Reviewerly/exHarmony huggingface dataset:
An Approach Enabling Various Queries on Encrypted Industrial Data Stream

Massive data are generated and collected by devices in the industrial Internet of Things. Data sources would encrypt the data and send them to the data center through the gateway. For some supervision purpose, the gateway needs to observe the encrypted data stream and label the suspicious data. Instead of decrypting ciphertext at the gateway, which is not efficient, this paper presents a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mi>Φ</mml:mi></mml:mrow></mml:math>-searchable functional encryption scheme that supports inner product evaluations on encrypted data. Based on this scheme, an approach enabling various queries on the encrypted industrial data stream is proposed. The adaptive security of our proposed underlying functional encryption scheme can be proven under general subgroup decision assumptions, and our scheme has the smaller public key, the smaller secret key, and the smaller ciphertext size compared to the related schemes. In addition, the experimental results show that our proposed scheme is efficient. Especially for the gateway, querying on the encrypted data only needs less than 20ms, which is practical for industrial data stream auditing scenario.
On the selection of the optimal topology for particle swarm optimization

In this paper, we deal with the problem of selecting the best topology in Particle Swarm Optimization. Unlike most state-of-the-art papers, where statistical analysis of a large number of topologies is carried out, in this work we formalize mathematically the problem. In this way, the problem is to find the best topology in the set of all simple connected graphs of n nodes. To determine which is the best topology, each graph in this set must be measured with a function that evaluates its quality. We introduce the concepts of equivalent neighborhood and equivalent topology to prove that for any simple connected graph there is an equivalent tree. The equivalence between two topologies means that each particle belonging to these has the same local best in both. Therefore, the problem can be simplified in complexity to find the best tree in the set of all trees with n nodes. Finally, we give some examples of equivalent topologies, as well as the applicability of the obtained result.
IVAN: An Interactive Herlofson’s Nomogram Visualizer for Local Weather Forecast

In 1947, N. Herlofson proposed a modification to the 1884 Heinrich Hertz’s Emagram with the goal of getting more precise hand-made weather forecasts providing larger angles between isotherms and adiabats. Since then, the Herlofson’s nomogram has been used every day to visualize the results of about 800 radiosonde balloons that, twice a day, are globally released, sounding the atmosphere and reading pressure, altitude, temperature, dew point, and wind velocity. Relevant weather forecasts use such pieces of information to predict fog, cloud height, rain, thunderstorms, etc. However, despite its diffusion, non-technical people (e.g., private gliding pilots) do not use the Herlofson’s nomogram because they often consider it hard to interpret and confusing. This paper copes with this problem presenting a visualization based environment that presents the Herlofson’s nomogram in an easier to interpret way, allowing the selection of the right level of detail and at the same time inspection of the sounding row data and the plotted diagram. Our visual environment was compared with the classic way of representing the Herlofson’s nomogram in a formal user study, demonstrating the higher efficacy and better comprehensibility of the proposed solution.
Detecting, Understanding and Resolving Build and Test Conflicts

Collaborative software development allows developers to contribute to the same project simultaneously performing different activities. Although this might increase development productivity, it also brings conflicts among developers contributions. Different kinds of conflicts can arise, but previous studies have often focused on merge conflicts. So we aim to further investigate build and test conflicts occurrence, that are conflicts revealed by failures when building and testing integrated code, respectively. For that, we intend to study the causes of build and test conflicts, their adopted resolution patterns, and the factors that are associated with the conflict occurrence. Based on these results, we plan to develop a tool for helping developers when resolving build and test conflicts. Our initial results, analyzing Java projects, show that most build conflicts are caused by missing declarations removed or renamed by one developer but referenced by the changes of another developer. We also verified these conflicts are often resolved by removing the dangling reference. Based on such finding, we developed a prototype that recommends fixes for these build conflicts.
The optimal solution to the problems by regression analysis

Problems are various possible and impossible questions, tasks and riddles that are being set up and attempt to solve in different ways.However, assuming that half of all problems are not solvable and that the remaining one-fourth cannot be defined, there are good chances for a successful mathematical solution to the second quarter of the problem.Problem-solving using regression analyses allows determining the relationship between the dependent response and the independent factors through defined regression functions, relationship estimates, predicting results, simulating data, optimizing the sizes, and improving the resolution process.Although there are many regression analyses, linear regression analyses are usually used.The author proposes the application of Procedure for selecting a significant regression analysis between 16 different regression analyses and Procedures for solving regression analyses.Using this approach in this release, an optimal solution of the problem of finding the optimal best sun exposure position for the solar collector is shown.
Towards an Extensible Architecture for Refactoring Test Code

As the software evolves, new codes are written, and many other codes are refactored. Refactoring also involves the test code, to ensure that it continues performed, and adequately verifying the behavior of the software. This work proposes the creation of an extensible architecture named EARTC to perform refactoring safely in test code. The coding of a specific refactoring for the test code is hampered by coupling to the unit testing automation framework so that it becomes desirable to eliminate this coupling from the refactoring code. The architecture proposed in this work implements extension points, which allows refactoring to be performed regardless of the test framework to be used, that is, other refactorings can be added to the architecture without the need to change the test code. Additionally, the architecture enables other testing frameworks to be coupled without interfering with their internal structure. To validate the independence among architecture modules, a Design Structure Matrix was done, which shows that the objectives were achieved. Also, to analyze the results of the proposed architecture in an experiment, a tool called Neutrino was implemented. The results obtained with Neutrino are satisfactory and show that the architecture meets the objectives described for the accomplishment of this work.
Micro-controlled EOG Device for Track and Control Military Applications

This paper presents a system with tracking and remote control capabilities for military applications. An electrooculogram and a micro-controlled system with wireless communication were developed as controller based on the eye movement. The system can be used as remote control for military purposes and also for soldier monitoring. A proof of concept to act and be tested as mouse pointer was implemented with reduced circuitry and PIC microcontroller in order to achieve low cost and low profile platform. Experimental results are shown to validate a prototype of the proposed system.
SelecWeb: A Software Tool for Automatic Selection of Web Frameworks

Web applications and services are fundamental to designing smart infrastructure and cities. Developers often use various development technologies when developing web or cloud applications. One of such major technologies is web frameworks (e.g., Rails, Spring, Django, and CodeIgniter), which permit developers to develop without worrying about the low-level details. Programmers may choose from a variety of web frameworks, and different languages that support them, each with its own strengths and weaknesses. Organizations work in different application domains and have diverse priorities and constraints with regard to the development of applications and services. In this paper, we propose an automatic tool, SelecWeb, for selecting a web framework based on a set of criteria and developer preferences. The set of selection criteria is developed by us and is a contribution of this paper. The tool currently uses analytic hierarchy process (AHP) for comparison, analysis, and decision-making. We provide a detailed description and analysis of the tool including a case study for web framework selection. Conclusions are drawn with design ideas on future extension of the tool using machine learning.
Augmented, Hyper-mediated, IRL

In this article, I explore how digital data collection in the context of the Berkeley-Abiquiú Collaborative Archaeology (BACA) project works, some of the affordances of this new-ish technology, and how they articulate with analogue art practices to achieve the goals of engaged research. Thinking with affordances helps me reflect critically on what digital data recording offers our research goals. In this case, the most important aspect of using digital data recording is how it changes our relationship to time. New orientations of research time created by such technology is an opportunity to engage creatively with how archaeology can represent complexity, produce embodied experience, and share senses of place through both digital and analogue practices. As archaeologists trying to think trans-humanistically, we need to reflect critically on digital technologies to produce engaged research. This is always a shifting target. New uses reveal new possibilities, and vice versa. But newness is not what makes an impact, a difference, or changes the way we do research together; what makes a difference is the result, effects, and affects of these affordances.
Hierarchically Non-continuous Regression Prediction for Short-Term Photovoltaic Power Output

Photovoltaic (PV) power generation utilizing clean solar energy is increasingly conducive to relieving energy crisis and environmental pollution. Affected by the fluctuation and uncertainty of meteorological factors, short-term PV power is volatile in nature, posing threats to power supply reliability and stability. Consequently, accurate PV production forecasting plays a vital role in steadily running and managing a power system. However, due to the intrinsic characteristics of variability and fluctuation in PV data, it is challenging to get acceptable output prediction via conventional regression methods. Moreover, the raw data in our regression task originates from a PV plant whose stored PV values are hierarchically non-continuous with conspicuously diverse classes, making it even harder to conduct precise prediction. In this paper, we propose a tree-based prediction model based on the XGBoost regression algorithm. The experimental results show that the proposed prediction model achieves the highest average forecasting accuracy and stable generalization performance, indicating its validity for hierarchically non-continuous short-term PV output prediction.
Matrix Model of Cognitive Activity as One of the Meta Basis of Digital Education

Due to the transition to informatization and digital education society focuses on self-education. Digitalization development will demand the search for meta basis in strategic and tactical approaches to education: there will be formalization of educational information adoption by step-by-step implementation of logical schemes of an approximate basis of actions. It is shown that the educational environment has a considerable impact on the preparation of competitive engineers. The education guidance, a workbook and the reference media on the studied subject are modern educational methodological support for creation of necessary conditions to provide sufficient achievement of theoretical material and practical skills to organize effective students’ self-work. The technology of the organization of self-educational students’ activity on the basis of matrix model of cognitive activity is rather simple and clear both for teachers and students, and can be applied to studying of any subject. By means of cognitive and activity matrix all volume of preparation material breaks into four modules, each of which has various level of complexity. The first module contains the simplest tasks of the first level of complexity, the second one includes the tasks of the second level of complexity, etc. Each module contains the optimum number of theoretical data and tasks, both with detailed stage-by-stage analysis and an explanation and for self-work. The presented discretization and formalization of development of the subject by means of matrix model of cognitive activity opens only one of possible ways to digital education.
Real-time Collision Avoidance for Unmanned Ships under Constraints of Rules

Real-time collision avoidance is a key problem in the design of unmanned intelligent mobile systems. In this paper, an improved artificial potential field method combined with the ”Maritime rules” is proposed for intelligent mobile systems with constraint of rules. As an example, the autonomous collision avoidance system for an unmanned ship is designed in detail and the simulation results are provided to verify the success of the proposed method.
A Time Efficient Threshold Based Ant Colony System for Cloud Load Balancing

To enhance the speed of data transfer and remote server working performances, the suggested algorithm accomplishes load balancing in virtual machines by maintaining high availability and avoiding downtime issues when a datacenter experiences heavy traffic. This result has been obtained through minimizing the average response time and datacenter processing time by decently scheduling the requests and balancing the incoming load between the VMs. To achieve so, a combination of two scheduling techniques, Ant Colony Optimization System coupled with Threshold implemented Load Balancer algorithm has been designed. This paper also brings up comparisons among various cloud task scheduling algorithms such as Round-Robin (RR) and Active VM Load Balancer with the proposed technique. All algorithms have been simulated using Cloud Analyst toolkit package. Experimental results showed that the proposed Threshold based ACO system outperformed other stated algorithms.
New Tab Page Recommendations Strongly Concentrate Web Browsing to Familiar Sources

To what extent do contemporary web technologies that seek to personalize users' browsing experience trap them in filter bubbles? Existing research has yielded mixed results on the possibility of such influence, but empirical research in this area has been entirely cross-sectional. In this paper, we report results from a longitudinal controlled web experiment conducted to determine whether passive recommendations embedded in common computer user-interfaces (UIs) reinforce users' habitual browsing behaviors, to the detriment of the diversity of the set of pages they tend to visit online. Inspired by classical demonstrations of a part-set cueing effect in memory, our experimental design manipulates the behaviour of the 'New Tab' page for consenting volunteers over a two month-long period in randomized time blocks of equal length. Analysis of their browsing behavior shows that users visit on average 15% fewer unique web pages while their browser's 'New Tab' page displays recommendations based on conventional frequency and recency-based algorithms, than if the display is left blank. This effect is seen systematically for all participants in our study. Further analysis of browsing behavior in this experiment clearly identifies the source of the difference between these modes of browsing: users consistently visit a greater diversity of web pages while typing in URLs in the URL/search bar when there are no recommendations on the 'New Tab' page. Finally, using a simulation study, modelling user behavior as a random walk on a graph, we extracted quantitative predictions about the extent to which discovery of new sources of information may be hindered by the concentration of browsing driven by such personalized 'New Tab' recommendations in classical browser UIs.
mLearning Versus Paper and Pencil Practice for Telling Time: Impact for Attention and Accuracy

The purpose of this study was to investigate the impact of mLearning or mobile device practice on the attention and accuracy of student's use of math concepts, specifically, telling time. A single subject, alternating treatment design was used to compare mLearning to paper and pencil practice in four 3rd grade male students. Results were mixed; two children were observed to be more on-task during the mLearning practice, and two children were observed to perform similarly across both conditions. Additionally, two children performed similarly on correctly completed problems across both conditions, and two children performed better using paper and pencil practice. All students completed more math problems during the paper and pencil practice.
Can Software Metrics Be Unified?

Software metrics produce discrete values as output from input source code as an indication of software quality. Many software have automated software metrics with different tools that are producing varying result. Measurement of software metrics cannot be said to be precise, repeatable and reproducible. This is consequent of varying definitions, design and implementation of the same software metrics, varying result, assessment and analysis of the same metrics from relative and personalized approaches to varying benchmarks, non-uniform definition of implementation contexts, software measurement terminologies and lack of standard reference and calibration with respect to the measure of “level of confidence” in software measurement. Several studies have proposed the unification of software metrics without necessarily looking at the underlying causes of these widely observed inconsistencies across existing metrics and their automated tools. This work identified pitfalls ways to minimize variances in the implementation of software measurements across contexts. From this stage of an ongoing research, we are determining the possibility of objectively unifying software metrics by closing the gap in observed sources of expressed variance and adoption of metrological approaches to software measurement.
Secure Key Agreement Model for Group Data Sharing and Achieving Data Deduplication in Cloud Computing

Safe along with sound knowledge deduplication will noticeably cut back the communication and storage outlay in server storage space services, and has potential application in our huge data-driven society. Existing knowledge deduplication scheme area unit naturally intends to also resist brute-force attacks or confirm the strength and knowledge convenience. In the existing system, key written agreement is a drawback. In the proposed system, to get rid of key written agreement drawback, we tend to implement block style based mostly on key agreement protocol to share knowledge in CSP. It allows multiple partners to freely distribute information in cluster. The proposed system is a chunk base-type contract procedure to wire numerous partners, which might supplely expand to amount of partners inside very CSP setting as per the construction of the chunk style, and to remove knowledge redundancy drawback we tend to use knowledge deduplication system within which knowledge owner can transfer file and send to cluster manager and cluster manager checks knowledge deduplication over native domain. In this, the approved person transfers knowledge over cloud environment to transfer file, and knowledge owner can send key request to key authority for secret key. Once the key is received from key authority owner can transfer file and send to cluster manager and check file deduplication on native domain and if file isn’t offered on native domain then send file to cloud. During access, the user can send key request to any or all cluster members and after receiving the key from cluster member, file can be transferred.
Under Sampling Adaboosting Shapelet Transformation for Time Series Feature Extraction

To predict for machine defects, a classifier is required to classify the time series data collected from the sensors into the fault state and the normal state. In many cases, the data collected by sensors is time series data collected at various frequencies. Excessive computer load is required to handle this as it is. Therefore, there has been a lot of research being done on the process of extracting features that are highly classified from time series data. In particular, data generated at real-world is unbalanced and noisy, requiring time series classifiers to minimize their impact. