Reviewerly/exHarmony huggingface dataset:
Klasifikasi Bekas Gigitan Ular Menggunakan Active Contour Model Dan K Nearest Neighbor

Abstrak Indonesia termasuk salah satu negara tropis yang memiliki tingkat risiko terkena gigitan ular yang tinggi. Penyebab utama kematian dari kasus gigitan ular tentunya adalah karena racun yang disemprotkan oleh ular berbisa tersebut melalui gigi taringnya. Penyebab lainnya adalah kesalahan dalam mengidentifikasi bekas gigitan tersebut secara visual. Terdapat perbedaan anatomi gigitan pada ular berbisa dan tidak sehingga mengakibatkan perbedaan bekas gigitan pada korban. Pada penelitian ini dibangun sistem identifikasi bekas gigitan ular yang dapat mengidentifikasi bekas gigitan ular tersebut oleh ular berbisa atau tidak dengan metode Active Contour Model dan K Nearest Neighbor. Dengan melakukan beberapa pengujian terkait parameter yang digunakan pada metode tersebut, didapat nilai akurasi tertinggi pada metode K Nearest Neighbor adalah dengan menggunakan aturan jarak correlation, nilai K = 3, dan sistem klasifikasi tidak menggunakan distance weight. Kata kunci : bite mark, active contour, k nearest neighbor Abstract Indonesia is categorized as one of tropical countries that have a high risk of snakebites. This surely may endanger rural citizensâ€™ lives for there are still many snakes found in rural areas. The main cause of death from snakebite cases is by reason of the venom squirted from snakeâ€™s canine teeth. Others causes are errors in identifying the bite marks visually. There are anatomical differences between puncture wounds from venomous and non-venomous snakes. This study established a snakebite identification system using Active Contour Model and K Nearest Neighbor (KNN) methods. By performing some tests related to the parameters used in the method, the highest accuracy value on K Nearest Neighbor method was obtained by using the correlation distance rule, the K value = 3, without using distance weight in the classification system. Keywords: bite mark, active contour, k nearest neighbor
AN ERROR ANALYSIS ON THE COMPLEX SENTENCES INSTUDENTS’ WRITING

English language has some sentence types used in writing. The complex sentence is oneof the sentence types that occur in writing. However, in the practice, it is found that some studentsstill make errors and have difficulties in writing it. This study attempted to find the kinds of erroron constructing complex sentences in students‟ writing. The purpose of this study is to identify theerrors in the students‟ writing of English Education Study Program at STKIP PGRI Sidoarjo onthe use of complex sentences. The methodology used in this study is descriptive qualitativemethod. The source of data of this study was the errors of complex sentences taken from theseventh semester students‟ written task of English Education Study Program at STKIP PGRISidoarjo. This study found that there were 74 errors in students‟ writing on constructing complexsentences. The errors of complex sentences were classified into errors of omission, errors ofaddition, errors of misformation, and errors of misordering. There were 70% of errors ofmisformation, 23% of errors of omission, 4% of errors of addition, and 3% of errors ofmisordering. Many students still make errors in using the correct form of verb in complexsentences which considered as error of misformation. To keep away doing the same mistakes, thestudents are supposed to try many times on writing complex sentences using correct form of verb.
An Advanced User Intent Model Based On User Learning Process

User intent analysis is a continuous research hotspot in the field of query expansion. However, the big amount of irrelevant feedbacks in search log has negatively impacted the precision of user intent model. By observing the log, it can be found that tentative click is a major source of irrelevant feedback. It is also observed that a kind of new feedback information can be extracted from the log to recognize the characteristics of tentative clicks. With this new feedback information, this paper proposes an advanced user intent model and applies it into query expansion. Experiment results show that the model can effectively decrease the negative impact of irrelevant feedbacks that belong to tentative clicks and increase the precision of query expansion, especially for those informational queries.
Artificial Immune System Optimization Technique for Robust and Secure Image Watermarking

For a secure data image transmission purpose, digital watermarking techniques are used by embedding and extracting the same watermark into digital content. One of the widely used transform domains for watermarking of most digital images is the Discrete Wavelet Transform domain (DWT)and the hybridization in the digital domain of the image watermarking scheme using (DWT) and Singular Value Decomposition (SVD),which has shown its efficiency in many watermarking schemes. A scaling factor is used to modify the coefficients before inserting them into singular values of the suitable sub-band for host image. In this paper, we propose an optimal watermarking scheme based on DWT and SVD techniques using an Artificial Immune System (AIS) algorithm. This is done with the aim of optimizing imperceptibility and robustness by finding the best scaling factor and searching for the appropriate location for the watermark insertion. Besides, Arnold Transform encryption is used for adding security to the watermark image embedded in the host image. After embedding the watermark, the watermarked image is submitted to several attacks like median filtering, JPEG compression, cropping, and rotation with different distortion strengths. The imperceptibility and robustness of the watermarked image are checked out by measuring the Peak Signal to Noise Ratio (PSNR) and Normalized Correlation Coefficient (NCC). The proposed scheme provides some competitive simulations results proving the efficiency of our proposed method. Our arguments are motivated by the attractive obtained values of PSNR and NCC parameters, compared to those discussed in the recent literature.
Memes de Internet para el ejercicio analítico y expresivo: caso desde la enseñanza en diseño gráfico

