Reviewerly/exHarmony huggingface dataset:
Bornon: Bengali Image Captioning with Transformer-based Deep learning approach

Image captioning using Encoder-Decoder based approach where CNN is used as the Encoder and sequence generator like RNN as Decoder has proven to be very effective. However, this method has a drawback that is sequence needs to be processed in order. To overcome this drawback some researcher has utilized the Transformer model to generate captions from images using English datasets. However, none of them generated captions in Bengali using the transformer model. As a result, we utilized three different Bengali datasets to generate Bengali captions from images using the Transformer model. Additionally, we compared the performance of the transformer-based model with a visual attention-based Encoder-Decoder approach. Finally, we compared the result of the transformer-based model with other models that employed different Bengali image captioning datasets.
Grounded Human-Object Interaction Hotspots from Video (Extended Abstract)

Learning how to interact with objects is an important step towards embodied visual intelligence, but existing techniques suffer from heavy supervision or sensing requirements. We propose an approach to learn human-object interaction "hotspots" directly from video. Rather than treat affordances as a manually supervised semantic segmentation task, our approach learns about interactions by watching videos of real human behavior and anticipating afforded actions. Given a novel image or video, our model infers a spatial hotspot map indicating how an object would be manipulated in a potential interaction, even if the object is currently at rest. Through results with both first and third person video, we show the value of grounding affordances in real human-object interactions. Not only are our weakly supervised hotspots competitive with strongly supervised affordance methods, but they can also anticipate object interaction for novel object categories. Project page: http://vision.cs.utexas.edu/projects/interaction-hotspots/
Building Bridges: Implementing Redundancy Analysis by means of a Neural Network

When analyzing data, there are situations where it is convenient to divide the analyzed variables into two subsets: a X block, of range p, that plays an independent or predictor role and a Y block, of range q, whose role is dependent, each of them containing the measurements of n individuals. However, knowing a priori which one is independent and which one is dependent is not trivial. The Redundancy Analysis was developed by van den Wollenberg (1977) as a particular case of CCA (Hotelling, 1936). Given two standarized data sets X (orthogonalizable) and Y, it consists in determining a set of orthonormal redundant components wi (i = 1, ..., min(p,q)) such that the squared correlation of each of the redundant variables Xwi with all the Y variates (Eq. 1) is maximized subject to unitary variance of the redundant variable. Thus, the Redundancy Index (RI) of X over Y, proposed by Stewart and Love (1968), is maximized (Eq. 2). Such index is an asymmetrical measurement for the amount of explanation one set has over the other. By comparing Rx and Ry, it can be determined which set of variables is explanatory and which one is the response.
A Multi-objective Cluster-based Biased Random-Key Genetic Algorithm with Online Parameter Control Applied to Protein Structure Prediction

The protein structure prediction problem is one of the most important bioinformatics problems.Computational methods can be used to approach this problem and de novo methods are able to generate protein structures without the need of having known similar structures to the predicted protein.These methods transform the prediction problem into an optimization problem, using optimization models that combine different energy functions and high-level information.These models usually have only a single optimization objective.However, it is known that this single objective optimization approach may harm the optimization search due to the existence of conflicts between the different terms that compose the optimization objective.The proposed model has three objectives: energy function, secondary structure, and contact maps.A multi-objective Biased Random-Key Genetic Algorithm (BRKGA) with online parameter control, named MOBO, is proposed as the optimizer.The final predictor comprises two phases of the MOBO algorithm and selects a final structure using the MUFOLD-CL clustering method.Results obtained demonstrated that the proposed predictor generated highly competitive results with the literature.
Universal Key to Authentication Authority with Human-Computable OTP Generator

The subject of this paper is an enhanced alternative to the Multi-Factor Authentication (MFA) methods.The improvement lies in the elimination of any supplementary gadgets/devices or theft-sensitive biometric data, by substituting it with direct human-computer authentication optionally supplemented by cognitive biometric.This approach remains secure also in untrusted systems or environments.It allows only one secret as a universal private key for all obtainable online accounts.However, the features of this new solution pretend it to be used by the Authentication Authority with the Single-Sign-On (SSO) method of identity and access management, rather than for individual services.This secret key is used by our innovative challengeresponse protocol for human-generated One-Time Passwords (OTP) based on a hard lattice problem with noise introduced by our new method which we call Learning with Options (LWO).This secret has the form of an outline like a kind of handwritten autograph, designed in invisible ink.The password generation process requires following such an invisible contour, similar to a manual autograph, and it can also be done offline on paper documents with an acceptable level of security and usability meeting the requirements for post-quantum symmetric cyphers and commercial implementation also in the field of IoT.
Encrypting JPEG-compressed images by substituting Huffman code words

