Search results for: cloud data privacy and integrity

Authors: M. A. I Perera, C. R. Wijesinghe, A. R. Weerasinghe

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his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes.

Keywords: cancer subtypes, gene expression data analysis, clustering, cluster validation

Procedia PDF Downloads 137

Authors: Matthew Montebello

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Student engagement within a virtual learning environment generates masses of data points that can significantly contribute to the learning analytics that lead to decision support. Ideally, similar data is collected during student interaction with a physical learning space, and as a consequence, data is present at a large scale, even in relatively small classes. In this paper, we report of such an occurrence during classes held in a HiFlex modality as we investigate the advantages of adopting such a methodology. We plan to take full advantage of the learner-generated data in an attempt to further enhance the effectiveness of the adopted learning environment. This could shed crucial light on operating modalities that higher education institutions around the world will switch to in a post-COVID era.

Keywords: HiFlex, big data in higher education, learning analytics, virtual learning environment

Procedia PDF Downloads 188

Authors: Shahzad Hassan, Kamran Saeed

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People are always in search of Wi-Fi hotspots because Internet is a major demand nowadays. But like all other technologies, there is still room for improvement in the Wi-Fi technology with regards to the speed and quality of connectivity. In order to address these aspects, Harald Haas, a professor at the University of Edinburgh, proposed what we know as the Li-Fi (Light Fidelity). Li-Fi is a new technology in the field of wireless communication to provide connectivity within a network environment. It is a two-way mode of wireless communication using light. Basically, the data is transmitted through Light Emitting Diodes which can vary the intensity of light very fast, even faster than the blink of an eye. From the research and experiments conducted so far, it can be said that Li-Fi can increase the speed and reliability of the transfer of data. This paper pays particular attention on the assessment of the performance of this technology. In other words, it is a 5G technology which uses LED as the medium of data transfer. For coverage within the buildings, Wi-Fi is good but Li-Fi can be considered favorable in situations where large amounts of data are to be transferred in areas with electromagnetic interferences. It brings a lot of data related qualities such as efficiency, security as well as large throughputs to the table of wireless communication. All in all, it can be said that Li-Fi is going to be a future phenomenon where the presence of light will mean access to the Internet as well as speedy data transfer.

Keywords: communication, LED, Li-Fi, Wi-Fi

Procedia PDF Downloads 331

Authors: Renata Kurpiewska-Korbut

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Making an assumption that the use and sharing of data generated in humanitarian action constitute a core function of humanitarian organizations, the paper analyzes the position of the largest Polish humanitarian non-governmental organizations in the humanitarian data ecosystem in Ukraine and their approach to non-personal and personal data management since February of 2022. Both expert interviews and document analysis of non-profit organizations providing a direct response in the Ukrainian crisis context, i.e., the Polish Humanitarian Action, Caritas, Polish Medical Mission, Polish Red Cross, and the Polish Center for International Aid and the applicability of theoretical perspective of contingency theory – with its central point that the context or specific set of conditions determining the way of behavior and the choice of methods of action – help to examine the significance of data complexity and adaptive approach to data management by relief organizations in the humanitarian supply chain network. The purpose of this study is to determine how the existence of well-established and accurate internal procedures and good practices of using and sharing data (including safeguards for sensitive data) by the surveyed organizations with comparable human and technological capabilities are implemented and adjusted to Ukrainian humanitarian settings and data infrastructure. The study also poses a fundamental question of whether this crisis experience will have a determining effect on their future performance. The obtained finding indicate that Polish humanitarian organizations in Ukraine, which have their own unique code of conduct and effective managerial data practices determined by contingencies, have limited influence on improving the situational awareness of other assistance providers in the data ecosystem despite their attempts to undertake interagency work in the area of data sharing.

