Reviewerly/exHarmony huggingface dataset:
Human Blood Type Classification by ROI Based Pixel Segmentation and Neural Network

In the modern times digital image processing technology used by the end users has been in the interest as it provides the easy solution to the complicated issues. Like face recognition, image classification etc. We have proposed the concept of blood group type detection using image processing techniques based on the input images. It will be very difficult to detect the type of the blood to any end user. The need of the exact recognition is high in disaster situation where no lab or master people are accessible to distinguish its sort. Hence we have proposed a pixel cluster based analysis of the blood type based on the pixel analysis and Region of interest (ROI) based image segmentation. Later the use of neural network will help to classify the image based on the pixel analysis features. The proposed system results were obtained by using MATLAB. Successful results were obtained and accuracy of the proposed system is most desirable.
A IMPORTÂNCIA DA ASSISTÊNCIA DE ENFERMAGEM NA DOENÇA CELÍACA NO CONTEXTO DA ATENÇÃO PRIMÁRIA

Celiac Disease is an autoimmune condition related to the intolerance of certain individuals to gluten: a protein found in wheat, rye and barley. This descriptive study addresses the importance of nursing professionals in managing patients with celiac disease, especially from the perspective of primary care. The synthesis of the studies gathered in this review highlighted the non-existence of specific pharmacological treatment for celiac patients, as well as postulated the importance of adherence to a gluten-free diet. The nurse, as they represent the first line of contact with the patient, is often the health professional who spends the most time with the patient. Therefore, it is extremely important that the nursing professional act incisively with the celiac patient, transmitting to him the necessary information and care so that he can properly adhere to the gluten-restricted diet.
Deep Learning Network for Prediction of Human Personality by Handwriting Analysis

Personality is a blend of the person's different traits and skills. The detection of such  personal characteristics may be decided on the basis of the person's handwriting characteristics. Writing style can be specific to each entity and can be inferred on the basis of the nature, actions and some psychological characteristics of the person. It is interpreted that several scholars reported on handwriting-based personality and/or behavioural recognition, but most of them were restricted to a range of features. According to handwriting analysis, there may be a broad variety of features of writing stroke that have the personality traits of the author
Fuzzy Curves and System Identification

We introduce “fuzzy curves” and use them to identify significant input variables. Our method is computationally simple and identifies significant input variables easily in complex problems.
META-ANALISIS PENGGUNAAN VIDEO YOUTUBE DALAM PEMBELAJARAN DI ERA NEW NORMAL PADA SISWA SEKOLAH DASAR

The means used as one of the appropriate learning media and helping students learn while learning from home are learning videos via YouTube. Based on the conditions that occurred during the pandemic as well as the study of some of the above theories, the aim of this study was to analyze the use of YouTube videos in elementary school level learning and to find out an increase in learning outcomes and student learning motivation obtained when using YouTube videos in learning. The research used in this research is a type of qualitative research using the meta-analysis method to analyze the relevant research results. The collection of data obtained in this study is done by browsing the journals available in electronic media (internet) that are relevant according to the research title. analysis of the relevant data that has been presented above, it is known that the use of youtube can improve student learning outcomes. Evidenced by the results of the analysis literature reviews with an average value of  83.59.
Planning Algorithms for Robots Operating in Vineyards

Author(s): Thayer, Thomas C. | Advisor(s): Carpin, Stefano | Abstract: Contemporary vineyard management is in dire need of a way to make remote sensing data useful for irrigation purposes on the fine-grain scale. A robot can be used to adjust irrigation emitters within a vineyard, but first requires solving a difficult optimization problem, where a path must be planned that maximizes the cumulative adjustment of water emitters while the path's total length is limited by the battery life of the robot. This is formally called the Orienteering Problem, which is NP-hard. The physical structure of a vineyard constrains movement within it, and the colossal size of some vineyards means that special algorithms are needed to compute efficient solutions. Furthermore, useful extensions to this problem provide additional benefit for real-world vineyards. Solutions to the Team Orienteering Problem, which requires coordinated paths built for multiple agents, can make irrigation management more efficient using a team of robots. The Bi-Objective Orienteering Problem provides robot paths that can perform an additional task while adjusting water emitters, such as soil sampling for moisture content. These problems all assume deterministic movement costs, whereas robots traversing agricultural settings can encounter less desirable field conditions which reduce their speed. The Stochastic Orienteering Problem with Chance Constraints can be used to account for this uncertainty in path planning and provide a bound on the chance of failure. This problem is difficult to solve in large instances such as those encountered with agricultural routing, and therefore ways to speed up computation are needed. This dissertation addresses each of these variations of the Orienteering Problem within the context of vineyards. A special type of model is discussed called an Aisle Graph which represents the structure of a typical vineyard. For the mentioned variations of the Orienteering Problem, heuristic path planners are created which take advantage of this unique arrangement to provide highly economical paths for robots very quickly. Each of the heuristic planners is analyzed on real-world problem simulations constructed with datasets from commercial vineyards located in central California, and shown to be efficient at directing robots to adjust irrigation emitters in fields containing tens of thousands of vines.
Can the Transformer Be Used as a Drop-in Replacement for RNNs in Text-Generating GANs?