This paper presents a method for encrypting JPEGcoded images that preserves both compression ratio and format of a bit stream.Such solutions allow for selectively hiding information: image contents can be encrypted, while in-file metadata remain readable.Our algorithm is a symmetric, polygram substitution cipher, as it replaces Huffman code words and rearranges value bits that describe the main results of the Discrete Cosine Transform (DCT) of a pixel block: the DC coefficient and the first non-zero AC coefficient.Both length and format of a file are preserved, because bits are modified under constraints on their numbers.Such encryption is a kind of post-processing of a compressed bit stream, and thus it can be built on the top of an existing JPEG codec, without accessing its internals.Compared to previous similar solutions, our approach better hides image contours, exchanging AC for DC energy.Our work also reveals some properties of Huffman code tables and bit streams related to the JPEG standard.
Improving Re-rankCCP with Rules Quality Measures

Recommender Systems are software tools and techniques which aim at suggesting new items that may possibly be of interest to a user.Context-Aware Recommender Systems exploit contextual information to provide more adequate recommendations.In this paper we described a modification of an existing contextual post-filtering algorithm which uses rules-like user representation called Contextual Conditional Preferences.We extended the algorithm by taking into account rules quality measures while recommending items to a user.We proved that this modification increases the quality of recommendations, measured with precision, recall and nDCG, and has no impact on the execution time of the original algorithm.
Subcaterpillar Isomorphism: Subtree Isomorphism Restricted Pattern Trees To Caterpillars

In this paper, we investigate a subcaterpillar isomorphism that is a problem, for a rooted labeled caterpillar P and a rooted labeled tree T , of determining whether or not there exists a subtree in T which is isomorphic to P .Then, we design two algorithms to solve the subcaterpillar isomorphism for a caterpillar P and a tree T in (i) O(p + tDhσ) time and O(Dh) space and in (ii) O(p + tDσ) time and O(D(h + H)) space, respectively.Here, p is the number of vertices in P , t is the number of vertices in T , h is the height of P , H is the height of T , σ is the number of alphabets for labels and D is the degree of T .Furthermore, we give experimental results of the two algorithms for artificial data and real data.
Unggul dan Bepretasi

The library is the most important part of an institution because the library is very far from the ancient system with now, so the use of this library is very urgent in the world of education in general and in the world of students in particular. With a library system that is used in a professional way, superior and outstanding students will be formed. This study focuses on how the model of student empowerment in reading, library management in increasing reading interest, supporting and inhibiting factors of library management in increasing students' interest in reading at MTs Salafiyah Syafi'iyah Bandung Diwek Jombang. This research is qualitative research. While the data collection techniques using observation, interviews, and documentation. The data analysis technique uses data reduction, data display, and data verification. The model of empowering students in reading at MTs Salafiyah Syafi'iyah Diwek Jombang can be simulated with several points, namely programming for reading, motivating, and coaching the reader. In the management of the library at MTs Salafiyah Syafi'iyah Diwek Jombang there are several things that are carried out as functions of management, namely planning, organizing, implementing, and supervising. The inhibiting factor for library management in increasing students' reading interest is that it can be influenced by several factors, namely management management is still not carried out optimally, collections of books or library materials have not been maximized, human resources or librarian staff, and facilities and infrastructure.
Applying SoftTriple Loss for Supervised Language Model Fine Tuning

We introduce a new loss function based on cross entropy and SoftTriple loss, TripleEntropy, to improve classification performance for fine-tuning general knowledge pre-trained language models.This loss function can improve the robust RoBERTa baseline model fine-tuned with cross-entropy loss by about 0.02-2.29 percentage points.Thorough tests on popular datasets using our loss function indicate a steady gain.The fewer samples in the training dataset, the higher gain-thus, for smallsized dataset, it is about 0.71 percentage points, for mediumsized-0.86 percentage points, for large-0.20 percentage points, and for extra-large 0.04 percentage points.
Insights into Neural Architectures for Learning Numerical Concepts from Simple Visual Data

The paper reports some results on neural architectures for learning numerical concepts from visual data.We use datasets of small images with single-pixel dots (one to six per image) to learn the abstraction of small integers, and other numerical concepts (e.g. even versus odd numbers).Both fully-connected and convolutional architectures are investigated.The obtained results indicate that two categories of numerical properties apparently exist (in the context of discussed problems).In the first category, the properties can be learned without acquiring the counting skills, e.g. the notion of small, medium and large numbers.In the second category, explicit learning of counting is embedded into the architecture so that the concepts are learned from numbers rather than directly from visual data.In general, we find that CNN architectures (if properly crafted) are more efficient in the discussed problems and (additionally) come with more plausible explainability.
Special Issue on NIED Frontier Research on Science and Technology for Disaster Risk Reduction and Resilience 2022

