Reviewerly/exHarmony huggingface dataset:
When an attacker meets a cipher-image in 2018: A Year in Review

This paper aims to review the encountered technical contradictions when an attacker meets the cipher-images encrypted by the image encryption schemes (algorithms) proposed in 2018 from the viewpoint of an image cryptanalyst. The most representative works among them are selected and classified according to their essential structures. Almost all image cryptanalysis works published in 2018 are surveyed due to their small number. The challenging problems on design and analysis of image encryption schemes are summarized to receive the attentions of both designers and attackers (cryptanalysts) of image encryption schemes, which may promote solving scenario-oriented image security problems with new technologies.
Colour Histogram Segmentation for Object Tracking in Remote Laboratory Environments

Remote Laboratories are online learning environments where a major component of student’s learning objectives is met though visual feedback. This is usually through a static webcam feedback at non-HD resolution. An effective method of enhancing the learning procedure is by tracking certain objects of learning interests in the video feedback. Detecting and tracking moving objects within a video sequence commonly employs varying segmentation methods such as background subtraction to isolate objects of interest. This paper presents two colour histograms models as a method to segment frames from a video sequence and an end-to-end tracking system. Six tests and their results are presented in this paper with varying frame rates and sequencing times.
Research on Sensitivity of Speckle Center Coordinate Values by Contour and Background Noise and Elimination Method

The accuracy of measuring the target object displacement is greatly influenced by the offset of central coordinate value in a laser speckle contour (CCVLSC) due to the defects obtained in background or on measuring surface, as a measuring combination of both monocular vision and laser speckle is used. In this paper, the theoretical principle of displacement measurement is first presented by a combination of monocular vision and laser speckle. Then, a model between object displacement and CCVLSC (particularly, [Formula: see text] coordinate value) is derived. Finally, a denoising algorithm with competitive protection of contour effective points is proposed, on the basis of effects of noises coming from background and contour edge on CCVLSC. The algorithm includes ellipse fitting to laser speckle contour, calculating offsets between all contour points and the fitted eclipse, eliminating noise points with higher deviation (generally about 5% of all contour points) by using competitive strategy, ellipse refitting, and recalculating and re-eliminating until the deviation is below a specified threshold. It is shown that the algorithm can not only eliminate the fixed noise points in each round but also protect the number of effective points to the greatest extent. Finally, the feasibility of the algorithm is verified by two ways. One is an ideal data validation. It proves that the algorithm can guarantee the convergence towards the ideal center coordinate value. Another is an experimental verification. An experimental system is built up based on the relationship between object displacement and Y coordinate value of CCVLSC for obtaining relevant dada. It is shown by the comparison between predictions and experimental data that the algorithm has a better robustness and a higher accuracy of distance measurement than other typical algorithms.
LibGuides: Summer Reading Assignment: Junior

Uponyour returntoschoolinSeptember,yourteacherwillrequireyoutocompleteanassignment based on yourreading,whichwill countforpartofyourfirstmarkingperiodgrade.
Packet Loss Signaling for Encrypted Protocols

This document describes a protocol-independent method that employs twobits to allow endpoints to signal packet loss in a way that can beused by network devices to measure and locate the source of the loss.The signaling method applies to all protocols with a protocol-specific way to identify packet loss. The method is especiallyvaluable when applied to protocols that encrypt transport header anddo not allow an alternative method for loss detection.
Evaluation of a Brazilian simulator for virtual reality behavior therapy

Behavioral therapy combined with a virtual reality exposure (VRE) component can be useful for the treatment of fears and phobias. This study aimed to: (a) describe and evaluate a behavioral therapy procedure amplified by VRE for the treatment of fear of height and (b) record sense of presence and cybersickness during exposure to assess the Virtua Therapy simulator. The procedure consisted of: an initial session; six therapy sessions, which included graduate exposure, prevention of escape-avoidance responses, and functional analyses of behaviors; two follow-up sessions. Sense of presence and cybersickness were recorded. The intervention decreased the participants’ levels of anxiety and the frequency of avoidance of situations involving heights in the virtual environment, and they reported decreases in day-to-day avoidance responses, demonstrating therapeutic effects. The simulator produced sense of presence. Cybersickness occurred primarily during the first session, indicating habituation effect. It was concluded that the Virtua Therapy simulator is an appropriate device for behavioral therapy.
Research for the Unified Description Mechanism of the 3D model of the Launch Vehicle Based on Ontology

Abstract Aiming at the 3D model of the Launch vehicle, the article raises the unified description method based on the ontology and creates the hierarchical ontology model for the launch vehicle. At the end of the paper, an example of the tank which is based on the ontology is verified by the unified description method.
Designing for and with Care in Multispecies Kinship: Exploring Methods of Decentering the Human in Design

