Reviewerly/exHarmony huggingface dataset:
Research Guides: Ebooks - Finding and Using: Search like a librarian

Introduction to ebooks and how to find them through Temple Libraries (restricted) and public sources
Orientation Detection of Lines in Binary Images Using the Radon Transform

This paper addresses the problem of orientation determination of lines in binary images through the use of the Radon Transform. The Radon transform maps a line at a given angle to a point in feature space (also known as the sinogram). The sinogram is typically generated for a wide range of angles (from 0 to 179 degrees in this case). Consequently, lines at particular angles will map to points whose sinogram value is greater than that of other points in the sinogram. Thus, the use of a threshold on the maximum sinogram values at each angle will allow for the extraction of the orientation information from the original image.
Bullying and Cyberbullying in Adolesent

The rapid growth of electronic and computer-based communication and information sharing during the past decade has dramatically changed social interactions, especially among adolescents. However, in addition to its positive contribution, cyber-space communication also brings some undesirable consequences such as cyberstalking, cybercrime and cyberbullying. In 2017, Indonesia,  has known that amount of  internet usage has reached 143,26 million. According with survey by association of internet provider servive Indonesia in June 2016 that taken from each province were found 4,24 percent internet users were age more than 54 years old, 16,68 percent for ages 13-18 years old and 29,55 percent for 35-54 years old, 49,52 percent in 19-34 years old. Adolescents have grown up in a digitally connected world, enjoying many of the opportunities associated with electronic technology use.  Nowadays cyberbullying is becoming a big issue around the world. In cyberbullying, aggression occurs through electronic communication technologies, such as mobile phones or the internet     Cyberbullying is define as willful and repeated harm inflicted through the use of computers, cell phones and other electronic devices. In Indonesia, the prevalence cyberbullying among children is considerably high.
Mapping the relationship between proliferation and morphology in the developing mouse face

There is a long‐standing prediction that small changes in proliferation and apoptosis during the time frame of facial morphogenesis act to shape the face. Further, many studies show genetic alterations that cause structural birth defects affect local proliferation or apoptosis. Yet, it is unclear how much of local change in regional proliferation would be necessary to cause a defect. Here, we set out to understand the relationship between growth, morphology and proliferation and test that prediction that targeted proliferation shapes the developing face by quantifying proliferation and apoptosis in 3D and relating it to the growth of the face. We use whole mount staining for proliferation and apoptosis markers, whole tissue clearing methods, lightsheet microscopy and atlas and machine learning based quantification methods to identify individual proliferating or apoptotic nuclei within a 3D tissue structure at a set time point. We also employee geometric morphometric analysis of the same tissue structure to quantify overall morphology. By collecting data at various time points across facial development (E9.5–E11.5) and quantifying the age of each embryo, we are able to relate cell biological level growth to tissue level growth and morphological change and relate these two parameters in a way not performed previously. Support or Funding Information NIH NIDCR R01‐DE019638 to RM and BH, NSERC Discovery to BH, and CIHR Foundation grant to BH and RM, CIHR postdoctoral fellowship to RMG. Atlas based quantification of proliferation: A) Maximum Projection of the embryo highlighting the external morphology ‐ lateral view. B) Proliferation staining (phospho‐Histone H3) ‐ lateral view. C–D) Surface morphology of the atlas (n=5) C ‐ anterior view, D ‐ Lateral view. E–F) Heat map of proliferating cells (no density correction) E ‐ anterior view, F ‐ Lateral view. Figure 1
LibGuides: Sol Plaatje University Library and Information Services General Guide: Home

Welcome to your SPU LIS general portal where you can find links to our electronic databases, other library resources and open resources.
The Skeleton of Hyperbolic Graphs for Greedy Navigation

Random geometric (hyperbolic) graphs are important modeling tools in analyzing real-world complex networks. Greedy navigation (routing) is one of the most promising information forwarding mechanisms in complex networks. This paper is dealing with greedy navigability of complex graphs generated by using a metric (hyperbolic) space. Greedy navigability means that every source-destination pairs in the graph can communicate in such a way that every node passes the information towards that neighboring node which is "closest" to the destination in terms of node coordinates in the metric space. A set of compulsory links in greedy navigable graphs called Greedy Skeleton is identified. Because the two-dimensional hyperbolic plane (H^2, also known as the two dimensional Bolyai-Lobachevsky Space bolyai) turned out to be extremely useful in modelling and generating real-like networks, we deal with the statistical properties of the Greedy Skeleton when the metric space is H^2. Some examples of numerical studies and simulation results supporting the analytical formulae are also performed. The significance of the results lies in that every (either artificial or natural) network formation process aiming at greedy navigability must contain this Greedy Skeleton. Furthermore, this could be an important step towards the formal argumentation of the very high greedy navigability of some models observed only experimentally for the time being, and also to analyze equilibrium of greedy network navigation games on H^2.
LibGuides: Fun Things to do: Meditation & workouts

