Reviewerly/exHarmony huggingface dataset:
Building Efficient Neural Prefetcher

Data prefetching is a promising approach to mitigate computation slow down due to the memory wall. While modern workloads grow more and more complicated, their memory access patterns become less organized and rule-based prefetchers can no longer deliver improved performance, which motivates the research of adopting neural networks for prefetching. However, current neural prefetchers require high computation costs and large storage space to obtain good performance, which makes them far from practical. To this end, we address the efficiency issue in neural prefetchers and propose an effective approach to build light-weight models. Specifically, our method is aware of both machine learning and micro-architecture, where we introduce a novel neural prefetcher design space with knobs from both aspects. We optimize these knobs using workload characteristic observations, rigorous mathematical optimization, and efficient design space traversal, which provides us with highly-efficient neural prefetchers. Our approach is evaluated on SPEC CPU 2006, where our models can provide up to 60% IPC gain compared to no prefetching, outperforming non-neural based prefetchers. In comparison with the state of the art neural prefetcher, our models enjoy an average of 15.4 × multiply-accumulation reduction, 6.7 × parameters saving, with even better IPC gains. Although it is still challenging to provide implementable neural prefetcher, this order of magnitude computational and storage reduction, provided by our method, marks an important milestone towards practical neural prefetchers.
Extending the Life of Old Systems with More Memory

Extending the lifetime of computing systems is definitely one of the ways to reduce CO2. In this paper, we explore and suggest the options of extending memory in old systems by utilizing CXL technologies.
THE USE OF RETROSPECTIVE PROJECT DOCUMENTATION IN HISTORICAL RESEARCH: PROBLEMS AND SOLUTIONS

The article is devoted to the characteristics of the composition and content of project documentation using the example of documents permanently stored in the Russian State Archive in Samara. The author points out the problems existing among historians in working with scientific and technical documentation. She draws the attention of researchers involved in studying the history of industry and socio-economic development of territories, as well as individual enterprises and institutions, to the original information that can be gleaned from these documents, in contrast to other types of documentation. The article also highlights the activities of archive aimed at providing researchers with practical assistance in solving problems that arise when working with scientific and technical documentation.
A non-invasive middleware for games adaptation and motor rehabilitation controls

This work present the TeamBridge, a middleware able to perform the communication between digital games and hardware devices, like joysticks, mice and motion capture cameras. That communication does not require any modification to the game source code, allowing an old game to be adapted to work with a new hardware device. To prove this, tests were carried out with several games, including one of them being a commercial game. This middleware also allows the use of more than one device at the same time, so we can obtain more accurate information, one device can supply the deficiencies of the other. Finally, we performed tests to make sure that the middleware would not interfere with the user experience. Tests have shown that TeamBridge can receive, interpret and send information quickly, the time varies according to the device used, getting 33ms when used with Kinect, 40ms with Leap Motion and 255ms with the NED Glove.
Playing the Hypercube – Using Augmented Reality to Enhance a Multimodal Musical Performance

Multimodal performances aggregate multiple forms of interaction and stimulation to create artistical masterpieces. One of those performances is the Ode to Christus Hypercubus, by Jônatas Manzolli. To enhance the original version of this performance and add new layers of stimulation and interaction, an Augmented Reality (AR) experience was developed. This paper describes the development of this application, all the artistic concepts that were part of the development, and the technologies used to create the final experience. Finally, the paper describes a live performance using this AR interface in a real setting during an exhibition of the Ode to Christus Hypercubus.
A lower limb mixed reality system for the elderly

This work presents a mixed reality system for lower limb exercise that detects the user's gait and synchronizes the Street View navigation in the display. It uses an accessible RGB camera with a computer vision approach to detect the body. 11 Elderly volunteers tested the system for 5 minutes each session while therapists analyzed their physical and cognitive activity. In the meantime, the system stores the motion capture data for later use. We analyzed their behaviors in 20 recorded sessions.
A framework for evaluating depth perception in stereoscopic virtual environments

Understanding humans' notion of depth and how they interact with stereoscopic virtual environments is still a challenge. This context encompasses investigation about how features of these environments affect the human perception of depth. This perception is important during the execution of tasks, such as manipulating objects, which requires interpreting and understanding space-related information. Literature does not present general and flexible methods to measure such perception. This paper presents a general, extensible and flexible framework to assess the depth perception in different stereoscopic virtual environments that encompasses object manipulation tasks and visualization techniques. A study was conducted, considering three stereoscopy techniques (based on true anaglyph, color anaglyph and shutter glasses), twenty users, two immersive virtual environments (a simulator for dental anesthesia and a racing game), parameters (distance between user and virtual objects, virtual objects' sizes) and metrics (hit rate, error rate, time and presence questionnaire responses). Results indicate that the framework produces consistent verdicts about depth perception provided by studied stereoscopic techniques. The approach has potential to assist developers in the decision making related to the choice of a stereoscopy technique for a virtual environment, considering benefits and limitations.
TAT VR: a Virtual Reality Simulator for Military Shooting Training

