factor for direct use in fishery assessment and for future comparisons between populations of the same species at different locations. To provide quantitative information on the biology of marine fish species trawl from Nigeria coastal water.

Keywords: condition factor, growth pattern, marine fish species, Nigerian Coastal water

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2718 Ultra-High Molecular Weight Polyethylene (UHMWPE) for Radiation Dosimetry Applications

Authors: Malik Sajjad Mehmood, Aisha Ali, Hamna Khan, Tariq Yasin, Masroor Ikram

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Ultra-high molecular weight polyethylene (UHMWPE) is one of the polymers belongs to polyethylene (PE) family having monomer –CH2– and average molecular weight is approximately 3-6 million g/mol. Due its chemical, mechanical, physical and biocompatible properties, it has been extensively used in the field of electrical insulation, medicine, orthopedic, microelectronics, engineering, chemistry and the food industry etc. In order to alter/modify the properties of UHMWPE for particular application of interest, certain various procedures are in practice e.g. treating the material with high energy irradiations like gamma ray, e-beam, and ion bombardment. Radiation treatment of UHMWPE induces free radicals within its matrix, and these free radicals are the precursors of chain scission, chain accumulation, formation of double bonds, molecular emission, crosslinking etc. All the aforementioned physical and chemical processes are mainly responsible for the modification of polymers properties to use them in any particular application of our interest e.g. to fabricate LEDs, optical sensors, antireflective coatings, polymeric optical fibers, and most importantly for radiation dosimetry applications. It is therefore, to check the feasibility of using UHMWPE for radiation dosimetery applications, the compressed sheets of UHMWPE were irradiated at room temperature (~25°C) for total dose values of 30 kGy and 100 kGy, respectively while one were kept un-irradiated as reference. Transmittance data (from 400 nm to 800 nm) of e-beam irradiated UHMWPE and its hybrids were measured by using Muller matrix spectro-polarimeter. As a result significant changes occur in the absorption behavior of irradiated samples. To analyze these (radiation induced) changes in polymer matrix Urbach edge method and modified Tauc’s equation has been used. The results reveal that optical activation energy decreases with irradiation. The values of activation energies are 2.85 meV, 2.48 meV, and 2.40 meV for control, 30 kGy, and 100 kGy samples, respectively. Direct and indirect energy band gaps were also found to decrease with irradiation due to variation of C=C unsaturation in clusters. We believe that the reported results would open new horizons for radiation dosimetery applications.

Keywords: electron beam, radiation dosimetry, Tauc’s equation, UHMWPE, Urbach method

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2717 Impacts of Climate Change on Number of Snowy Days and Snow Season Lengths in Turkey

Authors: Evren Ozgur, Kasim Kocak

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As a result of global warming and climate change, air temperature has increased and will continue to increase in the future. Increases in air temperatures have effects on a large number of variables in meteorology. One of the most important effects is the changes in the types of precipitation, especially in mid-latitudes. Because of increasing air temperatures, less snowfall was observed in the eastern parts of Turkey. Snowfall provides most of the water supply in spring and summer months, especially in mountainous regions of Turkey. When the temperature begins to increase in spring season, this snow starts to melt and plays an important role in agricultural purposes, drinking water supply and energy production. On the other hand, defining the snow season is very crucial especially in mountainous areas which have winter tourism opportunities. A reduction in the length of the snow season (LSS) in these regions will result in serious consequences in the long run. In the study, snow season was examined for 10 meteorological stations that are located above the altitude of 1000m. These stations have decreasing trends in the ratio of number of snowy days to total precipitation days considering earlier studies. Daily precipitation records with the observation period of 1971-2011 were used in the study. Then, the observation period was separated into 4 non-overlapping parts in order to identify decadal variations. Changes in the length of the snow season with increasing temperatures were obtained for these stations. The results of LSS were evaluated with the number of snowy days for each station. All stations have decreasing trend in number of snowy days for 1971-2011 period. In addition, seven of the results are statistically significant. Besides, decrease is observed regarding the length of snow season for studied stations. The decrease varies between 6.6 and 47.6 days according to decadal snow season averages of the stations.