Library staff share free and fun resources we have both in the library and that we've found around the web. Check them out!
LibGuides: 2020 Summer Reading Program - Imagine Your Story!: COVID -19: Virtual and remote resources for libraries to share

Tennessee is part of the Collaborative Summer Learning Program (CSLP), and our theme for Summer Reading in 2020 is Imagine Your Story - Mythology and Fairytales.
How to Describe Conditions Like 2-out-of-5 in Fuzzy Logic: A Neural Approach

In many medical applications, we diagnose a disease and/or apply a certain remedy if, e.g., two out of five conditions are satisfied. In the fuzzy case, i.e., when we only have certain degrees of confidence that each of n statement is satisfied, how do we estimate the degree of confidence that k out of n conditions are satisfied? In principle, we can get this estimate if we use the usual methodology of applying fuzzy techniques: we represent the desired statement in terms of “and” and “or,” and use fuzzy analogues of these logical operations. The problem with this approach is that for large n , it requires too many computations. In this paper, we derive the fastest-to-compute alternative formula. In this derivation, we use the ideas from neural networks.
A Novel Secure and Robust Encryption Scheme for Medical Images

Medical imaging encloses different imaging techniques and processes to image the human body for medical diagnostic and treatment purposes. Hence it plays an important role to improve public health. The technological development in biomedical imaging specifically in X-ray, Computed Tomography (CT), nuclear ultrasound including Positron Emission Tomography (PET), optical and Magnetic Resonance Imaging (MRI) can provide valuable information unique to a person.In health care applications, the images are needed to be exchanged mostly over a wireless medium. The diagnostic images with confidential information of a patient need to be protected from unauthorized access during transmission. In this paper, a novel encryption method is proposed to improve the security and integrity of medical images.Chaotic map along with DNA cryptography is used for encryption. The proposed method describes a two-phase encryption of medical images.The performance of the proposed method is also tested by various analysis metrics. The robustness of the method against different noises and attacks is analyzed.The results show that the method is efficient and well suitable for medical images.
Implementing Differentiation in Early Education: The Impact on Student’s Academic Achievement

The purpose of this study was to investigate and examine the impact of implementing differentiated instructions on the learners’ academic achievements in kindergarten classrooms. The study employed the quantitative experimental design to either reject or accept the research hypothesis based on a sample of 28 students in a 3 weeks implementation process. The results revealed a statistical significance difference between the results of the experimental group learning through differentiated instructions and the control group learning without differentiated instructions. Hence, the outcome of the research discloses a positive impact of differentiated instructions on the learners’ achievements.
A proposal about training support service based on history of user’s action data

With the developing of IoT technique, it becomes easier to collect users’ action data. By analyzing and utilizing those data, consumer and producer will exchange their intelligence with each other then make better customize in product developing process. In this research, by using the sensor shoes which embed several sensor devices in its insole, collecting the action data of users and extract their action feature then make some advices that help to let whom training more efficiently is proposed. In this paper, we present a service model which uses Backpropagation Network to distinguish the users' action and extract their action feature by using Self-organizing Map from sensing data and review their performance in experiments.
Digitization Models of Education in Russia as the Basis of the Universities' Digital Collaborations

The article investigates the prerequisites for shaping digitization models for higher education in Russia subject to trends and normative regulation of digital economy development. Classification of the models that have taken shape has been proposed based on research into digitization strategy for universities in Russia; their certain characteristic features have been isolated. Aspects of influence exercised by the universities’ organizational forms in transition from the traditional (conventional) form to the innovative one have been studied. Models of digital universities in terms of components making up the model architecture of digitization processes and collaboration prospects have been put forward.
FORECASTING JUMLAH MAHASISWA BARU MENGGUNAKAN METODE AUTOMATIC CLUSTERING AND FUZZY LOGIC RELATIONSHIP MARKOV CHAIN (STUDI KASUS : FAKULTAS TEKNOLOGI INFORMASI DAN KOMUNIKASI VISUAL INSTITUT SAINS DAN TEKNOLOGI AL-KAMAL)

