Reviewerly/exHarmony huggingface dataset:
Error Analysis On The Students’ English Speech Of STMIK Sinar Nusantara

This research was aimed at finding out the student’s English speech errors of STMIK Sinar Nusantara using psycho-linguistic approach. This study belongs to the qualitative descriptive research with 30 respondents selected by using simple random sampling. The data were collected by recording the students’ presentation. After that the data were analyzed by conducting observation and classification the errors found in the respondents’ speech using psycho-linguistic approach proposed by Clark and Clark. The result of the study showed that there were 336 (100%) speech errors found which were than classified into Silent Pause (34%), Filled Pause (13.7%), Repeats (9.2%), Retraced False Start 0.3%), Corrections (4.5%), Interjections (3.7%), Stutters (14%), dan Slip of Tongue (20.1%).
Emotion Recognition Expressed on the Face By Multimodal Method using Deep Learning

Emotional recognition plays a vital role in the behavioral and emotional interactions between humans. It is a difficult task because it relies on the prediction of abstract emotional states from multimodal input data. Emotion recognition systems operate in three phases. A first that consists of taking input data from the real world through sensors. Then extract the emotional characteristics to predict the emotion. To do this, methods are used to exaction and classification. Deep learning methods allow recognition in different ways. In this article, we are interested in facial expression. We proceed to the extraction of emotional characteristics expressed on the face in two ways by two different methods. On the one hand, we use Gabor filters to extract textures and facial appearances for different scales and orientations. On the other hand, we extract movements of the face muscles namely eyes, eyebrows, nose and mouth. Then we make an entire classification using the convolutional neural networks (CNN) and then a decision-level merge. The convolutional network model has been training and validating on datasets.
Linear models for total coverage problem with connectivity constraints using multiple unmanned aerial vehicles

The use of unmanned aerial vehicles (UAVs) has recently increased both in civilian and military operations, and the planning of their routes is critical. This research investigates a routing problem in which a UAV network, equipped with sensors, covers a given area and maintains connectivity with its neighbouring UAVs and the base station, while respecting to the UAVs lifetime. To cover the area, two integer linear programming models are formulated to solve two problems optimally. In the first one, covering means that all positions should be visited. However, in the second one, covering means that every position should be covered at least by one UAV. Due to the limited communication radius of the UAVs, connectivity then has to find inter-UAVs routing paths to satisfy the communication between UAVs and the base. We verify by experiments that the models, using Cplex, can provide an optimal solution of different area dimensions.
Uncertainly Guided Multi-Scale Underwater Image Enhancement Network with Tone Mapping Block

Underwater image enhancement remains a challenging problem for severe color distortions of the underwater images. In this work, an Uncertainly Guided Multi-scale Underwater Image Enhancement Network (UMUEN) with Tone Mapping Block is introduced by us to address this problem. In the proposed framework, a confidence module is induced and the confidence map is utilized as guidance to reconstruct more confident enhanced results in training step. So as to resolve the color distortion problems, we further design a tone mapping block to correct the color shift. The effectiveness of different constituents of the UMUEN is showed through an ablation study. Large quantities of experiment results demonstrate that the proposed UMUEN performs better compare with the state-of- the-art methods on real-world datasets.
Estimation of Various Scalar Multiplication Algorithms in ECC

this modern era of security, public key cryptography is quite popular and holds a great significance. Various public key cryptosystems are available in today’s environment such as RSA and ECC. Elliptic Curve cryptography is beneficial in a lot of aspects which includes shorter key as compared to other cryptosystems, high security, fast processing speed, low storage, low bandwidth, small software print, low hardware implementation costs, high performance. The main and the costliest step in ECC is the Scalar Multiplication. In scalar multiplication, integer multiple of an element in additive group of elliptic curves is calculated. In this paper, we compare various available algorithms for the scalar multiplication used in ECC.
Methods of Early Diagnostics Fiber Optical Communication Lines

This article investigates major methods of early diagnosticsfiber optical communication lines. On this way, research points of the optical communication were analyzed in Uzbekistan. Finally, this investigation is finalized with strong recommendation and suggestions.
From 2D Sketches to Photo-Realistic Images using Generative Adversarial Networks

With increasing technological advancements, there is a need for automation in this ever-evolving world. This may result in improved efficiency, faster work and enhanced capabilities. Sketch-to-image translation is an image processing application that can be used as a helping hand in a variety of fields. One of these is the utilization of Generative Adversarial Networks to guide edges to photographs, with the assistance of image generators and discriminators who work connected to produce realistic images. We have also incorporated Histogram of Oriented Gradients (HOG) as a feature/image descriptor. The HOG technique counts the gradient orientations to differentiate the target and the background. Support Vector Machine (SVM) is the classifier used for classification. This HOG and SVM model can be improved, altered and executed as multi-program software.
Security Enhancement in Data Propagation for Wireless Network

