Reviewerly/exHarmony huggingface dataset:
Development of marker-based augmented reality system for object detection in an optimum latency time

Augmented reality is an emerging technique to monitor real-time environment to take a decision based on the collected data. With the advancement in the concept of augmented reality and rapid development of robots, there is a need to develop a system or a method to reduce the latency in the most challenging conditions. Although, now some applications are using marker less augmented reality technique due to complications in object detection and tracking in Boston dynamics (robotics) and real-time application we relied on fiducial marker based system. This paper mainly proposes an AR system which explains a guideline to detect the fiducial marker by an object (unidirectional movement) at minimum latency time. In this experiment, fiducial marker detection and position orientation with respect to the camera has been processed by 'Aforge.NET Framework' in combination with C# language and pose estimation. We designed machine marker detection algorithm and mathematics equation which compute the latency time in different challenging conditions lux, distance frame per second of camera in an optimum latency time.
Region Based Cryptography A Study of Difference Between the .jpg Image and .png Image After Recombined RGB Images

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Detecting New Word Meanings: A Comparison of Word Embedding Models in Spanish

Semantic neologisms (SN) are defined as words that acquire a new word meaning while maintaining their form. Given the nature of this kind of neologisms, the task of identifying these new word meanings is currently performed manually by specialists at observatories of neology. To detect SN in a semi-automatic way, we developed a system that implements a combination of the following strategies: topic modeling, keyword extraction, and word sense disambiguation. The role of topic modeling is to detect the themes that are treated in the input text. Themes within a text give clues about the particular meaning of the words that are used, for example: viral has one meaning in the context of computer science (CS) and another when talking about health. To extract keywords, we used TextRank with POS tag filtering. With this method, we can obtain relevant words that are already part of the Spanish lexicon. We use a deep learning model to determine if a given keyword could have a new meaning. Embeddings that are different from all the known meanings (or topics) indicate that a word might be a valid SN candidate. In this study, we examine the following word embedding models: Word2Vec, Sense2Vec, and FastText. The models were trained with equivalent parameters using Wikipedia in Spanish as corpora. Then we used a list of words and their concordances (obtained from our database of neologisms) to show the different embeddings that each model yields. Finally, we present a comparison of these outcomes with the concordances of each word to show how we can determine if a word could be a valid candidate for SN.
Weighted HRW and its applications

Rendezvous Hashing also known as Highest Random Weight (HRW) has beenused in many load balancing applications where the central problem ishow to map an object to as server such that the mapping is uniform andalso minimally affected by the change in the server set. Recently, ithas found use in DF election algorithms in the EVPN context and loadbalancing using DMZ. This draft deals with the problem of achievingload balancing with minimal disruption when the servers have differentweights. It provides an algorithm to do so and also describes a fewuse-case scenarios where this algorithmic technique can apply.
Sources of Information on Reproductive Health among Teenage Girls in Kaptembwo, Nakuru County, Kenya

The study aimed at establishing the sources of information on reproductive health among teenage girls in Kaptembwo, Nakuru County, Kenya. Data was collected from a sample of 127 teenage girls aged between 13-19. Purposive sampling technique was used. The results obtained from Kaptembwo showed that, five (5) different sources were identified as the ones that provide the teenagers in Kaptembwo with reproductive health information. Majority of the teenage girls reported that they received their information on reproductive health from their peers. The study concludes that sources have been found to be interacting with access and use of reproductive health information among teenage girls. Some information sources get more used than others depending on reliability in providing potential reproductive health information. The preferred source for information depends on the type of information to be delivered, the overriding principle being the source must be authoritative in that type of information.
초등학교 교사의 ‘읽기 부진아’ 지도와 연수 경험에 대한 조사 연구

This study investigated the concept of reading underachievers as perceived by elementary school teachers along with their thoughts about their teaching status in South Korea. The research was conducted with approximately 100 incumbent elementary school teachers in order to investigate their ideas concerning their status and their tendencies and perception regarding reading underachiever teaching in school. An online survey, that used Google Drive, was conducted for the week of July 20th to 25th, 2018. In this study elementary school teachers indicated that the most important underachievement of their students was basic reading and writing. They perceived reading poor children were those who could not read loudly, those who had poor vocabulary, those students who lacked in reading ability to check facts, or those who did not read to find meaning. They found that there were one to two poor readers in their classes. More than 80% of the teachers volunteered to teach the reading underachievers who had been detected in their classrooms. However, only 40 (41.2%) of the respondents had participated in vocational training. The results of this study indicate that appropriate support has not been provided to teachers who directly deal with reading poor children. And the teachers failed to name the reading diagnostic tools correctly, and it can be presumed that they had poor information or knowledge about them. This research concluded that educational circles should not spare multilateral support so that teachers become self-confident and are able to make the correct judgments regarding learners' reading problems, choose a method most appropriate for the learners' characteristics, and apply it effectively.
E2E Authentication in XMPP: Certificate Issuance and Revocation

