Reviewerly/exHarmony huggingface dataset:
Collaborative Design Curation

This proposed research investigates new media and interaction techniques to address creativity challenges facing design teams. I propose role-based layers within zoomable spaces, as a novel technique for reducing collaborative fixation, while maintaining shared awareness and shared visual context. My research will enable design teams to create layered, multiscale design curation spaces which can modulate individual and collaborative creative processes.
Implementation of the TDWG Standards Documentation Specification

The Standards Documentation Specification (SDS) was ratified as a TDWG standard in 2017 (Baskauf et al. 2017). It specified formatting guidelines for documents, but also established a data model for standards components and their versions. The SDS provided broad guidelines for Internationalized Resource Identifier (IRI) use, and associated specific metadata properties to particular components, but left many details to implementers. Since 2017, progress has been made toward implementing the requirements of the SDS. Part of that work was reformatting existing documents to comply with the standard, but another major effort was designation of IRI patterns, assembling the necessary metadata, and creating a system that can generate the many vocabulary-related documents necessary to comply with the SDS. Thse documents not only include human-readable documents, but also machine-readable documents that can be acquired through content negotiation. In addition, the system makes available dumps that can be loaded into a graph database for querying. In this presentation, we will review these developments and see how the newly-available machine-readable metadata can be used to answer questions about existing standards and future controlled vocabularies.
Designing to Reflect Our Better Nature

We present a set of technologies designed in our research group where the focus has been on highlighting the nuanced but critical agency of people to shape interaction with their world using and through computers. Our design stance emerged by critically seeing technology's existing power and authority. Taken separately, design traits that promote agency are visible but not necessarily salient. This demo presents different technologies that approach this design direction from different angles and in different contexts. Through this demo, we hope to widen the discussion on the role of design to bring about a kind of power and authority that reflects us not as compliant consumers but more in terms of our better natures.
Homomorphic Encryption Scheme to Enhance the Security of Data

Data generated in digital devices need to be secured for its use by the authorized users. Different security algorithms such as symmetric and asymmetric cryptosystems have been developed to secure the data while in transmission as well as at rest. However, data is not secure while processing. This paper explores the concept of Homomorphic Encryption (HE) based solution for secured functional evaluation of data. The proposed FHE-AES/DH cloud security model executes encryption on the data and encrypted data is transmitted to the cloud server. The functional evaluation is carried out on uploaded data by the third party without knowing the contents. These models hide the content of data in order to protect security and privacy. A banking data set has been used for the case study. The FHE-AES model takes less time for functional evaluation compared to FHE-DH model.
Analysis of task execution in a data visualisation interface and its influence on individual performance

This research paper presents an approach for the evaluation of data visualisation interfaces through the analysis of the TTF (Task Technology Fit) value, the user experience and the characteristics that have an influence during task execution. An experiment was carried out to analyse an interface for consulting energy data collected by monitoring systems in the home. The results show that the digital solution analysed does not offer the necessary fit to obtain satisfactory results in terms of individual performance, generating high execution times and error rates. The research confirms that the proposed method enables evaluation of data visualisation interfaces and shows the criticality of the mental load factor.
Ambivalence

This demonstration is built on the postcolonial scholar, Homi Bhabha's idea of Ambivalence and exhibits experiences of "smooth" and "rough" tactile feelings simultaneously to convey to a typical smartphone user the struggles of electronic waste (e-waste) workers when they dismantle, test, and recycle broken electronic devices. The demonstration consists of two components: 1) a mobile game that imitates e-waste workers' routine tasks, and 2) a smart glove that reacts correspondingly to the player's moves in the game by simulating unpleasant feelings. This demonstration introduces the harsh and inconvenient experiences that e-waste workers face in recycling practices, along with the familiar smooth tactile experiences in touch-based interactive devices. The co-presence and concurrent experiences of "smooth" and "rough" create an 'ambivalence' and allow the user to reflect on the stark differences between the two worlds of interactions with mobile phones. This demonstration is aimed to later develop empathetic connections between people with different privileges and backgrounds.
Towards Adaptive Flow Programming for the IoT: The Fluidware Approach