Traditional military shooting training methods have high costs, logistics complexity, spatial-temporal constraints, and safety risk. VR-based simulation can help address these drawbacks while serving as a platform for supplementing current training approaches, providing more convenience, accessibility, and flexibility. This work aims at analyzing the application of virtual reality in the Brazilian Army's pistol shooting training through the TAT VR simulator. This simulator was tested by a sample composed of five Army officers and one Navy officer with practical shooting experience. The results were compared with reference values obtained from related work. The data showed that TAT VR reached the reference values for the two evaluated parameters: sense of presence and effectiveness.
Mixed Reality Laptops: A Protocol to Evaluate Enhanced Viewing Experiences on Consumer Laptops Using Parallax Engine

Research into Fish Tank Virtual Reality (FTVR) techniques commonly uses specific wearable sensors such as infrared cameras, glasses, or helmets to estimate the position of the user's eyes. However, using only existing RGB cameras on laptops is more affordable for users as they are already widely available on devices. In this work, we continue and increase previous results using face feature detection software to implement the FTVR technique in 3D applications using standard laptops without needing extra devices. The main contribution is to enhanced the Parallax Engine solution to: 1)This work also defines and tests a protocol to evaluate the user experience and the sense of the presence of the Parallax Engine; 2) adding a new dimension in parallax mode (Parallax3DoF), with freedom of horizontal, vertical and depth movement with cameras in 3D scenes; 3) we eliminate the need for Python servers and the intermediation of network communication between Unity and these servers; and 4) improve integration, performance, and user experience of monoscopic FTVR mode (FishTank), with the virtual camera locked in the 3D environment of laptop screens. Parallax Engine uses Google Media Pipe for face mesh detection via an open-source implementation called the Media Pipe Plugin, available for Unity. We evaluated the proposed solution and almost doubled the FPS of the tool. In addition, we did not find fatigue problems, the interface was considered very good on the SUS scale, and the immersion was considered acceptable. We also compared the immersion and user experience of the FishTank and Parallax3DoF visualization modes, and the users evaluated better the Parallax3DoF in both. We aim in future work to explore this technique further and test it with more users.
Exploring User-Interaction Techniques by Using a Strength Feedback Measurement Device to Encourage Strength Movements of People with Hand Impairments

This study presents a validation and maintenance of a virtual reality game proposed in the literature to assist hand rehabilitation processes. In order to allow direct user interaction, that game uses Oculus Rift and Leap Motion to track the hands. The authors proposed four traditional therapy hand-gestures exercises for user interaction. In this study, we analyzed the game together with physiotherapists, applied changes suggested, added the Myo Armband in order to get the electromyography values on exercises execution, and proposed a new game version. We evaluated the new version with mostly non-disabled people. Results show that participants' strength increased and they were interested in playing the game more often. Still, some improvements are needed to evaluate the game with patients further.
Virtual Reality System for Inspection and Training in Wheel Loader

In this study, a simulator is proposed for inspection and training of a wheel loader based on a first-person serious game and virtual reality. The simulator was developed using a cross-platform game engine and integrated into various virtual reality headsets. The goal of the game was to conduct maintenance inspection procedures on the wheel loader of a mining company. A group of 34 users tested the simulator and completed a survey. The results showed that the system is suitable for inspection and training of staff before they can use a real wheel loader at a mining company. The findings revealed that implementing a simulator for inspection and maintenance training can enhance the process, reducing expenses and increasing safety. In addition, methods in the real-world of training are scarcely sufficient to instruct operators in all dangerous situations. These methods are generally effective, but they do not give operators the real-life impression of all scenarios. In this sense, the serious game makes the training effective because it gives operators a sense of realism. Beyond, the simulator can be extended to include other types of procedures with several situations.
Using Image Synthesis Frameworks to Produce Stereoscopic Views for Mobile AR: a Comparative Study

This paper investigates different methods for generating stereoscopic views for a head-mounted smartphone augmented reality (AR). Four conditions were compared, a reference stereoscopic video, produced using two mobile phone cameras separated by 63mm, a dual camera phone with limited interpupillary distance (12mm), and two stereoscopic stimuli generated from a single monoscopic view, each using a different view synthesis frameworks. The test was carried out in respect to subjective perceived stereoscopic quality using the SAMVIQ quality of experience methodology. Results suggest a significant advantage for the reference and dual video feeds in complex scenes, where the scene content is structurally diverse and significant occlusion exists. The performance of image synthesis framework improve for simpler scenes, where occlusions are few and structures are mostly flat, but remain inferior to the true stereoscopic capture methods.
Quantitative evaluation f stereoscopic augmented reality visualization using an optical see-through head-mounted display.

