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Articles 5041 - 5070 of 25663

Full-Text Articles in Engineering

Design And Implementation Of A Bioinspired Leaf Shaped Hybrid Rectenna As A Green Energy Manufacturing Concept, Kayhan Çeli̇k, Erol Kurt Jul 2022

Design And Implementation Of A Bioinspired Leaf Shaped Hybrid Rectenna As A Green Energy Manufacturing Concept, Kayhan Çeli̇k, Erol Kurt

Turkish Journal of Electrical Engineering and Computer Sciences

In this communication, the novel low cost hybrid energy harvester combining rectifying antenna with the solar cell for feeding the low power energy systems are reported. The bioinspired leaf shaped monopole antenna is designed to work in the most used communication frequency bands such as GSM-1800, UMTS-2100, WIFI-2.45 and LTE-2.65 GHz for the energy harvesting purposes and microstrip low pass filter is also added on the feeding line for the second harmonic rejection for increasing the efficiency of the harvester. The solar cell is placed on the ground plane of the designed leaf shaped antenna for using volumetric space efficiently …

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Measuring The Rol Of Digital Engineering: It's A Journey, Not A Number, Tom Mcdermott, Kaitlin Henderson, Eileen Van Aken, Alejandro Salado, Joseph Bradley Jul 2022

Measuring The Rol Of Digital Engineering: It's A Journey, Not A Number, Tom Mcdermott, Kaitlin Henderson, Eileen Van Aken, Alejandro Salado, Joseph Bradley

Engineering Management & Systems Engineering Faculty Publications

Systems engineering as a discipline has long had difficulty providing quantifiable evidence of its value (Honour 2004); DE transformation provides an opportunity to better measure its value. Transitioning from a document-based to a model-based approach is expensive, and organizations want to know if the effort and cost to adopt MBSE is worth it.

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Non-Gaussian Analysis Of Herbarium Specimen Damageto Optimize Specimen Collection Management, Aris Yaman, Yulia Aris Kartika, Ariani Indrawati, Zaenal Akbar, Lindung P. Manik, Wita Wardani, Tutie Djarwaningsih, Taufik Mahendra, Dadan R. Saleh Jul 2022

Non-Gaussian Analysis Of Herbarium Specimen Damageto Optimize Specimen Collection Management, Aris Yaman, Yulia Aris Kartika, Ariani Indrawati, Zaenal Akbar, Lindung P. Manik, Wita Wardani, Tutie Djarwaningsih, Taufik Mahendra, Dadan R. Saleh

Knowledge Engineering and Data Science

Damage to specimen collections occurs in practically every herbarium across the world. Hence, some precautions must be taken, such as investigating the factors that cause specimen damage in their collections and evaluating their herbarium collection handling and usage policy. However, manual investigation of the causes of herbarium collection damage requires a lot of effort and time. Only a few studies have attempted to investigate the causes of herbarium collection damage. So far, the non-gaussian approach to detecting the causes of damage to herbarium specimens has not been studied before. This study attempted to explore the effect of species type, time, …

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Social Distancing Monitoring System Using Deep Learning, Amelia Ritahani Ismail, Nur Shairah Muhd Affendy, Asmarani Ahmad Puzi Jul 2022

Social Distancing Monitoring System Using Deep Learning, Amelia Ritahani Ismail, Nur Shairah Muhd Affendy, Asmarani Ahmad Puzi

Knowledge Engineering and Data Science

COVID-19 has been declared a pandemic in the world by 2020. One way to prevent COVID-19 disease, as the World Health Organization (WHO) suggests, is to keep a distance from other people. It is advised to stay at least 1 meter away from others, even if they do not appear to be sick. The reason is that people can also be the virus carrier without having any symptoms. Thus, many countries have enforced the rules of social distancing in their Standard Operating Procedure (SOP) to prevent the virus spread. Monitoring the social distance is challenging as this requires authorities to …

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Automatic 3d Cranial Landmark Positioning Based Onsurface Curvature Feature Using Machine Learning, Putu Hendra Suputra, Anggraini Dwi Sensusiati, Myrtati Dyah Artaria, Gijsbertus Jacob Verkerke, Eko Mulyanto Yuniarno, I Ketut Eddy Purnama Jul 2022

