Reviewerly/exHarmony huggingface dataset:
Exploring Long Tail Visual Relationship Recognition With Large Vocabulary

Several approaches have been proposed in recent literature to alleviate the long-tail problem, mainly in object classification tasks. In this paper, we make the first large-scale study concerning the task of Long-Tail Visual Relationship Recognition (LTVRR). LTVRR aims at improving the learning of structured visual relationships that come from the long-tail (e.g., rabbit grazing on grass). In this setup, the subject, relation, and object classes each follow a long-tail distribution. To begin our study and make a future benchmark for the community, we introduce two LTVRR-related benchmarks, dubbed VG8K-LT and GQA-LT, built upon the widely used Visual Genome and GQA datasets. We use these benchmarks to study the performance of several state-of-the-art long-tail models on the LTVRR setup. Lastly, we propose a visiolinguistic hubless (VilHub) loss and a Mixup augmentation technique adapted to LTVRR setup, dubbed as RelMix. Both VilHub and RelMix can be easily integrated on top of existing models and despite being simple, our results show that they can remarkably improve the performance, especially on tail classes. Benchmarks, code, and models have been made available at: this https URL.
PERENCANAAN SISTEM PEMBANGKIT LISTRIKTENAGA SURYA OFF-GRID PADA GEDUNG PERKANTORAN DINAS PENDIDIKAN KABUPATEN GOWA SEBAGAI ENERGI ALTERNATIF

In this study, Solar Power Plant (PLTS) planning was made by utilizing the roof of office buildings in accordance with the regulation of the Ministry of Energy and Mineral Resources no. 49 of 2018 which regulates the essentials to encourage the acceleration of solar energy development, especially solar panels in Indonesia. Solar energy is a renewable energy source that is abundantly available in Indonesia. One way to utilize solar energy is to convert it into electrical energy using photovoltaic modules or solar modules known as Solar Power Plant (PLTS). Technical and economic analysis methods were used in this study for the planning of the PLTS system as a source of electrical energy in office buildings. This PLTS was designed to supply electricity with an estimated daily energy load requirement of around 89.36 kWh. This Off-Grid PLTS planning required 91.96 m2 of land, 4 arrays with 60 solar panels, 3 arranged in series and 5 in parallel. The components required for this plan are 4 SCC units, 24 battery units, and 1 inverter units with PLTS output power per year kWh/year. Performance Ratio (PR) in the PLTS system as a reference that the system is feasible to be realized with a PR value of 85% and an initial investment of Rp. 1.098.082.205,96 which cover the cost of the PLTS system components and installation costs.
Adaptive spam filtering system using complement Naïve Bayes model

Naive Bayes filter is a simple probabilistic filtering method based on Bayes theorem. A crucial problem with the conventional Naive Bayes filter is the assumption of uniform priors in the computati...
K-means clustering algorithm for data distribution in cloud computing environment

This study analyses the data structure in cluster analysis. It is a clustering method that randomly selects a known number of points and then continues to expand. Through the comparative experiment...
PENINGKATKAN HASIL BELAJAR MELALUI MODEL TGT (TEAMS GAMES TOURNAMENT) PADA MATAPELAJARAN MATEMATIKA DI SD NEGERI 4 JATI MULYO

This research was conducted to examine the use of TGT (Teams Games Tournament) as the effort to improve student learning outcomes in mathematics in grade II SD Negeri 4 Jatimuyo Jati Agung subdistrict South Lampung.This research is a class action research which used sample of 20 students in the Class II SDN 4 Jati Agung subdistrict South Lampung regency. The research process is conducted through three cycles of the overall data were taken using observation and tests. The results showed that the use TGT (Teams Games Tournament) has a positive impact on learning outcomes. It can be seen from the increase in the students’ score as well as the learning activities in the classroom which proves the method TGT (Teams Games Tournament) in Mathematics can improve student learning achievement. Thus the method of TGT as an effort to improve student learning outcomes in learning in mathematics class II SDN 4 Mulyo Jati Agung Jati subdistrict South Lampung regency in the academic year 2014/2015 is proven to improve learning outcomes. Keywords: TGT (Teams Games Tournament), learning outcomes, learning activities
PERANCANGAN APLIKASI SENSUS PENDUDUK PADA BADAN PUSAT STATISTIK KOTA MAKASSAR BERBASIS ANDROID