The objective of this position paper is to present Fluidware, a proposal towards an innovative programming model for the IoT, conceived to ease the development of flexible and robust large-scale IoT services and applications. The key innovative idea of Fluidware is to abstract collectives of devices of the IoT fabric as sources, digesters, and targets of distributed “flows” of contextualized events, carrying information about data produced and actuating commands. Accordingly, programming services and applications implies declaratively specifying “funnel processes” to channel, elaborate, and re-direct such flows in a fully-distributed way, as a means to coordinate the activities of devices and realize services and applications. The potential applicability of Fluidware and its expected advantages are exemplified via example in the area of ambient assisted living.
Hybrid telecentric triangulation sensor system with real-time field-dependent deconvolution

High-resolution optical inspection techniques typically require expensive imaging systems. One possible approach for reducing the overall cost of such systems is to combine optics of limited performance with digital image restoration techniques. In this contribution, we introduce a new hybrid system based on the combination of a field-programmablegate-array (FPGA), a large telecentric lens with strong field dependent chromatic aberrations and different types of object-adapted projections for 2D and 3D inspection tasks. The optical design tries to minimize cost and weight by replacing the – typically very large – first refractive group of the object-sided telecentric lens by one thin diffractive optical element. This approach can correct the field-dependent aberrations very well. Unfortunately, strong chromatic aberrations are unavoidable. For restoration, we use digital image processing by means of advanced deconvolution algorithms. The necessary number of operations for the strong fielddependent aberrations is extremely high. We combine algorithmic approaches (convolutions using singular-value decomposition) and parallelization directly on the FPGA to achieve live restoration (15 Hz) for a custom-built image sensor with three megapixels. The power consumption is low and a compact processing unit is realized. This hybrid (digital-optical) imaging system is used for 2D- and 3D inspection based on adaptive triangulation. One approach is based on inverse fringe projection. Ray-tracing based on the sensor setup and a reference CAD-model of the part to be tested is used for computing a fringe mask. This mask is inscribed on a spatial light modulator, which then projects the fringes towards the object. If the object under test is without faults, high-frequency equidistant straight-line fringes will result on the image sensor and low height measurement uncertainties at low lateral resolutions, even for non-cooperative objects, are achievable. The importance of a large depth-of-field and constant image-scale along the optical axis for the inverse fringe projection lead to the decision of a telecentric objective.
(Keynote) Artful Design

What is the nature of design, and the meaning it holds in human life? What does it mean to design well-to design ethically? How can the shaping of technology reflect our values as human beings? Drawing from the unconventional book Artful Design: Technology in Search of the Sublime [1], this keynote breaks down the designs of everyday tools, software, toys, musical instruments, and social experiences, examining the ways in which we shape technology and how technology shapes our society, and us in turn. This is a meditation for the "engineer with a soul" as well as for anyone curious (or concerned) about technology - not only what it does for us, but also what it does to us.
RECOGNITION ALGORITHMS FOR CORRELATION OF WELLS DURING DEVELOPMENT OF MINERALS

The article presents the problem of detecting an earth layer, containing minerals, describes the recognition algorithms for computing devices of a portable type, designed to help the exploration geologist. These devices would be useful to the exploration geologist at the time of determining the direction of the ridge containing minerals. To solve the problem of finding minerals, it is proposed to use a universal heterogeneous multiprocessing computing platform (MСP), developed in M. A. Kartsev Computing System Research and Development Institute intended for high‑speed processing of large‑scale data when solving a wide range of hydroacoustics, radar, geophysics and mineral exploration tasks.
Decision Support System for Proposed Physical Development of Bantul Building Using Case-Based Reasoning

Abstract In accordance with Regulation number 1 the year 1994 concerning the general spatial plan, the development must be optimally utilized without ignoring the principle of balance and sustainability. Development programs implemented by the Government of Bantul (for the rest of the abstract defines as Bantul), specifically the physical construction of the building, or in other words the infrastructure is currently progressing incredibly fast. It is marked with the number of facilities and public services buildings in the Bantul such as government buildings, educational and health facilities, etc. The process of physical building assessment submitted by the regional work units (Satuan Kerja Perangkat Daerah/SKPD). It requires good planning since it involves massive costs and also complies with general spatial planning of Bantul. This research aimed to establish a system of decision making to assess a proposal of the physical development building by using case-based reasoning (CBR). The assessment process is done by entering values on the elements of assessment and also to determine the priority rating for each type of building. The algorithm used is k-Nearest Neighbor with a similarity function by using the Normalized Euclidean Distance. The results show that recommendations follow-on from physical development proposal assessment decision depends on the recommendation of previous cases buildings that ranked first in a list of cases with the results of its smallest Euclidean. Leaders as decision-makers can make decisions by following recommendations issued by the system, but leaders can also determine the outcome of their decisions without following system recommendations.
Unstructured Data Analysis with Passphrase-Based REST API NoSQL for Big Data in Cloud

