Reviewerly/exHarmony huggingface dataset:
Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

In this paper, we propose a robust 3D detector, named Cross Modal Transformer (CMT), for end-to-end 3D multi-modal detection. Without explicit view transformation, CMT takes the image and point clouds tokens as inputs and directly outputs accurate 3D bounding boxes. The spatial alignment of multi-modal tokens is performed by encoding the 3D points into multi-modal features. The core design of CMT is quite simple while its performance is impressive. It achieves 74.1% NDS (state-of-the-art with single model) on nuScenes test set while maintaining faster inference speed. Moreover, CMT has a strong robustness even if the LiDAR is missing. Code is released at https://github.com/junjie18/CMT.
Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection

In this paper, we propose a long-sequence modeling framework, named StreamPETR, for multi-view 3D object detection. Built upon the sparse query design in the PETR series, we systematically develop an object-centric temporal mechanism. The model is performed in an online manner and the long-term historical information is propagated through object queries frame by frame. Besides, we introduce a motion-aware layer normalization to model the movement of the objects. StreamPETR achieves significant performance improvements only with negligible computation cost, compared to the single-frame baseline. On the standard nuScenes benchmark, it is the first online multi-view method that achieves comparable performance (67.6% NDS & 65.3% AMOTA) with lidar-based methods. The lightweight version realizes 45.0% mAP and 31.7 FPS, outperforming the state-of-the-art method (SOLOFusion) by 2.3% mAP and 1.8× faster FPS. Code has been available at https://github.com/exiawsh/StreamPETR.git.
MORPHODYNAMICS OF THE TELUK NIPAH SHORELINES

The coastal retreat is one of the most common problems taking place at littoral zones, and it will only become an issue if the area is overwhelmed with commercial developments and anthropogenic activities. The coastal erosion experienced by the shoreline of Teluk Nipah, which is located at the west of Pangkor Island in Malaysia, has triggered some levels of attention among the local authorities and community. The root cause of the erosion and shoreline retreat rates remain uncertain, is due to the unavailability of records studies on beach morphodynamics in the past. Hence, this study aims to assess the decadal shoreline changes of Teluk Nipah by using remote sensing technology. Landsat satellite imageries, which ranges from 1990 to 2018, have been acquired for quantification of the shoreline change rate at Teluk Nipah using a GIS software - ArcGIS. The analysis results indicated that the shoreline is dynamic and unstable between the 1990s to 2010s. The most populated area of the shoreline experienced critical erosion that requires immediate attention by the stakeholders.&#x0D; Keywords: Coastal morphology, coastal retreat, erosion, littoral zone, remote sensing
Utilizing WhatsApp As An Educational Technology Tool In Improving Students’ Speaking For ESP Instruction

This study is designed to develop a WhatsApp social media approach to improve students' speaking skills in English for Specific Purposes (ESP) instruction. This approach seems to stimulate students to be more involved in free speaking activities so that their speaking skills can improve and they become more being motivated. This study used Classroom Action Research (CAR) namely (1) planning, (2) actions, (3) observation, and (4) reflection. This research is focused on second semester students of in civil Engineering students so that the number of students is not much. This inspires them to focus more on researching and motivating the students themselves. With the success of Cycle II, voice note social media can be a millennial innovation for English teachers, both teachers and lecturers. It was conducted for about two cycles namely cycle I and cycle II. According to the results of speaking test, findings showed that the implementation English for Specific Purposes (ESP) in teaching had positive meaningful effect on improving students’ speaking skill after being obtained test results both cycle 1 and cycle II in civil Engineering students of UKI Paulus Makassar. It can be concluded that utilizing WhatsApp as an educational technology tool improves students’ speaking for ESP instruction in civil Engineering students of UKI Paulus Makassar.
You only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration

Medical image registration is a fundamental task for a wide range of clinical procedures. Automatic systems have been developed for image registration, where the majority of solutions are supervised techniques. However, those techniques rely on a large and well-representative corpus of ground truth, which is a strong assumption in the medical domain. To address this challenge, we propose a novel unified unsupervised framework for image registration and segmentation. The highlight of our framework is that patch-based representation is key for performance gain. We first propose a patch-based contrastive strategy that enforces locality conditions and richer feature representation. Secondly, we propose a patch stitching strategy to eliminate artifacts. We demonstrate, through our experiments, that our technique outperforms current state-of-the-art unsupervised techniques.
Online Fruits and Vegetables Recycling and Reuse System