&#x0D; Abstraction&#x0D; Forecasting or forecasting is a calculation analysis technique that is done by carrying out qualitative and quantitative approaches to think about future events using reference data in the past. The purpose of this study is to predict the number of new students at the Faculty of Information and Visual Communication Technology at the Al-Kamal Institute of Science and Technology in the academic year 2020/2021. Prediction of the number of new students in the Faculty of Information and Visual Communication Technology of the Al-Kamal Institute of Science in the future accurately is very important to do, because many decisions can be taken by the Leaders of the Al-Kamal Institute of Science and Technology from these predictions. Markov Chain Automatic Clustering and Fuzzy Logic Relationship Method was chosen because it has a better level of accuracy among other Fuzzy Logic methods. The data used in this study are secondary data obtained from the Academic Information System of the Al-Kamal Institute of Science and Technology. Based on this research it was found that the predicted results of the number of new students of the Faculty of Information and Visual Communication Technology at the Al-Kamal Institute of Science and Technology in the academic year 2020/2021 amounted to 64 with a MAPE of 8.25%
Generation of Digital Signature for Blockchain victimization Hash operate

This paper considers the issue about advanced mark age, and advances the code to actualize this. We can make a protected way for the transmission of any exchange or information. This strategy is utilized in the blockchain innovation. We can actualize it utilizing various strategies, here we are utilizing hash work. Here in this paper we have used the Xilinx 14.7 ISE design suit software for simulation.
Library Guides: ORCID: ResearchGate and ORCID

Enhance your research impact and make it easier to find your publications using ORCID. How to let ResearchGate make use of your ORCID iD
Connecting soldiers with relay robots in challenging environments

Real-time exchange of information amongst a team of soldiers is critical to the success of their mission in a battle field environment. The soldiers may not have a direct Line-of-Sight (LoS) between them in places with geographical separations and obstacles. A team of robots can be readily used in these scenarios to act as relays and facilitate real-time exchange of information between the soldiers. If there is no direct LoS between a pair of soldiers, the robots can be strategically placed and moved to act as a communication gateway between the soldiers. This article addresses the problem of placing a minimum number of robots in the environment such that any pair of soldiers can exchange information between each other either through direct LoS or through a series of relay robots. This problem is challenging, even in known environments, as the shape of the obstacles could be non-convex. We first show that this optimization problem is closely related to several NP-Hard problems. We then present fast heuristics that can find good feasible solutions to the problem. The heuristics sample the environment for potential robot locations and solve a connected set-cover problem to find a subset of locations that can provide the desired connectivity. The performance of the proposed heuristics is tested on a large number of problem instances generated by varying the number and placement of soldiers, and the shapes of the obstacles.
Per-Step Reward: A New Perspective for Risk-Averse Reinforcement Learning

We present a mean-variance policy iteration (MVPI) framework for risk-averse control in a discounted infinite horizon MDP optimizing the variance of a per-step reward random variable. MVPI enjoys great flexibility in that any policy evaluation method and risk-neutral control method can be dropped in for risk-averse control off the shelf, in both on- and off-policy settings. This flexibility reduces the gap between risk-neutral control and risk-averse control and is achieved by working on a novel augmented MDP directly. We propose risk-averse TD3 as an example instantiating MVPI, which outperforms vanilla TD3 and many previous risk-averse control methods in challenging Mujoco robot simulation tasks under a risk-aware performance metric. This risk-averse TD3 is the first to introduce deterministic policies and off-policy learning into risk-averse reinforcement learning, both of which are key to the performance boost we show in Mujoco domains.
One Shoot In-Door Surveillance Module Based On MCA Associative Memory

Several studies and researches had been made to develop In-Door Surveillance module. Most of them had depended on traditional techniques tend to be more complicated. After revolutionary development in Artificial intelligence that simulates the human brain, many industrial companies has started to build more efficient and intelligent surveillance systems depending on artificial intelligence techniques. Thus, this research would deal with an Indoor surveillance module depending on non-traditional techniques, which is Multi-Connect Architecture Associative Memory (MMCA). The proposed module would process any given pre-processed image-stream and decide whether it is secured or non-secured case. This process had been done by training the proposed module with one selected secured image. The study found that accuracy values were between (74.6 – 97.2%). Accuracy was almost around 95% which is considered a promising results in real-time of execution.
A two stage auction mechanism for cloud resource allocation

The contemporary writing on cloud asset distribution is generally centered on considering the associations among clients and cloud directors. All things considered, the ongoing development in the clients' requests and the rise of private cloud suppliers (CPs) lure the cloud chiefs to lease additional assets from the CPs in order to deal with their accumulated errands and pull in more clients. This additionally renders the cooperation’s between the cloud directors and the CPs a significant issue to examine. In this paper, we examine the two collaborations through a two-arrange sell off component. For the collaborations among clients and cloud supervisors, we embrace the alternatives based consecutive closeouts to plan the cloud asset portion worldview. When contrasted with existing works, our system can deal with clients with heterogeneous requests, give honesty as the overwhelming methodology, appreciate a straightforward victor assurance strategy, and block the postponed passage issue. We likewise give the presentation examination of the OBSAs, which is among the first in writing. Concerning collaborations between cloud directors and CPs, we propose two parallel markets for asset gathering. We catch the narrow-mindedness of the CPs by their offered costs. We direct an extensive examination of the two markets and distinguish the offering methodologies of the cloud directors.
Subject Guides: Linking to Library Resources: Home