In the current climate crisis, creating a symbiotic collaboration between all members of an ecosystem has become a prominent topic. By reevaluating human-centered methodologies through a cultural p ...
Static Context Header Compression (SCHC) and fragmentation for LPWAN, application to UDP/IPv6

This document defines the Static Context Header Compression (SCHC)framework, which provides both a header compression mechanism and anoptional fragmentation mechanism. SCHC has been designed for Low PowerWide Area Networks (LPWAN). SCHC compression is based on a commonstatic context stored both in the LPWAN device and in the networkinfrastructure side. This document defines a generic headercompression mechanism and its application to compress IPv6/UDPheaders. This document also specifies an optional fragmentation andreassembly mechanism. It can be used to support the IPv6 MTUrequirement over the LPWAN technologies. Fragmentation is needed forIPv6 datagrams that, after SCHC compression or when such compressionwas not possible, still exceed the layer-2 maximum payload size. TheSCHC header compression and fragmentation mechanisms are independentof the specific LPWAN technology over which they are used. Thisdocument defines generic functionalities and offers flexibility withregard to parameter settings and mechanism choices. This documentstandardizes the exchange over the LPWAN between two SCHC entities.Settings and choices specific to a technology or a product areexpected to be grouped into profiles, which are specified in otherdocuments. Data models for the context and profiles are out of scope.
Obtaining optimal velocity thresholds for deep-seated landslides using different fitting algorithms and receiver operating characteristic

The Philippine Institute of Volcanology and Seismology - Project Dynaslope (PHIVOLCS - Dynaslope) developed an early warning system (EWS) for deep-seated landslide which uses threshold values as a basis in issuing alerts (i.e., A0, A2, and A3). Movements in the subsurface, which is measured through tilt sensors, is one of the parameters being monitored. An alert is raised every time the measurement exceeds velocity threshold. However, the sensor data exhibits frequent fluctuations and may cause false alerts. At present, simple moving average (SMA) is being used to attenuate noisy data. However, SMA exhibits delay at higher values which may also cause missed alerts. To prevent this issue, a suitable fitting algorithm should be implemented to reduce data noise and a site-specific optimal velocity threshold should be defined to capture impending alerts. This paper shows different techniques in fitting the sensor data and identifying the optimal velocity threshold (A2 alert) for the three sites: (1) Brgy. Sagasa, Dadong, Tarragona, Davao Oriental - dadtb, (2) Brgy. Magsaysay, Kibawe, Bukidnon - magta, and (3) Brgy. Tue, Tadian, Mt. Province - tuetb. Among the six algorithms tested, locally weighted scatterplot smoothing (LOWESS) found to be the most suitable algorithm due to its low root mean square error (RMSE) of 4.689 as compared to other algorithms. Using LOWESS and receiver operating characteristic (ROC) analysis, the optimal velocity thresholds for A2 alert are 0.73 cm/day, 0.50 cm/day, and 0.03 cm/day for magta, dadtb, and tuetb respectively. Also, LOWESS exhibits a favorable area under the curve (AUC) of 0.991. Thresholds will be further investigated to incorporate the response of the stakeholders at risk in order to maintain the integrity of the EWS.
Path Analysis on The Biological and Social Life Course Factors Affecting Childs Speech and Language Development Delay

Background : The development in children occurs once during the period of their life. The la­ngu­age ability is an indicator of all the development. The lack of stimulation can cause speech and la­ngu­­age disorders and this disorder can persist. This study aimed to determine the effects of bio­lo­gi­cal and social life course factors on delayed speech and language development. Subjects and Method : This study was an observational analytic with cross-sectional approach, conducted in 25 integrated health posts (posyandu) located in Sleman Regency, Yogyakarta in March to April 2019. The total sample of 225 toddlers was chosen using fixed exposure sampling. The dependent variable was delayed speech and language development. The independent variables we­re income, employment, nutritional status, birth weight, history of toxoplasma, rubella, CMV and TORCH, history of infection, duration of gadget use, language, frequency of posyandu visit, and early childhood education (PAUD). Data collection on delayed speech and language de­ve­lop­ment were measured by Denver II. The data were analyzed by path analysis. Results : Speech and language delayed development was directly decreased with normal birth weight (b= -2.19; 95% CI= -3.58 to -0.79; p= 0.002), employed mother (b = -1.32; 95% CI = -2.38 to -0.27; p = 0.013), good nutritional status (b = -2.14; 95% CI = -3.37 to -0.91; p = 0.001), re­gu­lar­ly attend integrated health post (b = -1.29; 95% CI = -2.31 to -0.26; p = 0.013 ), mono language (b = -1.02; 95% CI = -1.99 to -0.04; p = 0.041), low duration of gadget use (b = -1.59; 95% CI = 0.23 to 2.33; p = 0.017). Speech and language delayed development was directly increased with history of di­sease (b = 1.37; 95% CI = 0.34 to 2.40; p= 0.009), and did not attend Pre-school (b = 1.28; 95% CI = -2.65 to -0.53; p = 0.003). It was indirectly affected by number of children, income, and history of TORCH. Conclusion : Delays in speech and language development are directly influenced by birth weight, infection history, employment, nutritional status, frequency to posyandu (integrated health posts), long usage of gadgets, PAUD (pre-school) and indirectly influenced by income and the number of children. Keywords : the development of speech and language, the use of gadgets Correspondence: Merlita Indriasih. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir.Sutami 36A Surakarta 57126, Central Java, Indonesia. Email: merlitaindriasih@gmail.com . Mobile: 085­641097941. Journal of Maternal and Child Health (2019), 4(6): 11-22 https://doi.org/10.26911/thejmch.2019.04.06.02
Memetic particle swarm optimisation for missing value imputation