This specification defines a way for a certificate authority to serve certificate signing requests via XMPP in order to issue X.509 certificates for the use in end-to-end and c2s SASL EXTERNAL authentication.
CsSyllabusLOR Computer Science Syllabus Learning Object Repository

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
PERANCANGAN SISTEM PAKAR DETEKSI PERTUMBUHAN TANAMAN SEMANGKA BERBASIS WEBSITE DENGAN CERTAINTY FACTOR

Expert system is a computer system that resembles the ability in making decisions of an expert and is part of artificial intelligence, hence with it to detect the growth of watermelon plants not everyone can know the growth of watermelon plants without an expert. The purpose of making these systems and applications to design and build Expert System for Watermelon Plant Growth Based Detection that uses certainty factor for use by farmers and the community to know the growth of watermelon plants without having to ask directly to expert experts, which can be said that the calculation of certainty factor on the characteristics of watermelon disease has a confidence level of 99.70%, because in this case Certainty Factor commonly used for decision making in the face of uncertainty of an event. This app is designed by beginning with SDLC and use case.
Electronic Prose Literary Text: Generative Algorithms And Formal Limitations

Thearticlerevealsthekeyaspectsrelatingtothe influence done by the formallimitationsliterature and some DADA techniques on the modern electronic prose literary texts. The basic types of the formal limitations, which were used in the combinatorial literature of the mid-XX century, can be easily integrated into an electronic literary discourse. The material for this research is the texts in English and in Russian introduced through and with different technologies and platforms. The research presents the general scientific methods of observation and description in combination with the method of a comparative analysis considering the language material and a complex linguistic text analysis, including a lingua-stylistic analysis. During analysis, it has been found that the most part of the electronic generative literary texts are technically improved samples of the formal limitations. However, the electronic environment gives to them the ambivalent status. Despite the fact that a surface level of poetic text has an open structure and arbitrary nature of linking components, an internal structure of each electronic sample text is predetermined. In each electronic literary generative text, there is a complex set of algorithmic limits whose final number leads to organizing a verbal level of a literary work. The basic marker, highlighting OULIPO (Ouvroir de literature potentielle) combinatorial technique, influences electronic literature, shows the rapid increase of texting data volume involved into the programmed generator work that is attributed to the use of artificial intelligence.
A new recommendation method for pertinent collaborative learners based on their intelligence and a fuzzy measure

This paper considers learners' intelligence as an influencing factor for collaborative learning. We propose a novel recommendation approach for pertinent collaborative learners. This approach is based on the learners' collaboration according to the multiple and triarchic intelligence theories. Our contribution is mainly a two-fold proposition: (1) We adopt the conceptual model of learners' intelligence, that we have proposed in other paper, and which we enhance by adding multiple intelligence and triarchic intelligence as sub-classes of the 'intelligence' class. (2) We adopt a process that aims at (a) acquiring knowledge of an individual learner's intelligence according to the multiple and triarchic intelligence theories, (b) recommending pertinent collaborators using a mathematical aggregation operator that relies on a fuzzy measure that facilitates consideration of the importance of each criterion as well as its interaction with others. An illustrative example shows the effect of this interaction.
PERSONALITY VALUE QUALITIES OF AN IDEAL HIGHER EDUCATION TEACHER

The paper analyses the results of the survey, conducted by the scientists among the students of foreign and Ukrainian higher education institutions, and our own scientific researches on the personality value qualities of an ideal higher education teacher. It has been defined that students of foreign higher education institutions focus on the following personality value qualities of an ideal higher education teacher: the first position is taken by expertise in the relevant field, communication skills; the second is taken by teaching tact, intelligence, empathy, emotional stability, openness; the third is occupied by self-awareness, tolerance, knowledge of behavioural strategies, creativity, and ability to build relationships with students. At the same time, the negative characteristics that a higher education teacher should not have are revealed, namely: in the first position students point out bias and injustice and the following positions are taken by arrogance; illiteracy; unprofessionalism; pride; condescension, vanity, etc.&#x0D; The analysis of the researches of the Ukrainian scientists demonstrates the following personality value qualities of an ideal higher education teacher, which are identified in the descending sequence: high intelligence; in-depth knowledge of the discipline, mastery of teaching methodology, teaching tact, communication skills; fairness, creativity, attentiveness, sense of humour and benevolence; moral rectitude, organizational skills, emotional and volitional stability; adherence to principles, exactingness, politeness and responsibility.&#x0D; In this paper we present our own survey among the students of the Ukrainian higher education institutions and introduce the following personality value qualities of an ideal higher education teacher in the descending order: moral; communication; mastery of teaching methodology of the discipline; intelligence, expertise in the relevant field and in-depth professional knowledge; organizational and volitional qualities.
A Fast Iterative Method for Removing Impulsive Noise from Sparse Signals

