Reviewerly/exHarmony huggingface dataset:
Decision Tree classification N Tier Solution for preventing SQLInjection Attack on Websites

The current situation has dragged everyone into the contiguous usage of web applications. As every task is performed based on web applications, it is very important that we will have to think and secure the web applications to the most out of it. What is SQLIA? It could be defined as the one that is implemented by the users who actually does not possess any of the access permissions though they want to abuse the access rights in the database and steal the data or edit them or delete as desired. To achieve SQL injection attacks, malicious query is written to leak out the data that is highly confidential. Interference of the SQL injection attack shall be well executed through the public interface as that is the existing source that an application provides when the case is that the host-level entry point and the network are secured enough. Some the suspicions that a SQLIA pretend to expose is that it cannot be applied without single quotes, space or double dashes.
Thermal model of lava in Mt. Agung during December 2017 episodes derived from Integrated SENTINEL 2A and ASTER remote sensing datasets

Abstract In the beginning of December 2017, Mt. Agung eruption powered down to minor ash emissions and on the middle of December, aerial photographs of the crater were taken by Indonesia Centre of Volcanology and Geological Hazard Mitigation (PVMBG) showing a steadily growing lava occupying approximately one third of the crater. 3D digital elevation model (DEM) of crater were created by PVMBG during and before the eruption, corresponded to lava volume around 2 x 10 −2 km 3 has been filled the crater. Here we present a method for deriving thermal model within the lava during eruption on 8 and 9 December 2017 using observations from multi infrared satellite SENTINEL 2A and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). We use Thermal Eruption Index (TEI) based on the Shortwave infrared (SWIR) on SENTINEL 2A and Thermal Infrared (TIR) on ASTER, allowing us to differentiate thermal domain within the lava. This study has successfully produced model of sub-pixel temperature (T h ), radiant flux (Φrad) and crust thickness model of lava (Δh). The subpixel temperature and radiant flux during the eruption is in the range 655 to 975 °C and 179 MW respectively. The crust thickness model of the lava in the range of 9 to 14 m and the total volume of lava crust during this period is estimated at 3 x 10 −3 km 3 . The combination of infrared satellite remote sensing data shows a potential for fast and efficient classification of difference thermal domains and derive thermal model of lava.
Safely Caching HOG Pyramid Feature Levels, to Speed up Facial Landmark Detection

A problem in object detection is finding the scale of interest, which is often solved by multi-scale analysis. One of the drawbacks of multi-scale analysis is that all scales are weighted equally important. We extend [7] to video data, using our method which caches Histogram of Oriented Graidents (HOG) feature levels. Utilizing a Bayesian Network (Bayes Net) to discover a policy for when partial or full pyramid updates are required to prevent loss of tracking. Without sacrificing significant accuracy from the original implementation.
PENGARUH MOTIVASI BELAJAR DAN FAKTOR KELUARGA TERHADAP HASIL BELAJAR PESERTA DIDIK KELAS VSEKOLAH DASAR