espanolEl meme de Internet como producto de comunicacion a traves de las redes sociales y otras plataformas online se convierte en un elemento capaz de dinamizar el proceso de aprendizaje. Recurriendo a estudios previos, se detecta que funciona como herramienta de sintesis, analisis y evaluacion de contenidos; de la misma manera, potencia la capacidad para generar contenidos expresivos y comunicativos. A traves de una encuesta piloto y un grupo focal con la plantilla docente de la Escuela de Diseno Grafico de la Pontificia Universidad Catolica de Ecuador Sede Esmeraldas, se comprueba que estos consideran estos recursos como innovadores y motivadores para su incorporacion al metodo docente, de la misma manera que arrojan cuestiones interesantes para investigaciones futuras. EnglishThe Internet meme as a product of communication through social networks and other online platforms becomes an element capable of dynamizing the learning process. Using previous studies, it is detected that it works as a tool for synthesis, analysis and evaluation of contents; in the same way, it boosts the capacity to generate expressive and communicative contents. Through a pilot survey and a focus group with the teaching staff of the Graphic Design School of the Pontificia Universidad Catolica de Ecuador Sede Esmeraldas, it is verified that they consider these resources as innovative and motivating for their incorporation to the teaching method, in the same way that they throw interesting questions for future research.
A Parallel Computation Algorithm for Image Feature Extraction

We present a new method for image feature-extraction for learning image classification. An image is represented by a feature vector of distances that measure the dissimilarity between regions of the image and a set of fixed image prototypes. The method uses a text-based representation of images where the texture of an image corresponds to patterns of symbols in the text string. The distance between two images is based on the LZ-complexity of their corresponding strings. Given a set of input images, the algorithm produces cases that can be used by any supervised or unsupervised learning algorithm to learn image classification or clustering. A main advantage in this approach is the lack of need for any image processing or image analysis. A non-expert user can define the image-features by selecting a few small images that serve as prototypes for each class category. The algorithm is designed to run on a parallel processing platform. Results on the classification accuracy and processing speed are reported for several image classification problems including aerial imaging.
Library Guides: Trinity LibTech Research Showcase 2019: About LibTech 2019

An archive of the research presented at the Trinity LibTech Research Showcase, held as part of the 2019 LIBER Conference
Self-Sovereign Identity: a Comparison of IRMA and Sovrin

In this document we try to compare two of them: IRMA and Sovrin, the purpose of which is to give our audience an idea about what they are about, what the differences are, and where we stand today. The comparison is rather high-level, and touch upon functionality, protocols and maturity. We conclude that this area is still evolving (and quite rapidly). Quite a few issues remain to be resolved, most of which perhaps are not of a technical nature, but have to do with usability/user friendliness, legal stuff, adoption and the ability and willingness of businesses to transition to this new way of working.
Fast Generation of Perfect Gaussian Integer Sequences of Primitive Length

The different constructions of perfect Gaussian integer sequences (PGISs) have been extensively investigated in the recent literature. Those sequences have also been applied in a wide range of comb-spectrum code division multiple access as well as precoded orthogonal frequency-division multiplexing systems. This paper presents the long PGISs of primitive length based on the novel polynomial computations over finite fields. Such a polynomial can be expressed by the newly discovered exponent, which is less than the previously known Kasami exponent. This fact leads to the fast generation of long PGISs.
Adaptando NMT a la traducción de pies de imagen en Wikimedia Commons para idiomas con pocos recursos

espanolEste articulo presenta una adaptacion a dominio exitosa de un sistema de Traduccion automatica neuronal (NMT) utilizando un corpus bilingue creado con los pies de imagen utilizados en Wikimedia Commons para los pares de idiomas espanol-euskera e ingles-irlandes. EnglishThis paper presents a successful domain adaptation of a general neural machine translation (NMT) system using a bilingual corpus created with captions for images in Wikimedia Commons for the Spanish-Basque and English-Irish pairs.
Absorbing Diagonal Algorithm for Enhancing Randomized SVD Algorithms in Collaborative Filtering✱

