Search results for: data mining applications and discovery

Authors: Gayan Mapitiya

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Maintaining good occupational health and safety (OHS) performance is significant at the coalface, especially in industries such as mining, power, and construction. Coalface workers are vulnerable to high OHS risks such as working at heights, working with mobile plants and vehicles, working with underground and above ground services, chemical emissions, radiation hazards and explosions at everyday work. To improve OHS performance of workers, OHS key performance indicators (KPIs) (for example, lost time injuries (LTI), serious injury frequency rate (SIFR), total reportable injury frequency rate (TRIFR) and number of near misses) are widely used by managers in making OHS business decisions such as investing in safety equipment and training programs. However, in many organizations, workers at the coalface hardly see any relevance or value addition of OHS KPIs to their everyday work. Therefore, the aim of the study was to understand why coalface workers perceive that OHS KPIs are not practically relevant to their jobs. Accordingly, this study was conducted as a qualitative case study focusing on a large electricity and gas firm in Australia. Semi-structured face to face interviews were conducted with selected coalface workers to gather data on their attitude towards OHS KPIs. The findings of the study revealed that workers at the coalface generally have no understanding of the purpose of KPIs, the meaning of each KPI, origin of KPIs, and how KPIs are correlated to organizational performance. Indeed, KPIs are perceived as ‘meaningless obstacles’ imposed on workers by managers without a rationale. It is recommended to engage coalface workers (a fair number of representatives) in both KPIs setting and revising processes while maintaining a continuous dialogue between workers and managers in regards OHS KPIs.

Keywords: KPIs, coalface, OHS risks, case-study

Procedia PDF Downloads 119

Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless nodes in a sensor network gather and process critical information designed to process and communicate, information flooding through such network is critical for decision making and data processing, the integrity of such data is one of the most critical factors in wireless security without compromising the processing and transmission capability of the network. This paper presents mechanism to securely transmit data over a chain of sensor nodes without compromising the throughput of the network utilizing available battery resources available at the sensor node.

Keywords: hybrid protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node data processing, Z-MAC

Procedia PDF Downloads 147

Authors: Aydın Kavak, Özkan Coruk, Adnan Aydıner

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Long-term performance of pavement structures is significantly impacted by the stability of the underlying soils. In situ subgrades often do not provide enough support required to achieve acceptable performance under traffic loading and environmental demands. NovoCrete® is a powder binder-mineral for cement stabilized road pavements soils. NovoCrete® combined with Portland cement at optimum water content increases the crystallize formations during the hydration process, resulting in higher strengths, neutralizes pH levels, and provides water impermeability. These changes in soil properties may lead to transforming existing unsuitable in-situ materials into suitable fill materials. The main features of NovoCrete® are: They are applicable to all types of soil, reduce premature cracking and improve soil properties, creating base and subbase course layers with high bearing capacity by reducing hazardous materials. It can be used also for stabilization of recyclable aggregates and old asphalt pavement aggregate, etc. There are many applications in Germany, Turkey, India etc. In this paper, a few field application in Turkey will be discussed. In the road construction works, this binder material is used for cement stabilization works. In the applications 120-180 kg cement is used for 1 m3 of soil with a 2 % of binder NovoCrete® material for the stabilization. The results of a plate loading test in a road construction site show 1 mm deformation which is very small under 7 kg/cm2 loading. The modulus of subgrade reaction increase from 611 MN/m3 to 3673 MN/m3.The soaked CBR values for stabilized soils increase from 10-20 % to 150-200 %. According to these data weak subgrade soil can be used as a base or sub base after the modification. The potential reduction in the need for quarried materials will help conserve natural resources. The use of on-site or nearby materials in fills, will significantly reduce transportation costs and provide both economic and environmental benefits.