Keywords: climate change, global warming, precipitation, snowfall, Turkey

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2716 Attack Redirection and Detection using Honeypots

Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

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2715 Awareness and Utilization of Social Network Tools among Agricultural Science Students in Colleges of Education in Ogun State, Nigeria

Authors: Adebowale Olukayode Efunnowo

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This study was carried out to assess the awareness and utilization of Social Network Tools (SNTs) among agricultural science students in Colleges of Education in Ogun State, Nigeria. Simple random sampling techniques were used to select 280 respondents from the study area. Descriptive statistics was used to describe the objectives while Pearson Product Moment Correlation was used to test the hypothesis. The result showed that the majority (71.8%) of the respondents were single, with a mean age of 20 years. Almost all (95.7%) the respondents were aware of Facebook and 2go as a Social Network Tools (SNTs) while 85.0% of the respondents were not aware of Blackplanet, LinkedIn, MyHeritage and Bebo. Many (41.1%) of the respondents had views that using SNTs can enhance extensive literature survey, increase internet browsing potential, promote teaching proficiency, and update on outcomes of researches. However, 51.4% of the respondents perceived that SNTs usage as what is meant for the lecturers/adults only while 16.1% considered it as mainly used by internet fraudsters. Findings revealed that about 50.0% of the respondents browsed Facebook and 2go daily while more than 80% of the respondents used Blackplanet, MyHeritage, Skyrock, Bebo, LinkedIn and My YearBook as the need arise. Major constraints to the awareness and utilization of SNTs were high cost and poor quality of ICTs facilities (77.1%), epileptic power supply (75.0%), inadequate telecommunication infrastructure (71.1%), low technical know-how (62.9%) and inadequate computer knowledge (61.1%). The result of PPMC analysis showed that there was an inverse relationship between constraints and utilization of SNTs at p < 0.05. It can be concluded that constraints affect efficient and effective utilization of SNTs in the study area. It is hereby recommended that management of colleges of education and agricultural institutes should provide good internet connectivity, computer facilities, and alternative power supply in order to increase the awareness and utilization of SNTs among students.

Keywords: awareness, utilization, social network tools, constraints, students

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2714 A Deep Learning Approach for the Predictive Quality of Directional Valves in the Hydraulic Final Test

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

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2713 Analysis of Cycling Accessibility on Chengdu Tianfu Greenway Based on Improved Two-Step Floating Catchment Area Method: A Case Study of Jincheng Greenway

Authors: Qin Zhu

Abstract:

Under the background of accelerating the construction of Beautiful and Livable Park City in Chengdu, the Tianfu greenway system, as an important support system for the construction of parks in the whole region, its accessibility is one of the key indicators to measure the effectiveness of the greenway construction. In recent years, cycling has become an important transportation mode for residents to go to the greenways because of its low-carbon, healthy and convenient characteristics, and the study of greenway accessibility under cycling mode can provide reference suggestions for the optimization and improvement of greenways. Taking Jincheng Greenway in Chengdu City as an example, the Baidu Map Application Programming Interface (API) and questionnaire survey was used to improve the two-step floating catchment area (2SFCA) method from the three dimensions of search threshold, supply side and demand side, to calculate the cycling accessibility of the greenway and to explore the spatial matching relationship with the population density, the number of entrances and the comprehensive attractiveness. The results show that: 1) the distribution of greenway accessibility in Jincheng shows a pattern of "high in the south and low in the north, high in the west and low in the east", 2) the spatial match between greenway accessibility and population density of the residential area is imbalanced, and there is a significant positive correlation between accessibility and the number of selectable greenway access points in residential areas, as well as the overall attractiveness of greenways, with a high degree of match. On this basis, it is proposed to give priority to the mismatch area to alleviate the contradiction between supply and demand, optimize the greenway access points to improve the traffic connection, enhance the comprehensive quality of the greenway and strengthen the service capacity, to further improve the cycling accessibility of the Jincheng Greenway and improve the spatial allocation of greenway resources.

Keywords: accessibility, Baidu maps API, cycling, greenway, 2SFCA

Procedia PDF Downloads 58
2712 Pilot Scale Production and Compatibility Criteria of New Self-Cleaning Materials

Authors: Jonjaua Ranogajec, Ognjen Rudic, Snezana Pasalic, Snezana Vucetic, Damir Cjepa

Abstract:

The paper involves a chain of activities from synthesis, establishment of the methodology for characterization and testing of novel protective materials through the pilot production and application on model supports. It summarizes the results regarding the development of the pilot production protocol for newly developed self-cleaning materials. The optimization of the production parameters was completed in order to improve the most important functional properties (mineralogy characteristics, particle size, self-cleaning properties and photocatalytic activity) of the newly designed nanocomposite material.