Technological developments and changes in government systems are developing rapidly. Both of these lead to efforts to carry out duties, protect functions and serve the community. This encourages the government to take various adjustment steps quickly in line with the dynamics of development that occur. One of them is through a population census. The population census is an important issue that must be handled properly. The population census in this study takes population data in an area based on the number of male population, female population, ratio, and population density. The data was taken and submitted to the Makassar City Statistics Agency. Population Census is a presentation of information that has the ability to present accurate information, and helps facilitate the search for a population census data. The population census is carried out every 5 years which is carried out by census officers to carry out data collection to each resident's house, the data collection process is carried out by conventional recording and submitting it to the central statistics agency for database entry. With this application, it is expected to provide convenience to Population census officers to perform the process of inputting population data and the data is directly stored in the database without having to return to the office to input again.
Taxation, Foreign Aid and Political Governance in Africa

This study examines the hypothesis that foreign aid dilutes the positive role of taxation on political governance. The empirical evidence is based on the Generalised Method of Moments and 53 African countries for the period 1996-2010. For more policy options, the dataset is disaggregated into fundamental characteristics of African development based on income levels, legal origins, natural resources and landlockedness. While the hypothesis is invalid in baseline Africa, low income and English common law countries of the continent, the research cannot conclude on its validity for other fundamental characteristics of development. Policy implications, caveats and directions for future research are discussed.
Poster: The Low Impact of COVID-19 on Rural Community Network Traffic

With this poster we present an initial analysis of the implications of the COVID-19 pandemic and regional lockdowns on Internet traffic and credit transfers within a rural community network in Bokondini, Indonesia. We find initial evidence that phenomena observed in other large-scale datasets around lockdowns did not occur in this context, with little change observed in network utilization. We do find a marginal increase in the frequency and size of transfers in the network and observe some users accessing health information and using health-related applications.
Kampong Youth Creative Festival in the Midst of Pandemic: ‘Ambreg’- Pandemic Kite Design Competition

In March 2020 Indonesia entered COVID-19 pandemic situation which affected everyone and changed how one interact to others. Activities halted for several months and now Indonesia is entering the new normal phase. This is also the situation for Kampong Pondok Pucung a suburban kampong located in southern Tangerang. However, the youth in this particular kampong refused to be passive where they collaborate with students and lecturer from School of Design, UPH to craft creative festival called ‘Ambreg’ (translated: to be together) in the form of pandemic kite design competition. The festival is also aimed as a design campaign to raise Kampong Pondok Pucung community awareness on COVID-19 pandemic and what is new normal means. The interesting part is how the collaboration used digital and physical platform from the research preparation, designing festival up to action using the combination of Participatory Action Research (PAR) and Design Thinking (DT). The festival and its collaboration demonstrate the new normal hybrid ways of how art intertwine digitally and physically to become tools of community empowerment, especially to build creativity and imagination for kampong youth.
Analisis Ketersediaan, Kondisi, dan Penggunaan Media Pembelajaran IPA di SDN 41 Mallari Kecamatan Awangpone Kabupaten Bone

This research is a type of qualitative descriptive research that aims to determine the availability, condition, and use of science learning media at SDN 41 Mallari, Awangpone District, Bone Regency. The subjects in this study were teachers of grades I, II, III, IV, V, and VI. Data collection is done by observation, interviews, and documentation. Data reduction analysis techniques, data display, and conclusion drawing/verification. The results of this study indicate that the availability of science learning media is not fully available in accordance with the standard in the Regulation of the Minister of Education and Culture of the Republic of Indonesia Number 23 of 2013 concerning Minimum Service Standards for Basic Education in Districts/Cities and eleven types according to the scope of science learning materials in elementary schools. Most of the science learning media are in a damaged condition, both the complete and incomplete available media, and the absence of special officers who take care of the science learning media makes the media unmanageable, with the availability of damaged learning media and incomplete components making the media can not be used.
Common Information Space For Industrial Companies Under The Background Of Industry 4.0

Common information space is a dynamic space for all members of society to produce, acquire, transmit, and absorb information. It’s a kind of space that makes information produce circulate and exchange and interacts with other spatial elements of the social system. At present, the common information space plays an important role in the development of the high-tech sector of the economy. This article discusses the dynamic, open, and blend characteristics which information space has. It is shown in the paper that common information space consists of three layers of government information, social organization information, and private information. Complex functions of common information space such as energy supply, integration, control, and service are provided in the paper. It is shown in the paper that the development of high-tech industries is inseparable from the common information space, which provides support for the development of high-tech. The high-tech industry can share information through the common information space and achieve more reasonable resource allocation and save corporate costs to create more wealth. The establishment of a common information space allows implementing of an ecosystem approach to the development of the high-tech industry.
Fast approximate calculation of valid domains in a satisfiability-based product configurator