Keywords: soil, stabilization, cement, binder, Novocrete, additive

Procedia PDF Downloads 226

Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

Procedia PDF Downloads 151

Authors: Noshaba Dilbar, Maria Jabbar

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Medicinal plants are considered to be the richest source of drug discovery. The main cause of medicinal properties of plants is the presence of bioactive compounds in them. Phytochemical screening is the valuable process that detects bioactive compounds(secondary metabolites) in plants. The present study was carried out to determine phytochemical profile and ethnobotanical importance of Capparidaceae species. ( Capparis spinosa and Dipterygium glaucum). The selection of plants was made on basis of traditional knowledge of their usage in ayurvedic medicines. Different type of solvents(ethanol, methanol, chloroform, benzene and petroleum ether) were used to make extracts of dry and fresh plants. Phytochemical screening was made by using various standard techniques. Results reveal the presence of large range of bioactive compounds i.e alakloids, saponins, flavonoids, terpenoids, glycosides, phenols and steroids. Methanol, petroleum ether and chloroform extracts showed high extractability of bioactive compounds. The results obtained ensure these plants a reliable source of pharmacological industry and can be used in making of various biological friendly drugs.

Keywords: bioactive compounds, Capparidaceae, phytochemical screening, secondary metabolites

Procedia PDF Downloads 180

Authors: Eric Hawkinson, Edgaras Artemciukas

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This study outlines iterations of designing mobile augmented reality (MAR) applications for tourism specific contexts. Using a design based research model, several cycles of development to implementation were analyzed and refined upon with the goal of building a MAR platform that would facilitate the creation of augmented tours and environments by non-technical users. The project took on several stages, and through the process, a simple framework was begun to be established that can inform the design and use of MAR applications for tourism contexts. As a result of these iterations of development, a platform was developed that can allow novice computer users to create augmented tourism environments. This system was able to connect existing tools in widespread use such as Google Forms and connect them to computer vision algorithms needed for more advanced augmented tourism environments. The study concludes with a discussion of this MAR platform and reveals design elements that have implications for tourism contexts. The study also points to future case uses and design approaches for augmented tourism.

Keywords: augmented tourism, augmented reality, user experience, mobile design, e-tourism

Procedia PDF Downloads 221

Authors: Kunal Ahluwalia, Ampara Aramcharoen, Chan Wai Luen, Swee Hock Yeo

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The different process engineering applications of vibratory finishing technology have led to its versatile use in the development of aviation components. The most noteworthy applications of vibratory finishing include deburring and imparting the required surface finish. In this paper, vibratory finishing has been used to study its effectiveness in removal of laser shock peened (LSP) layers from Titanium workpieces. A vibratory trough operating at a frequency of 25 Hz, amplitude 3.5 mm and titanium specimens (Ti-6Al-4V, Grade 5) of dimensions 50 x 50 x 10 mm³ were utilized for the experiments. A vibrating fixture operating at 200 Hz was used to provide vibration to the test piece and was immersed in the vibratory trough. It was evident that there is an increase in efficiency of removal of the complex featured layer and smoother surface finish with the introduction of the vibrating fixture in the vibratory finishing setup as compared to the conventional vibratory finishing setup wherein the fixture is not vibrating.

Keywords: laser shock peening, material removal, surface roughness, vibrating fixture, vibratory finishing

Procedia PDF Downloads 225

Authors: Veronica Diaz Quezada

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The society of the 21st century requires training of engineers capable of solving routine and non-routine problems in applications of the limit of real functions, as part of the course Calculus I. For this purpose, research was conducted with a methodological design that combines quantitative and qualitative procedures and that aims, to identify and to characterize the types of problems according to their nature and context, through the application of a mathematics test; to know— through a questionnaire— the opinion of difficulties in their solution, previous and missing knowledge of some students of three engineering careers of a state university in Chile. This research is completed with three case studies. The results favor the performance of students in solving problems of a fantasist and realistic context, but these do not guarantee mathematical skills which are necessary to solve non-routine problems of limit applications. In conclusion, through this research, it became clear that the students of the three engineerings do not have all the necessary skills to solve problems of application of the limit of a function of the real variable.