Automatic 3d Cranial Landmark Positioning Based Onsurface Curvature Feature Using Machine Learning, Putu Hendra Suputra, Anggraini Dwi Sensusiati, Myrtati Dyah Artaria, Gijsbertus Jacob Verkerke, Eko Mulyanto Yuniarno, I Ketut Eddy Purnama

Knowledge Engineering and Data Science

Cranial anthropometric reference points (landmarks) play an important role in craniofacial reconstruction and identification. Knowledge to detect the position of landmarks is critical. This work aims to locate landmarks automatically. Landmarks positioning using Surface Curvature Feature (SCF) is inspired by conventional methods of finding landmarks based on morphometrical features. Each cranial landmark has a unique shape. With the appropriate 3D descriptors, the computer can draw associations between shapes and landmarks using machine learning. The challenge in classification and detection in three-dimensional space is to determine the model and data representation. Using three-dimensional raw data in machine learning is a serious …

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The Effect Of Resampling On Classifier Performance: Anempirical Study, Utomo Pujianto, Muhammad Iqbal Akbar, Niendhitta Tamia Lassela, Deni Sutaji Jul 2022

The Effect Of Resampling On Classifier Performance: Anempirical Study, Utomo Pujianto, Muhammad Iqbal Akbar, Niendhitta Tamia Lassela, Deni Sutaji

Knowledge Engineering and Data Science

An imbalanced class on a dataset is a common classification problem. The effect of using imbalanced class datasets can cause a decrease in the performance of the classifier. Resampling is one of the solutions to this problem. This study used 100 datasets from 3 websites: UCI Machine Learning, Kaggle, and OpenML. Each dataset will go through 3 processing stages: the resampling process, the classification process, and the significance testing process between performance evaluation values of the combination of classifier and the resampling using paired t-test. The resampling used in the process is Random Undersampling, Random Oversampling, and SMOTE. The classifier …

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A Comparison Of Machine Learning Models To Prioritise Emailsusing Emotion Analysis For Customer Service Excellence, Mohammad Yasser Chuttur, Yashinee Parianen Jul 2022

A Comparison Of Machine Learning Models To Prioritise Emailsusing Emotion Analysis For Customer Service Excellence, Mohammad Yasser Chuttur, Yashinee Parianen

Knowledge Engineering and Data Science

There has been little research on machine learning for email prioritization for customer service excellence. To fill this gap, we propose and assess the efficacy of various machine learning techniques for classifying emails into three degrees of priority: high, low, and neutral, based on the emotions inherent in the email content. It is predicted that after emails are classified into those three categories, recipients will be able to respond to emails more efficiently and provide better customer service. We use the NRC Emotion Lexicon to construct a labeled email dataset of 517,401 messages for our proposal. Following that, we train …

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Fish Image Classification Using Transfer Learning Method Withadaptive Learning Rate, Rizka Suhana, Wayan Firdaus Mahmudy, Agung Setia Budi Jul 2022

Fish Image Classification Using Transfer Learning Method Withadaptive Learning Rate, Rizka Suhana, Wayan Firdaus Mahmudy, Agung Setia Budi

Knowledge Engineering and Data Science

The diversity of fish species in coral reef ecosystems is one of the indications in determining health in coral reef ecosystems. Many Indonesian Fisheries and Marine Research and Development Agency experts carefully classify fish images. A reliable technique for performing image classification is Convolutional Neural Network (CNN). Transfer learning appears and adopts part of CNN, namely the modified convolution layer. The paper aims to solve the fish classification problem using the pre-trained model of Mobilenet V2. The model has a low computational process and does not use too many memory resources when training image data. The research image data used …

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Human Facial Expressions Identification Using Convolutionalneural Network With Vgg16 Architecture, Luther Alexander Latumakulita, Sandy Laurentius Lumintang, Deiby Tineke Salaki, Steven R. Sentinuwo, Alwin Melkie Sambul, Noorul Islam Jul 2022

Human Facial Expressions Identification Using Convolutionalneural Network With Vgg16 Architecture, Luther Alexander Latumakulita, Sandy Laurentius Lumintang, Deiby Tineke Salaki, Steven R. Sentinuwo, Alwin Melkie Sambul, Noorul Islam