Calculating valid domains is an important feature of an interactive product configurator. Since it is an NP hard problem, it is necessary (for large real-world instances) to calculate valid domains only approximately in order to keep the response time low. In this paper, we present a new fast and accurate approximation algorithm to calculate the valid domains in a satisfiability based interactive product configurator. The algorithm is based on building a full implication graph during unit propagation and performing a search in that implication graph in order to approximate whether a domain value is valid. We experimentally compared our new algorithm to the algorithm used by the commercial SAT-based configurator CAS Merlin and measured speedups of up to 18-fold while maintaining the same accuracy.
Identity-based Provable Data Possession for Multicloud Storage with Parallel Key-Insulation

Cloud Storage is the primary component of many businesses on cloud.Majority of the enterprises today are adopting a multicloud strategy to keep away from vendor lock-in and to optimize cost.Auditing schemes are used to ascertain the integrity of cloud data.Of these schemes, only the Provable Data Possession schemes (PDP) are resilient to key-exposure.These PDP schemes are devised using Public Key Infrastructure (PKI-) based cryptography, Identity-based cryptography, etc. PKI-based systems suffer from certificate-related communication/computational complexities.The Identity-based schemes deal with the exposure of only the auditing secret key (audit key).But with the exposure of both the audit key and the secret key used to update the audit key, the auditing process itself becomes a complete failure.So, an Identity-based PDP scheme with Parallel Key-Insulation is proposed for multiple cloud storage.It reduces the risk of exposure of both the audit key and the secret key used to update the audit key.It preserves the data privacy from the Third Party Auditor, secure against malicious Cloud Service Providers and facilitates batch auditing.The resilience to key-exposure is proved using the CDH assumption.Compared to the existing Identity-based multicloud schemes, it is efficient in integrity verification.
Research on new energy trading system based on blockchain

With the rapid development of new energy industry, the new energy structure is gradually shifting from centralized system to distributed system. The problems of trust and fair trade have become increasingly prominent in traditional centralized energy trading systems. The decentralized blockchain technology can provide a trusted, safe and transparent technical solution for energy transactions. This paper proposes a blockchain-based new energy trading platform in multi-seller-multi-buyer distributed new energy power platform. It establishes multi-party trust relationship through blockchain technology and optimizes transaction strategy by multi-party game algorithm to improves multi-party revenue. Simulation results prove that the proposed solution can reduce energy consumption and optimize energy structure, which provides a reference for theory and technology of new energy trading platform.
Copy-Move Forgery Detection Based on Euclidean Distance and Texture Feature Analysis

Digital images are important part of our life. Copy and Move forgery detection techniques are designed to detect edited part of the image. The copy and move forgery techniques are based on the feature detection and matching. The techniques which are designed so far use the Euclidean distance concept for feature matching. The feature detection techniques which are much popular like Haar transformation are used for feature extraction. In this research, the PCA algorithm is used for the simplification of features which are extracted with Haar transformation. The GLCM algorithm is used for texture feature analysis of input image. In the end, Euclidean distance is used for feature matching and mismatched features are marked as forgery. The proposed approach is implemented in MALTAB and results are analyzed in terms of accuracy.
Research on CNN for Anti-missile Object Detection Algorithm Based on Improved Attention Mechanism

In military applications, it has great research value to mine reliable military information from remote sensing image data. Since the precision and recall rate of the CNN (convolutional neural networks) in the object detection process is low, and cannot meet the requirements of military combat indicators. An improved CNN for the anti-missile object detection algorithm based on improved attention mechanism is studied. First, DehazeNet algorithm was used to improve the recognition of the target while is obscured by the fog in the antimissile remote sensing data set, and the data set was re-clustered through the K-means algorithm; then based on the idea of ECANet attention mechanism to improve and reorganize its pooling layer, and an improved attention module I-ECANet (Impproved ECANet). Improved the last residual layer of each group of convolution and residual layers in the YOLOv3 network to the I-ECANet attention module, training network before and after improvement; finally, use the test set to test and analyze the anti-missile remote sensing image. The results shown that the precision, recall, and average detection precision of the algorithm have been greatly improved, with the precision rate reaching 97.6%, an increase of 6.8%, and recall rate reached 95.7%, an increase of 3.8%, Average detection precision reached 95.1%, an increase of 4.4%, and detection speed reached 33.87 images per second. It shows that the improved algorithm proposed in this paper has wide application value.
TH42. APPLICATION OF REFERENCE-BASED CELL TYPE ESTIMATION IN PLACENTAL TISSUE AND COMPARISON WITH A REFERENCE-FREE APPROACH FOR DNA METHYLATION STUDIES