Keywords: case studies, engineering program, limits, problem solving

Procedia PDF Downloads 135

Authors: Baylasan Al-Amoudi, Hala Abdulmajeed, Amjad Jilani

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This project explores the role of artificial intelligence (AI) in enhancing user engagement on TikTok by examining the app’s AI-driven features. Through a structured survey of 4 main questions and experimental analysis, we tried to examine how TikTok’s recommendations, algorithms, search engine, and filter tools influence user interactions and satisfaction. A diverse cohort of 20 participants, including casual users and content creators, were involved to provide a broad perspective on user experiences. The examination highlights the recommendation algorithm’s ability to deliver highly personalized content, creating a seamless and engaging experience. TikTok’s search engine is shown to simplify content discovery by enabling users to find specific topics or trends related to their preferences. Meanwhile, the filter tools are found to encourage creativity, particularly for content creators, by offering versatile options to enhance video quality and visual appeal. By evaluating the unique roles of these AI features, the project underscores their significance in maintaining TikTok’s appeal and driving consistent user engagement.

Keywords: TikTok, hashtags, filters, viral sounds, for you page

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Authors: Sunil Kumar

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For many years, small organic molecules derived naturally from microbes and plants have delivered a number of expedient therapeutic drug agents. The search for naturally occurring lead compounds has continued in recent years as well, with the constituents of marine flora and fauna along with those of telluric microorganisms and plants being investigated for their anti-bacterial and anti-cancer activities. It has been observed that such promising lead molecules incline to promptly generate substantial attention among scientists like synthetic organic chemists and biologists. Subsequently, the availability of a given precious natural product sample may be enriched, and it may be possible to determine a preliminary idea of structure-activity relationships to develop synthetic analogues. For instance, anti-tumor drug topotecan is a synthetic chemical compound similar in chemical structure to camptothecin which is found in extracts of Camptotheca acuminate. Similarly, researchers at AstraZeneca discovered anti-biotic pyrrolamide through a fragment-based lead generation approach from kibdelomycin, which is isolated from Staphylococcus aureuss.

Keywords: anticancer, antibiotic, lead molecule, natural product, synthetic analogues

Procedia PDF Downloads 156

Authors: Wajid Rehman, Sirajul Haq, Bakhtiar Muhammad, Syed Fahad Hassan, Amin Badshah, Muhammad Waseem, Fazal Rahim, Obaid-Ur-Rahman Abid, Farzana Latif Ansari, Umer Rashid

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Five novel triorganotin (IV) compounds have been synthesized and characterized. The tin atom is penta-coordinated to assume trigonal-bipyramidal geometry. Using in silico derived parameters; the objective of our study is to design and synthesize promiscuous antibacterials potent enough to combat resistance. Among various synthesized organotin (IV) complexes, compound 5 was found as potent antibacterial agent against various bacterial strains. Further lead optimization of drug-like properties was evaluated through in silico predictions. Data mining and computational analysis were utilized to derive compound promiscuity phenomenon to avoid drug attrition rate in designing antibacterials. Xanthine oxidase and human glucose- 6-phosphatase were found as only true positive off-target hits by ChEMBL database and others utilizing similarity ensemble approach. Propensity towards a-3 receptor, human macrophage migration factor and thiazolidinedione were found as false positive off targets with E-value 1/4> 10^-4 for compound 1, 3, and 4. Further, displaying positive drug-drug interaction of compound 1 as uricosuric was validated by all databases and docked protein targets with sequence similarity and compositional matrix alignment via BLAST software. Promiscuity of the compound 5 was further confirmed by in silico binding to different antibacterial targets.

Keywords: antibacterial activity, drug promiscuity, ADMET prediction, metallo-pharmaceutical, antimicrobial resistance