Wireless communication technology is rapidly progressing due to its high quality and high speed of information transfer from one location to another. It is necessary to ensure the safety of wireless sensor networks with this progress. One of the main security concerns in WSNs is eavesdropping, an intrusion that collects information from other devices across the network. Eavesdropping attacks are insidious and it is hard to realise that they happen. When connected with a network, users can feed sensitive information inadvertently, such as passwords, account numbers, browsing, email content, etc. Security improvement in wireless network communication is therefore required.
Occlusion detection and processing using optical flow and particle filter

Object tracking systems continue to be an intensive area of research, for which detection and processing of occlusion is a well-known challenge. This paper proposes a new approach to detection and handling of occlusion based on the integration of two known techniques, optical flow and particle filtering. Results of preliminary experiments show that the proposed method can detect and overcome the occlusion problem successfully during the tracking process.
Accessibility Utilizing Private Key Verification with Steganography over Difference Methods of Secure Information

Cloud is the normally utilized file to store, transmit, get and share mixed media substance. Cloud utilizes web to play out these undertakings because of which information turns out to be increasingly inclined to assaults. Information security and protection are compromised. This can be kept away from by constraining information access to confirmed clients and by concealing the information from cloud benefits that can't be trusted. Concealing information from the cloud administrations includes scrambling the information before putting away it into the cloud. Information to be imparted to different clients can be encoded by using Cipher Text-Policy Attribute Based Encryption (CP-ABE). CP-ABE is utilized which is a cryptographic method that controls access to the scrambled information. The matching put together calculation based with respect to bi-linearity is utilized in ABE because of which the prerequisites for assets like memory and force supply builds rapidly. Most of the gadgets that we use today have restricted memory. Therefore, a productive blending free CP–ABE get to control plot utilizing elliptic bend cryptography has been utilized. Blending based calculation is supplanted with scalar item on elliptic bends that lessens the important memory and asset prerequisites for the clients. Despite the fact that matching free CP-ABE is utilized, it is simpler to recover the plaintext of a mystery message if cryptanalysis is utilized. Along these lines, this work proposes to consolidate cryptography with steganography in such a manner by installing crypto content into a picture to give expanded degree of information security and information proprietorship for problematic sight and sound applications. It makes it harder for a cryptanalyst to recover the plaintext of a mystery message from a stego-object if steganalysis were not utilized. This plan fundamentally improved the information security just as information protection.
Geological Characteristics and Ore-Controlling Factors of the Yazigou East Au Polymetallic Deposit in Mangya Town, Qinghai Province, China

The Yazigou East Au Polymetallic Deposit is located in the Qimantag Mountain in the western section of East Kunlun.It is adjacent to the southwestern margin of the Qaidam Basin in the north and adjacent to the Aerjinshan in the northwest.In terms of tectonics, it belongs to the Kendrick-Suhaitu-Hongmuhongcun north volcanic arc zone (third-order tectonic unit) northern Kunlun magmatic arc (second-order tectonic unit) East Kunlun arc-basin system (first-order tectonic unit).The metallogenic belt to which this deposit belongs is the East Kunlun (orogenic belt) Fe, Pb, Zn, Cu, Co, Au, W, Sn and asbestos metallogenic belt.There are skarn-type Fe polymetallic deposits in the contact zone.The formation of ore bodies in the SKⅠ, SKⅡ skarn zones, C3-2 magnetic anomaly and C3-3 magnetic anomaly in this area is closely related to it, therefore the volcanic rock formation of the Elashan Formation and the carbonate rock formation of the Tanjianshan Formation are important indicators for searching for skarn-type polymetallic minerals in this area.
Generalized Architecture for Reconfigurable Hardware Security Incorporating PKI

Software-based techniques represent the dominant paradigm for the implementation of network security. Due to the rapidly growing and dynamic nature of contemporary networks security threats are becoming challenging and the overheads of a purely software approach are mounting to enormous proportions. Higher scales of hardware integration have also produced novel types of hardware threats and attacks which cannot be addressed by a purely software approach. Hence the interest in hardware security approaches is increasing. In this paper, we propose a general architecture for hardware-based security that can address the custom security needs of the users. The architecture incorporates the security model adopted in the Public Key Infrastructure (PKI) model for security.
An Experimental Technique for OCR Line and Word Segmentation using Probability Distribution Estimation