Knowledge Engineering and Data Science

The human facial expression identification system is essential in developing human interaction and technology. The development of Artificial Intelligence for monitoring human emotions can be helpful in the workplace. Commonly, there are six basic human expressions, namely anger, disgust, fear, happiness, sadness, and surprise, that the system can identify. This study aims to create a facial expression identification system based on basic human expressions using the Convolutional Neural Network (CNN) with a 16-layer VGG architecture. Two thousand one hundred thirty-seven facial expression images were selected from the FER2013, JAFFE, and MUG datasets. By implementing image augmentation and setting up the …

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Sentiment Analysis Of Amazon Product Reviews Usingsupervised Machine Learning Techniques, Naveed Sultan Jul 2022

Sentiment Analysis Of Amazon Product Reviews Usingsupervised Machine Learning Techniques, Naveed Sultan

Knowledge Engineering and Data Science

Today, everything is sold online, and many individuals can post reviews about different products to show feedback. Serves as feedback for businesses regarding buyer reviews, performance, product quality, and seller service. The project focuses on buyer opinions based on Mobile Phone reviews. Sentiment analysis is the function of analyzing all these data, obtaining opinions about these products and services that classify them as positive, negative, or neutral. This insight can help companies improve their products and help potential buyers make the right decisions. Once the preprocessing is classified on a trained dataset, these reviews must be preprocessed to remove unwanted …

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Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel Jul 2022

Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel

Turkish Journal of Electrical Engineering and Computer Sciences

The number of people who die due to cardiovascular diseases is quite high. In our study, ECG (electrocar-diogram) signals were divided into segments and waves based on temporal boundaries. Signal similarity methods such as convolution, correlation, covariance, signal peak to noise ratio (PNRS), structural similarity index (SSIM), one of the basic statistical parameters, arithmetic mean and entropy were applied to each of these sections. In addition, a square error-based new approach was applied and the difference of the signs from the mean sign was taken and used as a feature vector. The obtained feature vectors are used in the artificial …

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Transmorph: A Transformer Based Morphological Disambiguator For Turkish, Hi̇lal Özer, Emi̇n Erkan Korkmaz Jul 2022

Transmorph: A Transformer Based Morphological Disambiguator For Turkish, Hi̇lal Özer, Emi̇n Erkan Korkmaz

Turkish Journal of Electrical Engineering and Computer Sciences

The agglutinative nature of the Turkish language has a complex morphological structure, and there are generally more than one parse for a given word. Before further processing, morphological disambiguation is required to determine the correct morphological analysis of a word. Morphological disambiguation is one of the first and crucial steps in natural language processing since its success determines later analyses. In our proposed morphological disambiguation method, we used a transformer-based sequence-to-sequence neural network architecture. Transformers are commonly used in various NLP tasks, and they produce state-of-the-art results in machine translation. However, to the best of our knowledge, transformer-based encoder-decoders have …

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Kean University Students Preparing For Cybersecurity Certification Exams In Free Summer Program, Stanley Mierzwa Jul 2022

Kean University Students Preparing For Cybersecurity Certification Exams In Free Summer Program, Stanley Mierzwa

Center for Cybersecurity

Fifteen Kean University students and recent graduates this summer are studying for cybersecurity certifications in a virtual pilot program offered free of charge through the University’s Center for Cybersecurity.

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An Ontology For Cardiothoracic Surgical Education And Clinical Data Analytics, Maryam Panahiazar, Yorick Chern, Ramon Riojas, Omar S.Latif, Usha Lokala, Dexter Hadley, Amit Sheth, Ramin E.Beygui Jul 2022

An Ontology For Cardiothoracic Surgical Education And Clinical Data Analytics, Maryam Panahiazar, Yorick Chern, Ramon Riojas, Omar S.Latif, Usha Lokala, Dexter Hadley, Amit Sheth, Ramin E.Beygui

Faculty Publications

The development of an ontology facilitates the organization of the variety of concepts used to describe different terms in different resources. The proposed ontology will facilitate the study of cardiothoracic surgical education and data analytics in electronic medical records (EMR) with the standard vocabulary.

