Reviewerly/exHarmony huggingface dataset:
A Fast Data Hiding Algorithm for H.264/AVC Video in Bitstream Domain

There are many algorithms for data hiding in H.264/AVC video sequences, most of which focus on embedding in the decoded domain. However, these schemes always perform badly in embedding speed. Aimed at simplifying computing complexity and developing a fast algorithm, we propose in this paper a new data hiding scheme for H.264/AVC video with a high embedding speed. Instead of hiding data into the elements in the encoding process, we analyze the structure of H.264/AVC video bitstream and look for appropriate bits to modify in order to minimize the change caused to the original stream. Our algorithm chooses the last byte of those less important NALU (Network Abstraction Layer Unit) to hide secret data. The experimental results showed that the proposed algorithm achieves an impressive embedding speed while maintaining good visual quality and embedding capacity.
Extending openness in education support services for out-of-school children in underprivileged circumstances

Openness has underpinned much of the evolution of the Internet and digital technologies that support learning. Worldwide, openness in education has provided access to high-quality learning opportunities for school-age learners during the last two decades. During this same era, several global initiatives have made it their mission to educate all children of the world. However, despite major technological advancements in education and new innovative learning solutions, efforts to reduce large numbers of out-of-school children do not show promising outcomes in many parts of the world, let alone quality outcomes. This paper analyses the importance of context for educational outcomes and examines the need to understand socio-cultural and economic limiting factors of out-of-school children in underprivileged contexts in Pakistan. In such contexts, development demands sustainable and adaptable solutions. In identifying possible ‘solutions’, innovative strategies to educate out-of-school children is explored through combining traditional one-room schoolhouse methods with innovative digital technology and Open
DEVELOPMENT OF ADAPTIVE CAPACITIES OF A PERSON WITH SPECIAL EDUCATIONAL NEEDS IN AN ADAPTIVE INCLUSIVE SPACE.

Summary. The article discusses the impact of self-concept on the adaptive capacity of a person with special needs. It is considered how the system of ideas influences the development of the individual. The origins of the problem are described, the characterization of the personality of students with disability status is given. The origins of the problem are described, the characterization of the personality of students with disability status is given. The main task of adaptive inclusive space as a system should be to promote the transformation of the student's inner position, namely, negative personal formations in the structure of self-concept. When developing mechanisms for adaptation of students with special needs, it is necessary to take into account the self-concept, which is characterized by identification with its social status of a disabled person and an increasing tendency to preserve such facilities. The origins of the problem are described, the characterization of the personality of students with disability status is given.&#x0D; Тhe ways of correction of the self-concept of the disabled, namely, the stimulation to reflexive activity, as a condition that provides the transition to awareness of oneself and problems that hinder the development and adaptation to the educational space, which involves the realization of the subject of special activity, at the same time cognitive and personal character that is already the beginning of the process of developing the adaptive capacity of a student with special needs. One of the conditions for the unfolding of reflection is the failure of the activity, the violation of its natural course, when attempts to use the known methods of action do not work or it is obvious that they cannot be used in this case. The presence of such contradictions requires the personality to resolve the question of their life orientations, which is a mechanism for the development of adaptive capacity of the individual. The corrective component of adaptive inclusive space should help to change the negative concept to the professional self-concept as a result of the interaction of information coming from the internal, subjective world and the external environment, represented primarily by the educational environment of the higher education institution.
Reference Exascale Architecture

While political commitments for building exascale systems have been made, turning these systems into platforms for a wide range of exascale applications faces several technical, organisational and skills-related challenges. The key technical challenges are related to the availability of data. While the first exascale machines are likely to be built within a single site, the input data is in many cases impossible to store within a single site. Alongside handling of extreme-large amount of data, the exascale system has to process data from different sources, support accelerated computing, handle high volume of requests per day, minimize the size of data flows, and be extensible in terms of continuously increasing data as well as increase in parallel requests being sent. These technical challenges are addressed by the general reference exascale architecture. It is divided into three main blocks: virtualization layer, distributed virtual file system, and manager of computing resources. Its main property is modularity which is achieved by containerization at two levels: 1) application containers - containerization of scientific workflows, 2) micro-infrastructure - containerization of extreme-large data service-oriented infrastructure. The paper also presents an instantiation of the reference architecture - the architecture of the PROCESS project (PROviding Computing solutions for ExaScale ChallengeS) and discuss its relation to the reference exascale architecture. The PROCESS architecture has been used as an exascale platform within various exascale pilot applications. This work will present the requirements and the derived architecture as well as the 5 use cases pilots that it made possible.
A Resource Effective Approach for Distributed Machine Learning over a Local Network

