Reviewerly/exHarmony huggingface dataset:
Safe Sharing Sites

In this paper we argue that data-sharing is an activity that sits at the crossroads of privacy concerns and the broader challenges of data governance surrounding access and use. Using the Sidewalk Toronto “smart city” proposal as a starting point for discussion, we outline these concerns to include resistance to data monopolies, public control over data collected through the use of public infrastructure, public benefit from the generation of intellectual property, the desire to broadly share data for innovation in the public interest, social — rather than individual — surveillance and harms, and that data use be held to standards of fairness, justice and accountability. Data-sharing is sometimes the practice that generates these concerns and sometimes the practice that is involved in the solution to these concerns. Our safe sharing site approach to data-sharing focuses on resolving key risks associated with data-sharing, including protecting the privacy and security of data subjects, but to do so in a manner that is independent of the various legal contexts of regulation and governance. Instead, we propose that safe sharing sites connect with these different contexts through a legal interface consisting of a registry that provides transparency in relation to key information that supports different forms of regulation. Safe sharing sites also offer assurances and auditability regarding the data-sharing, further supporting a range of regulatory interventions. It is therefore not an alternative to these interventions but an important tool that can enable effective regulation. A central feature of a safe sharing site is that it offers an alternative to the strategy of de-identifying data and then releasing it, whether within an “open data” context or in a more controlled environment. In a safe sharing site computations may be performed on the data in a secure and privacy-protective manner without releasing the raw data, and where all data-sharing is transparent and auditable. Transparency does not mean that all data-sharing becomes a matter of “public” view, but rather that there is the ability to make these activities visible to organizations and regulators in appropriate circumstances while recognizing the potential confidentiality interests in data uses. In this way safe sharing sites facilitate data-sharing in a manner that manages the complexities of sharing while reducing the risks and enabling a variety of forms of governance and regulation. As such it offers a flexible and modular piece of legal-technical infrastructure for the new economy.
Relationship between students’ multiple intelligence-based instructional areas and assessment on academic achievements

The aim of this research is to investigation of the relationship between students' multiple intelligence based instructional (MIBI) areas and their assessment academic achievements the grade point averages of their students in Indonesia, mathematics, science and technology and social class. The research sample contains of 71 classroom Students' who worked in primary schools in the Banten Province during the 2016-2017 academic year. The research method used is the evaluation method based on Stake model by using qualitative research. In the research, uses techniques using observation data, interviews, questionnaires and study documentation. In the analysis of the data obtained from this study, Descriptive Statistics, Independent Sample t-test and Pearson Product Moment Correlation Coefficient were used. The findings of the study, suggest that there was no statistically significant difference between the classroom Students' average scores of verbal-linguistic, visual-spatial, naturalistic, musical, logical-mathematical, intrapersonal, interpersonal and bodily-kinaesthetic intelligence areas in terms of the "gender" and "grade level" variables. The result stage is a very good learning outcome with assessment academic achievements that include cognitive, affective and psychomotor.
Viewboard Effectiveness on Raharja Internet Cafe Website as Sales Information Submission Media

Information is a key to success in communicating. Communication will not be possible without information. But if the information we convey is wrong it will cause a problem. At Raharja University there is a facility that provides needs services to students such as searching for material, printing, scans, and binding documents, there are also accessories and service places if there are students who have problems with the equipment given for study, Raharja Internet Cafe. Raharja Internet Cafe has a website to be used by students who want to order their needs. However, the admin who maintains Raharja Internet Cafe cannot monitor what products or goods are the best-selling or the most sold because they are not well monitored. With no monitoring of the admin sales process or the guard cannot report the goods to the University, or the conventional data recording process. These problems are certainly considered ineffective because Raharja University is engaged in technology in each of its lecture activities. Creating a viewboard on the Raharja Internet Cafe website as a medium for delivering sales information is the solution. The method that I use is a method of data collection namely observation and literature study and a qualitative approach. The results of this study are that the presence of a viewboard on the Raharja Internet Cafe website can facilitate the admin or guard of Raharja Internet Cafe to make a report to the Raharja University.
Hyper Sensorial -- Human Computed Neurodivergent Poem

In this video artwork, the author looks at the interaction between neurodiversity and media design, focusing on his acoustic condition of hyperacusis as well as his neurodivergent condition of Asperger's. There are many inner thoughts that the hyper sensorial acoustic disorder brings, and the author creates poems as an output, interrelating art and technology in the cognitive process, and underlining a cross-connection between the data and emotions.
TrussFormer