Keywords: pilot production, self-cleaning materials, compatibility, cultural heritage

Procedia PDF Downloads 371
2711 A Tool for Rational Assessment of Dynamic Trust in Networked Organizations

Authors: Simon Samwel Msanjila

Abstract:

Networked environments which provides platforms and environments for business organizations are configured in different forms depending on many factors including life time, member characteristics, communication structure, and business objectives, among others. With continuing advances in digital technologies the distance has become a less barrier for business minded collaboration among organizations. With the need and ease to make business collaborate nowadays organizations are sometimes forced to co-work with others that are either unknown or less known to them in terms of history and performance. A promising approach for sustaining established collaboration has been establishment of trust relationship among organizations based on assessed trustworthiness for each participating organization. It has been stated in research that trust in organization is dynamic and thus assessment of trust level must address such dynamic nature. This paper assess relevant aspects of trust and applies the concepts to propose a semi-automated system for assessing the Sustainability and Evolution of trust in organizations participating in specific objective in a networked organizations environment.

Keywords: trust evolution, trust sustainability, networked organizations, dynamic trust

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2710 Remote Sensing and GIS Based Methodology for Identification of Low Crop Productivity in Gautam Buddha Nagar District

Authors: Shivangi Somvanshi

Abstract:

Poor crop productivity in salt-affected environment in the country is due to insufficient and untimely canal supply to agricultural land and inefficient field water management practices. This could further degrade due to inadequate maintenance of canal network, ongoing secondary soil salinization and waterlogging, worsening of groundwater quality. Large patches of low productivity in irrigation commands are occurring due to waterlogging and salt-affected soil, particularly in the scarcity rainfall year. Satellite remote sensing has been used for mapping of areas of low crop productivity, waterlogging and salt in irrigation commands. The spatial results obtained for these problems so far are less reliable for further use due to rapid change in soil quality parameters over the years. The existing spatial databases of canal network and flow data, groundwater quality and salt-affected soil were obtained from the central and state line departments/agencies and were integrated with GIS. Therefore, an integrated methodology based on remote sensing and GIS has been developed in ArcGIS environment on the basis of canal supply status, groundwater quality, salt-affected soils, and satellite-derived vegetation index (NDVI), salinity index (NDSI) and waterlogging index (NSWI). This methodology was tested for identification and delineation of area of low productivity in the Gautam Buddha Nagar district (Uttar Pradesh). It was found that the area affected by this problem lies mainly in Dankaur and Jewar blocks of the district. The problem area was verified with ground data and was found to be approximately 78% accurate. The methodology has potential to be used in other irrigation commands in the country to obtain reliable spatial data on low crop productivity.

Keywords: remote sensing, GIS, salt affected soil, crop productivity, Gautam Buddha Nagar

Procedia PDF Downloads 269
2709 Message Passing Neural Network (MPNN) Approach to Multiphase Diffusion in Reservoirs for Well Interconnection Assessments

Authors: Margarita Mayoral-Villa, J. Klapp, L. Di G. Sigalotti, J. E. V. Guzmán

Abstract:

Automated learning techniques are widely applied in the energy sector to address challenging problems from a practical point of view. To this end, we discuss the implementation of a Message Passing algorithm (MPNN)within a Graph Neural Network(GNN)to leverage the neighborhood of a set of nodes during the aggregation process. This approach enables the characterization of multiphase diffusion processes in the reservoir, such that the flow paths underlying the interconnections between multiple wells may be inferred from previously available data on flow rates and bottomhole pressures. The results thus obtained compare favorably with the predictions produced by the Reduced Order Capacitance-Resistance Models (CRM) and suggest the potential of MPNNs to enhance the robustness of the forecasts while improving the computational efficiency.

