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A Half- Yearly E-Newsletter Of The Department Of Computer Science And Engineering, Manipal Institute Of Technology - Jul 2021, Ashalatha Nayak Dr. 2021 Department of Computer Science and Engineering Manipal Institute of Technology

A Half- Yearly E-Newsletter Of The Department Of Computer Science And Engineering, Manipal Institute Of Technology - Jul 2021, Ashalatha Nayak Dr.

Faculty work

No abstract provided.


Wall Detection Via Imu Data Classification In Autonomous Quadcopters, Jason Hughes, Damian Lyons 2021 Fordham University

Wall Detection Via Imu Data Classification In Autonomous Quadcopters, Jason Hughes, Damian Lyons

Faculty Publications

Abstract—An autonomous drone flying near obstacles needs to be able to detect and avoid the obstacles or it will collide with them. In prior work, drones can detect and avoid walls using data from camera, ultrasonic or laser sensors mounted either on the drone or in the environment. It is not always possible to instrument the environment, and sensors added to the drone consume payload and power - both of which are constrained for drones. This paper studies how data mining classification techniques can be used to predict where an obstacle is in relation to the drone based only on …


Geometric Analysis Leads To Adversarial Teaching Of Cybersecurity, Christian Servin, Olga Kosheleva, Vladik Kreinovich 2021 El Paso Community College

Geometric Analysis Leads To Adversarial Teaching Of Cybersecurity, Christian Servin, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

As time goes, our civilization becomes more and more dependent on computers and therefore, more and more vulnerable to cyberattacks. Because of this threat, it is very important to make sure that computer science students -- tomorrow's computer professionals -- are sufficiently skilled in cybersecurity. In this paper, we analyze the need for teaching cybersecurity from the geometric viewpoint. We show that the corresponding geometric analysis leads to adversarial teaching -- an empirically effective but not-well-theoretically-understood approach, when the class is divided into sparring mini-teams that try their best to attack each other and defend from each other. Thus, our …


Dynamic Planning Networks, Norman Tasfi, Miriam A M Capretz 2021 Western University

Dynamic Planning Networks, Norman Tasfi, Miriam A M Capretz

Electrical and Computer Engineering Publications

We introduce Dynamic Planning Networks (DPN), a novel architecture for deep reinforcement learning, that combines model-based and model-free aspects for online planning. Our architecture learns to dynamically construct plans using a learned state-transition model by selecting and traversing between simulated states and actions to maximize information before acting. DPN learns to efficiently form plans by expanding a single action conditional state transition at a time instead of exhaustively evaluating each action, reducing the number of state-transitions used during planning. We observe emergent planning patterns in our agent, including classical search methods such as breadth-first and depth-first search. DPN shows improved …


Computational Frameworks For Multi-Robot Cooperative 3d Printing And Planning, Laxmi Prasad Poudel 2021 University of Arkansas, Fayetteville

Computational Frameworks For Multi-Robot Cooperative 3d Printing And Planning, Laxmi Prasad Poudel

Graduate Theses and Dissertations

This dissertation proposes a novel cooperative 3D printing (C3DP) approach for multi-robot additive manufacturing (AM) and presents scheduling and planning strategies that enable multi-robot cooperation in the manufacturing environment. C3DP is the first step towards achieving the overarching goal of swarm manufacturing (SM). SM is a paradigm for distributed manufacturing that envisions networks of micro-factories, each of which employs thousands of mobile robots that can manufacture different products on demand. SM breaks down the complicated supply chain used to deliver a product from a large production facility from one part of the world to another. Instead, it establishes a network …


Multi-Agents For Microgrids, Salem Al-Agtash, Nisrein Al-Mutlaq, Mohamed Elabbas, Asma Alkhraibat, Mohamad Al Hashem 2021 Santa Clara University

Multi-Agents For Microgrids, Salem Al-Agtash, Nisrein Al-Mutlaq, Mohamed Elabbas, Asma Alkhraibat, Mohamad Al Hashem

