Reviewerly/exHarmony huggingface dataset:
Attention-driven tree-structured convolutional LSTM for high dimensional data understanding

Modeling sequential information for image sequences is a vital step of various vision tasks and convolutional long short-term memory (ConvLSTM) has demonstrated its superb performance in such spatiotemporal problems. Nevertheless, the hierarchical data structures (e.g., human body parts and vessel/airway tree in biomedical images) in various tasks cannot be properly modeled by sequential models. Thus, ConvLSTM is not suitable for analyzing tree-structured image data that has a rich relation among its elements. In order to address this limitation, we present a tree-structured ConvLSTM model for tree-structured image analysis which can be trained end-to-end. To demonstrate its effectiveness, we first evaluate the proposed tree-structured ConvLSTM model on a synthetic Tree-Moving-MNIST dataset for tree-structured modeling. Experimental results demonstrate the superiority of the tree-structured ConvLSTM model for tree-structured image analysis compared with other alternatives. Additionally, we present a tree-structured segmentation framework which consists of a tree-structured ConvLSTM layer and an attention fully convolutional network (FCN) model. The proposed framework is validated on four large-scale coronary artery datasets. The results demonstrate the effectiveness and efficiency of the proposed method, showing its potential use cases in the analysis of tree-structured image data.
Design Principles and Action Reflection for Agent-Based Assistive Technology

This paper is aimed at formalizing the interplay among a person to be assisted, an assistive agent-based software, and a caregiver. We propose general principles for designing the interplay between a person to be assisted and an agent based on formal argumentation theory to characterize the agent’s reasoning processes. These principles emerge from a novel perspective to understand assistive technology using the concept of zone of proximal development (ZPD) from social sciences. ZPD can be understood as a measurement of activity development, comparing what a person can perform with or without external help. We characterize a rational agent in four ZPD zones: (I) independent activity execution, agent takes no action; (II) $$ ZPD_H $$ : a person supported by another person, agent takes no action; (III) $$ZPD_S$$ : a person is supported by an agent; and (IV) $$ ZPD_{H+S}$$ : a person is supported by a caregiver and a software agent at the same time. An algorithm was developed for the agent to reason about the actions to be selected in different situations, based on formal argumentation theory for allowing non-monotonic reasoning. The formal models and algorithm were implemented in a prototype system using augmented reality as interface. Future work includes evaluating the principles and algorithm in actual use situations.
Speckle patterns for multiscale monitoring of deformation

The strain sensitive patterns (SSP) play an important role in digital image correlation (DIC) techniques. An unsuitable chosen speckle patterns may result in inaccurate results. A new SSP based on multiscale of the speckle sizes is proposed in this work. A brief description of its synthesis algorithm is presented. An algorithm is proposed for evaluation of effectiveness of speckle pattern used for multiscale monitoring of in-plane displacement and strain fields. Eight different structures computer generated are studied. The images of these patterns are numerically deformed as to simulate rotation or one axis tensile. Cross-correlation between each pattern and its deformed state is found. The patterns’ quality is evaluated and presented in tabular and graphical form. SSP containing features appropriate for both high and low magnification is chosen as a result.
Towards Combined Process &amp; Tool Variability Management in Software Testing

Context. Modern software engineering approaches that rely on continuous and automated testing, like Agile Software Engineering and the late DevOps movement, require integrated and fully functional testing tool chain environment, to efficiently identify defects in software artifacts. Such an environment includes the implementation of established testing processes that are utilized by the development teams. However, in practice, different testing tool chains and processes are implemented depending on particular project requirements such as programming language, selected testing tool, or system architecture. This variety of required technologies and processes frequently results in an environment of isolated test automation solutions. Thus, there is a need for a managed and controllable set of testing tool chain variants that consider structured methods to integrate variability. Goal. In this paper, we show ongoing work, as part of a flexible Test Automation Framework (TAF), with focus on requirements for the variability of testing tool chains, established testing processes, and candidate solution approaches. Method. We build on best practices from software and systems testing and variability management to implement variability in the TAF. Results. First results showed that several Test Automation (TA) solutions exist, which support variability in a limited manner and, therefore, increase the need for modeling variability in a flexible TAF. Conclusion. In the context of Software Test Automation, a combination of Variability Modeling (VM) methods for testing architectures, business processes, and a definition of common interface definitions is promising towards a TAF that enables a flexible tool and process integration.
Diffractive optical elements investigation in the phase domain