TrussFormer is an integrated end-to-end system that allows users to 3D print large-scale kinetic structures, i.e., structures that involve motion and deal with inertial forces. TrussFormer builds on TrussFab, from which it inherits the ability to create static large-scale truss structures from 3D printed connectors and PET bottles. TrussFormer adds movement to these structures by placing linear actuators into them: either manually, wrapped in reusable components called assets, or by demonstrating the intended movement. TrussFormer verifies that the resulting structure is mechanically sound and will withstand the dynamic forces resulting from the motion. To fabricate the design, TrussFormer generates the underlying hinge system that can be printed on standard desktop 3D printers. We demonstrate TrussFormer with several example objects, including a 6 legged walking robot and a 4m tall animatronics dinosaur with 5 degrees of freedom.
Explorations on Single Usability Metrics

A long-term summative evaluation program was undertaken at Microsoft. This program focused on generating a Single Usability Metric (SUM) score across products over time but encountered a number of issues including error rate reliability, challenges establishing objective time-on-task targets, and scale anchoring. These issues contributed to making SUM difficult to communicate, prompting exploration of an alternative single usability metric using simple thresholds developed from anchor text and inter-metric correlations.
High Throughput/Gate FN-Based Hardware Architectures for AES-OTR

This paper presents high throughput/gates Feistel network (FN)-based AES-OTR hardware architectures. AES-OTR is an authenticated encryption (AE) scheme as a block cipher mode of operation using AES. While AES-OTR is one of the most theoretically efficient AEs using AES and has superior features, its practical efficiency in hardware is unclear due to no known reports of its hardware implementation. In this paper, we present efficient AES-OTR hardware architectures. In contrast to conventional AE architectures, our architecture forms the 2-round FN of OTR, which makes it easy to integrate the peripheral into hardware for OTR operations. The proposed architectures had 2.4 and 13.5 times higher throughput/gates than the de facto standard AE (i.e., AES-GCM) core on FPGA and ASIC, respectively, through logic syntheses.
Demonstration of SeeingVR

Current virtual reality applications do not support people who have low vision. We present SeeingVR, a set of 14 tools that enhance a VR app for people with low vision by providing visual and audio augmentations. A user can select, adjust, and combine different tools based on their preferences. We demonstrate the design of SeeingVR in this paper.
MementoKey

In this paper, we introduce a novel system of password generation, MementoKey, consisting of private words that exist only in a user's memory and a corresponding set of public (non-secret) words that will facilitate users' recall of the private words, which they are associated with. We will demonstrate how MementoKey offers a useful alternative to existing options for storing passwords in password managers, or to using cryptographically weak, but memorable, passwords. We have conducted a user study to evaluate the word-association technique for recalling passwords and the effectiveness of our prototype software training and checking system to guide the user successfully through the memorization process. Our study involving 60 diverse participants indicates that our prototype can effectively lead users through a visualization and memorization technique to create a strong word-association memory between pairs of adjectives and nouns.
Prediction of Availability of Packed Red Cells (PRC) at PMI Surabaya City Using Ensemble Kalman Filter as Management of Blood Transfusion Management

Blood transfusion in terms of both quality and quantity is needed by patients with various health problems they experience. Along with the increased need for blood transfusion, the management of blood transfusion arrangements (blood collection from donors, selection, distribution, storage), and the ability of nurses to provide transfusion to patients is needed. If there are a lot of mistakes in both the ability of management and the ability of nurses, it can not only lead to a fatal impact on a patientbut also increase amount of need for blood transfusion. Due to the importance of blood transfusion, maintaining the stability of blood stock must be done so as not to cause blood loss due to exces of the blood stock. To minimize such loss, blood prediction is needed. The objective of this study is to predict blood demand for blood type of Packed Red Cells (PRC) or concentrated red blood cells at PMI Surabaya by using the method of Ensemble Kalman Filter (EnKF) and Ensemble Kalman Filter Square Root (EnKF-SR). The simulation results show that both methods have high accuracy with an error of less than 1% and RMSE of EnKF-SR. The best simulation exhibited the error between the real data and the simulation with EnKF-SR was in the order of 0.0023574, whereas with EnKF was some 0.025566 with generated 400 ensembles.
Embedded System to Recognize Movement and Breathing in Assisted Living Environments

The goal of this paper pretends to show how a bed system with an embedded system with sensor is able to analyze a person’s movement, breathing and recognizing the positions that the subject is lying on the bed during the night without any additional physical contact. The measurements are performed with sensors placed between the mattress and the frame. An Intel Edison board was used as an endpoint that served as a communication node from the mesh network to external service. Two nodes and Intel Edison are attached to the bottom of the bed frame and they are connected to the sensors.
PERANCANGAN FILM ANIMASI PENDEK 2D SEBAGAI MEDIA KAMPANYE PENANGANAN ANXIETY DISORDER