Computer Science and Engineering

Microgrid systems are built to integrate a generation mix of solar and wind renewable energy resources that are generally intermittent in nature. This paper presents a novel decentralized multi-agent system to securely operate microgrids in real-time while maintaining generation, load balance. Agents provide a normal operation in a grid-connected mode and a contingency operation in an islanded mode for fault handling. Fault handling is especially critical in microgrid operation to simulate possible contingencies and microgrid outages in a real-world scenario. A robust agent design has been implemented using MATLAB-Simulink and Java Agent Development Framework technologies to simulate microgrids with load …


Bayesian Adaptive Path Allocation Techniques For Intra-Datacenter Workloads, Ali Malik, Ruairí de Fréin, Chih-Heng Ke, Hasanen Alyasiri, Obinna Izima 2021 Technological University Dublin

Bayesian Adaptive Path Allocation Techniques For Intra-Datacenter Workloads, Ali Malik, Ruairí De Fréin, Chih-Heng Ke, Hasanen Alyasiri, Obinna Izima

Conference papers

Data center networks (DCNs) are the backbone of many cloud and Internet services. They are vulnerable to link failures, that occur on a daily basis, with a high frequency. Service disruption due to link failure may incur financial losses, compliance breaches and reputation damage. Performance metrics such as packet loss and routing flaps are negatively affected by these failure events. We propose a new Bayesian learning approach towards adaptive path allocation that aims to improve DCN performance by reducing both packet loss and routing flaps ratios. The proposed approach incorporates historical information about link failure and usage probabilities into its …


Backpropagation Neural Network With Combination Of Activation Functions For Inbound Traffic Prediction, Purnawansyah Purnawansyah, Haviluddin Haviluddin, Herdianti Darwis, Huzain Azis, Yulita Salim 2021 Universitas Muslim Indonesia, Indonesia

Backpropagation Neural Network With Combination Of Activation Functions For Inbound Traffic Prediction, Purnawansyah Purnawansyah, Haviluddin Haviluddin, Herdianti Darwis, Huzain Azis, Yulita Salim

Knowledge Engineering and Data Science

Predicting network traffic is crucial for preventing congestion and gaining superior quality of network services. This research aims to use backpropagation to predict the inbound level to understand and determine internet usage. The architecture consists of one input layer, two hidden layers, and one output layer. The study compares three activation functions: sigmoid, rectified linear unit (ReLU), and hyperbolic Tangent (tanh). Three learning rates: 0.1, 0.5, and 0.9 represent low, moderate, and high rates, respectively. Based on the result, in terms of a single form of activation function, although sigmoid provides the least RMSE and MSE values, the ReLu function …


Face Images Classification Using Vgg-Cnn, I Nyoman Gede Arya Astawa, Made Leo Radhitya, I Wayan Raka Ardana, Felix Andika Dwiyanto 2021 Politeknik Negeri Bali, Indonesia

Face Images Classification Using Vgg-Cnn, I Nyoman Gede Arya Astawa, Made Leo Radhitya, I Wayan Raka Ardana, Felix Andika Dwiyanto

Knowledge Engineering and Data Science

Image classification is a fundamental problem in computer vision. In facial recognition, image classification can speed up the training process and also significantly improve accuracy. The use of deep learning methods in facial recognition has been commonly used. One of them is the Convolutional Neural Network (CNN) method which has high accuracy. Furthermore, this study aims to combine CNN for facial recognition and VGG for the classification process. The process begins by input the face image. Then, the preprocessor feature extractor method is used for transfer learning. This study uses a VGG-face model as an optimization model of transfer learning …


Data-Oriented Approaches Towards Mobile, Network And Secure Systems, Shangqing Zhao 2021 University of South Florida

Data-Oriented Approaches Towards Mobile, Network And Secure Systems, Shangqing Zhao

USF Tampa Graduate Theses and Dissertations

With the rapid evolvement of information science, data-oriented research has solicited a new philosophy for the future mobile network and security design, since it can not only encourage new designs achieving more efficient and reliable networks, but also pose new challenges towards security designs. In this dissertation, we propose four novel data-oriented designs or frameworks to prompt or calibrate the performance with respect to efficiency, reliability, and security.