This paper pursuits to lessen the Traffic incidents entitled “ONLINE FRUITS AND VEGETABLES RECYCLING AND REUSE SYSTEM” . Online culmination and veggies recycling and reuse gadget refers back to the technique of creating reuse of unsold veggies and culmination.These unsold ones are processed in numerous bureaucracy through grading them in exclusive classes like healthy, 1/2 of spoiled and waste.In this we've got taken a few culmination like mango and custered apple for culmination for veggies, we've got taken Eggplant or brinjal and sour defend through appearing the deep mastering approach. CNN classify it as Grade A or Grade B or Grade C. Grade A kind Fruits are used to sale and vegetable used to make curries, B grade culmination or vegetable are used to make Pickles and ultimate grade used to make herbal fertilizers.The predominant goal of the gadget is to advantage the farmers for the unsold ones.
THE STUDY OF THE PERSONAL CHARACTERISTICS OF STUDENTS OF A TRANSPORT UNIVERSITY THAT DETERMINE THE EFFECTIVENESS OF ADAPTATION PROCESSES IN THE INCREASINGLY COMPLEX CONDITIONS OF PROFESSIONAL ACTIVITY

The modern social order does not limit the requirements for the model characteristics of transport industry specialists to the criteria for the completeness of specialized knowledge and skills as part of universal and professional competencies, but also requires a formed focus on continuous replenishment of professional baggage, abilities for self-realization and self-development. The relevance of the article is due to the need to study the personal characteristics of students - future specialists in the transport industry - allowing optimal adaptation to the socio-technological conditions of professional activity. Multivariate analysis shows that the mechanisms of adaptation processes are due to the presence of the following characteristics: sthenicity; leadership; communication; technical and formula-digital thinking; prudence; mental abilities. Purposeful formation of the identified qualities is possible in the educational system of the university based on the integration of creative, sports, volunteer, social types of educational activities and professional and applied physical training within the framework of mastering the disciplines of physical culture and sports. A pilot study of the initial level of formation of personal characteristics that ensure the formation of adaptation mechanisms to the socio-technological conditions for the implementation of professional activities in transport has proved the need for the formation of these qualities in the educational system of the university. The study involved 3-4 year students of the Samara University of Communications (118 people).
Semi-supervised Domain Adaptation for Dependency Parsing with Dynamic Matching Network

Supervised parsing models have achieved impressive results on in-domain texts.However, their performances drop drastically on out-ofdomain texts due to the data distribution shift.The shared-private model has shown its promising advantages for alleviating this problem via feature separation, whereas prior works pay more attention to enhancing shared features but neglect the in-depth relevance of specific ones.To address this issue, we for the first time apply a dynamic matching network on the shared-private model for semi-supervised crossdomain dependency parsing.Meanwhile, considering the scarcity of target-domain labeled data, we leverage unlabeled data from two aspects, i.e., designing a new training strategy to improve the capability of the dynamic matching network and fine-tuning BERT to obtain domain-related contextualized representations.Experiments on benchmark datasets show that our proposed model consistently outperforms various baselines, leading to new state-of-theart results on all domains.Detailed analysis on different matching strategies demonstrates that it is essential to learn suitable matching weights to emphasize useful features and ignore useless or even harmful ones.Besides, our proposed model can be directly extended to multi-source domain adaptation and achieves best performances among various baselines, further verifying the effectiveness and robustness.
Locality-Sensitive Hashing for Long Context Neural Machine Translation

After its introduction, the Transformer architecture (Vaswani et al., 2017) quickly became the gold standard for the task of neural machine translation.A major advantage of the Transformer compared to previous architectures is the faster training speed achieved by complete parallelization across timesteps due to the use of attention over recurrent layers.However, this also leads to one of the biggest problems of the Transformer, namely the quadratic time and memory complexity with respect to the input length.In this work we adapt the locality-sensitive hashing approach of Kitaev et al. ( 2020) to self-attention in the Transformer, we extended it to cross-attention and apply this memory efficient framework to sentence-and document-level machine translation.Our experiments show that the LSH attention scheme for sentence-level comes at the cost of slightly reduced translation quality.For document-level NMT we are able to include much bigger context sizes than what is possible with the baseline Transformer.However, more context does neither improve translation quality nor improve scores on targeted test suites.
Principled Paraphrase Generation with Parallel Corpora