Keywords: humanitarian data ecosystem, humanitarian data management, polish NGOs, Ukraine

Procedia PDF Downloads 80

Authors: Daniel C. Bonzo

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Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

Procedia PDF Downloads 125

Authors: Celal Dudak, Aslı Utku, Burak Yağlioğlu

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Uninterrupted and continuous satellite communication through the whole orbit time is becoming more indispensable every day. Data relay systems are developed and built for various high/low data rate information exchanges like TDRSS of USA and EDRSS of Europe. In these missions, a couple of task-dedicated communication satellites exist. In this regard, for Turkey a data relay system is attempted to be defined exchanging low data rate information (i.e. TTC) for Earth-observing LEO satellites appointing commercial GEO communication satellites all over the world. First, justification of this attempt is given, demonstrating duration enhancements in the link. Discussion of preference of RF communication is, also, given instead of laser communication. Then, preferred communication GEOs – including TURKSAT4A already belonging to Turkey- are given, together with the coverage enhancements through STK simulations and the corresponding link budget. Also, a block diagram of the communication system is given on the LEO satellite.

Keywords: communication, GEO satellite, data relay system, coverage

Procedia PDF Downloads 427

Authors: Tanawat Hongthai, Dusit Thanapatay

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This paper presents the development of encrypted near field communication (NFC) data exchange format transmission in an NFC passive tag for the feasibility of implementing a genuine product authentication. We propose a research encryption and checking the genuine product into four major categories; concept, infrastructure, development and applications. This result shows the passive NFC-forum Type 2 tag can be configured to be compatible with the NFC data exchange format (NDEF), which can be automatically partially data updated when there is NFC field.

Keywords: near field communication, NFC data exchange format, checking the genuine product, encrypted NFC

Procedia PDF Downloads 265

Authors: Yung Gi Wu

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With the growing of computer and network, digital data can be spread to anywhere in the world quickly. In addition, digital data can also be copied or tampered easily so that the security issue becomes an important topic in the protection of digital data. Digital watermark is a method to protect the ownership of digital data. Embedding the watermark will influence the quality certainly. In this paper, Vector Quantization (VQ) is used to embed the watermark into the image to fulfill the goal of data hiding. This kind of watermarking is invisible which means that the users will not conscious the existing of embedded watermark even though the embedded image has tiny difference compared to the original image. Meanwhile, VQ needs a lot of computation burden so that we adopt a fast VQ encoding scheme by partial distortion searching (PDS) and mean approximation scheme to speed up the data hiding process. The watermarks we hide to the image could be gray, bi-level and color images. Texts are also can be regarded as watermark to embed. In order to test the robustness of the system, we adopt Photoshop to fulfill sharpen, cropping and altering to check if the extracted watermark is still recognizable. Experimental results demonstrate that the proposed system can resist the above three kinds of tampering in general cases.

Keywords: data hiding, vector quantization, watermark, color image

Procedia PDF Downloads 351

Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

Procedia PDF Downloads 182

Authors: Zahra Mohagheghian, Fatema Agharebparast

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Professional ethic is a subject that has been an issue today, so most of the businesses, including the teaching profession, understand the need and importance of it. So they need to develop a code of professional ethics for their own. In this regard, this study seeks to answer the question, with respect to the integrity of the Qur'an (Nahl / 89), is it possible to contemplate the divine teachers conduct to extract the divine pattern for teaching and training? In the code of conduct for divine teachers what are the most important moral obligations and duties of the teaching professionals? The results of this study show that the teaching of Khidr, according to the Quran’s verses, Abundant and subtle hints emphasized that it can be as comprehensive and divine pattern used in teaching and in the drafting of the charter of professional ethics of teachers used it. Also, the results show that in there have been many ethical principles in prophet Khidr’s teaching pattern.The most important ethical principles include: Student assessment, using objective and not subjective examples, assessment during teaching, flexibility, and others. According to each of these principles can help teachers achieve their educational goals and lead human being in their path toward spiritual evaluation.