Areas of computer science such as data science and machine learning have boomed in recent years due to the increase in the availability of data. This has led to a need in the upsurge of computational power of various systems to handle large datasets consisting of images, text, audios, etc. However, training a machine learning model on a single node system can prove to be a tedious as well as time consuming task. One of the solutions to this problem is distributing the model training process. Some of the current solutions that allow distributed machine learning are limited to multiple GPUs on a single node. This work attempts to propose a system which aims to solve this problem by providing a platform that allows distributing the machine learning process over a local network (using locally available nodes). This will ensure the effective use of all the resources available.
Computer Troubleshooting Expert System Damage Certainty Factor Method Using Web Based

The problems are most common in essence PT.Sinar Blessings Prosperity is still much work to be done manually, as is the case particularly in the logistics department of administration calculations using a single computer, use the computer that is still its own random origin are still common will of computer technology , where if there is damage to require a long time to fix his computer. Therefore, in this study using expert system troubleshooting computer malfunction with the methods certanty factor to help PT. Sinar Inti Sejahtera Blessing in detecting damage to the computer, so as to minimize the company's performance, minimize expenditures on computer repair, thus better able to improve the performance of employees in PT.Sinar Inti Sejahtera Blessing.
Online student feedback analysis system

Online Student Feedback Analysis System is a web based system which collects the feedback from students. The admin should provide username and password for eachstudent. The students are permitted to change their password.Forthe purpose of security, the students who give correct usernameand password are allowed to view their details. There are three types of feedback forms used to get details from the students; they are feedback on subject, feedback on institute and feedback on faculty. After filling and submitting the feedback forms, they can visualize it in graphical form. Once in six months, admin will update the entire details.
Predictive Analytics for Disaster Management

Predictive analytics helps analyze past events to identify and extract patterns and populations vulnerable to natural calamities.Large number of supervised and unsupervised approaches can be used to identify at risk areas and improve predictions of future events.In addition, predictive analytics techniques can also provide insight for understanding the economic and human impact of natural calamities.Heavy rainfall prediction is a major problem for meteorological department and it is closely associated with the economy and human life.Here the natural disasters we will be focusing on are floods and droughts which are encountered by people across the globe every year.One of the leading causes for this is rainfall.Thus, our main focus will be on rainfall prediction with the help of different parameters and how this prediction can further help us .
What is the difference between a person’s natural behavior in life and the behavior of an actor on the stage

An article possesses psychological features and patterns of human behavior in life and on scene.It touches the circle of problems connected with professions of stage director and actor.The article is dedicated to the students and tutors of sportive and art performances departments.
LibGuides: Library Emergency Remote Support: Overview: Emergency Remote Support

Library support and information for Fisher students studying remotely and faculty teaching remotely.
An Enriched Kasumi Encryption Algorithm by Modifying F-functions for 4G LTE

Long Term Evolution (LTE) has become most wide-ranging Fourth Generation (4G) cellular networks for its high speed data rates and advanced features. This new generation network provides more security than previous generation mobile communication system. But this popular and secure telecommunication system is also affected by some cryptanalysis under some cases. Thus it requires strong security algorithms for users and network security purposes. Kasumi is one of the most popular block cipher security algorithms that used F-function composed of FI, FL, and FO subfunctions. The function F is proclaimed as the core of the block ciphers. It creates the relationship between cipher text and encryption key more complex by offering confusion property.In this paper, the components of F-function of KASUMI have been investigated to determine its cryptographic strength and proposed an enhanced Kasumi algorithm by modifying its functionalities. Finally, this paper shows the comparison in performances between original and improved Kasumi algorithms.
Managing Research Data - workshop slides

Slides used in the 'Managing Research Data' workshops offered by the Centre for eResearch, University of Auckland.
An IoT Architecture to Provide Hybrid Context Reasoning