Keywords: multiphase diffusion, message passing neural network, well interconnection, interwell connectivity, graph neural network, capacitance-resistance models

Procedia PDF Downloads 129
2708 A Study on Automotive Attack Database and Data Flow Diagram for Concretization of HEAVENS: A Car Security Model

Authors: Se-Han Lee, Kwang-Woo Go, Gwang-Hyun Ahn, Hee-Sung Park, Cheol-Kyu Han, Jun-Bo Shim, Geun-Chul Kang, Hyun-Jung Lee

Abstract:

In recent years, with the advent of smart cars and the expansion of the market, the announcement of 'Adventures in Automotive Networks and Control Units' at the DEFCON21 conference in 2013 revealed that cars are not safe from hacking. As a result, the HEAVENS model considering not only the functional safety of the vehicle but also the security has been suggested. However, the HEAVENS model only presents a simple process, and there are no detailed procedures and activities for each process, making it difficult to apply it to the actual vehicle security vulnerability check. In this paper, we propose an automated attack database that systematically summarizes attack vectors, attack types, and vulnerable vehicle models to prepare for various car hacking attacks, and data flow diagrams that can detect various vulnerabilities and suggest a way to materialize the HEAVENS model.

Keywords: automotive security, HEAVENS, car hacking, security model, information security

Procedia PDF Downloads 333
2707 Smart Airport: Application of Internet of Things for Confronting Airport Challenges

Authors: Ali Safaeianpour, Nima Shamandi

Abstract:

As air traffic expands, many airports have evolved into transit centers for people, information, and commerce, and technology implementation is an absolute part of airport development. Several challenges are in the way of implementing technology in an airport. Airport 4.0 proposes the "Smart Airport" concept, which focuses on using modern technologies such as Big Data, the Internet of Things (IoT), advanced biometric systems, blockchain, and cloud computing to alter and enhance passengers' journeys. Several common IoT concrete topics as partial keys to smart airports are discussed and introduced, ranging from automated check-in systems to exterior tracking processes, with the goal of enlightening more and more insightful ideas and proposals about smart airport solutions. IoT will dramatically alter people's lives by infusing intelligence, boosting the quality of life, and assembling it smarter. This paper reviews the approaches to transforming an airport into a smart airport and describes several enabling components of IoT and challenges that can hinder the implementation of a smart airport's function, which require to be addressed.

Keywords: airport 4.0, digital airport, smart airport, IoT

Procedia PDF Downloads 96
2706 Identification of Mx Gene Polymorphism in Indragiri Hulu duck by PCR-RFLP

Authors: Restu Misrianti

Abstract:

The amino acid variation of Asn (allele A) at position 631 in Mx gene was specific to positive antiviral to avian viral desease. This research was aimed at identifying polymorphism of Mx gene in duck using molecular technique. Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) technique was used to select the genotype of AA, AG and GG. There were thirteen duck from Indragiri Hulu regency (Riau Province) used in this experiment. DNA amplification results showed that the Mx gene in duck is found in a 73 bp fragment. Mx gene in duck did not show any polymorphism. The frequency of the resistant allele (AA) was 0%, while the frequency of the susceptible allele (GG) was 100%.

Keywords: duck, Mx gene, PCR, RFLP

Procedia PDF Downloads 305
2705 Comparison of Different DNA Extraction Platforms with FFPE tissue

Authors: Wang Yanping Karen, Mohd Rafeah Siti, Park MI Kyoung

Abstract:

Formalin-fixed paraffin embedded (FFPE) tissue is important in the area of oncological diagnostics. This method of preserving tissues enabling them to be stored easily at ambient temperature for a long time. This decreases the risk of losing the DNA quantity and quality after extraction, reducing sample wastage, and making FFPE more cost effective. However, extracting DNA from FFPE tissue is a challenge as DNA purified is often highly cross-linked, fragmented, and degraded. In addition, this causes problems for many downstream processes. In this study, there will be a comparison of DNA extraction efficiency between One BioMed’s Xceler8 automated platform with commercial available extraction kits (Qiagen and Roche). The FFPE tissue slices were subjected to deparaffinization process, pretreatment and then DNA extraction using the three mentioned platforms. The DNA quantity were determined with real-time PCR (BioRad CFX ) and gel electrophoresis. The amount of DNA extracted with the One BioMed’s X8 platform was found to be comparable with the other two manual extraction kits.