The synthetic word big data is emerging from almost every source in the modern world pertaining to any and every field, either technical or nontechnical. This big data generating at a rapid pace is difficult to analyze and yield productive decisions using the traditional tools like relational stores. NoSQL data stores stand as an alternative to deal with streaming big data. Though a wide set of NoSQL databases exist, column-oriented store Cassandra and document-based MongoDB are chosen to carry out the current work due to their simplicity and easy to set up environment. Both the chosen NoSQL databases are highly scalable with minimal security added at a single node level. However, the scalability exists at either load or retrieval levels but not both as desired by an enterprise to satisfy their end users and attain huge profits out of minimal investments. Moving toward this end, there is a need to design a system in which scalable load and retrieval operations with strengthened security is to be developed. Also, it is essential to enlighten the big data users to choose an appropriate NoSQL store among abundant available ones. Hence, in this work, Passphrase-Based REST API model is developed to enhance the security for huge scalable data. Among a huge set of NoSQL data stores, Cassandra and MongoDB are chosen to carry out the research which proved worth efficient in achieving better results for drastically increasing the number of records. Also, the proposed security implemented is to further strengthen the entire system from being tampered.
Heuristic Search for Tetris: A Case Study

Games represent important benchmark problems for AI. One-player games, also called puzzles, often resemble real world optimization problems and, thus, lessons learned on such games are also important for such problems. In this paper we focus on the game of Tetris, which can also be seen as a packing problem variant. We provide an empirical evaluation of a heuristic search approach for Tetris with the following goal: Having an effective heuristic function at hand, we want to answer the question how much the additional tree search pays off. We are especially interested if there is a so called sweet spot that represents the best ratio between score achieved and time invested in the search. This knowledge is crucial in order to be able to implement deep-learning approaches in the light of limited computing resources, i.e. to produce many good games to be learned from in rather short time. Our experiments reveal that such a sweet spot exists and hence, using this knowledge, only a fraction of time is needed for producing the same amount of learning data with similar quality.
Enhancing Asynchronous Linear Solvers Through Randomization

Asynchronous iterative methods present a mechanism to improve the performance of parallel algorithms for highly parallel computational platforms by removing the overhead associated with synchronization among computing elements. This paper considers a class of asynchronous iterative linear system solvers that employ randomization to determine the component update orders, and specifically focusing on the effects of non-uniform distributions. Results show that using distributions favoring the selection of components with a larger residual may lead to a faster convergence than that when selecting uniformly. In particular, in the best case of parameter choices, average times for the normal and exponential distributions were, respectively, 13.3% and 17.3% better than the performance with a uniform distribution.
Augmented Reality Application for Introduction Traditional House and Objects of Aceh

Abstract The traditional house is one of the highest culture of art value. Lack of knowledge about traditional houses and traditional Acehnese objects among the general public, making the cultural values of Aceh diminishing. Efforts to improve realization of Acehnese people to preserving a culture of Aceh, one of them is by making Augmented Reality technology as a medium to visualize traditional house and traditional Acehnese objects to be 3D animation. The method used in this research is marker based tracking. The software that used was Vuforia, blender 3D and unity. In this application, a user will find an animation traditional house of Aceh and 9 3D object traditional object of Aceh. Conclusions from the study are augmented reality technology can be applied to Android devices, with the best distance test results of a camera reading the marker is 20 cm to 60 cm and 0° to 40° for the best angle.
Commit Message Generation from Code Differences using Hidden Markov Models

Commit messages are developer-written messages that document code changes. Such change might be adding features, fixing bugs or simply code updates. Although these messages help in understanding the evolution of any software, it is quite often that developers disregard the process of writing these messages, when making a change. Many automated methods have been proposed to generate commit messages. Due to the inability of those techniques to represent higher order understanding of code changes, the quality of these messages in terms of logic and context representation is very low as opposed to developer written messages. To solve this problem, previous work used deep learning models -specifically, sequence-to-sequence models- were used to automate that task. This model delivered promising results on translating code differences to commit messages. However, after the model's performance was thoroughly investigated in previous work. It was found out that code differences corresponding to almost every high quality commit messages generated by the model were very similar to one or more training sample code differences on a token level. Motivated by that observation, a k-nearest neighbor algorithm that outputs the same exact message of the nearest code difference was proposed in previous work. Inspired by the traditional solution to sequence modeling; Hidden Markov Models, we show that HMMs outperforms sequence-to-sequence models without outputting the same exact message of the nearest code diff, our experiments show an enhancement of 4% against sequence to sequence models.
Research on Chaotic Digital Image Encryption Algorithm