More that 2 million cases of anxiety disorder occur in Indonesia every year. The term of anxiety disorder is not common in the community due to lack of campaigne and sosialisation. It will cause severe depresion and even commit suicide if it is not treated properly. The purpose of this design is to campaigne anxiety disorder’s sympton into the community through some one point of view who experinced anxiety disorder before and providing solution to the patients through two dimention animation media. This design using the theory of principle of animation, cinematography theory, design theory, aesthetic theory, semiotic theory and campaigne theory with qualitatif research methods and produces animation media that supported by social media, poster, x-banner, booklet, tote bag, t-shirt, pin and journal book using a hand drawing &amp; vector tehnique in custom digital art and infographic style. Media is mad in accordance with the concept calm and educative. Calm concept applied through medium colour which is a blend colour of green and blue known as the colour of anxiety disorder awareness ribbon.
Exploring Latent Factors Influencing the Adoption of a Processed Food Traceability System in South Korea

Several recalls of dietary supplements and infant formula not only caused direct economic loss to processors but also created distrust of food traceability systems(FTSs) initiated by government. In Korea, mandatory FTS regulations on infant formula and dietary supplements were enacted at the end of 2014, allowing the government to collect electronic traceability data to cope with food outbreaks. The aim of this study is to examine the influence and process of latent factors by developing a theoretical model and testing empirical data from the Korean processed food sector. The particular value of this study is to identify the latent factors influencing the diffusion of an electronic FTS. Three external factors (organizational adaptability, validity and awareness of FTS) were incorporated into a technology acceptance model (TAM) based on previous studies, and structural equation modeling (SEM) was used as a tool for confirmatory analysis. The validity of FTSs has a prominent effect on attitudes toward FTSs and compliance intentions. Contrary to the findings of previous studies, organizational adaptability does not influence a positive effect on attitudes toward FTS. Furthermore, subgroup analysis showed that retailers reacted significantly to the different influences than manufacturers. The findings of this paper have implications for both policy makers and regulatory authorities. The results of this theoretical and practical study contribute to establishing a conceptual framework and motivate additional researches on FTS adoption and diffusion in processed food sectors.
EdgeSegNet: A Compact Network for Semantic Segmentation.

In this study, we introduce EdgeSegNet, a compact deep convolutional neural network for the task of semantic segmentation. A human-machine collaborative design strategy is leveraged to create EdgeSegNet, where principled network design prototyping is coupled with machine-driven design exploration to create networks with customized module-level macroarchitecture and microarchitecture designs tailored for the task. Experimental results showed that EdgeSegNet can achieve semantic segmentation accuracy comparable with much larger and computationally complex networks (>20x} smaller model size than RefineNet) as well as achieving an inference speed of ~38.5 FPS on an NVidia Jetson AGX Xavier. As such, the proposed EdgeSegNet is well-suited for low-power edge scenarios.
12. Head-Driven Phrase Structure Grammar

Head-Driven Phrase Structure Grammar is a constraint-based theory. It uses features and values to model linguistic objects. Values may be complex, e. g. consist of feature values pairs themselves. The paper shows that such feature value pairs together with identity of values and relations between feature values are sufficient to develop a complete linguistic theory including all linguistic levels of description. The paper explains the goals of researchers working in the framework and the way they deal with data and motivate their analyses. The framework is explained with respect to an example sentence that involves the following phenomena: valence, constituent structure, adjunction/modification, raising, case assignment, nonlocal dependencies, relative clauses.
Paraxial design of a four-component zoom lens with zero separation of principal planes and fixed position of an image focal point composed of members with constant focal length

Our paper presents a detailed theoretical analysis of a four-component zoom lens with coincident principal planes, fixed position of the image focal point, and an approximately corrected Petzval sum. New formulas enabling the calculation of paraxial parameters of such optical systems are derived, and the practical application of these formulas is shown in an example. The position of the optical center of these optical systems does not depend on the object distance (for a given value of focal length of the zoom), and the position of the image focal point (with respect to the last element of the system) is fixed during the operation of the zoom. Such optical systems could be used in various measuring systems in photogrammetry, computer vision, triangulation sensors, fringe projection techniques, surveying, machine vision, etc.
Self-Quotient Image based CNN