Segmentation is always an important step in designing an Optical Character Recognition (OCR) of any script. In this paper, we focus on the line and word segmentation in typewritten Gurmukhi script documents. In order to perform this task, we consider OCR based methodology where several processing steps are implemented. The typewritten documents suffer from several issues such as noise, skew, and quality of the document. In this work, we present a combined pre-processing scheme where document thresholding and skew detection and correction schemes are implemented where image thresholding is obtained using Niblack’s method and skew correction is carried out using gradient histogram algorithm and uniform orientation is obtained. Later, line segmentation scheme is applied where probability density function is applied to generate the text distribution in the probability map. Here, identifying the relation of the text to the exact line is a challenging task hence, we present a 2D-Gaussian modelling which helps to identify the text boundaries in the x and y direction. The proposed methodology is applied for typewritten Gurmukhi documents and an experimental study is carried out to show that the proposed approach achieves better performance when compared with the existing techniques
Grade Card Model using Fuzzy Logic

The Students domain provides us a treasure to unveil many interesting applications of Fuzzy Logic, which in turn support the Education System for better decision making. The base of the Education System is the Students Performance which is represented by his/her Grade. This article presents a model for developing a Grade Card for a Graduate Student using Fuzzy Logic.
Design of Multi Granularity Quantum Switching Node Structure for Embedded Intelligent System

The load-bearing modes of power man services are quite different.Network switching nodes not only need to support the exchange of quantum signal, synchronous signal and classic signal, but also need to have multi granularity signal exchange function to support the encrypted transmission of power services with different service levels.The multi granularity quantum switch node structure based on fiber level switch layer, band level switch layer and wavelength level switch layer is adopted to improve the flexibility of switch node and reduce the scale of cross connection matrix.At the same time, the wavelength selection switch is introduced into the multi granularity quantum switching node, which ensures the same path exchange between the quantum signal and the synchronous signal of the same user through the programmable flexible wavelength selection.The simulation results show that the quantum switch node structure is feasible in the application of power man.
A Classical Scheme of AES algorithm using Cipher key

Expanding might want information insurance in PC systems diode to the occasion of numerous cryptanalytic calculations hence causing information immovably over a transmission connect is basically vital in a few applications. Equipment usage of cryptanalytic calculations square measure physically secure than bundle executions since outside aggressors can't change them. So as to accomplish better in the present intensely stacked correspondence systems, equipment execution could be an insightful choice as far as higher speed and dependableness. In This paper shows the gear utilization of Advanced cryptography dynamic (AES) rule abuse Xilinx-virtex five Field Programmable Gate Array .In solicitation to achieve higher tempo and lesser freedom Sub PC memory unit movement, Inverse Sub PC mu action, join Column action and Inverse solidify Column assignments square measure arranged as LUTs and Read Only Memorie .This move toward give a turnout of three.74Gbps utilizing just one of hard and fast cuts in
Camera based Smart Surveillance System

One of the key sectors which is now concern worldwide is security and privacy.Due to the emergence of protecting premises, providing security is one of the most important tasks.Thus, to provide security, the video surveillance system was introduced.But video surveillance system has few drawbacks such as human intervention to observe footage, storage, and expertise to analyze multiple camera system.To overcome it, in their project authors have made a system that automatically tracks each individual under surveillance, maintains logs instead of video recordings, analyzes frames and generates helpful insights.Convolution Neural Network (CNN) based deep learning model is used to build the system.
Investigating Project States Boosting Spontaneous Software Evolution

Social coding platforms (SCPs) have realized spontaneous software evolution, where new source code and ideas are spontaneously proposed by altruistic developers. Although there are many projects operated by active communities performing spontaneous evolution, it is yet unclear that how such successful projects and communities have been formed and governed. In this paper, we propose a method that can investigate the history of every project in the SCP. Introducing the concept of project as a city, we consider every project in the SCP as a city, where a government and citizens develop a city through collaborative activities. We then identify essential attributes that characterize a state of a city. For each attribute, we develop metrics that quantify the state S(p, t) of a project p at time t. An experimental evaluation investigating GitHub projects of famous code editors shows that the proposed metrics well visualize the history of the projects from essential perspectives of a city.
Curried Functions

Currying is a technique which allows new functions to be created from existing functions by binding one or more parameters to a specific value. It is a major source of reuse of functions in Python which means that functionality can be written once, in one place and then reused in multiple other situations.
Assessment of Object Segmentation Techniques for Object Based Image Retrieval