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Authors: Aritra Majumdar

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While organizations strive to expand their new customer base, retaining existing relationships is a key aspect of improving overall profitability and also showcasing how successful an organization is in holding on to its customers. It is an experimentally proven fact that the lion’s share of profit always comes from existing customers. Hence seamless management of renewal journeys across different channels goes a long way in improving trust in the brand. From a quality assurance standpoint, time travel testing provides an approach to both business and technology teams to enhance the customer experience when they look to extend their partnership with the organization for a defined phase of time. This whitepaper will focus on key pillars of time travel testing: time travel planning, time travel data preparation, and enterprise automation. Along with that, it will call out some of the best practices and common accelerator implementation ideas which are generic across verticals like healthcare, insurance, etc. In this abstract document, a high-level snapshot of these pillars will be provided. Time Travel Planning: The first step of setting up a time travel testing roadmap is appropriate planning. Planning will include identifying the impacted systems that need to be time traveled backward or forward depending on the business requirement, aligning time travel with other releases, frequency of time travel testing, preparedness for handling renewal issues in production after time travel testing is done and most importantly planning for test automation testing during time travel testing. Time Travel Data Preparation: One of the most complex areas in time travel testing is test data coverage. Aligning test data to cover required customer segments and narrowing it down to multiple offer sequencing based on defined parameters are keys for successful time travel testing. Another aspect is the availability of sufficient data for similar combinations to support activities like defect retesting, regression testing, post-production testing (if required), etc. This section will talk about the necessary steps for suitable data coverage and sufficient data availability from a time travel testing perspective. Enterprise Automation: Time travel testing is never restricted to a single application. The workflow needs to be validated in the downstream applications to ensure consistency across the board. Along with that, the correctness of offers across different digital channels needs to be checked in order to ensure a smooth customer experience. This section will talk about the focus areas of enterprise automation and how automation testing can be leveraged to improve the overall quality without compromising on the project schedule. Along with the above-mentioned items, the white paper will elaborate on the best practices that need to be followed during time travel testing and some ideas pertaining to accelerator implementation. To sum it up, this paper will be written based on the real-time experience author had on time travel testing. While actual customer names and program-related details will not be disclosed, the paper will highlight the key learnings which will help other teams to implement time travel testing successfully.

Keywords: time travel planning, time travel data preparation, enterprise automation, best practices, accelerator implementation ideas

Procedia PDF Downloads 164

Authors: Hassan Bohra, Mingfeng Wang

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Conjugated porous polymers (CPPs) are amorphous, insoluble and highly robust organic semiconductors that have been largely synthesized by traditional transition-metal catalyzed reactions. The distinguishing feature of CPP materials is that they combine microporosity and high surface areas with extended conjugation, making them ideal for versatile applications such as separation, catalysis and energy storage. By applying a modular approach to synthesis, chemical and electronic properties of CPPs can be tailored for specific applications making these materials economical alternatives to inorganic semiconductors. Direct arylation - an environmentally benign alternative to traditional polymerization reactions – is one such reaction that extensively over the last decade for the synthesis of linear p-conjugated polymers. In this report, we present the synthesis and characterization of a new series of robust conjugated porous polymers synthesized by facile direct arylation polymerization of thiophene-flanked acceptor building blocks with multi-brominated aryls with different geometries. We observed that the porosities and morphologies of the polymers are determined by the chemical structure of the aryl bromide used. Moreover, good control of the optical bandgap in the range 2.53 - 1.3 eV could be obtained by using different building blocks. Structure-property relationships demonstrated in this study suggest that direct arylation polymerization is an attractive synthetic tool for the rational design of porous organic materials with tunable photo-physical properties for applications in photocatalysis, energy storage and conversion.

Keywords: direct arylation, conjugated porous polymers, triazine, photocatalysis

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Authors: M. Kamel, A. Hoayek, M. Batton-Hubert

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With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.

Keywords: logs, anomaly detection, ML, scoring, NLP

Procedia PDF Downloads 100

Authors: Vinh Duy Cao, Carlos Salas-Bringas, Anna M. Szczotok, Marianne Hiorth, Anna-Lena Kjøniksen

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The increasing cost of energy supply for the purposes of heating and cooling creates a demand for more energy efficient buildings. Improved construction techniques and enhanced material technology can greatly reduce the energy consumption needed for the buildings. Microencapsulated phase change materials (MPCM) suspensions utilized as heat transfer fluids for energy storage and heat transfer applications provide promising potential solutions. A full understanding of the flow and thermal characteristics of microcapsule suspensions is needed to optimize the design of energy storage systems, in order to reduce the capital cost, system size, and energy consumption. The MPCM suspensions exhibited pseudoplastic and thixotropic behaviour, and significantly improved the thermal performance of the suspensions. Three different models were used to characterize the thixotropic behaviour of the MPCM suspensions: the second-order structural, kinetic model was found to give a better fit to the experimental data than the Weltman and Figoni-Shoemaker models. For all samples, the initial shear stress increased, and the breakdown rate accelerated significantly with increasing concentration. The thermal performance and rheological properties, especially the selection of rheological models, will be useful for developing the applications of microcapsules as heat transfer fluids in thermal energy storage system such as calculation of an optimum MPCM concentration, pumping power requirement, and specific power consumption. The effect of temperature on the shear thinning properties of the samples suggests that some of the phase change material is located outside the capsules, and contributes to agglomeration of the samples.