In this paper we address the problem of fine-tuned text generation with a limited computational budget.For that, we use a well-performing text generative adversarial network (GAN) architecture -Diversity-Promoting GAN (DPGAN), and attempted a drop-in replacement of the LSTM layer with a self-attention-based Transformer layer in order to leverage their efficiency.The resulting Self-Attention DPGAN (SADPGAN) was evaluated for performance, quality and diversity of generated text and stability.Computational experiments suggested that a transformer architecture is unable to drop-in replace the LSTM layer, under-performing during the pre-training phase and undergoing a complete mode collapse during the GAN tuning phase.Our results suggest that the transformer architecture need to be adapted before it can be used as a replacement for RNNs in text-generating GANs.
On-chip time and frequency modes for the generation and processing of complex photon states

We exploit the time and frequency modes generated on integrated quantum platforms for the practical generation and coherent processing of complex photon states (two-level time-entangled photons, d-level frequency-entangled photon pairs, and d-level cluster states), by using only standard silicon-based chips and fiber telecommunications components.
Portfolio Approach for Optimization the Usage of E-resources

Because of their widespread use in everyday life, Information and Communication Technologies (ICT) are now included in all aspects of teaching activities. The use of various digital tools into the traditional educational process transforms and modifies it. Their efficiency depends on a greater knowledge of them. Although much research has been done on technology-enhanced teaching, there is a need for a current perspective on its influence at the classroom level. The current paper focuses on the analysis and searching for an optimal decision for the effective applying of ICT resources in the field of education. The usefulness and the frequency of using the most popular e-resources in the vocational subjects are compared. A Portfolio approach for optimization the usage of e-resources is proposed and an optimization problem for their optimal utilization is defined and solved.
Research on Network Security Collaborative Defense Technology Based on Swarm Intelligence and Big Data Network Security

Currently, Internet technology and the construction of Internet platforms are undergoing a great deal of development with new technologies being applied to upgrade and optimize the performance of various Internet platforms, which in turn creates a good environment for the development of various network technologies. The evolution of technology for cloud computing and the Internet of Things (IoT), has led to changes in data types and data processing methods. Moreover, the network technologies have generated a great deal of unstructured data, greatly enriching the content of network databases and ushering in the era of big data. The rich resources offered by the big data platform and their potential for resolving problems and improving efficiency, can be used to advantage but only if big data and data fusion processes are well-understood. Much of the research and analysisof the technologies related to big data have been inspired by patterns of behaviour observed in insect communities, which has led to the development and optimization of the swarm intelligence algorithm. This paper examines and analyzes the security issues associated with the Internet platform, proposes a collaborative network security defense mechanism, and provides a reference for the construction of a secure Internet environment.Keywords: swarm intelligence; big data; network security; collaborative defenseCite AsY. Bingjie, Y. Huifeng, S. Chenjun, Z. Zhi, F. Jinghang, Research on Network Security Collaborative Defense Technology Based on Swarm Intelligence and Big Data Network Security, Engineering Intelligent Systems, vol. 29 no. 6, pp. 379-386, 2021.
Self-Supervised Intrinsic Image Decomposition Network Considering Reflectance Consistency

We propose a novel intrinsic image decomposition network considering reflectance consistency. Intrinsic image decomposition aims to decompose an image into illumination-invariant and illumination-variant components, referred to as ``reflectance'' and ``shading,'' respectively. Although there are three consistencies that the reflectance and shading should satisfy, most conventional work does not sufficiently account for consistency with respect to reflectance, owing to the use of a white-illuminant decomposition model and the lack of training images capturing the same objects under various illumination-brightness and -color conditions. For this reason, the three consistencies are considered in the proposed network by using a color-illuminant model and training the network with losses calculated from images taken under various illumination conditions. In addition, the proposed network can be trained in a self-supervised manner because various illumination conditions can easily be simulated. Experimental results show that our network can decompose images into reflectance and shading components.
Market Basket Analysis for Determination of Consumer Behavior at XYZ Stores Using R Programming