Keywords: DNA extraction, FFPE tissue, qiagen, roche, one biomed X8

Procedia PDF Downloads 87
2704 Impact of Displacements Durations and Monetary Costs on the Labour Market within a City Consisting on Four Areas a Theoretical Approach

Authors: Aboulkacem El Mehdi

Abstract:

We develop a theoretical model at the crossroads of labour and urban economics, used for explaining the mechanism through which the duration of home-workplace trips and their monetary costs impact the labour demand and supply in a spatially scattered labour market and how they are impacted by a change in passenger transport infrastructures and services. The spatial disconnection between home and job opportunities is referred to as the spatial mismatch hypothesis (SMH). Its harmful impact on employment has been subject to numerous theoretical propositions. However, all the theoretical models proposed so far are patterned around the American context, which is particular as it is marked by racial discrimination against blacks in the housing and the labour markets. Therefore, it is only natural that most of these models are developed in order to reproduce a steady state characterized by agents carrying out their economic activities in a mono-centric city in which most unskilled jobs being created in the suburbs, far from the Blacks who dwell in the city-centre, generating a high unemployment rates for blacks, while the White population resides in the suburbs and has a low unemployment rate. Our model doesn't rely on any racial discrimination and doesn't aim at reproducing a steady state in which these stylized facts are replicated; it takes the main principle of the SMH -the spatial disconnection between homes and workplaces- as a starting point. One of the innovative aspects of the model consists in dealing with a SMH related issue at an aggregate level. We link the parameters of the passengers transport system to employment in the whole area of a city. We consider here a city that consists of four areas: two of them are residential areas with unemployed workers, the other two host firms looking for labour force. The workers compare the indirect utility of working in each area with the utility of unemployment and choose between submitting an application for the job that generate the highest indirect utility or not submitting. This arbitration takes account of the monetary and the time expenditures generated by the trips between the residency areas and the working areas. Each of these expenditures is clearly and explicitly formulated so that the impact of each of them can be studied separately than the impact of the other. The first findings show that the unemployed workers living in an area benefiting from good transport infrastructures and services have a better chance to prefer activity to unemployment and are more likely to supply a higher 'quantity' of labour than those who live in an area where the transport infrastructures and services are poorer. We also show that the firms located in the most accessible area receive much more applications and are more likely to hire the workers who provide the highest quantity of labour than the firms located in the less accessible area. Currently, we are working on the matching process between firms and job seekers and on how the equilibrium between the labour demand and supply occurs.

Keywords: labour market, passenger transport infrastructure, spatial mismatch hypothesis, urban economics

Procedia PDF Downloads 270
2703 Energy Efficient Building Design in Nigeria: An Assessment of the Effect of the Sun on Energy Consumption in Residential Buildings

Authors: Ekele T. Ochedi, Ahmad H. Taki, Birgit Painter

Abstract:

The effect of the sun and its path on thermal comfort and energy consumption in residential buildings in tropical climates constitute a serious concern for designers, building owners, and users. Passive design approaches based on the sun and its path have been identified as a means of reducing energy consumption as well as enhancing thermal comfort in buildings worldwide. Hence, a thorough understanding regarding the sun path is key to achieving this. This is necessary due to energy need, poor energy supply, and distribution, energy poverty, and over-dependence on electric generators for power supply in Nigeria. These challenges call for a change in the approach to energy-related issues, especially in terms of buildings. The aim of this study is to explore the influence of building orientation, glazing and the use of shading devices on residential buildings in Nigeria. This is intended to provide data that will guide designers in the design of energy-efficient residential buildings. The paper used EnergyPlus to analyze a typical semi-detached residential building in Lokoja, Nigeria using hourly weather data for a period of 10 years. Building performance was studied as well as possible improvement regarding different orientations, glazing types and shading devices. The simulation results show some reductions in energy consumption in response to changes in building orientation, types of glazing and the use of shading devices. The results indicate 29.45% reduction in solar gains and 1.90% in annual operative temperature using natural ventilation only. This shows a huge potential to reduce energy consumption and improve people’s well-being through the use of proper building orientation, glazing and appropriate shading devices on building envelope. The study concludes that for a significant reduction in total energy consumption by residential buildings, the design should focus on multiple design options rather than concentrating on one or few building elements. Moreover, the investigation confirms that energy performance modeling can be used by building designers to take advantage of the sun and to evaluate various design options.