We are very pleased to publish this special issue, dedicated to NIED Frontier Research on Science and Technology for Disaster Risk Reduction and Resilience 2022. There are four papers, two reviews, and one note in this issue. In the last year of the NIED’s fourth mid/long term plan period, which began in 2016, natural disasters have occurred every year, including earthquake disasters such as the 2016 Kumamoto earthquake (M7.3) and the 2018 Iburi, Hokkaido earthquake (M7.1). Rainfall disasters include the heavy rainfall in northern Kyushu in July 2017, southwestern Japan in July 2018, northern Kyushu in August 2019, Kanto and Tohoku in October 2019, and Kyushu in July 2020. In the summer of 2022, the heavy rainfall and extreme weather continued over Japan. The first three papers and one note contain hazard and risk information. Dohi et al. present the development of Japan Tsunami Hazard Information Station (J-THIS), Cui et al. present a study of the estimation of damage based on analysis of SNS Information, Nakamura provides avalanche risk information, and Ise et al. note information linkage by the Shared Information Platform for Disaster Management (SIP4D). Horiuchi et al. review the contribution of the E-Defence shaking table. This special issue also includes two social science works. Nagata et al. present tsunami disaster risk reduction education programs, and Yamazaki-Honda reviews promoting coherence among disaster risk reduction, climate change adaptation, and sustainable development for disaster resilience. In the first half of the 21st century, a mega disaster such as the Nankai Trough earthquake is expected to occur. Extreme climatic events are also becoming more frequent: typhoons, floods, heavy rains and snows, landslides, and heat waves. We hope this issue provides information useful to all readers who study natural disasters.
IMPLEMENTASI BALANCE SCORE CARD PERSPEKTIF PENJAMINAN MUTU PENDIDIKAN ISLAM

Abstract The orientation of this article is to investigate and examine more deeply the meaning of the balance score card, aspects of the balance score card and its implementation in the perspective of quality assurance of Islamic education. In this paper, the author tries to analyze more deeply and systematically in implementing new management strategies that can encourage quality improvement in institutions by using a balanced score card approach based on Islamic principles. The type of research in this article uses a library research approach in which data collection techniques are obtained from various primary references and secondary data which are then reduced and keyed. Research results: (1). Application of Balance Score Card in Islamic Education Quality that is balanced both financially (profit) and non-financially (non-profit), (2). Standardization of Performance Measures from the Perspective of the Balance Score Card (in terms of finance, customers, internal business processes and learning and growth). With a comprehensive performance measurement that does not only measure financial but combines financial and non-financial measures, educational institutions can carry out better organizational performance. Keywords: Balance Score Card; Quality Assurance; Islamic Education. Abstrak Orientasi artikel ini untuk menyelisik dan menelaah lebih dalam makna balance score card, aspek balance score card dan implementasinya dalam perspektif penjaminan mutu Pendidikan Islam. Dalam tulisan ini penulis mencoba menganalisis lebih dalam serta sistematis dalam menerapkan strategi manajemen baru yang dapat mendorong peningkatan mutu di lembaga dengan menggunakan pendekatan balance score card disandari dengan prinsip-prinsip Islam. Jenis penelitian dalam artikel ini menggunakan pendekatan Library research yang mana teknik pengumpumlan data diperoleh dari pelbagai referensi primer dan sekunder yang kemudian data direduksi dan disimpulkan. Hasil penelitian: (1). Penerapan Balance Score Card dalam Mutu Pendidikan Islam yang secara seimbang baik secara financial (profit) dan non-financial (non-profit), (2). Standarisasi Ukuran Keberhasilan Kinerja Perspektif Balance Score Card (dalam aspek keuangan, pelanggan, proses bisnis internal dan pembelajaran dan pertumbuhan). Dengan pengukuran kinerja yang komprehensif tidak hanya mengukur keuangan tetapi menggabungkan ukuran keuangan dan non-keuangan, lembaga pendidikan dapat menjalankan kinerja organisasi yang lebih baik. Kata Kunci: Balance Score Card; Penjaminan Mutu; Pendidikan Islam.
Development of Web Service and Telegram Bot for Location-Based Health Service Information System

In the era of technological advances and the current era, the city of Sidoarjo is known as an industrial city and is also known as a densely populated city because many immigrants seek work in Sidoarjo City. The Sidoarjo City Government also pays attention to the health level of its people, to promote better health services, a forum or media is needed to obtain information on the location of health services in Sidoarjo City, therefore the people of Sidoarjo need a location-based health service information system application. The existence of the covid-19 pandemic is also an impetus for writers to develop web services and telegram bots which will later be used as tools to search for health care places. The development uses the webhook method which is used to design the telegram bot and performs system testing using BlackBox testing. The development of this web service is used for hospital and polyclinic data processing where the data format used is JSON and uses the Python programming language and the Flask Restful framework, which later utilizes the API using the telegram bot as a data source, and the function of the telegram bot as a data search tool. hospitals and polyclinics were developed using the botogram module and the python programming language. After developing and testing the web service system and the telegram bot can be used as originally planned and can help find health service places and their locations, where the web service is used for processing hospital and poly data while the telegram bot can be used to search for hospital and poly data.
Women’s speech, a call for economic empowerment: An appraisal analysis

The phenomenon of women participation in entrepreneurship sector is rising significantly during the last decade. In reality, women still face many barriers in entrepreneurship both professionally and personally. In 29 August 2019, Najwa Shihab delivered an inspiring keynote speech in Global Conference on Women and Entrepreneurship held by Alibaba and Lazada in Jakarta. Since Najwa Shihab's speech got many responses from the audiences, it is highly considerable to investigate the content of the speech from a linguistic point of view. This study aimed at analyzing the spoken text from Najwa Shihab’s speech through Critical Discourse Analysis (CDA). For specific investigation, Appraisal framework was used in this study. The study focused on the attitude which relates to the feelings, emotion, reactions, and judgments of behaviour on Najwa Shihab’s speech about women and entrepreneurship. The design of the study was descriptive qualitative. The findings showed that the speech used 55 clauses which consisted of 27 clauses of affect (49%), 18 clauses of judgment (33%), and 10 clauses of appreciation (18%). All clause-complexes had attitudes. The use of affect dominated the percentage of attitudes. Furthermore, this speech also encouraged women to do 3 things: dare to change the paradigm of clichés and stereotypes into strength, dare to take a role in the national and global economy to ensure that women's voices and perspectives are present in every discussion and decision making, and support each other and bring the community that can empower other women.
Network methodology of smart education

The article attempts to systematically comprehend the changes that the new era of smart education entails. The analytical basis of the study was the theoretical work and publications of Russian and foreign scientists describing the experience of intro-ducing certain elements of smart education into practice. During the analysis, the principles of network methodology were identified and its theoretical and practical aspects in smart education were revealed. The theoretical aspect is based on the work of scientists in the field of communication theory. The principles of network method-ology include the presence of social networks and network graphs (network models). The practical aspects of the network methodology are revealed through the transfor-mation of traditional practices in the field of education: educational environment, curriculum, academic discipline, electronic interactive textbook, forms and methods for monitoring learning outcomes, a virtual classroom. In the conclusion, the authors provide some characteristic features of the transfor-mation of the education system: non-linear networking, standardization and hierarchy of goals and content, the presence of a large database.
Biostratigraphy of the Late Cretaceous-Early Paleocene Succession in Selected Wells, Jambur Oil field, Kirkuk, Northern Iraq

The Late Cretaceous-Early Paleocene Shiranish and Aliji formations have been studied in three selected wells in Jambur Oil Field (Ja-50, Ja-53, and Ja-67) in Kirkuk, Northeastern Iraq. This study included lithostratigraphy and biostratigraphy. The Late Campanian-Maastrichtian Shiranish Formation consist mainly of thin marly and chalky limestone beds overlain by thin marl beds, with some beds of marly limestone representing an outer shelf basinal environment, the unconformable contact with the above Middle Paleocene-Early Eocene Aliji Formation contain layers of limestone with marly limestone and chalky limestone which represents an outer shelf basinal environment. Five Biozones in the Shiranish Formation were determined which are: 1.Globotruncanita calcarata Range Zone (part). 2.Globotruncanella havanensis Partial Range Zone. 3.Globotruncana aegyptiaca Interval Zone. 4.Gansserina gansseri Interval Zone (Part). 5.Abathomphalus mayaroensis Range Zone. While in Aliji Formation there were two biozones determined which are: 1.Guembelitria Cretacea Partial-Range Zone. 2.Parvularugoglobigerina eugubina Total-Range Zone.
PERANCANGAN UI/UX APLIKASI DAFTAR ACARA SIARAN (DAS) LPP RRI PURWOKERTO MENGGUNAKAN FIGMA

Radio Republik Indonesia (RRI) is a radio whose broadcasts are intended for the benefit of the nation and state. In carrying out work management, the Public Broadcasting Institution (LPP) RRI Purwokerto can still be said to be not optimal enough, where the preparation and management of reports is still done manually. This causes employees in the planning and broadcaster divisions to experience difficulties when compiling a list of broadcast events. Therefore, the right solution is needed to overcome these problems, namely by designing the User Interface (UI) and User Experience (UX) of the broadcast program list application. The method used in the preparation of this research is design thinking and the use of the Figma application for UI design. The results of this study aim to provide a UI/UX design for the broadcast event list application so that it can help the preparation and management process to be faster, more efficient, and user friendly.