Incomplete values in databases stand as a major concern for data analysts and many methods have been devised to handle them in different missing scenarios. Many researchers are increasingly using evolutionary algorithms for handling them. In this paper, a memetic algorithm based approach is proposed which integrates the principles of particle swarm optimisation and simulated annealing, a local search method. A novel initialisation strategy for PSO is also proposed in order to seed good particles into the population. Simulated annealing prevents PSO from premature convergence and helps it in reaching global optimum. PSO algorithm exhibits explorative behaviour and SA exhibits exploitative behaviour and serves as the right combination for memetic algorithm implementation. The proposed algorithm is implemented in different datasets to estimate the missing values and the imputation accuracy and the time taken for execution is found to be better than other standard methods.
Underexposed Image Correction via Hybrid Priors Navigated Deep Propagation

Enhancing visual qualities for underexposed images is an extensively concerned task that plays important roles in various areas of multimedia and computer vision. Most existing methods often fail to generate high-quality results with appropriate luminance and abundant details. To address these issues, we in this work develop a novel framework, integrating both knowledge from physical principles and implicit distributions from data to solve the underexposed image correction task. More concretely, we propose a new perspective to formulate this task as an energy-inspired model with advanced hybrid priors. A propagation procedure navigated by the hybrid priors is well designed for simultaneously propagating the reflectance and illumination toward desired results. We conduct extensive experiments to verify the necessity of integrating both underlying principles (i.e., with knowledge) and distributions (i.e., from data) as navigated deep propagation. Plenty of experimental results of underexposed image correction demonstrate that our proposed method performs favorably against the state-of-the-art methods on both subjective and objective assessments. Additionally, we execute the task of face detection to further verify the naturalness and practical value of underexposed image correction. What's more, we employ our method to single image haze removal whose experimental results further demonstrate its superiorities.
An Analytic Calculus for the Intuitionistic Logic of Proofs

The goal of this article is to take a step toward the resolution of the problem of finding an analytic sequent calculus for the logic of proofs. For this, we focus on the system Ilp, the intuitionistic version of the logic of proofs. First we present the sequent calculus Gilp that is sound and complete with respect to the system Ilp; we prove that Gilp is cut-free and contraction-free, but it still does not enjoy the subformula property. Then, we enrich the language of the logic of proofs and we formulate in this language a second Gentzen calculus Gilp∗. We show that Gilp∗ is a conservative extension of Gilp, and that Gilp∗ satisfies the subformula property.
IMPLEMENTATION AND PROBLEMS OF INTRODUCING THE MODELLING METHOD WHEN TRAINING THE INTENDING LABOUR TRAINING AND TECHNOLOGIES TEACHERS

The article is devoted to a problem of implementation, application and importance of a modeling method in the system of training the intending labor training and technologies teachers. The mainstay of applying a modeling method during teaching professional disciplines to the intending experts is described. Stages of applying a modeling method on the example of material models in the course of conducting practical classes on special disciplines for intending labor training and technologies teachers in the institutions of higher education are characterized. In the conditions of global changes and challenges, providing a new level of qualified specialists, intending technology teachers, starting with the traditional teaching system and up to the competence development of the individual is carried out by the implementation of non-traditional teaching approaches. The formation of technical and practical levels of competence of intending labor training teachers is the indicator of high intelligence, technical experience and fundamental knowledge. Therefore, the problem of forming theoretical thinking can be successfully solved only when scientific models of the studied phenomena take their rightful place. A solution to problems of an experimental part, which makes certain intellectual difficulties for students, allow teachers to form positive interest and motivation to a subject matter that, in turn, increases quality of teaching. Therefore, applying models in the educational activity allows to implement the main objectives of the educational activity, namely the formation of highly qualified specialists. Ways to influence the development of technical thinking and the importance of forming the creative person in the conditions of modern changes in the system of teaching the competent specialists of the educational area «Technology education» are defined.
The Impact of the Implementation of Capability Maturity Model Integration on User Satisfaction: Case Study on Software Companies in Jordan