In the wireless domain, packet corruption and packet collision are two major threats that jeopardize the performance of a mobile network. To cope with the packet corruption, we propose the STAteful inter-Packet …


Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao 2021 University of Arkansas, Fayetteville

Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao

Graduate Theses and Dissertations

Nowadays industries are collecting a massive and exponentially growing amount of data that can be utilized to extract useful insights for improving various aspects of our life. Data analytics (e.g., via the use of machine learning) has been extensively applied to make important decisions in various real world applications. However, it is challenging for resource-limited clients to analyze their data in an efficient way when its scale is large. Additionally, the data resources are increasingly distributed among different owners. Nonetheless, users' data may contain private information that needs to be protected.

Cloud computing has become more and more popular in …


Creation Of A Customized College Student Cybersecurity Awareness Online Learning Solution, Stanley Mierzwa, Iassen Christov, Bruno Lima 2021 Kean University

Creation Of A Customized College Student Cybersecurity Awareness Online Learning Solution, Stanley Mierzwa, Iassen Christov, Bruno Lima

Center for Cybersecurity

Many businesses, agencies, for-profit and non-profit organizations have implemented cybersecurity awareness training programs for their staff.


Interrelation Of Thermal Stimulation With Haptic Perception, Emotion, And Memory, Mehdi Hojatmadani 2021 University of South Florida

Interrelation Of Thermal Stimulation With Haptic Perception, Emotion, And Memory, Mehdi Hojatmadani

USF Tampa Graduate Theses and Dissertations

Haptics is an interdisciplinary field of science that deals with how humans perceive and respond to different sensory cues perceived through touch. Thermal haptics as a branch deals with how humans perceive the temperature sensation and respond to that. The process in which thermal perception occurs is well known to researchers. What seems missing in the literature is how temperature interacts or sometimes intervenes in other physiological and psychological aspects of our lives. In this research, a series of studies are presented where the main focus was how temperature and brain interact with each other to impede or enhance our …


Efficient Yet Robust Privacy For Video Streaming, Luke Cranfill, Junggab Son 2021 Kennesaw State University

Efficient Yet Robust Privacy For Video Streaming, Luke Cranfill, Junggab Son

Master of Science in Computer Science Theses

MPEG-DASH is a video streaming standard that outlines protocols for sending audio and video content from a server to a client over HTTP. The standard has been widely utilized by the video streaming industry. However, it creates an opportunity for an adversary to invade users’ privacy. While a user is watching a video, information is leaked in the form of meta-data, the size and time that the server sent data to the user. This information is not protected by encryption and can be used to create a fingerprint for a video. Once the fingerprint is created, the adversary can use …


Modernization Of Scienttific Mathematics Formula In Technology, Iwasan D. Kejawa Ed.D, Prof. Iwasan D. Kejawa Ed.D 2021 University of Nebraska - Lincoln

Modernization Of Scienttific Mathematics Formula In Technology, Iwasan D. Kejawa Ed.D, Prof. Iwasan D. Kejawa Ed.D

Department of Mathematics: Faculty Publications

Abstract
Is it true that we solve problem using techniques in form of formula? Mathematical formulas can be derived through thinking of a problem or situation. Research has shown that we can create formulas by applying theoretical, technical, and applied knowledge. The knowledge derives from brainstorming and actual experience can be represented by formulas. It is intended that this research article is geared by an audience of average knowledge level of solving mathematics and scientific intricacies. This work details an introductory level of simple, at times complex problems in a mathematical epidermis and computability and solvability in a Computer Science. …


Promoting Diversity In Academic Research Communities Through Multivariate Expert Recommendation, Omar Salman 2021 University of Arkansas, Fayetteville

Promoting Diversity In Academic Research Communities Through Multivariate Expert Recommendation, Omar Salman