In this work we demonstrate the advantages of investigating diffractive optical elements in the phase domain. In this regime we can detect features that are not restrained by the diffraction limit and relate them to the geometrical and optical properties of the sample under test. To accomplish that, we use the custom made spectral high resolution interference microscope. Phase map recordings allow for easier and more precise localization of the positions, where phase changes happen. We show the localization capabilities by detecting phase singularities created by a trench. We also apply the concept to abrupt phase jumps of a phase diffractive component and determine the achievable resolution.
Kontseptual'nye osnovy formirovaniia kul'tury zhizni v obrazovatel'nom prostranstve vysshei shkoly

In the article from the position of acmesynergetic and socio-cultural approaches with the help of general theoretical methods of research of pedagogical problems and included monitoring of the processes of socialization, acculturation and acmeologization of university students the key concepts of formation of the culture of life of students in the educational space of higher education were developed and justified.
Spatial Distribution and Source Identification of Loess Heavy Metal Pollution in Northern Baoji, China

The spatial distribution of heavy metal pollution in loess is an essential prerequisite and scientific basis for detecting and evaluating the quality of loess ecosystem and the sustainable development of regional environment, but lack of research in special soil such as loess. Distribution characteristics and pollution sources of heavy metals in the northern loess area of Baoji is studied by means of geo-statistics and cluster analysis. The results showed that heavy metal pollution still existed in this area, and the pollution in Changqing town was obviously higher than the surrounding area. Consequently, different management strategies can be adopted in the loess area to reduce the contamination load of heavy metal, and attention should be paid to human activities, such as mining, transportation and gas emission, especially.
Determining Frequent Item Sets using Partitioning Technique for Large Transaction Database

Objectives: Mining of frequent item sets in transactional databases has been in widely use since years.This traditional technique involves mining of frequent itemsets on the entire set of records present in the transaction database at once.This has been causing performance issues such as out of memory, large turnaround time for the computation.The aim of the study is to propose suitable technique to overcome memory issues, reduce overall turnaround time and enable the determination of frequent item sets based on specific season or a time period.Methods/Analysis: Frequent item sets mining can be used for decision making in large number of real-life applications.With the growth in amount of data, quite a number of FIM (frequent itemset mining) approaches were proposed to meet the requirements of scalability.However, some existing approaches have met this requirement to some extent; they require high consumption of CPU and memory.In this study, we present another approach, named FIMUPT (frequent itemset mining using partitioning technique).The proposed technique eliminates processing of all records at once; instead it processes the records in small chunks in multiple increments.This technique makes various partitions of relevant size from large transaction database.It processes the partitions one after another instead of large transaction database.This scheme also has a provision to pass support threshold values for various partitions.Every partition of transaction database can be mapped to a season or a time period as needed.Findings: We observed that the proposed techniques perform very well in terms of computational time and memory usage.Size of the partition is decided based on the total number of transactions present, size of main memory and time period applicable for the entire transaction database.It consumes less memory since partition size is less compared entire transaction database.As the single partition is processed at once in the memory, it eliminates large memory needs of traditional technique [reference Wikipedia].We have used sample dataset from the data mining library source spfm which is an open source.The size of the data sets we have used are 50MB and 100MB.Algorithms such as Apriori failed to run on 100MB datasets throwing out of memory error.Applications: However, with the partitioned approach successful executions were observed.Our test environment produced 15 partitions of entire transaction database.It concludes that with less memory size, we can process larger number of transaction records to perform data mining tasks.When compared with the existing approaches, experimental results tell that FIMUPT gives a performance gain of 19% on average.This technique eliminates out of memory issues seen in Apriori algorithm and its variant algorithm.
A Pattern Language for Knowledge Handover When People Transition