The Capability Maturity Model Integration, as part of the software process improvement, has been receiving attention due to the belief of its relevance to the customer satisfaction factor.This research aims at offering software companies in Jordan an overview of Capability Maturity Model Integration methodology and its benefits for the software industry.To study the impact of its implementation on customer satisfaction, through the quality of the software, and provide recommendations on increasing the awareness of Capability Maturity Model Integration, a quantitative study is designed.Four perspectives related to Capability Maturity Model Integration have been studied: the effect of its implementation on customer satisfaction as well as software quality, the effect of software quality on customer satisfaction, and the effect of its implementation on customer satisfaction through the software quality.The results concluded that there is a direct effect of implementing Capability Maturity Model Integration on customer satisfaction and software quality.It also shows that higher software quality positively affects customer satisfaction; i.e. software quality plays a mediation role between the effect of Capability Maturity Model Integration implementation and the customer satisfaction.
THE PRACTICE AND OBSTACLE FACTORS IN THE TEACHING OF ENGLISH TO YOUNG LEARNERS IN PUBLIC PRIMARY SCHOOLS IN PRINGSEWU, LAMPUNG PROVINCE, INDONESIA

In learning English for beginners like children, teachers have a very important role and will have a big effect on the outcomes of the learning process. In fact, most students in primary schools are difficult to understand English. Therefore, this study is aimed to examine the practices and obstacle factors in the teaching of English to young learners in six public primary schools (grade 4-6) in Pringsewu, Lampung province. This is descriptive research study that observes the process of teaching and learning and gives interviews to the teachers related to the teaching of English to young learners to gather relevant and proper data. The data is analyzed  based on themes and categories identified from the available literature quantitatively and qualitatively. The findings indicate English is taught through Indonesian language. Moreover, it shows that teachers who teach English are lack of proper pre-service training because most of them are not graduated from English Education. Therefore, they are lacking understanding and knowledge of the purpose, procedures and approaches of teaching English to young learners. The teachers also lack of in-service professional development courses on how to deal with young learners because the English position is only as local content. English gets less attention from both schools and government. Therefore, they never get in-service training, textbooks, syllabus and other facilities. This study recommends the change of minister of education regulation that positioning English as a local content to be compulsory subject to maximize the learning process to meet the challenge of globalization era.
Att utveckla sångröstens övre tonomfång - En studie av det egna sångtekniska arbetet

This study aims to show the problem of getting a desirable upper tone range. In this context, it means tones from the two-line octave and upwards. The starting point for the work is the author's own singing problems and previous experiences. Therefore, the study is based on action research where the author examines her own practice with high tones, under the instruction of Anna-Lena Tideman, a singing teacher and singer with many years of experience.The aim of the study is to elucidate and to discuss a development process of the voice's upper tone range, focusing on sustainability, flexibility, strength and dynamics. The study also wants to show how certain factors may influence this type of vocal-technical work. The result presents relevant singing exercises and singing technical focus areas, designed to promote and to further develop the author's singing technique. This includes a conscious work with passages and registers, as well as exercises for support and breathing. The study also shows that the work with singing high tones includes many different aspects, and is influenced by several factors such as the singer's active listening, temporary fatigue, as well as previously established singing habits that may imply unforeseen challenges.
Teach an all-rounder with experts in different domains

In many automatic speech recognition (ASR) tasks, an ideal model has to be applicable over multiple domains. In this paper, we propose to teach an all-rounder with experts in different domains. Concretely, we build a multi-domain acoustic model by applying the teacher-student training framework. First, for each domain, a teacher model (domain-dependent model) is trained by fine-tuning a multi-condition model with domain-specific subset. Then all these teacher models are used to teach one single student model simultaneously. We perform experiments on two predefined domain setups. One is domains with different speaking styles, the other is nearfield, far-field and far-field with noise. Moreover, two types of models are examined: deep feedforward sequential memory network (DFSMN) and long short term memory (LSTM). Experimental results show that the model trained with this framework outperforms not only multi-condition model but also domain-dependent model. Specially, our training method provides up to 10.4% relative character error rate improvement over baseline model (multi-condition model).