Graduate Theses and Dissertations

Expert recommendation is the process of identifying individuals who have the appropriate knowledge and skills to achieve a specific task. It has been widely used in the educational environment mainly in the hiring process, paper-reviewer assignment, and assembling conference program committees. In this research, we highlight the problem of diversity and fair representation of underrepresented groups in expertise recommendation, factors that current expertise recommendation systems rarely consider. We introduce a novel way to model experts in academia by considering demographic attributes in addition to skills. We use the h-index score to quantify skills for a researcher and we identify five …


Forecasting Stock Exchange Data Using Group Method Of Data Handling Neural Network Approach, Marzieh Faridi Masouleh, Ahmad Bagheri 2021 Institute of Technology and Higher Education, Iran

Forecasting Stock Exchange Data Using Group Method Of Data Handling Neural Network Approach, Marzieh Faridi Masouleh, Ahmad Bagheri

Knowledge Engineering and Data Science

The increasing uncertainty of the natural world has motivated computer scientists to seek out the best approach to technological problems. Nature-inspired problem solving approaches include meta-heuristic methods that are focused on evolutionary computation and swarm intelligence. One of these problems significantly impacting information is forecasting exchange index, which is a serious concern with the growth and decline of stock as there are many reports on loss of financial resources or profitability. When the exchange includes an extensive set of diverse stock, particular concepts and mechanisms for physical security, network security, encryption, and permissions should guarantee and predict its future needs. …


Do Missing Link Community Smell Affect Developers Productivity: An Empirical Study, Toukir Ahammed, Sumon Ahmed, Mohammed Shafiul Alam Khan 2021 University of Dhaka, Bangladesh

Do Missing Link Community Smell Affect Developers Productivity: An Empirical Study, Toukir Ahammed, Sumon Ahmed, Mohammed Shafiul Alam Khan

Knowledge Engineering and Data Science

Missing link smell occurs when developers contribute to the same source code without communicating with each other. Existing studies have analyzed the relationship of missing link smells with code smell and developer contribution. However, the productivity of developers involved in missing link smell has not been explored yet. This study investigates how productivity differs between smelly and non-smelly developers. For this purpose, the productivity of smelly and non-smelly developers of seven open-source projects are analyzed. The result shows that the developers not involved in missing link smell have more productivity than the developers involved in smells. The observed difference is …


Indonesian Sentence Boundary Detection Using Deep Learning Approaches, Joan Santoso, Esther Irawati Setiawan, Christian Nathaniel Purwanto, Fachrul Kurniawan 2021 Institut Sains dan Teknologi Terpadu Surabaya, Indonesia

Indonesian Sentence Boundary Detection Using Deep Learning Approaches, Joan Santoso, Esther Irawati Setiawan, Christian Nathaniel Purwanto, Fachrul Kurniawan

Knowledge Engineering and Data Science

Detecting the sentence boundary is one of the crucial pre-processing steps in natural language processing. It can define the boundary of a sentence since the border between a sentence, and another sentence might be ambiguous. Because there are multiple separators and dynamic sentence patterns, using a full stop at the end of a sentence is sometimes inappropriate. This research uses a deep learning approach to split each sentence from an Indonesian news document. Hence, there is no need to define any handcrafted features or rules. In Part of Speech Tagging and Named Entity Recognition, we use sequence labeling to determine …


Detection Of Disease And Pest Of Kenaf Plant Based On Image Recognition With Vggnet19, Diny Melsye Nurul Fajri, Wayan Firdaus Mahmudy, Titiek Yulianti 2021 Brawijaya University, Indonesia

Detection Of Disease And Pest Of Kenaf Plant Based On Image Recognition With Vggnet19, Diny Melsye Nurul Fajri, Wayan Firdaus Mahmudy, Titiek Yulianti

Knowledge Engineering and Data Science

One of the advantages of Kenaf fiber as an environmental management product that is currently in the center of attention is the use of Kenaf fiber for luxury car interiors with environmentally friendly plastic materials. The opportunity to export Kenaf fiber raw material will provide significant benefits, especially in the agricultural sector in Indonesia. However, there are problems in several areas of Kenaf's garden, namely plants that are attacked by diseases and pests, which cause reduced yields and even death. This problem is caused by the lack of expertise and working hours of extension workers as well as farmers' knowledge …


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