Collaborative filtering is a main-stream technique to alleviate information overload. Singular Value Decomposition (SVD) has become very popular in the field of collaborative filtering. For computation of collaborative filtering, traditional SVD algorithms are too slow, randomized SVD algorithms using sampling techniques are more practical than them. The approximation accuracy of these randomized SVD algorithms, however, comes with a high price at their sampling. The enlargement of sample-set picked by the sampling will dramatically increase the computational complexity. The algorithm proposed in this paper aims to give a more efficient precision-improvement to these randomized SVD algorithms under some assumptions of collaborative filtering.
Inhibitory Integrate and Fire Neuron Based on Quantum-Dot Intra-Band Transitions in a Semiconductor Laser

Photonic neuromorphic engineering is an emerging field that aims to combine the merits of non-von-Neumann architectures with the high bandwidth and parallelism of the optical domain [1], Especially, laser-neurons can enhance these features, by exhibiting a wide pallet of dynamics. Recently, we demonstrated, an optically triggered inhibitory multi-section laser neuron where nanosecond responses were linked to quantum-dot (QD) waveband transitions [2], In our approach the inhibitory neuron is activated through ground-state (GS) input (considered excitation signal), but contrary to conventional excitatory neurons, generates excited state (ES) output, which we link to an inhibition signal. In this work, we utilize a numerical model that targets a simpler structure (single-section laser). Results confinn the role of intra-band transport time to inhibitory operation whereas dynamic analysis confirmed integrate and fire functionality alongside picosecond spikes, thus providing increased temporal resolution and simpler implementation compared to electro-optic or multi-section devices [2].
Estimation of Global Solar Radiation on Horizontal Surface in Kano, Nigeria Using Air Temperature Amplitude.

The need for the renewable source of energy is inevitable due to uneven distribution of the fossil fuel, its transportation expenses, political and military invasions to control and manipulate the possession, carbon emission, highly depleted and non-renewable nature. Solar energy studies of a given geographical location require inputs such as solar radiation profile for the performance estimation and development of various solar technologies. Advance solar radiation measuring equipment such as pyranometer and pyrheliometer are normally installed at the selected locations to collect, measure and output data. However, many developing nations could not afford the cost and maintenance of such equipment and hence the need for modeling the global solar radiation using different estimating methods with appropriate daily or monthly climatic data from meteorological stations. The main objective of this work is to calibrate, validate and evaluate four air temperature-based models namely the Hargreavees model, Allen model, Bristow-Campbell model and the Samani model to estimate global solar radiation potentialities at the Kano Airport, Nigeria using air temperature as the sole parameter as the input because of its easiness in availability and accessibility and can be used for any location in Nigeria without the sunshine hour parameter data. Statistical performance analysis of each model was evaluated, the performance parameter values vary from one model to another Samani model has the best fit amongst the models, and is therefore recommended for global solar radiation estimation for the location under consideration.
Отбор источников для систематического обзора литературы: сравнение экспертного и алгоритмического подходов

Two approaches to the selection of sources for a systematic literature review are compared – expert approach and algorithmic approach, based on an analysis of citation networks. Comparative analysis is conducted on the example of the research field of studying mass behavior. A comparison of two approaches according to formal and substantive criteria allows us to draw conclusions on the significant difference, but also complementarity of the obtained results. Sources selected by the algorithmic approach do not reproduce the history of the development of the research field described through sources selected by the expert approach. Adding expert elements to the algorithmic approach leads to a result that gives an idea of the links between classical and modern publications and groups of modern works that are interesting to explore in the future studies. The data obtained allow drawing a conclusion about the main reasons for the inconsistency of the results and formulating recommendations for the implementation of the proposed methodology in other areas
Experiments in Information Flow Analysis

Designing programs that do not leak confidential information continues to be a challenge. Part of the difficulty arises when partial information leaks are inevitable, implying that design interventions can only limit rather than eliminate their impact.
Human Factors and Multilayer Networks

Analysts of specific application domains, such as experts in systems biology or social scientists, are often interested to visually analyze a number of different network structures in conjunction, ...
Internet, Technology, and the Future: An Interview with Vint Cerf

This chapter presents an interview with Vint Cerf, one of the fathers of the Internet. The chapter discusses his personal views on ethics, data and privacy, net neutrality, public policy, self-driving cars, genetic codes, and reflections on the future.
An Optimal Strategy to Recover Nonlocality of Polarization-Entangled State from a SPDC Source via Entanglement Swapping Relay