Data mining is one of the fields of science in the world of informatics which has an important role, especially with regard to data. There are many algorithms and methods that can be used to process data. The paper this time the author tries to conduct research on consumer behavior by using one of the data mining techniques, namely market basket analysis. This research uses the R Programming tool, where it is hoped that the research can be carried out effectively and efficiently. Based on the research conducted, it is known that there has been a significant purchase of several items that have been described as a plot. The tendency of consumers to buy several items followed by other items can be a consideration for arranging the layout of goods on the sales shelf or arranging product stock in a supermarket.
Real time Health Achieve Management System using Multi Advanced Based Encryption (MA- BE) Algorithm

The uprising of clinical field is improvement secure Personal Health Record (IAR) through the web. Unequivocal Health Record (IAR) is a succeeding record where accomplishment Digital Data and data identified with the chance of a patient is kept by the patient. The IAR proprietor redistributes the IAR to the purged servers for the wide database the board and for the security. The patient achieve ought to be remained mindful of high affirmation and security. The security structures are utilized to shield the individual Digital Data from free. Understanding Digital Data can be recovered by various individuals. Every authority is submitted with locate an enormous pace a specific method of qualities. The way control and security the board is a stunning undertaking in the patient succeeding record the board structure. Digital Data proprietors update the individual Digital Data into cut off cloud server farms. This endeavor proposes a novel patient-driven structure and a suite of Digital Data discover an OK pace control IARs put aside in semi-confided in servers. To accomplish multi level fine-grained and adaptable Digital Data locate a gigantic pace IARs, it use Advanced Based Encryption (ABE) frameworks to encode every patient's IAR record. Various Digital Data proprietors can locate a fundamental pace respects. In this proposed scheme could be extended to Multi Advanced Based Encryption (MA-BE) for multiple way to the access control mechanism.
IMPROVING STUDENTS’ VOCABULARY BY MAKING CLIPPING AS NEWS READER OF FIRST SCIENCE CLASS

Several problems of Vocabulary are found in the first science class in SMAN 2 Pamekasan. The students` felt bored to study and difficult to memorize vocabulary are general problem. To solve the problems an action research was conducted by the researcher and the teacher by using clipping as news reader to develop students` vocabulary. Therefore, the problem of this research is about how the clipping implementation as news reader can develop students’ vocabulary. And the aim was to develop students’ vocabulary in English. Based on the result of test in In the preliminary study there was 21% only who passed, in cycle 1 students get achievement 42% (10 students) who passed the minimum score (KKM, 75), it was increased to the second cycle 92 % (22 Students) who passed the target score (KKM, 75) and there 2 students only who were still failed. So the researcher and teacher decided that the implementation of making clipping as news reader technique can develop students’ vocabulary of first science class in SMAN 2 Pamekasan. Keywords :  Making Clipping, News Reader, Vocabulary, Science Class
THE USE OF “GROW WITH ENGLISH A THEMATIC ENGLISH COURSE FOR ELEMENTARY STUDENT” COURSEBOOK : TEACHER PERCEPTION

Instructional media is an important role for the continuity of the teaching and learning process. There are various types of instructional media that can be used by the teacher. In this opportunity, the researchers conducted the research dealth with the use of coursebook as instructional media in the classroom. This study aims at finding out teacher's perception  toward the use of  English textbooks in elementary school. This study used descriptive qualitative research design. The respondent of this study is an English teacher of elementary school in West Bandung. The researcher used revealed interview, observation, and document analysis in collecting data. The results of this study that the cover of the book is interesting, the content is easy to understand and the many pictures attract students to learn. Keywords :  Teacher Perception, Coursebook
Intriguing Properties of Contrastive Losses

We study three intriguing properties of contrastive learning. First, we generalize the standard contrastive loss to a broader family of losses, and we find that various instantiations of the generalized loss perform similarly under the presence of a multi-layer non-linear projection head. Second, we study if instance-based contrastive learning (with a global image representation) can learn well on images with multiple objects present. We find that meaningful hierarchical local features can be learned despite the fact that these objectives operate on global instance-level features. Finally, we study the phenomenon of feature suppression among competing features shared across augmented views, such as "color distribution" vs "object class". We construct datasets with explicit and controllable competing features, and show that, for contrastive learning, a few bits of easy-to-learn shared features can suppress, and even fully prevent, the learning of other sets of competing features. In scenarios where there are multiple objects in an image, the dominant object would suppress the learning of smaller objects. Existing contrastive learning methods critically rely on data augmentation to favor certain sets of features over others, and could suffer from learning saturation for scenarios where existing augmentations cannot fully address the feature suppression. This poses open challenges to existing contrastive learning techniques.
Pragmatic competence of pre-trained language models through the lens of discourse connectives.