Handover of knowledge and responsibilities can cause problems when people transfer to other parts of a company or retire. Handover issues became apparent in Japan when many people from the Baby Boomer Generation retired simultaneously in 2007. In particular, this was a resounding issue in the software industry. Most business people are familiar with the concept of a handover. Although effective handovers are crucial for seamless business operations during personnel changes, the preferable elements for a handover are ambiguous. In this paper, we outline a “Pattern Language for Knowledge Handover when People Transition”. The pattern language consists of handover patterns. Actual handover patterns were pattern mined from our experience as well as from industrial interviews. We originally started with handover anti-patterns which identify actual problems for a handover. This led us to pattern mine the handover patterns that provide strategies to mitigate these problems. The examples are from software industry, but these patterns are applicable to other domains.
Communication space in the library and information sphere

Specific features of the communication space in the library and information sphere are discussed. The communication process players and factors are named. The communication space scheme for the library and information sphere is proposed. The scheme comprises: library and information staff, target audience (users), partners, and regulatory authorities. The formal and informal communication channels are characterized and compared with their advantages and drawbacks named. Several procedures for choosing communication channels relevant to target audience are proposed to increase effectiveness of the communication process and validity of communicant-recipient information transfer. Optimum communication channel selection stages and factors are characterized. Communication barriers due to wrong communication channel and their negative consequences for the communication process are described. Knowledge of the communication space in the library and information sphere and communication channel selection algorithm enables to exclude the communication barriers.
Real-time Optimization of Cooling Units in Data Center Utilizing Cordination Systems with ICT Equipment

In this paper, we investigate optimal management of a data center cooling system in coordination with ICT equipments. In recent data centers, a system manager has become able to access data in servers such as equipment temperatures, power consumption, fan rotation speeds and computational loads. The technological advance would allow one to model the cooling process more accurately and to feedback online data to control algorithms for air conditioning units, which would contribute to enhancing energy efficiency for the cooling system. In this paper, we first model the cooling process based on the above data and then formulate an optimization problem to be solved at a certain time interval to determine the reference set-point of the air conditioning units. The real-time optimization scheme is then demonstrated on a real data center cooling testbed.
School Culture and Instructional Leadership: A Comparison between High-Performing and Low-Performing Urban Secondary Schools

In the school setting, instructional leadership has been asserted as the most crucial type of leadership that is closely linked to professional culture in schools. The main reason is that instructional leadership pertains to the core functions of education, instruction, and learning in classrooms, which also directly constitute as the main components of school culture. The purpose of the study presented in this paper was to examine and analyze the patterns of differences and relationships between instructional leadership and school culture of some high-and low-performing secondary schools. This study found that the school culture and instructional leadership of high-performing schools were markedly different from that of the low-performing schools. In high-performing schools, the school heads maintained positive attitudes toward students, staff, and parents; created a school culture and climate conductive to learning; and predominantly emphasized teachers’ professional values and collegiality. The findings imply that a school head should establish clear school vision and mission, set professional goals for staff, and build a two-way communication channel with teachers. School heads also should set high expectations on teachers and students, and create a positive school culture and climate of learning.
CONTENT BASED IMAGE RETRIEVAL TECHNIQUES FOR RETRIEVAL OF MEDICAL IMAGES FROM LARGE MEDICAL DATASETS – A SURVEY

In this computing era, data are represented as images that are to be processed for retrieval.Need for high accuracy in retrieval made this area more challenging.Content Based Image Retrieval system uses features of query image with that of an existing database image set for retrieval using precision and recall ratio.Features of images include color, shape, texture, etc. Techniques for retrieval include histogram, wavelength transformation, statistical methods, Euclidean distance, etc. Color feature though forms the fundamental image feature for retrieval techniques, other features are also considered to be more important and necessary as they play vital role in retrieval process.Many programs and tools have been developed to formulate and execute queries.CBIR researchers need to improve precision rate (accuracy), that lead to variation of search ranges and search object increment.This in turn brought about the combination of two or more features for efficient retrieval.Together with features, today's research is highly concentrated on image set with large varied databases, documents of differing sorts and with varying characteristics that have high social implications.The image set can be motion or motionless.Earlier research concentrated on motionless images in CBIR while motion images are also considered in recent years.This paper presents the literature survey on recent medical image retrieval techniques.
Development of Rough Terrain Mobile Robot Control Strategy Capable of Position and Direction Estimation by a Single Marker