The authors of the current study aimed to propose a calibration method for accurate augmented reality visualisation using an optical see-through head-mounted display, and to qualitatively evaluate visualisation accuracy for the application in computer assisted surgery.An adaptation of stereo single-point active alignment method was proposed as the calibration procedure together with verification. Three tests were performed: display of points in 3D space, on the plane and on the surface of a skull phantom on inexperience users (5 participants) and experienced users (17 participants).The highest accuracy of visualization was obtained for skull phantom visualisation for an inexperienced user (3.00 mm, std 0.75 mm), while the lowest accuracy was obtained in a 3D visualisation test for an inexperienced user (22.95 mm, std 18.04 mm). The largest error was related to the depth component and amounted to 18.49 mm, std 18.10 mm for an inexperienced user.It is possible to achieve relatively high visualisation accuracy (less than 5 mm for visualisation in space) for selected users but providing it for the group of inexperienced users seems to remain a major challenge. The accuracy of point indication can be substantially and statistically significantly increased by visualising objects on surfaces. The proposed methods and obtained results can serve as a basis for further implementation of augmented reality visualisation on an optical see-through head-mounted display in applications requiring high-quality augmented reality guidance of manual tasks.
Approaching The Firm’s Innovation Capability through Knowledge Management Lens

Firm innovation capability has attracted attention of researchers and the term innovation has been largely explained in the strategic management literature in a variety of dimensions. In this attempt, organizational knowledge strategy, a knowledge-oriented culture and knowledge management sharing have been proposed to play a key role in determining firm’s innovation capability. This paper aims to draw together knowledge from two different scientific disciplines i.e. strategic management and knowledge management. A conceptual model emerges as we specifically recognize the core KM concepts as a prospective basis for explaining the phenomenon of firm innovation capability by drawing literature based definitions on knowledge strategy, knowledge centered culture and knowledge sharing. This study advances towards conceptualizing the domain of firm innovation capability by applying the ‘Knowledge Management Lens’ composed of knowledge strategy, knowledge oriented culture and knowledge sharing.
RESORT PANTAI BATAKAN BARU

Geographically, Indonesia is an agricultural country with a very wide area and many have abundant natural resources, one of which is the beach which is often used by the government as a tourism industry sector. When viewed from the flow of tourist visitor growth in South Kalimantan, it has surged every year. In order for the development of the tourism sector of Batakan Baru Beach to increase, facilities and accommodations are needed that can accommodate all tourist activities. The right choice of accommodation facilities is a resort with a coast to coast glamping resort concept with a biomorphic architecture analogy design method. The choice of this concept is able to solve design problems that are disaster responsive and environmentally friendly and able to shape the behavior of visitors to participate in protecting the environment.
Web page classification using deep learning with text and image-based analysis

This study investigates an approach that combines text and image data to classify web pages based on their content. In this methodology, Convolutional Neural Networks (CNN) are used to analyze text data, while the YOLOv8 (You Only Look Once v8) algorithm is utilized for the analysis of image content. In the experiments, 20 web pages have been manually classified and these classifications have served as a benchmark for comparing the results of the model. The final classification of a web page was determined by weighing data from YOLO at 30% and data from CNN at 70%. Experimental results of the study have shown a significant improvement in accuracy with a value of 0.602 for the classification algorithm employing both CNN and YOLO, compared to those using either CNN or YOLO exclusively.
Student textual feedback sentiment analysis using machine learning techniques to improve the quality of education

Several educational institutions worldwide work hard to obtain student feedback to explore their views on the courses and faculty. This feedback is utilized to enhance the institution’s environment. In this modern world, institutes use data or feedback collection techniques. Still, they do not have proper techniques to analyze and use this data to improve the institute's educational quality from such textual feedback. This study presents techniques for analyzing the sentiments of student textual feedback. In this paper, machine learning methods, including Random Forest, Multinomial Nave Bayes Classifier, and Long Short-Term Memory, are applied. These methods are compared, and the experimental findings show that Long Short-Term Memory provides higher accuracy than other techniques.
K-means is probabilistically poor