Keywords: latent heat, microencapsulated phase change materials, pseudoplastic, suspension, thixotropic behaviour

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Authors: Tony Cripps, Larry Kimber

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This paper will begin by briefly explaining how blockchain technology works. Then, after highlighting a few of the ways it promises to heavily impact all aspects of the digital landscape, the focus will shift to Blockchain in the field of education, with specific emphasis placed on practical applications in foreign language education. Blockchain is a decentralized Internet-based software application that guarantees truth in transactions. This means whenever two parties engage in a transaction using Blockchain, it is time-stamped, added to a block of other transactions, and then permanently attached to an unalterable ‘chain’ of blocks. The potential for developing applications with Blockchain is therefore immense, since software systems that ensure the impossibility of outside tampering are invaluable. Innovative ideas in every imaginable domain are presently being entertained and Blockchain in education is no exception. For instance, records kept within and between institutions of students’ grade performance, academic achievement and verification of assignment/course completion are just a few examples of how this new technology might potentially be used to revolutionize education. It is hoped that this paper will be of use to all educators interested in the application of technology in the field of education.

Keywords: blockchain, disruption, potential, technology

Procedia PDF Downloads 141

Authors: A. Peniak, J. Makarovič, P. Rafajdus, P. Dúbravka

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The purpose of this work is to optimize a Switched Reluctance Motor (SRM) for an automotive application, specifically for a fully electric car. A new optimization approach is proposed. This unique approach transforms automotive customer requirements into an optimization problem, based on sound knowledge of a SRM theory. The approach combines an analytical and a finite element analysis of the motor to quantify static nonlinear and dynamic performance parameters, as phase currents and motor torque maps, an output power and power losses in order to find the optimal motor as close to the reality as possible, within reasonable time. The new approach yields the optimal motor which is competitive with other types of already proposed motors for automotive applications. This distinctive approach can also be used to optimize other types of electrical motors, when parts specifically related to the SRM are adjusted accordingly.

Keywords: automotive, drive system, electric car, finite element method, hybrid car, optimization, switched reluctance motor

Procedia PDF Downloads 525

Authors: Leo Nnamdi Ozurumba-Dwight

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Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

Procedia PDF Downloads 180

Authors: Haifa Ben Saber, Mourad Elloumi

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In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of constant rows with a group of columns. This kind of clustering is called biclustering. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed. We introduce a new algorithm called, Enumerative tree (EnumTree) for biclustering of binary microarray data. is an algorithm adopting the approach of enumerating biclusters. This algorithm extracts all biclusters consistent good quality. The main idea of ​​EnumLat is the construction of a new tree structure to represent adequately different biclusters discovered during the process of enumeration. This algorithm adopts the strategy of all biclusters at a time. The performance of the proposed algorithm is assessed using both synthetic and real DNA micryarray data, our algorithm outperforms other biclustering algorithms for binary microarray data. Biclusters with different numbers of rows. Moreover, we test the biological significance using a gene annotation web tool to show that our proposed method is able to produce biologically relevent biclusters.

Keywords: DNA microarray, biclustering, gene expression data, tree, datamining.

Procedia PDF Downloads 374

Authors: Lynn Ruggieri

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The worldwide pandemic has only increased sustainability awareness. The public is demanding that businesses be held accountable for their impact on the environment. While financial data enjoys uniformity in reporting requirements, there are no uniform reporting requirements for non-financial data. Europe is leading the way with some standards being implemented for reporting non-financial sustainability data; however, there is no uniformity globally. And without uniformity, there is not a clear understanding of what information to include and how to disclose it. Sustainability reporting will provide important information to stakeholders and will enable businesses to understand their impact on the environment. Therefore, there is a crucial need for this data. This paper looks at the history of sustainability reporting in the countries of the European Union and throughout the world and makes a case for worldwide reporting requirements for sustainability.