Masalah dalam penelitian ini adalah hasil belajar peserta didik kelas V Sekolah Dasar masih rendah yang diduga oleh motivasi belajar dan faktor keluarga. Penelitian ini bertujuan untuk mengetahui pengaruh antara motivasi belajar dan faktor keluarga terhadap hasil belajar peserta didik kelas V Sekolah Dasar. Jenis penelitian ini yaitu korelasional. Teknik pengumpulan data menggunakan Kuesioner (angket) dan dokumentasi. Penelitian ini dilaksanakan pada Gugus 1 Dahlia Rajabasa sebanyak 183 peserta didik dengan menggunakan teknik proposional random samplingdan yang dijadikan sebagai sampel yaitu sebanyak 136 responden peserta didik. Uji asumsi menggunakan uji normalitas, uji linieritas. Teknik analisis data pada penelitian ini menggunakan uji hipotesis regresi linier bergandahasil penelitian menunjukkan bahwa terdapat pengaruh motivasi belajar dan faktor keluarga terhadap hasil belajar peserta didik kelas V Sekolah Dasar dengan menggunakan regresi linier berganda koefisien korelasi sebesar 3,495491541 sehingga koefisien korelasi menunjukkan kategori sangat tinggi dengan nilai positif . Kata Kunci:faktor keluarga, hasil belajar, motivasi belajar.THE EFFECT OF LEARNINGMOTIVATION AND FAMILYFACTORS ON STUDENT GRADE V INELEMENTARY SCHOOLThe problem in this research is the learning result of the fifth grade students inelementary school are still low because of the learning motivation and familyfactors. The objective of this research is to find out the effect of learningmotivation and family factors on the learning result of the fifth grade students ofelementary school.The type of the research is correlational. The data collectingtechniques used are questionnaire (questionnaire) and documentation. Thisresearch was conducted by using 183 students and 136 students as the respondent.Test assumptions was done by using normality test, linearity test, and hypothesistest. The data analysis technique in this study is to show how much learningmotivation and family factors influence the learning result of the fifth gradestudents in elementary school using multiple linear regression. The correlationcoefficient is 3.495491541, so it shows a very high category with positive values.Keywords:family factors, learning result,learning motivation.
ANALISIS EFEKTIVITAS SISTEM INFORMASI AKUNTANSI SIKLUS PENDAPATAN PADA PT.GTS

This research aims to know the effectiveness of accounting information systems revenue cycle in PT. GTS engaged in the service of ' umrah and Hajj with an associate on the principal elements of the accounting information system. The methods used in this research is qualitative method with paradigm intepretif and etnometodologi approach. The research results showed that the system accounting information cycle revenue PT. GTS has been running effectively because it is already in compliance with the principal elements of the accounting information system. But the need for separation of functions in revenue cycle between the marketing function with receipt cash function of companies to prevent fraud carried out by related parts.
The Application of Murder Model with Image Media to Improving Student Learning Outcomes at the Fourth Grade Students

This research is to evaluate the learning&#x0D; outcomes of 4th grade students using the MURDER model with image&#x0D; media. This research is a Class Action Research conducted in three cycles and&#x0D; is collaborative research. Each cycle consists of several stages, namely the&#x0D; planning, implementation, observation, and reflection stages. This third cycle&#x0D; is useful for determining the final results of the research conducted. The&#x0D; subjects of this study were fourth-grade students of SDN (Sekolah Dasar Negeri or State of Primary School) Negeri Gumilir 04&#x0D; Cilacap Regency, Indonesian Country with a total of 49 students. The conclusion&#x0D; obtained from this study is that the use of the MURDER model with image media&#x0D; can improve the learning outcomes of fourth-grade elementary school students.
Dynamic algorithm selection for machine learning on time series

We present a software that can dynamically determine what machine learning algorithm is best to use in a certain situation given predefined traits. The produced software uses ideal conditions to ex ...
Networking Consumer Systems to Provide a Development Environment for Inside-Out Marker-Less Tracking for Virtual Reality Headsets

Many companies are working to create inside-out marker-less tracking for virtual reality headsets. Inside-out marker-less tracking can be found on consumer augmented reality devices, but currently there is no system available to researchers, developers, or consumers that provides this feature without custom hardware and software. Our research provides a development environment for testing content that would take advantage of this feature before consumer level inside-out marker-less virtual reality systems hit the market. The solution utilizes current commercial off-the-shelf hardware systems, and by networking them together, allows the user to move through a captured environment without needing tracking towers. Ultimately, it provides researchers and developers the opportunity to test content that both takes advantage of the free movement through rooms provided by inside-out tracking and is yet constrained by real-world boundaries such as walls within the virtual environment.
State Application to Renew Ed-Flex Authority Available for Public Comment

PDF Version DATE: July 11, 2019 SUBJECT: State Application to Renew Ed-Flex Authority Available for Public Comment CATEGORY: Public Review/Comment NEXT STEP
Spherical Structure-from-Motion for Casual Capture of Stereo Panoramas