To realize the practical implementation of device-independent quantum key distribution (DIQKD), the main difficulty is that its security is solely based on the detection loophole-free violation of the Clauser-Horne-Shimony-Holt (CHSH) inequality i.e. the CHSH value S > 2 [1]. To circumvent the inevitable losses in the transmission channels which create the detection loophole, several probabilistic methods to recover the nonlicality have been proposed. Here, we theoretically and experimentally investigate the optimal strategy for the method utilizing linear optical entanglement swapping relay (ESR) with photon pairs from spontaneous parametric-down conversion (SPDC) sources [2,3]. In the previous methods, it is common to employ the ESR node in Bob's system as shown in Fig. 1(a) (Hereafter, we call this configuration the local-heralding (LH).). We employ another configuration: The middle-heralding (MH) shown in Fig. 1(b), where the ESR node is placed in the middle of Alice and Bob similar to the measurement device independent QKD. We numerically compare S of the above two schemes by using the numerical simulation based on the characteristic-function approach [3]. The results are shown in Fig. 1(c). We see that the larger values of S are expected in the MH scheme when the dark count probabilities (ν) of the detectors are considered. In experiment, we perform the Bell-test experiment using the ESR with SPDC sources. We employ the MH scheme, and measure S changing the transmission losses. The experimental parameters (the average photon numbers and measurement angles) are chosen such that S is maximized under the condition of the experimental imperfections (mode-mismatch, dark count and so on) and the assumption of the unit local detection efficiencies (η = 1). While the overall detection efficiencies of our system (η ~ 15 %) are not the range of directly observing the violation of the CHSH inequality, S obtained by the experiment well agree with the numerical simulation with experimental parameters. When the overall transmission loss is set to be 10 dB, which corresponds to the transmittance of a 50 km-optical fiber, we observe S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">exp</sub> = 1.478, while S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> = 1.487 is expected by the numerical simulation. This result means that our numerical simulation can rigorously model the experiment. This allows us to estimate the nonlocality of the quantum state just before the local detection losses by the numerical simulation. The CHSH value is estimated to be S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">exp</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">η=1</sup> = 2.104 > 2, which indicates that the quantum state with experimental imperfections possesses the potential to violate the CHSH inequality.
The conorm code

Given an extension $F'/F$ of algebraic function fields over $\mathbb{F}_q$, we define the conorm AG-code defined via $F'$ associated to an AG-code defined via $F$.
Seamless infrastructure programming and control for quality-critical cloud applications

By providing elastic infrastructure capacity and flexible pay-as-you-go business model, Cloud environments can significantly reduce the operational cost for resource-intensive applications like big data, deep learning, and the Internet of Things (IoT). In the application lifecycle, Clouds can not only automate the provisioning of application infrastructure, the deployment of the software components, but also provide advanced features, e.g., dynamic migration, scaling, and programmable virtual networking, for adapting the complex application to be continuously operational. However, these advanced Cloud features are so far only used at runtime phase of the application and have not yet been effectively included in the application programming model, which makes the Cloud application optimisation difficult across the entire software development and operation (DevOps) lifecycle. For applications with high-quality constraints, e.g., when processing IoT data queries within a given time window, or transmitting the data from the source to the computing resource within required latency, only runtime adaption will not be sufficient if infrastructures are not correctly designed. We thus identify our key research question as: how to seamlessly program and control the virtual infrastructure in the Cloud application DevOps lifecycle? To tackle the problem, we leveraged Infrastructure as Code to represent infrastructure specifications and model infrastructure operations. By decoupling the infrastructure abstraction from the application DevOps, we proposed the Cloud programming model and control mechanism. Overlay network mechanisms were further explored to provision a networked infrastructure. Finally, we investigated blockchain to improve Cloud Service Level Agreement (SLA) for enhancing the infrastructure service quality assurance at runtime.
Detecting of Rash Driving using Rescue System

Real-time anomalous driving behaviors monitoring is a corner stone to improving driving safety. Existing works on driving behaviors monitoring using smart phones only provide a coarse-grained result, i.e. distinguishing anomalous driving behaviors from normal ones. To improve drivers’ responsiveness of their driving habits so as to prevent potential car accidents, we need to judge a fine-grained monitoring approach, which not only detects anomalous driving behaviors but also identifies specific types of anomalous driving behaviors, i.e. Weaving, Swerving, Side slipping, Fast U-turn, Turning and rapid braking. We intend a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution for this only a mobile phone placed in vehicle and with accelerometer sensor. A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with usual drunk driving patterns extracted from actual driving tests.
Old Wine in New Bottles? Critical and Comparative Perspectives on Identity Crimes under the Nigerian Cybercrime Act 2015

This article critically analyses the provisions on identity theft and identity fraud in the Nigerian Cybercrime Act passed in 2015. The objective of the article is to provide answers to three pressing questions: What was the law on identity crimes before the Cybercrime Act? How has the law addressed the peculiar challenges of identity theft and identity fraud online? Are the provisions of the law adequate and if not how should the law otherwise respond? This article provides an in-depth legal analysis of the relevant provisions of the law and highlights the gaps in the law through comparative analysis with UK and US laws. While the article proposes amendments to make the Nigerian law more effective in combatting identity crime, it also invariably pushes for harmonisation and consistency in the approach of national laws to the crime.