Round-trip Machine Translation (MT) is a popular choice for paraphrase generation, which leverages readily available parallel corpora for supervision.In this paper, we formalize the implicit similarity function induced by this approach, and show that it is susceptible to nonparaphrase pairs sharing a single ambiguous translation.Based on these insights, we design an alternative similarity metric that mitigates this issue by requiring the entire translation distribution to match, and implement a relaxation of it through the Information Bottleneck method.Our approach incorporates an adversarial term into MT training in order to learn representations that encode as much information about the reference translation as possible, while keeping as little information about the input as possible.Paraphrases can be generated by decoding back to the source from this representation, without having to generate pivot translations.In addition to being more principled and efficient than round-trip MT, our approach offers an adjustable parameter to control the fidelity-diversity trade-off, and obtains better results in our experiments.
Phoneme transcription of endangered languages: an evaluation of recent ASR architectures in the single speaker scenario

Transcription is often reported as the bottleneck in endangered language documentation, requiring large efforts from scarce speakers and transcribers.In general, automatic speech recognition (ASR) can be accurate enough to accelerate transcription only if trained on large amounts of transcribed data.However, when a single speaker is involved, several studies have reported encouraging results for phonetic transcription even with small amounts of training.Here we expand this body of work on speaker-dependent transcription by comparing four ASR approaches, notably recent transformer and pretrained multilingual models, on a common dataset of 11 languages.To automate data preparation, training and evaluation steps, we also developed a phoneme recognition setup which handles morphologically complex languages and writing systems for which no pronunciation dictionary exists.We find that fine-tuning a multilingual pretrained model yields an average phoneme error rate (PER) of 15% for 6 languages with 99 minutes or less of transcribed data for training.For the 5 languages with between 100 and 192 minutes of training, we achieved a PER of 8.4% or less.These results on a number of varied languages suggest that ASR can now significantly reduce transcription efforts in the speaker-dependent situation common in endangered language work.
Innovative Design of a New Type of Civil Aviation Aircraft in the Epidemic Era

the epidemic will accompany our lives for a long time, but the needs of economic development will continue to promote the development of the aviation industry.The delivery mode of traditional civil aviation aircraft can only passively respond to major disasters, including epidemics.Through the research on the problem of the development of my country's civil aviation and the air transportation after major disasters, I creatively imagined a new type of aviation duplex wide-body passenger aircraft.
Neural Machine Translation Applied in English Chinese: Turn Grammar Connotation into Words

Recent advances in Neural Machine Translation (NMT) have largely improved the quality of translations in a variety of language pairs, which helps promote the efficiency in communication and information exchange.English to Chinese translation, however, still suffers from lower accuracy and intelligibility partly due to their inequivalent language structures.This work compares the performance of three frequently used commercial NMT systems and aims to propose a new method of turning English grammar connotations, participles in particular, into Chinese lexical words.Hopefully, with more data analyzed, the performance of NMT in the language pair of English Chinese can be improved to meet the needs in different contexts.
Reviewing Russian software, databases and web-services used in scholarly activities

The author reviews Russian information products, i.e. software, databases and web-services. Depending on the tasks (searching materials; research, analysis of findings; preparing for publication; generating educational programs and courses; formal and informal communications; monitoring statistics of researcher activity (scientometrics, bibliometrics) to report to parent organization; advanced training and obtaining reliable information; searching for scholarly vacancies), the information products and services are discussed. The examples of universal products and services are provided. The author concludes that Russian software, databases and web-services may not completely meet the demands within scholarly activities, including research, as sometimes foreign hardware and software are needed. Significant portion of scholarly web-services is designed in Russia, and of them, the majority was designed, developed and implemented independently of Government Import Substitution Program, as opposed to the software connected to the installed OS. The paper is prepared within the framework of the State Order No. 730000F99.1 BV09AA00006 to RNPLS&amp;T.
Comparing the Brain Storm Optimization Algorithm on the Ambiguous Benchmark Set

In the field of evolutionary computation, benchmarking has a pivotal place in both the development of novel algorithms, and in performing comparisons between existing techniques. In this paper, the computational comparison of the Brain Storm Optimization (BSO) algorithm (a swarm intelligence paradigm inspired by the behaviors of the human process of brainstorming) was performed. A selected representative of the BSO algorithms (namely, BSO20) was compared with other selected methods, which were a mix of canonical methods (both swarm intelligence and evolutionary algorithms) and state-of-the-art techniques. As a test bed, the ambiguous benchmark set was employed. The results showed that even though BSO is not among the best algorithms on this test bed, it is still a well performing method comparable to some state-of-the-art algorithms.
Examining the Usability of a Short-Video App Interface Through an Eye-Tracking Experiment