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One-Bit Algorithm Considerations For Sparse Pmcw Radar, Ethan Triplett Jul 2022

One-Bit Algorithm Considerations For Sparse Pmcw Radar, Ethan Triplett

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Phase Modulated Continuous Wave (PMCW) radar an emerging technology for autonomous cars. It is more flexible than the current frequency modulated systems, offering better detection resolution, interference mitigation, and future development opportunities. The issue preventing PMCW adoption is the need for high sample-rate analog to digital converters (ADCs). Due to device limits, a large increase in cost and power consumption occurs for every added resolution bit for a given sampling rate. This thesis explores radar detection techniques for few-bit and 1-bit ADC measurements. 1-bit quantization typically results in poor amplitude estimation, which can limit detections if the target signals are …

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Preserving Users’ Privacy In Iot Systems Through Network-Based Access Control, Ahmed Khalid A Alhazmi Jul 2022

Preserving Users’ Privacy In Iot Systems Through Network-Based Access Control, Ahmed Khalid A Alhazmi

Theses and Dissertations

Privacy issues have plagued the rapid proliferation of the Internet of Things (IoT) devices. Resource-constrained IoT devices often obscure transparency for end-users. A lack of transparency and control complicates user trust in IoT. Additionally, a growing history of misuse and abuse exists in IoT. Notably, a smart TV has periodically scanned and collected users’ private information without consent, while power companies have adjusted the temperature of smart thermostats during heat waves. Due to a hybrid of distributed ecosystems within IoT, users cannot easily implement traditional access control over their devices as data flows within different nodes for storage and processing. …

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Finding Top-M Leading Records In Temporal Data, Yiyi Wang Jul 2022

Finding Top-M Leading Records In Temporal Data, Yiyi Wang

Dissertations and Theses Collection (Open Access)

A traditional top-k query retrieves the records that stand out at a certain point in time. On the other hand, a durable top-k query considers how long the records retain their supremacy, i.e., it reports those records that are consistently among the top-k in a given time interval. In this thesis, we introduce a new query to the family of durable top-k formulations. It finds the top-m leading records, i.e., those that rank among the top-k for the longest duration within the query interval. Practically, this query assesses the records based on how long …

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A Concept For Weighting Sentiment Phrase Using Deterministic Solution Of Algebraic Equations, Maryam Jalali, Morteza Zahedi, Abdolali Basiri Jul 2022

A Concept For Weighting Sentiment Phrase Using Deterministic Solution Of Algebraic Equations, Maryam Jalali, Morteza Zahedi, Abdolali Basiri

Turkish Journal of Electrical Engineering and Computer Sciences

Many text mining methods have used statistical information as text and language-independent procedures that are not deterministic. On the other hand, grammatical structure-based methods are limited to use in a certain language and text. We aim to suggest an algorithmic algebraic equation in a deterministic and nonprobabilistic way while maintaining the advantage of language independence. We propose a mathematical approach that transforms text and labels into a set of dumb equations. By solving the equations, each word is assigned a weight that can reflect the semantic information of that word, then we use the proposed algorithm to build a novel …

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Degree-Based Random Walk Approach For Graph Embedding, Sarmad N. Mohammed, Semra Gündüç Jul 2022

Degree-Based Random Walk Approach For Graph Embedding, Sarmad N. Mohammed, Semra Gündüç

Turkish Journal of Electrical Engineering and Computer Sciences

Graph embedding, representing local and global neighbourhood information by numerical vectors, is a crucial part of the mathematical modeling of a wide range of real-world systems. Among the embedding algorithms, random walk-based algorithms have proven to be very successful. These algorithms collect information by creating numerous random walks with a predefined number of steps. Creating random walks is the most demanding part of the embedding process. The computation demand increases with the size of the network. Moreover, for real-world networks, considering all nodes on the same footing, the abundance of low-degree nodes creates an imbalanced data problem. In this work, …

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Generating Ad Creatives Using Deep Learning For Search Advertising, Kevser Nur Çoğalmiş, Ahmet Bulut Jul 2022

Generating Ad Creatives Using Deep Learning For Search Advertising, Kevser Nur Çoğalmiş, Ahmet Bulut

Turkish Journal of Electrical Engineering and Computer Sciences

We generated advertisement creatives programmatically using deep neural networks. A landing page contains relevant text data, which can be used for generating advertisement creatives, i.e. ads. We treated the ad generation task as a text summarization problem and built a sequence to sequence model. In order to assess the validity of our approach, we conducted experiments on four datasets. Our empirical results showed that our model generated relevant ads on a template-based dataset with moderate hyperparameters. Training the model with more content increased the performance of the model, which we attributed to rigorous hyperparameter tune-up. The choice of word embedding …

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Prediction Of Broken Rotor Bar In Induction Motor Using Spectral Entropy Features And Tlbo Optimized Svm, Sudip Halder, Sunil Bhat, Bimal Dora Jul 2022