Hand-held capture of stereo panoramas involves spinning the camera in a roughly circular path to acquire a dense set of views of the scene. However, most existing structure-from-motion pipelines fail when trying to reconstruct such trajectories, due to the small baseline between frames. In this work, we propose to use spherical structure-from-motion for reconstructing handheld stereo panorama captures. Our initial results show that spherical motion constraints are critical for reconstructing small-baseline, circular trajectories.
Development of Kernel Mode RAM Driver for RAM Image on Windows

In the field of computer forensics live analysis through immediate intervention is an important way of gathering electronic evidence. The way to obtain evidence from volatile data using live analysis is to take an image of the RAM (Random Access Memory). The entire RAM has to be copied in order to import data from this image. However, since the user mode is the default mode in Windows operating systems only the running processes can be accessed. Therefore, RAM imaging software needs to work at Kernel Mode level. In this study, a RAM driver was developed using WDK (Window Driver Kit) to enable RAM imaging software to run in Kernel Mode. The developed driver works on Windows 8, 8.1 and 10 (32 bit and 64 bit) operating systems. Virtual addresses, physical addresses and table pages for RAM can be accessed using the developed RAM driver. In this way, image acquisition software using this driver is able to carry out bit-to-bit copying of RAM. In addition, a program to import a RAM image in c ++ using this driver has also been developed. When the image retrieval software is installed in RAM it occupies a meager 156 KB of space. Compared to the existing image acquisition software, the developed RAM driver and software seem to use the least RAM. In addition, there are no examples of Kernel Mode RAM Drivers developed using WDK in the literature.
InfoGuides: Oregon Ready to Read Grants: About the Ready to Read Grant

Help for applying and managing Ready to Read grant funds through the State Library of Oregon.
PEMBUATAN MOBILE GAME VIRTUAL PET ONLINE

Game virtual pet is a simulation game  about  the  raising  of an animal  . This game can be played using  mobile  phone that  has the Android  operating  system. In general, this game is more attractive to female players than male players, and sometimes given feature can make the player feel bored. Therefore made virtual pet online game that is not  boring  when  played by  female and male players, by providing additional gameplay and use the  social  media.  Gameplay  additions provided that battle, training, evolution,  help  friend,  and  transaction.  For  social  media features, adding friends can be done automatically using Facebook. Making virtual pet online game using Unity3D application, by utilizing the programming language C# and PHP. To view and assets used in the manufacturing of virtual pet online game was created using Adobe Illustrator. After  doing  the  implementa t ion and testing by interview showed that  the application  is  made to increase  the interest of female and men players to play for their gameplay additions and can be played without having to meet first.
Threshold Implementation of a Low-Cost CLEFIA-128 Cipher for Power Analysis Attack Resistance

Lightweight cryptography aims to satisfy the need for security and privacy in the resource constrained environment like smart cards, RFID and smart edge nodes in Internet of Things (IoT). CLEFIA is one of the ISO/IEC 29191-2 standard lightweight cryptographic algorithm suitable for these applications. Though CLEFIA is proven to be resistant to the cryptanalytic attacks, it is vulnerable to implementation attacks namely Side-Channel Attacks (SCAs). Power Analysis Attacks (PAAs) are the most popular type of SCA and the existing literature has shown successful PAA against CLEFIA. Hence there is a need for strong countermeasure against PAA. The contributions of this work are two-fold: (i) We have proposed a novel 16-bit serial architecture for CLEFIA-128 encryption with a Composite Field Architecture (CFA) based S1 box and Algebraic Normal Form (ANF) based S0 box (ii) A novel Threshold Implementation (TI) with 2-input shares is derived and implemented for the S0, S1 boxes. Thereby, two-shared top level CLEFIA architecture is constructed that shows sufficient first-order PAA resistance when validated using SAKURA-G FPGA board. The PAA categories considered are: (i) Evaluation style – Differential Power Analysis (DPA), Correlation Power Analysis (CPA), Mutual Information Analysis (MIA) with three different power models (ii) Conformance style –Test Vector Leakage Assessment (TVLA) Attack category. This work thereby becomes the first contribution to propose a first-order PAA resistance two-share TI-based CLEFIA implementation with a considerable area compromise, suitable for resource constrained applications.
An Improved Gaussian Pigeon-inspired Optimization Algorithm