A guide to assist in linking to content in Stoxen Library databases within Blackboard courses
Adaptive- Transition-Set Track Before Detect Algorithm Based on Dynamic Programming

Original dynamic programming based track-before-detect (DP- TBD) assumes that targets run with nearly uniform motions and known velocities. However, targets in real-world scenes do not always run with nearly uniform motions and their velocities are usually unknown, and all we know is the minimum and maximum speeds of these targets. Original DP- TBD suffers significant performance loss under the circumstances. Aiming at the problem, this paper proposes an adaptive-transition-set DP- TBD (ATS-DP- TBD) algorithm, which refines the transition set of DP-TBD by estimating the states of targets as DP- TBD processes the measurement frames. The transition set initially is rough, which is determined by the minimum and maximum speeds, then becomes more accurate by a filter. Simulation results show that the proposed ATS-DP-TBD outperforms the original DP-TBD, the detection probability increases by 0.17, and the number of the false alarms is reduced over 94%.
Implementasi dan Penggunaan Algoritma Base64 dalam Pengamanan File Video

Personal data is often the target of people who are not responsible for being misused. Theft is done is to benefit from people who have the data. In addition to theft of work files, theft is also carried out on video files. Theft of this file aims to find out what the contents of the video. Someone has a private recorded video that cannot be known by others. Misuse of video files will be fatal for the owner of the video. Cryptographic techniques are needed in video security. Caesar Cipher's algorithm can help users secure the video file. The Base64 algorithm can be used to change the ASCII 256 format to Base64 so that it is easy to send or store in a storage medium. This algorithm will make the file structure simpler so that it can be displayed and saved. By applying the Base64 and Caesar Cipher algorithms to video files, the security and confidentiality of these files will be guaranteed
Meta-Augmented Human: From Physical to Cognitive Towards Affective State Recognition

This thesis investigates how smart sensors can quantify the process of learning. Traditionally, human beings have obtained various skills by inventing technologies. Those who integrate technologies into daily life and enhance their capabilities are called augmented humans. While most existing augmenting human technologies focus on directly assisting specific skills, the objective of this thesis is to assist learning -- the meta-skill to master new skills -- with the aim of long-term augmentations.Learning consists of cognitive activities such as reading, writing, and watching. It has been considered that tracking them by motion sensors (in the same way as the recognition of physical activities) is a challenging task because dynamic body movements could not be observed during cognitive activities. I have solved this problem with smart sensors monitoring eye movements and physiological signals.I propose activity recognition methods using sensors built into eyewear computers. Head movements and eye blinks measured by an infrared proximity sensor on Google Glass could classify five activities including reading with 82% accuracy. Head and eye movements measured by electrooculography on JINS MEME could classify four activities with 70% accuracy. In a wild experiment involving seven participants who wore JINS MEME more than two weeks, deep neural networks could detect natural reading activities with 74% accuracy. I demonstrate Wordometer 2.0, an application to estimate the number of rear words on JINS MEME, which was evaluated in a dataset involving five readers with 11% error rate.Smart sensors can recognize not only activities but also internal states during the activities. I present an expertise recognition method using an eye tracker which performs 70% classification accuracy into three classes using one minute data of reading a textbook, a positive correlation between interest and pupil diameter (p < 0.01), a negative correlation between mental workload and nose temperature measured by an infrared thermal camera (p < 0.05), an interest detection on newspaper articles, and effective gaze and physiological features to estimate self-confidence while solving multiple choice questions and spelling tests of English vocabulary.The quantified learning process can be utilized for feedback to each learner on the basis of the context. I present HyperMind, an interactive intelligent digital textbook. It can be developed on HyperMind Builder which may be employed to augment any electronic text by multimedia aspects activated via gaze.Applications mentioned above have already been deployed at several laboratories including Immersive Quantified Learning Lab (iQL-Lab) at the German Research Center for Artificial Intelligence (DFKI).
Guides: Remote Instruction & Resources: Copyright in the Time of Pandemic

Guide to Jenks's online resources and other available resources for supporting your class during COVID-19.
John E. Riley Library: Grammarly: Teaching with Grammarly

Grammarly is a grammar, spelling, punctuation, misused word, and plagiarism checker available to NNU employees and students.
Library Guides: Research as a Transferable Skill: Courses for Faculty & Stakeholders

A library guide to online courses to prepare undergraduate students to engage in original research and scholarship projects.