Keywords: financial reporting, non-financial data, sustainability, global financial reporting

Procedia PDF Downloads 183

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm

Procedia PDF Downloads 445

Authors: Syamsul Syafiq, Maslina Daud, Hafizah Hasan, Ahmad Zairi, Shazil Imri, Ezaini Akmar, Norbazilah Rahim

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Over recent years, web development has changed significantly. Driven largely by the rise of trends like mobiles, the world of development is rapidly evolving. The rise of the Internet makes web applications crucial nowadays. The web application has been an interface for a company and one of the ways they present their portfolio to the client. On the other hand, the web has become part of the file management system which takes over the role of paper. Due to high demand in web applications, developers are required to develop a web application that are cost-effective, secure and well coded. A framework has been proposed to develop an application rather than using library style development. The framework is helping the developer in creating the structure of a web automatically. This paper will compare the advantages and disadvantages of web development using framework against library-style development. This comparison is based on a previous research paper focusing on two main indicators, which are the impact to management and impact to the developer.

Keywords: framework, library style development, web application development, traditional web, static web, dynamic web

Procedia PDF Downloads 228

Authors: Sahil Imtiyaz

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One of the biggest challenges has emerged from the ever-expanding, dynamic, and instantaneously changing space-Big Data; and to find a data point and inherit wisdom to this space is a hard task. In this paper, we reduce the space of big data in Hamiltonian formalism that is in concordance with Ising Model. For this formulation, we simulate the system using dye laser in FORTRAN and analyse the dynamics of the data point in energy well of rhodium atom. After mapping the photon intensity and pulse width with energy and potential we concluded that as we increase the energy there is also increase in probability of tunnelling up to some point and then it starts decreasing and then shows a randomizing behaviour. It is due to decoherence with the environment and hence there is a loss of ‘quantumness’. This interprets the efficiency parameter and the extent of quantum evolution. The results are strongly encouraging in favour of the use of ‘Topological Property’ as a source of information instead of the qubit.

Keywords: big data, optimization, quantum evolution, hamiltonian, dye laser, fermionic computations

Procedia PDF Downloads 198

Authors: Patrick J. Kerpan, Ryan C. Koop, Margaret M. Walker, Chris P. Swan

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The User Datagram Protocol (UDP) multicast is a vital part of data center networking that is being left out of major cloud computing providers' network infrastructure. Enterprise users rely on multicast, and particularly UDP multicast to create and connect vital business operations. For example, UPD makes a variety of business functions possible from simultaneous content media updates, High-Performance Computing (HPC) grids, and video call routing for massive open online courses (MOOCs). Essentially, UDP multicast's technological slight is causing a huge effect on whether companies choose to use (or not to use) public cloud infrastructure as a service (IaaS). Allowing the ‘chatty’ UDP multicast protocol inside a cloud network could have a serious impact on the performance of the cloud as a whole. Cloud IaaS providers solve the issue by disallowing all UDP multicast. But what about enterprise use cases for multicast applications in organizations that want to move to the cloud? To re-allow multicast traffic, enterprises can build a layer 3 - 7 network over the top of a data center, private cloud, or public cloud. An overlay network simply creates a private, sealed network on top of the existing network. Overlays give complete control of the network back to enterprise cloud users the freedom to manage their network beyond the control of the cloud provider’s firewall conditions. The same logic applies if for users who wish to use IPsec or BGP network protocols inside or connected into an overlay network in cloud IaaS.

Keywords: cloud computing, protocols, UDP multicast, virtualization

Procedia PDF Downloads 596

Authors: Muhammad Muhammad Suleiman

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Cloud Computing is a versatile concept that refers to a service that allows users to outsource their data without having to worry about local storage issues. However, the most pressing issues to be addressed are maintaining a secure and reliable data repository rather than relying on untrustworthy service providers. In this study, we look at how stenography approaches and collaboration with Digital Watermarking can greatly improve the system's effectiveness and data security when used for Cloud Computing. The main requirement of such frameworks, where data is transferred or exchanged between servers and users, is safe data management in cloud environments. Steganography is the cloud is among the most effective methods for safe communication. Steganography is a method of writing coded messages in such a way that only the sender and recipient can safely interpret and display the information hidden in the communication channel. This study presents a new text steganography method for hiding a loaded hidden English text file in a cover English text file to ensure data protection in cloud computing. Data protection, data hiding capability, and time were all improved using the proposed technique.