Objects relates more to human perception than any other attributes of an image. Image segmentation is a significant image processing technique to get the objects from complex image background. This work assesses the techniques of segmentation from basic global thresholding, edge based methods up to the advanced techniques such as K-means, Active Contour Model (Snakes) segmentation approaches. Later, results are post processed with the help of morphological operations and make them suitable for object based image retrieval. It also provides the comparative analysis and empirical assessment of performance of the proposed modified segmentation approaches.
Teaching Digital Design Using Cad Tools In A Teaching Oriented University

Digital Logic System Design is a very important course in electrical and computer engineering programs.Current teaching methods propose the integration of Hardware Description Language (Verilog or VHDL).This paper describes the author's experience in integrating Xilinx ISE tools and FPGA/CPLD logic devices into the teaching of digital logic system in a teaching-oriented university.The author's experience indicates that integrating CAD and FPGA/CPLD instead of the early introduction of HDL can better facilitate the learning of digital system design.
Regression

Simple linear regression models a variable Y as being, aside from a random error, a linear function of another variable X. The parameters of this linear relationship are unknown and need to be estimated. Least square estimators of these parameters are derived, and their distributions are determined when the error term is normally distributed with mean 0 and unknown variance. It is shown how to obtain confidence intervals and test hypotheses concerning these parameters. Multiple linear regression, which assumes a linear relationship between Y and variables X1,...,Xn, is also considered. R is used to do the computations.
Full-immersion virtual reality for experiential education: An exploratory user experience analysis

Experiential education is widely considered an effective pedagogy to foster learning for our rapidly changing world. Despite this, residential fieldtrips are on the decline. Recent advances in full-immersion virtual reality (VR) technology offer great potential to make situated experiential education, such as fieldtrips, more accessible to educational institutions, however, research on VR technology’s effectiveness in this context is lacking. This article documents exploratory action research which examines the effectiveness of full-immersion VR technology for experiential education by adopting a user experience (UX) analytical frame. Six university staff and five students who participated in a trial of a virtual environment developed for sustainable tourism education, discussed their user experience through semi-structured interviews. The UX lens which distinguished between three UX facets during the analysis, beyond the instrumental, emotion and affect, experiential, serves to identify research areas requiring attention and assists in the technology’s improvement prioritisation. Interviews revealed many positive perspectives thus lending support to VR technology’s suitability to foster experiential education, however, several negative experiences were also identified; principally motion sickness. The exploratory findings suggest that more research is warranted to more comprehensively examine VR technology’s capacity to foster experiential education and locate VR’s place in the education landscape.&lt;p&gt;&lt;/p&gt;
SynRec: A Prediction Technique using Collaborative Filtering and Synergy Score

Recommender systems are techniques designed to produce personalized recommendations. Data sparsity, scalability cold start and quality of prediction are some of the problems faced by a recommender system. Traditional recommender systems consider that all the users are independent and identical, its an assumption which leads to a total ignorance of social interactions and trust among user. Trust relation among users ease the work of recommender systems to produce better quality of recommendations. In this paper, an effective technique is proposed using trust factor extracted with help of ratings given so that quality can be improved and better predictions can be done. A novel-technique has been proposed for recommender system using film-trust dataset and its effectiveness has been justified with the help of experiments.
Are you taking your Metadata seriously?

Tony Davies, Peter Lampen and Robert Lancashire are worried about their metadata, or perhaps the lack of it. With the explosion of data and ways to mine and make use of it, having accurate and appropriate metadata about analytical data sets is vital if they are to be reused efficiently or at all. This is also an area that is being increasingly targeted by regulators, with the US FDA issuing guidance at the end of 2018; others will follow. You have been warned.
Application of Data-Driven Learning in College English Writing in Multimedia Network

Data-driven learning method is the main way for college students to learn English and strengthen their self-study ability. Data-driven learning method has the characteristics of various learning modes. By using data-driven learning method, searching in the corpus and analyzing the corpus, the language rules can be summarized.
Hidden Costs of E-Journals

Electronic journals are costly, and so are print journals. Both have their own cost base and, in general, that cost base is different for the different formats. Electronic journals require access and technology; print journals require shelving and a substantial warehouse among other things. A combined print and electronic environment is quite simply always going to be the most costly option since it includes the costs of both formats. The complexity comes about because libraries want better value for their subscription money and users want instant access to a broad range of serials at the desktop, preferably free at the point of use. Swets Information Services reckons that seventy-five percent of scholarly journals now have an online counterpart or are electronic only. The largest publishers account for only about thirty-three percent of the scholarly journals on the market and a much smaller percentage of the remaining titles.