Abstract In view of the problems of pseudo-randomness, complexity, short period and limited precision of traditional digital image encryption technology, this paper improves the traditional chaotic digital image encryption technology. Firstly, a random sequence is generated from the chaotic map according to the definition, and then the design process is improved according to the encryption algorithm, and finally the simulation experiment is performed. The improved algorithm uses the Henon-mapped chaotic sequence to generate the shuffle control parameters, and replaces the gray value with the improved two-dimensional Logistic map sequence, shuffles the array using the Henon map, and changes the image pixels using the improved two-dimensional Logistic map. Grayscale values, these algorithms are highly secure against exhaustive attacks, statistical attacks, and plain-text attacks. Even if the attacker knows the algorithm, it does not know the parameters of the algorithm and cannot obtain image information. The improved encryption algorithm can increase the key space and improve the security performance of the encryption algorithm. The image viewing effect is also very good, and the time is greatly shortened, which can fully meet the real-time requirements.
Measuring Content Complexity of Technical Texts: Machine Learning Experiments

Classifying texts by their content complexity is important for applications like adaptive foreign language reading recommender systems and information retrieval. The goal of this paper is to propose a computational model of technical texts’ content complexity based on three criteria: knowledge depth, required knowledge, and content focus. To implement this model, 28 features of content and lexical complexity were extracted from 1702 texts of three types: general blogs, science journalistic texts and research papers. The machine learning experiments showed that content features alone can provide high classification accuracy.
Tuning Parameters of the Koch and Zhao Stego Algorithm

This paper assumes that the Laplacian model is valid for the middle frequency DCT coefficients of a JPEG image and considers embedding with a two coefficient version of the Koch and Zhao stego algorithm. Under some mederate conditions, one can get a dependency of the cover image PSNR vs payload and embedding threshold. Employing some algebra allows us to substitute this bulk expression for an approximate but simple one. Next, solving the resulting equation for the embedding threshold, given PSNR and payload, yields us an approximate value of the threshold. On the other hand, by solving numerically the original, non-simplified equation, we get the math-model-accurate value of the threshold. Thus, it becomes possible to compare two threshold values (accurate and approximate). This comparison has been done for different texture-like images and results are listed below.
Region proposal-based semantic matcher

Unseen object detection problem is known as a semantic matching problem. Thus, a semantic matcher takes two images as an input – the request image and the test image. The request image represents an object class needed to be found on the test image. In this paper, we propose a new region proposal based semantic matcher. In our region based semantic matcher we use the same ideas as in R-CNN. Our Body CNN also generates proposals similar to classical Faster R-CNN, and Head-CNN compares proposals with a request descriptor, extracted from the request image. To extract features from the request image we use Request descriptor CNN. All three CNNs – Head, Body and Request descriptor are trained together, end-to-end for seen class object detection by request and then applied to both seen and unseen classes. We have trained and tested our CNN on Pascal VOC Dataset.
Effectiveness Evaluation of Sea-sky Joint Reconnaissance Force

Effectiveness evaluation of sea-sky joint reconnaissance force is an advantageous guarantee to acquire comprehensive advantages of information in off-shore non-military operations, but the fuzziness and continuity of qualitative and quantitative indicators in battlefield intelligence effectiveness evaluation can not be unified by traditional AHP method and fuzzy comprehensive evaluation method. Therefore, this paper uses cloud model theory to evaluate the effectiveness of the use of sea-sky joint reconnaissance force, and on the basis of establishing the effectiveness evaluation index system, realizes the transformation of intelligence factors from qualitative concept to quantitative numerical value. Finally, an example is given to verify the effectiveness and practicability of the effectiveness evaluation of the application of operational intelligence in offshore areas.
Adaptive T–S Fuzzy Control Using Output Feedback: SISO Cases

In Chaps. 5 and 6 , we have presented adaptive state feedback control designs for state-space T–S fuzzy systems with unknown parameters to achieve state tracking and output tracking, respectively. However, in reality, many systems may have states that are unmeasurable. For this situation, output feedback designs are more practical than state feedback. In this chapter, we consider adaptive output feedback control for discrete-time single-input single-output (SISO) T–S fuzzy systems described by input–output models.