An improved Gaussian Pigeon-inspired Optimization algorithm is proposed to maintain diversity and improve the accuracy of the global optimum. In the proposed algorithm, Gaussian mutation is used to maintain the diversity of exploration, and the judgment on global optimum is used to improve the accuracy of global optimum. The simulation results show that the improved Gaussian Pigeon-inspired Optimization algorithm preserves the diversity of early evolution to avoid premature convergence. In addition, the judgment on global optimum improves the accuracy of the global optimum. The entire algorithm shows excellent performance in global optimization and proved to be effective for solving multimodal and non-convex problems with higher dimensions.
[PDF] NCERT Solutions for Class 4 English Unit-8 The giving tree

NCERT Solutions for Class 4 English Unit-8 The giving tree, are part of  NCERT Solutions for Class 4 English. Here we have given NCERT Solutions for ...
Parallelization of Local Diagonal Extrema Pattern Feature Extraction on a GPU

Local Diagonal Extrema Pattern(LDEP) is used as a texture feature in object recognition, face recognition etc. LDEP feature extraction time is crucial in real time applications. To accelerate feature extraction time a Graphical Processing Unit is used. For the first time, we parallelize LDEP feature extraction using GPU. We obtain a θ(1) feature extraction time when tested on few images from medical domain.
[PDF] NCERT Solutions for Class 3 English Unit-5 The Yellow Butterfly

NCERT Solutions for Class 3 English Unit-5 The Yellow Butterfly of NCERT Solutions for Class 3 English. Here we have given NCERT Solutions for Class 3 ...
Smart Advertising in Videos Based on Comprehensive Content Analytics

Traditional video advertising ignores the contents of the video and its relation to the advertisement. In this demo, we develop a smart advertising system based on comprehensive content analytics, which can automatically match the contents of the video and the advertisement to promote the best advertising spaces. Our platform structurizes videos into meta-data with multiple semantic labels and temporal-spatial information. High level scene semantics is extracted based on the meta-data to match the theme of the advertisement. The system has served for industries, analyzed large scale video data and generated millions of advertising opportunities.
The finite size effect of asymmetric sending or not sending twin-field quantum key distribution with two-way communication

Odd-parity error rejection (OPER) can drastically improve the asymptotic key rate of sending-or-not-sending twin-field (SNS-TF) quantum key distribution (QKD). However, in practice, the finite key effects have to be considered for security. Here, we propose a zigzag approach to verify the phase-flip error of the survived bits after OPER. Based on this, we can take all the finite key effect efficiently in calculating the non-asymptotic key rate. Numerical simulation shows that our method here produces the highest key rate over all distances among all existing methods, improving the key rate by more than $100\%$ to $3000\%$ in comparison with different prior art methods with typical experimental setting. Also, we show that with the method here, the SNS-TF QKD can by far break the the absolute bound of repeater-less key rate with whatever detection efficiency. We can even reach a non-asymptotic key rate more than $40$ times of the practical bound and $13$ times of the absolute bound with $10^{12}$ pulses. Besides, we apply the McDiarmid inequality to estimate the phase flip error rate, further improving the key rate by more than $20\%$.
[PDF] NCERT Solutions for Class 3 English Unit-9 He is my brother

NCERT Solutions for Class 3 English Unit-9 He is my brother are part of NCERT Solutions for Class 3 English. Here we have given NCERT Solutions for Class ...
Cluster Validity Using Modified Fuzzy Silhouette Index on Large Dynamic Data Set