As pre-trained language models (LMs) continue to dominate NLP, it is increasingly important that we understand the depth of language capabilities in these models. In this paper, we target pre-trained LMs’ competence in pragmatics, with a focus on pragmatics relating to discourse connectives. We formulate cloze-style tests using a combination of naturally-occurring data and controlled inputs drawn from psycholinguistics. We focus on testing models’ ability to use pragmatic cues to predict discourse connectives, models’ ability to understand implicatures relating to connectives, and the extent to which models show humanlike preferences regarding temporal dynamics of connectives. We find that although models predict connectives reasonably well in the context of naturally-occurring data, when we control contexts to isolate high-level pragmatic cues, model sensitivity is much lower. Models also do not show substantial humanlike temporal preferences. Overall, the findings suggest that at present, dominant pre-training paradigms do not result in substantial pragmatic competence in our models.
Mutual-Learning Improves End-to-End Speech Translation.

A currently popular research area in end-to-end speech translation is the use of knowledge distillation from a machine translation (MT) task to improve the speech translation (ST) task. However, such scenario obviously only allows one way transfer, which is limited by the performance of the teacher model. Therefore, We hypothesis that the knowledge distillation-based approaches are sub-optimal. In this paper, we propose an alternative–a trainable mutual-learning scenario, where the MT and the ST models are collaboratively trained and are considered as peers, rather than teacher/student. This allows us to improve the performance of end-to-end ST more effectively than with a teacher-student paradigm. As a side benefit, performance of the MT model also improves. Experimental results show that in our mutual-learning scenario, models can effectively utilise the auxiliary information from peer models and achieve compelling results on Must-C dataset.
PELATIHAN PENGGUNAAN PLATFORM E-COMMERCE GUNA MENARIK MINAT SISWA BERWIRAUSAHA (PELATIHAN BAGI SISWA KELAS 3 MA ASWAJ AMBUNTEN)

This training is carried out to provide provisions for students who are in grade 3 MA Aswaj, because they will soon take off their uniforms to take on the next life. Currently the problem faced by students is technological stuttering, there is even a possibility that some of them still cannot turn off the computer, besides that students are millennials who are very close to the Internet but their smartphone usage is not used as a smart phone that should be, their cellphones are only used for non-productive activities such as chatting and playing games, so it becomes necessary to provide them with an understanding of how they should use their cellphones with productive things such as selling online using e-commerce platforms such as Shope, Tokopedia, Whatsapp and Instagram. This training is important considering that they will soon take off their uniforms and will move on to the next stage, namely the world of work, one of them. The training was carried out at the MA Aswaj School located in Ambunten Timur Village, Ambunten District, in the process of implementing the training the participants were very enthusiastic about participating and providing feedback in the form of questions to the presenters. After the material was delivered, the presenters carried out a simulation of selling online using the Shope, Bukalapak, Whatsapp and Instagram applications.
RANCANG BANGUN SISTEM PELAYANAN PENGURUSAN PAJAK PADA KANTOR KONSULTAN PAJAK R. NURSALIM & REKAN BERBASIS WEB

Tax Consultant Office R. Nursalim & Partners is a company that specializes in tax services and consulting. Currently, tax management and consulting services are still carried out face-to-face for registration and at the time of service. Therefore, a Web-Based Tax Management Service Information System was designed at the Tax Consultant Office of R. Nursalim & Partners which is expected to reduce face-to-face meetings. Information System for Web-Based Tax Management Services at the Tax Consultant Office of R. Nursalim & Partners which will be built using the Unified Modeling Language (UML) analysis and design method consisting of Use Case Diagrams, Activity Diagrams and Class Diagrams. Information System for Web-Based Tax Management Services at the Tax Consultant Office of R. Nursalim & Partners using the PHP programming language and using the MySQL database. The method used in designing this information system is the System Development Life Cycle (SDLC) method. The designed information system can be used by companies and clients in tax management services.
ANALISIS DAN PERANCANGAN SISTEM INFORMASI PURCHASING DI HOTEL HARRIS BATAM

Purchasing Department is one of the basic functions of a hotel. Harris Hotel Batam is a four-star hotel in Riau Islands Province. It is strategically located in the city center around the area of the shopping center, government center and adjacent to the international port. Purchasing is very important to run really - really. The method used in this thesis is descriptive. Harris Hotel Batam as an object in this research. Primary data were obtained from the documents contained in the purchasing department. Moreover, interviews done to the person concerned and direct observation. Assessment is done through a qualitative approach, by analyzing purchasing information systems, each department procurement process, inventory and manufacturing of inventory report still without using a computerized system. Because of the scope of the purchase is not only limited to how management successfully implement a mechanism for the procurement of goods in a timely manner and in accordance with the target. Things that should be considered such as the number and quality of the goods, while the price and time of delivery is the most important key in making a purchase. Besides, the results of the study concluded that with the analysis and design of information systems purchasing can provide input and guidance to increase the use of information systems to aid the efficiency of work on the part of purchasing at the Harris Hotel Batam.