Prediction Of Broken Rotor Bar In Induction Motor Using Spectral Entropy Features And Tlbo Optimized Svm, Sudip Halder, Sunil Bhat, Bimal Dora

Turkish Journal of Electrical Engineering and Computer Sciences

The information of the fault frequency characteristics is of great importance for all associated fault diag nostics. This requires a high-resolution spectrum analysis to achieve efficient monitoring of machinery faults, especially while diagnosing rotor bar breakage under light load conditions, because the fault frequencies almost overlap with the fundamental. In this context, rather than looking for frequencies associated with rotor faults, several frequency bands are observed separately in terms of the entropy contained within these bands. First, the motor current signal has been divided into several frequency bands using the continuous wavelet transform (CWT), and the spectral entropy is calculated …

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Supermodal Decomposition Of The Linear Swing Equation For Multilayer Networks, Kshitij Bhatta, Amirhossein Nazerian, Francesco Sorrentino, Majeed M. Hayat Jul 2022

Supermodal Decomposition Of The Linear Swing Equation For Multilayer Networks, Kshitij Bhatta, Amirhossein Nazerian, Francesco Sorrentino, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

We study the swing equation in the case of a multilayer network in which generators and motors are modeled differently; namely, the model for each generator is given by second order dynamics and the model for each motor is given by first order dynamics. We also remove the commonly used assumption of equal damping coefficients in the second order dynamics. Under these general conditions, we are able to obtain a decomposition of the linear swing equation into independent modes describing the propagation of small perturbations. In the process, we identify symmetries affecting the structure and dynamics of the multilayer network …

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Electrothermal Design Of A Gan-Based Axially Stator Iron-Mounted Fully Integrated Modular Motor Drive, Armin Ebrahimian, Waqar A. Khan, S. Iman Hosseini, Nathan Weise Jul 2022

Electrothermal Design Of A Gan-Based Axially Stator Iron-Mounted Fully Integrated Modular Motor Drive, Armin Ebrahimian, Waqar A. Khan, S. Iman Hosseini, Nathan Weise

Electrical and Computer Engineering Faculty Research and Publications

The concept of More Electric Aircraft (MEA) has gained a lot of attention from researchers recently. For such an application, two of the pivotal requirements are having a power dense and energy efficient propulsion system. To that end, in the design procedure of the electric motor and its drive system, high power density and efficiency over the entire operating range is the ultimate goal. Thus, the integration of the electric motor and drive system into a single unit has been introduced as an effective method to meet the design objectives. Therefore, this paper presents the design procedure of a module …

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Identification And Quantitation Of Aqueous Single- And Multianalyte Solutions Of The Isomers Ethylbenzene, M-, P-, And O-Xylene Using A Single Specifically Tailored Sensor Coating And Estimation Theory-Based Signal Processing, Nicholas Post, Florian Bender, Fabien Josse, Edwin E. Yaz, Antonio J. Ricco Jul 2022

Identification And Quantitation Of Aqueous Single- And Multianalyte Solutions Of The Isomers Ethylbenzene, M-, P-, And O-Xylene Using A Single Specifically Tailored Sensor Coating And Estimation Theory-Based Signal Processing, Nicholas Post, Florian Bender, Fabien Josse, Edwin E. Yaz, Antonio J. Ricco

Electrical and Computer Engineering Faculty Research and Publications

The isomer-specific detection and quantitation of m-, p-, and o-xylene and ethylbenzene, dissolved singly and as mixtures in aqueous solutions at concentrations from 100 to 1200 ppb by volume, is reported for a specifically designed polymer-plasticizer coating on a shear-horizontal surface acoustic wave (SH-SAW) device. The polystyrene-ditridecyl phthalate-blend coating was designed utilizing Hansen solubility parameters and considering the dipole moment and polarizability of the analytical targets and coating components to optimize the affinity of the sensor coating for the four chemical isomers. The two key coating sorption properties, sensitivity and response time constant, are determined by the …

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Analysis Of Digital Image Segmentation Algorithms, Khalilov Sirojiddin Jun 2022

Analysis Of Digital Image Segmentation Algorithms, Khalilov Sirojiddin

Karakalpak Scientific Journal

Ushbu maqolada zamonaviy axborot-kommunikatsiya texnologiyalaridan foydalanishni kengaytirish maqsadida raqamli tasvirni qayta ishlash usullari va algoritmlari tahlil qilinadi. Maqolada, shuningdek, raqamli tasvirni qayta ishlash, tasvirni segmentatsiyalash usullari, WaterShed, MeanShift, FloodFill, GrabCut algoritmlarining afzalliklari va kamchiliklari o'rganiladi.