Kleinberg introduced the concept of k-richness as a requirement for an algorithm to be a clustering algorithm. The most popular algorithm k means dos not fit this definition because of its probabilistic nature. Hence Ackerman et al. proposed the notion of probabilistic k-richness claiming without proof that k-means has this property. It is proven in this paper, by example, that the version of k-means with random initialization does not have the property probabilistic k-richness, just rebuking Ackeman's claim.
Towards explainability of hashtags in the light of Graph Spectral Clustering methods

Hashtags constitute an indispensable part of modern social media world. As more and more hashtags are invented, it becomes a necessity to create clusters of these hashtags. Nowadays, however, the clustering alone does not help the users. They are asking for justification or expressed in the modern AI language, the clustering has to be explainable. We discuss a novel approach to hashtag explanation via a measure of similarity between hashtags based on the Graph Spectral Analysis. The application of this similarity measure may go far beyond the classical clustering task. It can be used to provide with explanations for the hashtags. In this paper we propose such a novel view of the proposed hashtag similarity measure.
Revitalization Of Evacuation Track Guidelines Using Participatory Action Research (PAR) In Supiturang Village, Lumajang District

This research aims to determine evacuation routes that suit community needs to minimize losses and the number of victims caused by volcanic disasters. This is because there is infrastructure that can strengthen preparedness and reduce community vulnerability in facing disasters. The method used in this research is Participatory Action Research (PAR). Participatory Action Research is research that involves all parties who play an important role in studying ongoing actions by carrying out changes for the better. For data collection techniques, observation techniques were used, namely directly visiting the location of Supiturang village, Pronojiwo Lumajang. The conclusion from the results of the discussion in this research is that, geographically, Supiturang Village is one of the villages within the scope of Pronojiwo District, Lumajang Regency, East Java. The profile of local residents around Mount Semeru who have relatively limited access to assets makes these local residents a community that is less responsive in facing the threats and impacts of volcanic disasters that could arise at any time. The results of the revitalization of evacuation route instructions according to procedures in this activity consist of several stages as follows, initial mapping, organizing the community, determining a research agenda for social change, participatory mapping, formulating problems, developing organizing strategies, program implementation, and reflection.&#x0D; Keywords: Revitalization; Evacuation Route Instructions; Supiturang Village
Artificial intelligence in radial diagnostics of breast cancer

Breast cancer (BC) ranks second in prevalence among all malignant tumors and is the most frequent cancer in women. This literature review details the introduction of artificial intelligence (AI) systems based on ultra-precise neural networks into clinical practice. This direction in diagnostic medicine is very promising, and in many ways can improve the existing and firmly entered into everyday practice methods of breast imaging. Such methods include mammography, ultrasound (USG) and magnetic resonance imaging (MRI). Mammography screening is an advanced tool for early detection of breast cancer, which has reduced the mortality rate from the disease by 30% in the last thirty years. Nevertheless, the method has potential drawbacks, including false positives and false negatives due to the phenomenon of tissue summation on a two-dimensional image, as well as the increased density of anatomical structures of the breast. Artificial intelligence systems are designed to improve and simplify this imaging method, reducing the time required for image interpretation. At present, these digital systems for their implementation in practice are not yet sufficiently studied, there are many errors and flaws in the interpretation of mammograms. The next widely used method of breast visualization is ultrasound. This method is able to detect neoplasms hidden by mammography in women with anatomically dense breast tissue structure, which makes it particularly useful in cancer diagnosis in women of reproductive age. However, ultrasound also has its disadvantages, among which stand out the operator-dependence of the method. Currently, the artificial intelligence system S-detect (2018, Samsung Medison) is actively used, which is able to interpret the image, automatically reading information in real time, thus increasing the effectiveness of ultrasound. The program has already demonstrated high sensitivity, specificity and accuracy (95.8%, 93.8%, 89.6%, respectively) in detecting benign and malignant breast masses in the trial phases from 2019. To date, there are no approved guidelines for the use of artificial intelligence programs in ultrasound diagnostics, with further research and evidence of the utility of such synergy required. Artificial intelligence programs combined with MRI diagnostics have also demonstrated increased efficiency and sensitivity of the method. However, false positives and false negatives (including missed pathology) have also been reported in this combination.&#x0D; A literature review of PubMed and Google Scholar article databases was performed. The focus was on full-text articles.