Keywords: cloud computing, steganography, information hiding, cloud storage, security

Procedia PDF Downloads 198

Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

Abstract:

Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Mahmoud Zakeri Niri, Saber Moazami, Arman Abdollahipour, Hossein Ghalkhani

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The objective of this research is to hydrological evaluation of four widely-used satellite precipitation products named PERSIANN, TMPA-3B42V7, TMPA-3B42RT, and CMORPH over Zarinehrood basin in Iran. For this aim, at first, daily streamflow of Sarough-cahy river of Zarinehrood basin was simulated using IHACRES rainfall-runoff model with daily rain gauge and temperature as input data from 1988 to 2008. Then, the model was calibrated in two different periods through comparison the simulated discharge with the observed one at hydrometric stations. Moreover, in order to evaluate the performance of satellite precipitation products in streamflow simulation, the calibrated model was validated using daily satellite rainfall estimates from the period of 2003 to 2008. The obtained results indicated that TMPA-3B42V7 with CC of 0.69, RMSE of 5.93 mm/day, MAE of 4.76 mm/day, and RBias of -5.39% performs better simulation of streamflow than those PERSIANN and CMORPH over the study area. It is noteworthy that in Iran, the availability of ground measuring station data is very limited because of the sparse density of hydro-meteorological networks. On the other hand, large spatial and temporal variability of precipitations and lack of a reliable and extensive observing system are the most important challenges to rainfall analysis, flood prediction, and other hydrological applications in this country.

Keywords: hydrological evaluation, IHACRES, satellite precipitation product, streamflow simulation

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Authors: Sehrish Iftikhar, Ahmad Ali Shahid, Kiran Nawaz, Waheed Anwar

Abstract:

Discovery and development of new compounds require intense studies in chemistry, biochemistry. Numerous experiments under laboratory-, greenhouse- and field conditions can be performed to select suitable candidates and to understand their full potential. Novel fungicides are fundamental to combat plant diseases. Fusarium solani is important plant pathogen. New broad spectrum foliar fungicides against complex II were designed in this study. Complex II, namely succinate dehydrogenase (SDH), or succinate quinone oxidoreductase (SQR) is a multi-subunit enzyme at the crossroads of TCA and ETC at the inner mitochondrial membrane. The need for new and innovative fungicides is driven by resistance management, regulatory hurdles and increasing customer expectations amongst others. Fungicidal activity was assessed for the effect on mycelial growth and spore germination of the fungi using fungicide amended media assay. In mycelial growth assay compounds C10 and C6 were highly active against all the isolates. The compounds C1 and C10 were found most potent in spore germination test. It fully proved that the SDHIs designed in this paper displayed as good inhibitory effects against Fusarium solani.

Keywords: Wilt, Fusarium, SDH, antifungal

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Authors: Akalu Banbeta, Emmanuel Lesaffre, Reynaldo Martina, Joost Van Rosmalen

Abstract:

Including data from previous studies (historical data) in the analysis of the current study may reduce the sample size requirement and/or increase the power of analysis. The most common example is incorporating historical control data in the analysis of a current clinical trial. However, this only applies when the historical control dataare similar enough to the current control data. Recently, several Bayesian approaches for incorporating historical data have been proposed, such as the meta-analytic-predictive (MAP) prior and the modified power prior (MPP) both for single control as well as for multiple historical control arms. Here, we examine the performance of the MAP and the MPP approaches for the analysis of (over-dispersed) count data. To this end, we propose a computational method for the MPP approach for the Poisson and the negative binomial models. We conducted an extensive simulation study to assess the performance of Bayesian approaches. Additionally, we illustrate our approaches on an overactive bladder data set. For similar data across the control arms, the MPP approach outperformed the MAP approach with respect to thestatistical power. When the means across the control arms are different, the MPP yielded a slightly inflated type I error (TIE) rate, whereas the MAP did not. In contrast, when the dispersion parameters are different, the MAP gave an inflated TIE rate, whereas the MPP did not.We conclude that the MPP approach is more promising than the MAP approach for incorporating historical count data.

Keywords: count data, meta-analytic prior, negative binomial, poisson

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