Keywords: professional ethics, teaching-learning process, teacher, student, Quran

Procedia PDF Downloads 288

Authors: Mohammad Mosaddik Rahman

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This study embarks on an exploratory journey to assess the pervasive issue of heavy metal contamination in the water bodies along Chittagong Coast, Bangladesh. Situated along the mesmerizing Bay of Bengal, known for its potential as an emerging tourist haven, economic zone, ship breaking yard, confronts significant environmental hurdles. The core of these challenges lies in the contamination from heavy metals such as lead, cadmium, chromium, and mercury, which detrimentally impact both the ecological integrity and public health of the region. This contamination primarily stems from industrial activities, particularly those involving metallurgical and chemical processes, which release these metals into the environment, leading to their accumulation in soil and water bodies. The study's primary aim is to conduct a thorough assessment of heavy metal pollution levels, alongside an analysis of nutrient variations, focusing on nitrates and nitrites. Methodologically, the study leverages systematic sampling and advanced analytical tools like the Hach 3900 spectrophotometer to ensure precise and reliable data collection. The implications of heavy metal presence are multifaceted, affecting microbial and aquatic life, and posing severe health risks to the local population, including respiratory problems, neurological disorders, and an increased risk of cancer. The results of this study highlight the urgent need for effective mitigation strategies and regulatory measures to address this critical issue. By providing a comprehensive understanding of the environmental and public health implications of heavy metal contamination in Chittagong Coast, this research endeavours to serve as a catalyst for change, emphasising the need for pollution control and advancements in water management policies. It is envisioned that the outcomes of this study will guide stakeholders in collaborating to develop and implement sustainable solutions, ultimately safeguarding the region’s environment and public health.

Keywords: heavy metal, environmental health, pollution control policies, shipbreaking yard

Procedia PDF Downloads 42

Authors: Shende Suraj Balu, A. B. Deoghare, K. M. Pandey

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The human middle ear (ME) is a delicate and vital organ. It has a complex structure that performs various functions such as receiving sound pressure and producing vibrations of eardrum and propagating it to inner ear. It consists of Tympanic Membrane (TM), three auditory ossicles, various ligament structures and muscles. Incidents such as traumata, infections, ossification of ossicular structures and other pathologies may damage the ME organs. The conditions can be surgically treated by employing prosthesis. However, the suitability of the prosthesis needs to be examined in advance prior to the surgery. Few decades ago, this issue was addressed and analyzed by developing an equivalent representation either in the form of spring mass system, electrical system using R-L-C circuit or developing an approximated CAD model. But, nowadays a three-dimensional ME model can be constructed using micro X-Ray Computed Tomography (μCT) scan data. Moreover, the concern about patient specific integrity pertaining to the disease can be examined well in advance. The current research work emphasizes to develop the ME model from the stacks of μCT images which are used as input file to MIMICS Research 19.0 (Materialise Interactive Medical Image Control System) software. A stack of CT images is converted into geometrical surface model to build accurate morphology of ME. The work is further extended to understand the dynamic behaviour of Harmonic response of the stapes footplate and umbo for different sound pressure levels applied at lateral side of eardrum using finite element approach. The pathological condition Cholesteatoma of ME is investigated to obtain peak to peak displacement of stapes footplate and umbo. Apart from this condition, other pathologies, mainly, changes in the stiffness of stapedial ligament, TM thickness and ossicular chain separation and fixation are also explored. The developed model of ME for pathologies is validated by comparing the results available in the literatures and also with the results of a normal ME to calculate the percentage loss in hearing capability.

Keywords: computed tomography (μCT), human middle ear (ME), harmonic response, pathologies, tympanic membrane (TM)

Procedia PDF Downloads 164

Authors: Pavel H. Llamocca, Victoria Lopez

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The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

Procedia PDF Downloads 303

Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

Procedia PDF Downloads 244

Authors: Trevor Toy, Josef Langerman

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Around a quarter of the world’s data is generated by financial with an estimated 708.5 billion global non-cash transactions reached between 2018 and. And with Open Banking still a rapidly developing concept within the financial industry, there is an opportunity to create a secure mechanism for connecting its stakeholders to openly, legitimately and consensually share the data required to enable it. Integration and data sharing of anonymised transactional data are still operated in silos and centralised between the large corporate entities in the ecosystem that have the resources to do so. Smaller fintechs generating data and businesses looking to consume data are largely excluded from the process. Therefore there is a growing demand for accessible transactional data for analytical purposes and also to support the rapid global adoption of Open Banking. The following research has provided a solution framework that aims to provide a secure decentralised marketplace for 1.) data providers to list their transactional data, 2.) data consumers to find and access that data, and 3.) data subjects (the individuals making the transactions that generate the data) to manage and sell the data that relates to themselves. The platform also provides an integrated system for downstream transactional-related data from merchants, enriching the data product available to build a comprehensive view of a data subject’s spending habits. A robust and sustainable data market can be developed by providing a more accessible mechanism for data producers to monetise their data investments and encouraging data subjects to share their data through the same financial incentives. At the centre of the platform is the market mechanism that connects the data providers and their data subjects to the data consumers. This core component of the platform is developed on a decentralised blockchain contract with a market layer that manages transaction, user, pricing, payment, tagging, contract, control, and lineage features that pertain to the user interactions on the platform. One of the platform’s key features is enabling the participation and management of personal data by the individuals from whom the data is being generated. This framework developed a proof-of-concept on the Etheruem blockchain base where an individual can securely manage access to their own personal data and that individual’s identifiable relationship to the card-based transaction data provided by financial institutions. This gives data consumers access to a complete view of transactional spending behaviour in correlation to key demographic information. This platform solution can ultimately support the growth, prosperity, and development of economies, businesses, communities, and individuals by providing accessible and relevant transactional data for big data analytics and open banking.

Keywords: big data markets, open banking, blockchain, personal data management

Procedia PDF Downloads 64

Authors: Seon Soon Choi

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It is necessary to predict a fatigue crack propagation life for estimation of structural integrity. Because of an uncertainty and a randomness of a structural behavior, it is also required to analyze stochastic characteristics of the fatigue crack propagation life at a specified fatigue crack size. The essential purpose of this study is to present the good probability distribution fit for the fatigue crack propagation life at a specified fatigue crack size in magnesium alloys under various fatigue load ratio conditions. To investigate a stochastic crack growth behavior, fatigue crack propagation experiments are performed in laboratory air under several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability distribution of the fatigue crack propagation life is performed and the good probability distribution fit for the fatigue crack propagation life is presented. The effect of load ratio on variability of fatigue crack propagation life is also investigated.

Keywords: fatigue crack propagation life, load ratio, magnesium alloys, probability distribution

Procedia PDF Downloads 635

Authors: Arijit Basuray, Saibal Chatterjee

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Pulsed Power in the form of Recurrent Surge Generator (RSG) can be used for testing various parameters of Motor or Transformer windings including inter-turn, interlayer insulation. Windings with solid insulation in motor and transformer have many interfaces and undesirable defects, and these defects can be exposed under this nondestructive testing methodology. Due to rapid development in power electronics variable frequency drives (VFD), Dry Type or cast resin Transformer used with PWM Sine wave inverters for solar power, solid insulation system used nowadays are shifting more and more to a high-frequency application. Authors have used the recurrent surge generator for testing winding integrity as well as Partial Discharge(PD) at fast rising voltage enabling PD measurement at closer situation under which the insulation system is supposed to work. Authors have discussed test results on a different system with recurrent surge voltages of different rise time.

Keywords: fast rising voltage, partial discharge, pulsed power, recurrent surge generator, solid insulation

Procedia PDF Downloads 263

Authors: Asowata Osamede, Christo Pienaar, Johan Bekker

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Mismatch in electrical energy (power) or outage from commercial providers, in general, does not promote development to the public and private sector, these basically limit the development of industries. The necessity for a well-structured photovoltaic (PV) system is of importance for an efficient and cost-effective monitoring system. The major renewable energy potential on earth is provided from solar radiation and solar photovoltaics (PV) are considered a promising technological solution to support the global transformation to a low-carbon economy and reduction on the dependence on fossil fuels. Solar arrays which consist of various PV module should be operated at the maximum power point in order to reduce the overall cost of the system. So power regulation and conditioning circuits should be incorporated in the set-up of a PV system. Power regulation circuits used in PV systems include maximum power point trackers, DC-DC converters and solar chargers. Inappropriate choice of power conditioning device in a basic off-grid PV system can attribute to power loss, hence the need for a right choice of power conditioning device to be coupled with the system of the essence. This paper presents the design and implementation of a power conditioning devices in order to improve the overall yield from the availability of solar energy and the system’s total efficiency. The power conditioning devices taken into consideration in the project includes the Buck and Boost DC-DC converters as well as solar chargers with MPPT. A logging interface circuit (LIC) is designed and employed into the system. The LIC is designed on a printed circuit board. It basically has DC current signalling sensors, specifically the LTS 6-NP. The LIC is consequently required to program the voltages in the system (these include the PV voltage and the power conditioning device voltage). The voltage is structured in such a way that it can be accommodated by the data logger. Preliminary results which include availability of power as well as power loss in the system and efficiency will be presented and this would be used to draw the final conclusion.

Keywords: tilt and orientation angles, solar chargers, PV panels, storage devices, direct solar radiation

Procedia PDF Downloads 124

Authors: Dmitriy Kuptsov

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Tree data structures, such as binary or in general k-ary trees, are essential in computer science. The applications of these data structures can range from data search and retrieval to sorting and ranking algorithms. Naive implementations of these data structures can consume prohibitively large volumes of random access memory limiting their applicability in certain solutions. Thus, in these cases, more advanced representation of these data structures is essential. In this paper we present the design of the compact version of ternary tree data structure and demonstrate the results for the experimental evaluation using static dictionary problem. We compare these results with the results for binary and regular ternary trees. The conducted evaluation study shows that our design, in the best case, consumes up to 12 times less memory (for the dictionary used in our experimental evaluation) than a regular ternary tree and in certain configuration shows performance comparable to regular ternary trees. We have evaluated the performance of the algorithms using both 32 and 64 bit operating systems.

Keywords: algorithms, data structures, succinct ternary tree, per- formance evaluation

Procedia PDF Downloads 154

Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

Procedia PDF Downloads 100

Authors: Joy Olayemi Gbala, Fatai Olatokunbo, Philip Cloud

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Catastrophic dictatorship has been discovered to be the major leadership challenge that orchestrates stagnated and contrasted economy with dysfunctional democracy in Africa through willful misappropriation of resources and egregious subversion of the rule of law. Almost invariably, most African leaders inexplicably often become power drunk and addicted which usually leads to abuse of state power, abdication of constitutional duties, unjustly withdrawal of business license of operation, human right violation, election malpractices, financial corruption, disruptions of policies of democratic government transition, annulment of free and fair election, and disruptions of legal electoral procedures and unachievable dividends of democracy and many more. Owing to this, most African nations have gone and still go through political unrest and insurgencies leading to loss of lives and property, violent protests, detention of detractors and political activists and massive human displacement. This research work is concerned with, and investigates the causes, menace, consequences and impacts of subverting the rule of law in Africa on the economy and the development of the continent with a suggested practical solution to the plights.

Keywords: corruption, law, leadership, violation

Procedia PDF Downloads 142

Authors: Prabhakar C. Dhavale, Meenakshi M. Pawar

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In this paper, everyday tons of data is embedded on digital media or distributed over the internet. The data is so distributed that it can easily be replicated without error, putting the rights of their owners at risk. Even when encrypted for distribution, data can easily be decrypted and copied. One way to discourage illegal duplication is to insert information known as watermark, into potentially valuable data in such a way that it is impossible to separate the watermark from the data. These challenges motivated researchers to carry out intense research in the field of watermarking. A watermark is a form, image or text that is impressed onto paper, which provides evidence of its authenticity. Digital watermarking is an extension of the same concept. There are two types of watermarks visible watermark and invisible watermark. In this project, we have concentrated on implementing watermark in image. The main consideration for any watermarking scheme is its robustness to various attacks

Keywords: watermarking, digital, DCT-DWT, security

Procedia PDF Downloads 413

Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

Procedia PDF Downloads 51

Authors: André Smith, Amr Abdel-Dayem

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The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: colour data, local stereo matching, stereo correspondence, disparity map