The Convolutional Neural Networks (CNNs) are able to learn basic and high level features hierarchically with the highlight that it implements an end-to-end learning method. However, lacking in the ability to utilize prior information and domain knowledge has led to the neural networks hard to train. In this paper, a method using prior information is proposed, which is by appending prior feature-maps through a bypass input structure. As an implementation, we evaluate a convolutional neural network integrating with the Self-Quotient Image (SQI) algorithm. Through the bypass, we import the feature-maps from the SQI algorithm and concat them with the output of the first convolution layer. With the help of traditional image processing methods, CNNs can directly improve the accuracy and training stability, while the bypass is exactly a consistent point. Finally, the necessity of this bypass pattern is that it avoids the direct modification of original images. As CNNs are able to focus on far richer features than basic image processing methods, it is advisable for us to expose CNNs to the original data. It is exactly the main design idea that we make the output from synergistic processing algorithm bypass from the side.
CNTC: A Container Aware Network Traffic Control Framework

As a lightweight virtualization technology, containers are attracting much attention and widely deployed in the cloud data centers. To provide consistent and reliable performance, cloud providers should ensure resource isolation since each host consists of multiple containers sharing the host kernel. As a mainstream container system, Docker uses CGroup to provide CPU, memory, and disk resource isolation. Unfortunately, all present solutions ignore the network resource, leading to the resource competition and violating the performance of networked hosts. Although several researches discuss the possibility of leveraging Linux Traffic Control (TC) module to guarantee network bandwidth, they fail to capture the diversity and dynamics of container network resource demands and therefore cannot be applied to container-level network traffic control. In this paper, we propose a Container Network Traffic Control (CNTC) framework which can provide strong isolation and container-level management for network resource with joint consideration of container characteristics and quality of service. To simplify the traffic control, we also design a series of APIs which allow inexpert programmers to perform complicated traffic control on each container. Through experiment results, we show that CNTC works well in all network modes of containers.
Quantum distance bounding

We present a distance bounding (DB) protocol that employs quantum-bits (qubits) in the implementation of the rapid-bit exchange (a.k.a., challenge-response) phase, instead of classical bits. This is not the first attempt at using qubits in a DB protocol, as Abidin et al. proposed a way to implement DB protocols using qubits in RFIDSec 2016 [1]. We improve upon Abidin et al.'s protocol and make it resistant to photon number splitting attacks. In addition, our new protocol eliminates the need for communication from the prover to the verifier in the last authentication phase, which is necessary in the protocol by Abidin et al.
A Case Study of Outside Events verses the Thriving Speaking Center

In April, at the Excellence at the Center Conference, I participated in a national discussion in my role as Managing Editor of Communication Center Journal (CCJ). During my contributions to that larger discussion I noted that I believe it is time for writers and future writers of our subset of communication studies to begin to view our work more critically. While I made no mention of it, I was thinking about opportunities to engage from a critical perspective put forth by the publication of a communication center manuscript outside of CCJ in the last year.
Approach to use ontology based on electronic payment system and machine learning to prevent Fraud

Machine learning is a field of study of artificial intelligence that is based on statistical approaches to give computers the ability to learn from data. An ontology is the structured set of terms and concepts representing the meaning of a field of information, whether by the metadata of a namespace, or the elements of a domain of knowledge. in this paper we propose an approach to combine a machine learning with an ontology based on an electronic payment system and another ontology generated automatically to prevent and fight the risks of fraud.
Solving nurikabe with ant colony optimization

We present the first nature-inspired algorithm for the NP-complete Nurikabe pencil puzzle. Our method, based on Ant Colony Optimization (ACO), offers competitive performance with a direct logic-based solver, with improved run-time performance on smaller instances, but poorer performance on large instances. Importantly, our algorithm is "problem agnostic", and requires no heuristic information. This suggests the possibility of a generic ACO-based framework for the efficient solution of a wide range of similar logic puzzles and games. We further suggest that Nurikabe may provide a challenging benchmark for nature-inspired optimization.
Speed Optimization for Incremental Updating of Grid-Based Distance Maps

In the context of robotics and game AI, grid-based Distance Maps (DMs) are often used to fulfill collision checks by providing each traversable cell maximal clearance to its closest obstacle. A key challenge for DMs’ application is how to improve the efficiency of updating the distance values when cell states are changed (i.e., changes caused by newly inserted or removed obstacles). To this end, this paper presents a novel algorithm to speed up the construction of DMs on planar, eight-connected grids. The novelty of our algorithm, Canonical Ordering Dynamic Brushfire (CODB), lies in two aspects: firstly, it only updates those cells which are affected by the changes; secondly, it employs the strategy of Canonical Ordering from the fast path planning community to guide the direction of the update; therefore, the construction requires much fewer cell visits and less computation costs compared to previous algorithms. Furthermore, we propose algorithms to compute DM-based subgoal graphs. Such a spatial representation can be used to provide high-level, collision-free roadmaps for agents with certain safety radius to engage fast and rational path planning tasks. We present our algorithm both intuitively and through pseudocode, compare it to competing algorithms in simulated scenarios, and demonstrate its usefulness for real-time path planning tasks.