In the present study, a mobile robot control strategy of rough terrain capable of position and direction estimation by a single marker was proposed, and the effect was performed. To realize wheel / caterpillar mobile robot movement on the rough terrain such as house farm, two major problems (1) the precise position estimation and (2) the direction estimation are important before the development of the control theory. Generally, the position / direction have been estimated by the wheel rotation (odometry) and gyro or acceleration sensor's output integration, but there are many problems such as many impacts from the ground and the wheel slipping on the rough ground to the precise estimation. The aim of this study is to develop a method (algorithm) to estimate the mobile robot direction using a single marker placed at the top of the robot by changing the front movement and the target direction movement periodically. The reason using a single marker is that it is difficult process to find and analyze positions of the many markers attached on the robot in the camera image from a long distance, and the positions of many markers have been unstable by the tilting of the robot, agricultural product's shadow, getting dirty of the body and so on.
A Note on the Sidelnikov-Shestakov Attack of Niederreiter Scheme

The terminology “code based public-key cryptosystem” means that the algorithmic primitives of such public-key cryptosystems use error correcting codes. In papers [1, 2] methods of building such public-key cryptosystems have been suggested. The Niederreiter’s public-key cryptosystem [2] based on q-ary generalized Reed-Solomon codes was proposed in 1986, Sidelnikov and Shestakov [3] presented an attack on this public-key cryptosystem in 1992, showing its insecurity. By examining the attack algorithm, we note that one can change some redundant procedures to simplify the algorithm.
Features of the development of emotional representations of children in the process of familiarization with the nature of their native land

The author points out that for the full development of preschool children, psychological and pedagogical conditions are necessary that promote the development of the child's emotional sphere. One of the effective conditions is the use of effective methods of familiarization with the nature of the native land, which contribute to the development of emotional representations. Important conditions for the formation of emotional representations through familiarization with nature are: the organization of direct interaction with objects of nature in the course of observation and practical activity, the creation of situations for the accumulation and expansion of the experience of emotional representations associated with natural phenomena.
The Action Control Model for Robotic Fish Using Improved Extreme Learning Machine

To achieve fast and accurate adjustment of robotic fish, this paper proposes state prediction model based on the extreme learning machine optimized by particle swarm algorithm. The proposed model can select desirable actions for robotic fish according to precisely predicted states, “adjusting position” or “pushing ball” defined herein. Specifically, the extreme learning machine (ELM) is leveraged to predict the state of robotic fish, from the observations of current surrounding environment. As the outputs in ELM are varying with the randomly initialized parameters, particle swarm optimization (PSO) algorithm further improves the accuracy and robustness of the ELM by optimizing initial parameters. The empirical results on URWPGSim2D simulation platform indicate that the robotic fish tends to carry out appropriate actions using the state prediction model so that we can complete the game efficiently. It proves that the proposed model can make best use of the real-time information of robotic fish and water polo and derive fulfilling action strategy in various scenarios, which meet the requirements of motion control for robotic fish.
Generalized XOR non-locality games with graph description on a square lattice

We propose a family of non-locality unique games for 2 parties based on a square lattice on an arbitrary surface. We show that, due to structural similarities with error correction codes of Kitaev for fault tolerant quantum computation, the games have classical values computable in polynomial time for $d=2$ measurement outcomes. By representing games in their graph form, for arbitrary $d$ and underlying surface we provide their classification into equivalence classes with respect to relabeling of measurement outcomes, for a selected set of permutations which define the winning conditions. A case study of games with periodic boundary conditions is presented in order to verify their impact on classical and quantum values of the family of games. It suggests that quantum values suffer independently from presence of different winning conditions that can be imposed due to periodicity, as long as no local restrictions are in place.
Print or Electronic Course Readings: Implications for Library Space and Information Literacy Programmes

For several years, there has been a debate about digital vs. print format for study materials. The Academic Reading Format International Study (ARFIS) has shown that students clearly are in favour of paper, both in Norway and many other countries. These preferences have various implications not only for collection development decisions, but also for the availability of space in academic libraries. Study literature offered in digital format has huge advantages. It is not only more available, but makes it also makes it possible to free up much needed floor and shelving space in physical libraries. It also reduces the time and work spent on handling physical literature, from acquisition to re-shelving. So how can these advantages be balanced with students’ reading preferences? The authors discuss these challenges and suggest to developing training sessions on “How to use digital study literature?” Some Norwegian universities have already done this, and their results will be described.