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Critical Information Infrastructure Protection, Vulnerabilities, Threats And Challenges: A Critical Review, Krishna Prakasha Jun 2022

Critical Information Infrastructure Protection, Vulnerabilities, Threats And Challenges: A Critical Review, Krishna Prakasha

Manipal Journal of Science and Technology

Protection of Critical Information Infrastructure is a crucial requirement nowadays and requires immediate attention and a lot of prevention activities to avoid any cyber threat to critical IT services. This article aims to give a basic overview of Critical Information Infrastructure (CII) and Critical Sectors such as the Power and Energy Sector, Banking Financial Service and Insurance (BFSI), Telecommunications, Government Services, the Transport Sector, the Health Sector, etc. The consequences of attacks on these sectors have been examined, including their national and international challenges. This article shall also discuss the vulnerabilities of common CII, security controls, emerging trends, threats, and …

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Measuring Creativity In The Fermi Problem, A Type Of Mathematical Modeling, Applying Information Theory, Hidemichi Okamoto Jun 2022

Measuring Creativity In The Fermi Problem, A Type Of Mathematical Modeling, Applying Information Theory, Hidemichi Okamoto

Journal of Educational Technology Development and Exchange (JETDE)

Many methods of measuring creativity have been studied - mainly in psychology. In recent years, there have been attempts to incorporate such creativity into mathematical modelling, a topic handled in mathematics education. Accordingly, some studies have been trying to assess creativity in it. However, there have been no clear criteria or formulas that can be used for any problem, since a rubric has been created for each problem and evaluated individually. In the present study, to measure creativity in the Fermi problem, a type of mathematical modelling, a formula that applies information theory used in information science is proposed and …

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The Effective Strategies For Mitigation The Impact Of Covid-19 On Construction Projects In Egypt, Nora Magdy Essa, Ibrahim Mahdi, Hassan Mohamed Ibrahim Jun 2022

The Effective Strategies For Mitigation The Impact Of Covid-19 On Construction Projects In Egypt, Nora Magdy Essa, Ibrahim Mahdi, Hassan Mohamed Ibrahim

Future Engineering Journal

From the time when the first narrated infections in Wuhan China, in late 2019, COVID-19 has had a substantial peal on human life and health. By the early of 2020, the World Health Organization (WHO) announced the eruption of COVID-19, a public health crisis of international concern. On 11 March 2020, the World Health Organization officially announced COVID-19 a pandemic. The first case was infected in Egypt of covid-19 on Feb 14, 2020 (Gilbert et al., 2020). On 16 March 2020, the Egyptian Government began issuing decisions as preventative courses as part of the country's inclusive plan to cope with …

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Estimating The Weights Of Latticed Power Transmission Towers Using Genetic Programming, Ahmed M. Ebid Dr. Jun 2022

Estimating The Weights Of Latticed Power Transmission Towers Using Genetic Programming, Ahmed M. Ebid Dr.

Future Engineering Journal

The recent booming in the power network industry inspired a lot of researchers to develop models to estimate the optimum cost of transmission towers. Unlike previous researches which depended on design the tower from scratch, this research depends on collecting actual database from several projects around the globe and applying the well-known (GP) technique to develop a model to predict the tower weight. The accuracy of the developed formula was about 84%. The developed model could be used in early tender stage or to check design economy.

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Exploration Of Energy Efficient Computing For Data-Intensive Applications, Md Adnan Zaman Jun 2022

Exploration Of Energy Efficient Computing For Data-Intensive Applications, Md Adnan Zaman

USF Tampa Graduate Theses and Dissertations

The recent surge of data-intensive applications has stretched the performance and energy limit of today’s traditional computing system. The massive amount of data generated by data-intensive applications is not processed at the same speed due to bandwidth mismatch between the faster processing unit and slower memory. Memory access and communication bandwidth can be identified as the primary bottlenecks. Consequently, these two bottlenecks make up most of the total energy consumption. In light of this, we explore energy-efficient computing for data-intensive applications. We examine different aspects of two computing systems, such as in-memory computing and AI-enabled edge computing, more popularly known …

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