Keywords: energy consumption, energy-efficient buildings, glazing, thermal comfort, shading devices, solar gains

Procedia PDF Downloads 185
2702 A Smart Visitors’ Notification System with Automatic Secure Door Lock Using Mobile Communication Technology

Authors: Rabail Shafique Satti, Sidra Ejaz, Madiha Arshad, Marwa Khalid, Sadia Majeed

Abstract:

The paper presents the development of an automated security system to automate the entry of visitors, providing more flexibility of managing their record and securing homes or workplaces. Face recognition is part of this system to authenticate the visitors. A cost effective and SMS based door security module has been developed and integrated with the GSM network and made part of this system to allow communication between system and owner. This system functions in real time as when the visitor’s arrived it will detect and recognizes his face and on the result of face recognition process it will open the door for authorized visitors or notifies and allows the owner’s to take further action in case of unauthorized visitor. The proposed system is developed and it is successfully ensuring security, managing records and operating gate without physical interaction of owner.

Keywords: SMS, e-mail, GSM modem, authenticate, face recognition, authorized

Procedia PDF Downloads 767
2701 Adversary Emulation: Implementation of Automated Countermeasure in CALDERA Framework

Authors: Yinan Cao, Francine Herrmann

Abstract:

Adversary emulation is a very effective concrete way to evaluate the defense of an information system or network. It is about building an emulator, which depending on the vulnerability of a target system, will allow to detect and execute a set of identified attacks. However, emulating an adversary is very costly in terms of time and resources. Verifying the information of each technique and building up the countermeasures in the middle of the test is also needed to be accomplished manually. In this article, a synthesis of previous MITRE research on the creation of the ATT&CK matrix will be as the knowledge base of the known techniques and a well-designed adversary emulation software CALDERA based on ATT&CK Matrix will be used as our platform. Inspired and guided by the previous study, a plugin in CALDERA called Tinker will be implemented, which is aiming to help the tester to get more information and also the mitigation of each technique used in the previous operation. Furthermore, the optional countermeasures for some techniques are also implemented and preset in Tinker in order to facilitate and fasten the process of the defense improvement of the tested system.

Keywords: automation, adversary emulation, CALDERA, countermeasures, MITRE ATT&CK

Procedia PDF Downloads 183
2700 Cervical Cell Classification Using Random Forests

Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh

Abstract:

The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.

Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features

Procedia PDF Downloads 504
2699 Community Crèche Is a Measure to Prevent Child Injuries: Its Challenges and Measures for Improvement

Authors: Rabbya Ashrafi, Mohammad Tarikul Islam , Al-Amin Bhuiyan, Aminur Rahman

Abstract:

Injury is the leading killer of children in Bangladesh. Anchal (community crèche) is an effective intervention to prevent injuries among children under 5. Through the SoLiD project, 1,600 Anchals are in place in three sub-districts in Bangladesh. The objectives of the Anchal are to provide supervision and early childhood development stimulations (ECD) to the children. A locally trained caregiver supervises 20-25 children, 9 to 59 months old, from 9 a.m. to 1 p.m., six days a week. Although it was found effective, during its implementation phase several challenges were noticed. To identify challenges and means to overcome those to improve the Anchal activities. In-depth interviews were conducted with Anchal caregivers, their supervisors, and trainers. Focus group discussions were conducted with the mothers of the Anchal children. The study was conducted in the Manohardi sub-district in November 2015. Decay of knowledge and skills after 2-3 months of training, lack of formal certification and inappropriate selection of women as Anchal caregivers, and enrollment of small children (less than 12 months) were the important challenges. The reluctance of parents to send children to the Anchal at the proper time, failure to engage children in various ECD activities, ineffective conduction of parents and community leaders meeting by the Anchal caregivers, insufficient accommodation, and poor supply of logistics for children were also the important challenges. The suggestion for improvement was to recruit caregivers as per standard criteria, provide them refreshers training at three months intervals, train them on effective conduction of parents and community leaders meetings, provide a formal certificate, and ensure regular supply of logistics. The identified challenges are needed to be addressed by utilizing the suggestions obtained from the IDIs and FGDs to make the Anchal intervention more effective in preventing childhood injuries.

Keywords: comunity crech, earlychildhood development, measures for improvement, childhood injury

Procedia PDF Downloads 72