Considering the dynamic nature of the modern computational infrastructures provided by IoT, applications need to be aware of the contextual data that interest them, to be able to operate with as little human intervention as possible. Thus, context awareness becomes a key concept to provide adaptive services in IoT environments. Context reasoning is one of the more critical steps to obtain context awareness. However, a context reasoning strategy that can be applied satisfactorily in different application domains has not yet been found. Because of this, hybrid strategies for context reasoning are gaining prominence. In the literature, some researchers explore hybrid proposals, but these proposals do not offer flexibility on the use of the reasoning strategies. In this research, we conceive hybrid reasoning based on compositional rules, enabling a dynamic composition of different strategies. Thus, the context-aware applications can choose among different reasoning strategies, those that are most appropriate depending on the contexts that will be treated. To validate our architecture, we design and test it on a scenario based on healthcare. The obtained results showed that our architecture allows the utilization of hybrid strategies for context reasoning, improving situations identification, and decision-making.
Bounds on Complexity and Algorithms for Construction of Nondeterministic and Strongly Nondeterministic Decision Trees for Decision Tables

In this chapter, we consider bounds on the minimum complexity, an approach to proof of lower bounds, and algorithms for construction of nondeterministic and strongly nondeterministic decision trees. The bounds on complexity are true for arbitrary complexity functions. The approach to proof of lower bounds assumes that the complexity functions have the property $$\varLambda 2$$. The considered algorithms require complexity functions having properties $$\varLambda 1$$, $$\varLambda 2$$, and $$\varLambda 3$$.
Application of Principle Component Analysis in the Mapping of Hydrothermal Alteration Using Landsat 8 Image in Kokap, Kulon Progo

The presence of gold mineralization in Kokap, Kulon Progo as a result from hydrothermal alteration has been proven by several researchers through geochemical analysis. Alteration mapping with optical remote sensing images in the tropical areas is very difficult, due to atmospheric conditions, dense vegetation cover, and rapid weathering. This study aims to assess the ability of Landsat 8 images in mapping of hydrothermal alteration in Kokap, Kulon Progo with the Principles Component Analysis (PCA) method. Multispectral classification with the maximum likelihood algorithm is then performed to map the alteration types based on PC images and observation data in the field. Two alteration zones were succeeded be mapped; argillic zone and propylitic zone. The success of hydrothermal alteration mapping is then evaluated statistically using confusion matrix. The acceptable level of accuracy is 85% with a kappa coefficient greater than 0.8. The results showed that the best PCA were given by a combination of band ratio images of 5:2 and 6:7 with an accuracy of 56.4% and kappa coefficient of 0.36 which is below acceptance standard. The combination of Landsat 8 with ALOS Palsar DEM succeeded in increasing accuracy to 59.5% with kappa coefficient of 0.4.
Sequence Graphs Realizations and Ambiguity in Language Models

Several language models rely on an assumption modeling each local context as a (potentially oriented) bag of words, and have proven to be very efficient baselines. Sequence graphs are the natural structures encoding their information. However, a sequence graph may have several realizations as a sequence, leading to a degree of ambiguity. In this paper, we study such degree of ambiguity from a combinatorial and computational point of view. In particular, we present theoretical properties of sequence graphs. Several combinatorial problems are presented, depending on three levels of generalisation (window size, graph orientation, and weights), that we characterize with new complexity results. We establish different algorithms, including an integer program and a dynamic programming formulation to respectively recognize a sequence graph and to count the number of its distinct realizations.
Best Ways to Install PostgreSQL

This chapter covers the best ways to install PostgreSQL. It answers the following questions:
Laius: an energy-efficient FPGA CNN accelerator with the support of a fixed-point training framework

With the development of convolutional neural networks (CNNs), their high computational complexity and energy consumption become significant problems. Many CNN inference accelerators are proposed to reduce the consumption. Most of them are based on 32-bit float-point matrix multiplication, where the data precision is over-provisioned. This paper presents Laius, an 8-bit fixed-point LeNet inference engine implemented on FPGA. To achieve low-precision computation and storage, we introduce our fixed-point training framework called FixCaffe. To economise FPGA resources, we proposed a methodology to find the optimal bit-length for weight and bias in LeNet. We use optimisations of pipelining, tiling, and theoretical analysis to improve the performance. Experiment results show that Laius achieves 44.9 Gops throughputs. Moreover, with only 1% accuracy loss, 8-bit Laius largely reduces 31.43% in delay, 87.01% in LUT consumption, 66.50% in BRAM consumption, 65.11% in DSP consumption and 47.95% in power compared to the 32-bit version with the same structure.
Prevention of sexual harassment through the information services using the contextual teaching and learning approach in the senior high school