Procedia PDF Downloads 360

Authors: Jesmin Akter, Chang Hyuk Ahn, Ilho Kim, Fumitake Nishimura, Jaiyeop Lee

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This study aimed to compare two pre-treatment and two RNA extraction methods, namely PEG, and Nano bubble, Viral RNA Soil, and Mini Kit, in terms of their efficiency in detecting SARS-CoV-2 and PMMoV in influent and 1st sedimentation samples from a wastewater treatment plant. The extracted RNA samples were quantified and evaluated for purity, yield, and integrity. The results indicated that the nanobubble PEG method provided the highest yield of RNA, while the QIAamp Viral RNA Mini Kit produced the purest RNA samples. In terms of sensitivity and specificity, all these methods were able to detect SARS-CoV-2 and PMMoV in both influent and 1st sedimentation samples. However, the nanobubble PEG method showed slightly higher sensitivity compared to the other methods. These findings suggest that the choice of RNA extraction method should depend on the downstream application and the quality of the RNA required. The study also highlights the potential of wastewater-based epidemiology as an effective and non-invasive method for monitoring the spread of infectious diseases in a community.

Keywords: influent, PMMoV, SARS-CoV-2, wastewater based epidemiology

Procedia PDF Downloads 87

Authors: M. Abd elfattah, M. Ossman, Nahla A. Taha

Abstract:

The present work explored the use of Egyptian rice straw, an agricultural waste that leads to global warming problem through brown cloud, as a potential feedstock for the preparation of activated carbon by physical and chemical activation. The results of this study showed that it is feasible to prepare activated carbons with relatively high surface areas and pore volumes from the Egyptian rice straw by direct chemical and physical activation. The produced activated carbon from the two methods (AC1 and AC2) could be used as potential adsorbent for the removal of Fe(III) from aqueous solution contains heavy metals and polluted water. The adsorption of Fe(III) was depended on the pH of the solution. The optimal Fe(III) removal efficiency occurs at pH 5. Based on the results, the optimum contact time is 60 minutes and adsorbent dosage is 3 g/L. The adsorption breakthrough curves obtained at different bed depths indicated increase of breakthrough time with increase in bed depths. A rise in inlet Fe(III) concentration reduces the throughput volume before the packed bed gets saturated. AC1 showed higher affinity for Fe(III) as compared to Raw rice husk.

Keywords: rice straw, activated carbon, Fe(III), fixed bed column, pyrolysis

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Authors: Karima Qayumi, Alex Norta

Abstract:

The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: agent-oriented modeling (AOM), business intelligence model (BIM), distributed data mining (DDM), multi-agent system (MAS)

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Authors: Qing K. Zhu

Abstract:

Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

Procedia PDF Downloads 241

Authors: Brendan Mooney

Abstract:

We often do not consider the quality of the way we express ourselves as being fundamental to well-being. Society focuses predominantly on what we do, not the way we do it, to our great detriment. For example, those who have experienced domestic violence often comment that it was not what was said that hurt the most but the way it was said. In other words, the quality in the way the words were used communicated far more than the actual words themselves. This is an important area of focus for practitioners who may be inclined to emphasize who said what but not bring equal, if not more, focus to the quality of one’s expression. The aim of this study is to highlight how and why the way we express ourselves is more important than what we express, which includes words and all behaviors. Given we are a sensitive species it matters to pay attention to the communication that is not said. For example, we have the ability to recognize that a person is upset or angry by the way they walk into a room, even if they do not say anything or look at anyone. Our sensitivity allows us to detect even the slightest change in another’s emotional state, irrespective of what their exterior behaviors may be exhibiting. This study will focus on the importance of recognizing the quality in the way we express as being fundamental to wellbeing, as it allows us to easily and simply navigate life and relationships without needing to experience the usual pitfalls that otherwise prevail. This research utilizes clinical experience, client observations and client feedback, and several case studies were utilized to illustrate real-life examples of the above. This study is not so much a model of life but a way of life that confirms our deepest nature, that we are incredibly sensitive and far more so than we appreciate or utilize in everyday practical human life.

Keywords: communication, integrity, quality, sensitivity, wellbeing

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