Cluster validity index is applied to evaluate clustering results. It can be performed based on different measures and it can accomplish at data point level or cluster center level. In distance-based clustering methods, silhouette is an efficient point to point index measure, which defines relation based on compactness and separation distances. To validate fuzzy partitions, fuzzy silhouette index is used by applying defuzzification process. One of the applications of cluster validity is finding an optimal number of clusters in distance-based methods. As data size increases, point-wise index measure calculation takes more execution time. Hence, we proposed approaches to reduce time complexity by modifying fuzzy silhouette index at center to center and center to mean levels. All these methods are applied to find the right number of cluster and they are giving correct value in minimum execution time. All work is implemented in Matlab and effective results are given by our proposed methods.
Path Planning for an Autonomous Electric Vehicle based on Attractors Dynamics and Differential Evolution

This paper introduces a way of planning the path for autonomous electric vehicles (AEV)or robots using attractors dynamics through a numeric optimization problem, which is solved by a meta-heuristic algorithm called differential evolution (DE). The information given by the attractor dynamic approach (ADA)is used as a set of variables into an optimization problem with constraints, based on these variables, some restrictions are activated in order to find the best possible path, minimizing the distance between the vehicle and the target position and avoiding obstacles at the same time, without prior information on the environment.
Video Object Segmentation with 3D Convolution Network

We explore a novel method to realize semi-supervised video object segmentation with special spatiotemporal feature extracting structure. Considering 3-dimension convolution network can convolute a volume of image sequence, it is a distinct way to get both spatial and temporal information. Our network is composed of three parts, the visual module, the motion module and the decoder module. The visual module learns object appearance feature from object in the first frame for network to detect specific object in following image sequences. The motion module aims to get spatiotemporal information of image sequences with 3-dimension convolution network, which learns diversities of object temporal appearance and location. The purpose of decoder module is to get foreground object mask from output of visual module and motion module with concatenation and upsampling structure. We evaluate our model on DAVIS segmentation dataset[15]. Our model doesn't need online training compared with most detection-based methods because of visual module. As a result, it takes 0.14 second per frame to get mask which is 71 times faster than the state-of-art method-OSVOS[2]. Our model also shows better performance than most methods proposed in recent years and its meanIOU accuracy is comparable with state-of-art methods.
AgileCritPath: Identifying Critical Tasks in Agile Environments

Planning and monitoring the execution of software development activities in agile environments are not trivial procedures.One of the main flaws of agile planning is not considering the dependencies that exist between project tasks.Dependencies between tasks found in software development project plans may lead to the emergence of critical paths, where tasks need to be handled in a strict sequence because the completion of some tasks depends on the completion of others.Not managing such critical paths may reduce team performance and delay product delivery.We performed a study to demonstrate that not identifying dependencies may impair team performance and even increase the risk of costly project delays.The study is divided into three parts: (1) an exploratory study performed in the industry; (2) the development of a tool, AgileCritPath, as a way to support development teams in identifying critical project tasks; and (3) an in vivo evaluation of AgileCritPath based on the Technology Acceptance Model (TAM).The results of the exploratory study provided empirical evidence that there is a need to identify and control dependencies between the tasks in the development of software in agile environments.Using the AgileCritPath tool, allowed us to introduce the Critical Path Method concepts in an agile software development organization.Moreover, the in vivo evaluation demonstrated the benefits of managing tasks dependencies.
An Appearance Model and Feature Selection in Kernelized Correlation Filter Based Visual Object Tracking

In this chapter, we propose an eigenbasis vector based appearance model in kernelized correlation filter based visual object tracking by detection. The proposed appearance is learned using reconstructed targets in successive video frames. This learned appearance is used in KCF-based tracker in addition to raw pixel based appearance, i.e., without subspace reconstruction. The 2c number of HOG features are extractedSharma, Vijay K. from both the appearance models. Using a feature selection strategy, the number of feature channels is reduced to c. The kernel correlation for tracking by detection is computedAcharya, Bibhudendra for only c number of channels. To further improve the tracking accuracy, a discriminative parameter vector is learned in each video frame. This parameter vector is used to compute the scores of two intermediateMahapatra, K. K. tracked instances. The proposed method performs better than KCF-based tracker in a number of challenging video sequences.