In this paper, we propose a new method to reconstruct a signal corrupted by noise where both signal and noise are sparse but in different domains. The problem investigated in this paper arises in different applications such as impulsive noise removal from images, audios and videos, decomposition of low-rank and sparse components of matrices, and separation of texts from images. First, we provide a cost function for our problem and then present an iterative method to find its local minimum. The analysis of the algorithm is also provided. As an application of this problem, we apply our algorithm for impulsive noise Salt-and-Pepper noise (SPN) and Random-Valued Impulsive Noise (RVIN)) removal from images and compare our results with other notable algorithms in the literature. Furthermore, we apply our algorithm for removing clicks from audio signals. Simulation results show that our algorithms is simple and fast, and it outperforms other state-of-the-art methods in terms of reconstruction quality and/or complexity.
BCMA-ES II: revisiting Bayesian CMA-ES

This paper revisits the Bayesian CMA-ES and provides updates for normal Wishart. It emphasizes the difference between a normal and normal inverse Wishart prior. After some computation, we prove that the only difference relies surprisingly in the expected covariance. We prove that the expected covariance should be lower in the normal Wishart prior model because of the convexity of the inverse. We present a mixture model that generalizes both normal Wishart and normal inverse Wishart model. We finally present various numerical experiments to compare both methods as well as the generalized method.
Blind Image Steganalysis A Review

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Concise Binary Object Representation (CBOR) Tag for Coordinate Reference System (CRS) Specification

The Concise Binary Object Representation (CBOR, RFC 7049) is a dataformat whose design goals include the possibility of extremely smallcode size, fairly small message size, and extensibility without theneed for version negotiation. In CBOR, one point of extensibility isthe definition of CBOR tags. An existing CBOR tag, 103, allows for therepresentation of geographic coordinates. Proper exploitation ofgeographic coordinates requires an associated reference frame. Thepresent document defines a CBOR tag for referencing the coordinatereference system (CRS) for a geographic coordinate. It is intended asthe reference document for the IANA registration of the CBOR tagdefined.
LegoSNARK: Modular Design and Composition of Succinct Zero-Knowledge Proofs.

We study the problem of building non-interactive proof systems modularly by linking small specialized SNARKs in a lightweight manner. Our motivation is both theoretical and practical. On the theoretical side, modular SNARK designs would be flexible and reusable. Also, previous works (e.g., Geppetto) consider They have been successfully employed in previous works.(cite prev papers ). These approaches, however, tend to be ad-hoc and to reinventing the wheel. We propose to fill this gap. In practice, specialized SNARKs have the potential to be more efficient than general-purpose schemes, on which most existing works have focused. If a computation naturally presents different components (e.g. one arithmetic circuit and one boolean circuit), a general-purpose scheme would homogenize them to a single representation with a subsequent cost in performance. Through a modular approach one could instead exploit the nuances of a computation and choose the best gadget for each component. Our contribution is LegoSNARK, a toolbox (or framework) for commit-and-prove zkSNARKs (CP-SNARKs) that includes: 1) General composition tools: build new CP-SNARKs from proof gadgets for basic relationssimply. Formalize notion of cc-SNARK. 2) A lifting tool: a compiler to add commit-and-prove capabilities to a broad class of existing zkSNARKsefficiently. This makes them interoperable (linkable) within the same computation. For example, one QAP-based scheme can be used prove one component; another GKR-based scheme can be used to prove another. 3) A collection of succinct proof gadgets for a variety of relations. Additionally, through our framework and gadgets, we are able to obtain new succinct proof systems. Notably: -- LegoGro16, a commit-and-prove version of Groth16 zkSNARK, that operates over data committed with a classical Pedersen vector commitment, and that achieves a 5000× speedup in proving time. -- LegoUAC, a pairing-based SNARK for arithmetic circuits that has a universal, circuit-independent, CRS, and proving time linear in the number of circuit gates (vs. the recent scheme of Groth et al. (CRYPTO'18) with quadratic CRS and quasilinear proving time). -- LegoMM, a CP-SNARK for matrix multiplication that achieves optimal proving complexity.
Crisis of the human and the responsibilities of art/education

In the twenty-first century, we are experiencing a new round of acceleration in the Anthropocene. On all fronts, art and education are facing new challenges and chances. On the one hand, the technological and media developments have compelled art, design, and knowledge production to change, whereas the internet, big data, and artificial intelligence have brought about a revolution in education and learning. As a consequence, the ideas of art education and the form of the university are also remodeled. On the other hand, the reverse side of this technological optimism is the proletarianization of sensibility resulted from digitalized, intelligent, and automated technologies, as the motivations for art are depleted and replaced by the conveniences provided by the big data and artificial intelligence. How to find the force to reverse this trend? And how to locate “another register of the dialectic” – beyond that of the technologization of nature and the naturalization of technology, and of the technologicalization of humans and the humanization of technology – has become the fundamental mandate of art and education in the twenty-first century.
A Survey in Deep Learning Model for Image Annotation

Image annotation is generating the human-understandable natural language sentence for images. Annotating the image with sentence is one kind of the computer vision process that includes in the artificial intelligence. Annotation is working by combining computer vision and natural language processing. In image annotation, there are two types: sentence based annotation and single word annotation. Deep learning can get the more accurate sentence for the image. This paper is the survey for image annotation that applied the deep learning model. This discusses existing methods, technical difficulty, popular datasets, evaluation metrics that mostly used for image annotation.