This study explored the visual strategies and operational implications of users scrolling through short videos provided by a short-video app. A within-subjects design with 2 (title position: title above video/title below video) × 2 (interaction area position: lower left interaction area/lower right interaction area) conditions was adopted. The eye-tracking experiment and questionnaire survey were combined to understand participants’ preferences for different conditions. A total of 30 participants were recruited for the experiment. Both the eye-tracking experiment and questionnaire survey data showed that the participants preferred the design with the title above the video and the lower right interaction area. A plausible explanation is that the title above video arrangement facilitated information filtering and was congruent with the participants’ existing browsing habits. Meanwhile, the lower right interaction area was easy to operate and more accommodating.
Estimation of Change in Affective State Using Eye Tracking Features from Virtual Reality Technologies

Affective states play a prominent role in the context of human activation and motivation. Immersive VR-based presence provides opportunities to activate elderly people in the context of preferred leisure activities (Häussl et al., 2021) or to apply mindfulness interventions for their cognitive reserve (Paletta et al., 2021). The appropriate design of positively activating content is pivotal for appropriate changes in users’ affective states. The presented study provided insight into the potential of non-invasive VR-based eye tracking for automated estimation of affective state induced by video content, in an explorative pilot study with seven elderly persons living in a nursing home. The results indicate the feasibility of estimating mood change from typical eye movement features, such as, fixation duration and pupil diameter, as a promising future research topic.
Geographic Simulation of Denpasar City in Game Cities: Skylines

Cities: Skylines is a video game based on building and developing cities or CBG (City Build Game).This game is a representation of the planning system in this game is very efficient even though it does not present the whole process realistically.However, city design games are very well modeled and have real potential for educational purposes.In the development of the game, Cities: Skylines has an extensive application programming interface (API) that allows the game to be modified from the appearance and behavior of the game.With this mode, we can enter the city map in real time into the game to be simulated.This mod can map various land uses, buildings including infrastructure found in specific cities, to map relevant urban issues.Denpasar City will be the object of study to be simulated in real time in the Cities game, Skyline.Apart from being the capital city of Bali Province, Denpasar city has the heterogeneity and complexity of urban activities on a downtown scale in the Bali region.The perspective of infrastructure completeness, density and complexity are the reasons why Denpasar City deserves a simulation test in this study as the first pilot area to be simulated.By using an automatic geodata processing method, the simulation of urban areas in the Denpasar city area can be translated not only visually but also in terms of city-specific behavior.The use of gamebased simulations is able to provide views and make it easier for someone to understand the development of geographic knowledge, creativity, and spatial awareness of the city of Denpasar so that for educational purposes this is an opportunity for researchers, students and everyone in the future to better understand the city of Denpasar with more interactive media.
User-Centred Design for QR Store: a Case Study

This work describes the user centred design process of one of the first QR stores in Italy. Users related concerns in QR use and m-shopping experience have been surveyed, eliciting users’ expectations and needs for the effective and satisfactory use of the QR store to be designed. This has been achieved combining human factors reference data with studies on consumers behaviour buying in shopping malls and in m-commerce stores. Being the QR shopping a consumer experience happening in a multidimensional environment, multiple aspects of physical shops and environment, as well as of QR store app have been addressed during the design stage of the project, aiming at delivering: a) mobile interface of e-commerce service able to support effective and satisfactory buying tasks in public/crowded spaces, b) exhibition paths that match requirements of safety, security and trust in the m-commerce service and that, at the same time, represent an attraction element in environment, c) billboards for goods displaying, supporting ease of vision and information usability by both generic pedestrian flows and motivated customers. The paper also discusses the usability test in real environment to be conducted once the installation will be completed.
IMPLEMENTATION OF INDIVIDUAL EDUCATIONAL PATHS AT THE UNIVERSITY BASED ON A PERSONALIZED APPROACH

The topical problem of the implementation of individual educational trajectories in the modern university system is discussed. Special attention is paid to a personalized approach that determines the methodological basis of the direction under consideration. On the basis of theoretical analysis, the content of the concept of «individual educational paths» is considered. The peculiarities of the implementation of individual educational trajectories in the modern educational system of the university are clarified. The relevance of this direction is due to the requirements for the modern system of higher education, which is based on the principles of a personalized approach. The purpose of the study is to consider the author’s reasons for the insufficient dissemination and implementation of individual educational paths in domestic universities, and an attempt is made to find possible solutions for more effective implementation of this direction. The results of the analysis allowed us to determine that the basis of individual educational paths at the university is the subjective position of the student. Individualization of the educational system makes it possible to purposefully and effectively develop the professional and personal qualities of a student based on the already formed level of knowledge, skills and abilities.