This article discusses the prevention of sexual harassment through information services using the contextual teaching and learning approach. The research was conducted using quantitative method with experimental approach. This study population of high school students, whose samples were taken using cluster random sampling. Data were collected using a sexual harassment questionnaire as well as data analysis with Wilcoxon signed ranks test and a 't' test. After the research found that information service using contextual teaching and learning approach is effective in preventing teenage sexual abuse in high school. Teenagers from high school do sexual harassment as much as 27.37%. The most sexual abuse conducted by adolescents is verbal sexual abuse as much as 66.66%, visual as much as 62.69% and physical as much as 44.83%.
Support for Research Data Management in university libraries-How far have we come

Advances in computing and technology have triggered a tidal wave of data on a global scale.In this rapidly changing environment, data has become an output in its own right and stepsneed to be taken in order to ensure that data is appropriately managed, stored andpreserved. Ideal Research Data Management practices help to realise the potential of datato enrich knowledge through re-use and re-analysis, as well as provide mechanisms forvalidation and enhance reproducibility. Librarians are well-placed to support researchers tomanage their data optimally. Not only are they well-versed in metadata and findability, theyalso have an important role to play as advocates and balancing voices in a discussion whichis politically, ethically and culturally charged.This lightning talk will summarise research which explored the development of researchsupport services in New Zealand University Libraries via survey responses from all eightUniversities. The survey questions for the Research Data Management section wererepeated from a multi-country carried out in 2012. The sharing of data from the originalsurvey enabled some longitudinal analysis over this time period. Respondents were asked toprovide details on the level of services offered, partnerships with other units, job titles, stafftime, barriers to service development and skills gaps.Among the findings were a strong indication of growth in services, alongside a reduction inperceived barriers and an increase in staff capacity. The results point to a strong future forResearch Data Management support in libraries but also provide some warning as to areasthat require more development and greater level of collaboration. ABOUT THE AUTHOR(S)Jess Howie - I am Researcher Support Librarian at University of Waikato. My areas of interestinclude Research Data Management, scholarly communication, Open Access andresearch impact.
Audit Information System Using Cobit 5

A good SIAKAD is to provide good service to students, therefore it is not necessary to audit the academic information system which is one of the most important supports in a university, the existence of problems in the academic information system is very disturbing, both in service or in performance, as one example of printing KRS that is different from KHS, Sometimes there are differences in values between the values that exist in the system and KHS students, so there is a need for audits, whether from the security system or from user errors or users in running the system.Using Cobit version 5 is expected to be able to correct deficiencies in a system through the use of some parts of the domain in Cobit 5, in Cobit 5 there are several frameworks and Framework used, namely PAM (Process assessment model) with two domain processes, then DSS (Domain Support system) and MEA (Monitoring Evaluation and assess) with nine processes.From the results of audits conducted, measured from the ability level achieved, measurements obtained with the following data are the academic information systems in Mandala reaching 1.33. in other words that the academic information system currently exists at level 1 or Performing, and has a Gap of Capability Level that is expected to have a capability of 1.67.
LibGuides: Remote Library Services: Using Zoom

When you need or prefer to work remotely, there are many ways the Libraries can provide you with expert help and services. Always check the Libraries’ website for the latest information about our hours and services.
SJSU Research Guides: Reading List by Leganto: Student View

Create Reading Lists using Leganto. Leganto integrates electronic articles, streaming media, digitized content, physical materials, and more into a single list so students can access all their course materials in one place. Student View in Leganto
A Recommended Model for User Trust and Item Ratings

As an indispensable means of data filtering, the recommender systems are attracted and created heaps of interest within the past 10 years. The previous recommendation techniques and approaches are wide analysed within the data retrieval analysis communities, machine learning techniques and data processing. Because of their nice industrial demand, the advice systems are with success puzzled out in industrial environments and in business areas, like recommendation of the merchandise at Amazon, recommendation of music at iTunes, recommendation of films at Netflix, and so on. During this paper, we tend to propose a trust-based grid factoring technique for recommendations. TrustSVD arranges distinctive data sources into the advice demonstrate memory actuality objective to decrease the info poorness and chilly begin problems and their dirtiness of proposition execution. In Proposal System used proposal in factor-to-factor proposal And User trust suggestion and an examination of social trust information from four certifiable information sets recommends that the unequivocal and additionally the evident result of the 2 assessments and trust ought to be considered in a very recommendation seem. TrustSVD so develops better of a best in school proposal computation, SVD++ (which uses the categorical and bound result of assessed things), by in addition combining each the unequivocal and understood result of trustworthy and trusting in clients on the will of things for a dynamic customer. In addition, dynamic suggestion area unit occur with the help of high n suggestion calculations the projected framework is that the first to expand SVD++ with social place stock in data.