The information describing a person is constantly evolving and may become obsolete and contradict other information. A personal database, therefore, must be consistently updated upon the acquisition of new valid observations that contradict obsolete ones contained in the database. This study focuses on proposing a novel approach for dealing with the information obsolescence problem in the elderly-fall prevention context. Our approach aims to continuously monitor elderly information in order to detect the change in the behavior of an elderly person and to prevent him from falls. It consists of detecting contradictions between newly acquired information about a single elderly and what we already know about that person, then identifying among his observations those that have become obsolete and need to be updated. We propose a new approximate concept,£-Contradiction, which represents the confidence level of having a contradiction in a set of observations when a causal Bayesian network is our representation model. We propose a polynomial-time algorithm for detecting obsolete information and show that the resulting obsolete observations are given as an explanation AND-OR tree.
One Picture to Study One Thousand Words: Visualization for Qualitative Research in the Age of Digitalization

In this article, we argue for further advancing qualitative research methods by creating tools to investigate digital traces of digital phenomena. We specifically focus on large-scale textual data sets and show how interactive visualization can be used to augment qualitative researchers’ capabilities to theorize from trace data. We ground our approach on prior work in sensemaking, visual analytics, and interactive visualization (Munzner 2014; Russell et al. 1993) and show how tasks enabled by visualization systems can be synergistically integrated with the qualitative research process. Finally, we apply these principles with several open-source text mining and interactive visualization systems. We hope that this articlestimulates further interest and provides specific guidelines for developing and expanding the repertoire of open-source systems for qualitative research.
Mastering the pedagogical potential of cultural and educational city environment: The experience of implementing project-based master’s degree programme

The purpose of the study is to present the methodological fundamentals of the development of cultural and educational environment of the city within primary education. We proved the necessity of revising training techniques for teaching culture under conditions of higher education. We explained top priority of orientation towards humanitarian, anthropological and axiological approaches to organization of mastering local lore at school and university. The cultural and educational environment of the city, i.e. the place, where a person was born, is considered as a tool for the interiorization of universal human values. The study gave reasons for importance of involving children in local lore activities at primary school age. Local lore is considered as a scientific basis for designing the content of school subjects; as a cultural training, activity aimed at learning about the heritage of one’s native city, preserving and enhancing the cultural level of the region, its inner potential; as a social activity aimed at developing civic mindedness. The article determined the possibilities of using local lore to teach moral and spiritual values to primary schoolchildren. The study described experience of creating and implementing a project-based research-based master’s degree programme at Saratov State University, aimed at training primary school teachers to use local lore materials in the educational process at school. The article reveals the structural and content components of the educational programme, the main forms and teaching methods. The article outlines the topics for student projects in the field of literary, linguistic, mathematical, and ecological local lore. We presented various methodological forms of incorporating local material in the class and extracurricular activities of younger students: compilation of interactive educational resources (books, reference books, albums, presentations, didactic problem books), preparation of quest games, virtual excursions, subject and intersubject projects. The article gives examples of cross-curricular competitions, mathematical problems with regional content. The priority area is the immersion of students (both students and schoolchildren) in the cultural environment of the city, region.
On the exploration of a mobile executive functioning coaching solution for students with and without disabilities in post-secondary STEM education

This study investigated the insights of post-secondary science, technology, engineering, and mathematics (STEM) students with and without disabilities regarding their experiences with academic coaching through mobile phones and examined whether e-mentoring is effective in supporting the executive function skills (EFs) of those students. The researcher explored the design of a mobile EF coaching solution to satisfy individuals with diverse learning needs, especially students with disabilities, and to provide academic support to their post-secondary STEM gateway course. A parallel mixed methods study design was adopted. A total of seven participants completed the mobile coaching study. The pre/post-test results and the analysis of qualitative content showed improved EFs and learning strategies/skills for those students. Two levels of coding were used to analyse the qualitative data. This study added to the limited but growing research on implementing EF coaching via innovative technology tools to support students' academic goals and performance.
Evidential Deep Learning for Open Set Action Recognition

In a real-world scenario, human actions are typically out of the distribution from training data, which requires a model to both recognize the known actions and reject the unknown. Different from image data, video actions are more challenging to be recognized in an open-set setting due to the uncertain temporal dynamics and static bias of human actions. In this paper, we propose a Deep Evidential Action Recognition (DEAR) method to recognize actions in an open testing set. Specifically, we formulate the action recognition problem from the evidential deep learning (EDL) perspective and propose a novel model calibration method to regularize the EDL training. Besides, to mitigate the static bias of video representation, we propose a plug-and-play module to debias the learned representation through contrastive learning. Experimental results show that our DEAR method achieves consistent performance gain on multiple mainstream action recognition models and benchmarks. Code and pre-trained models are available at {\small{\url{this https URL}}}.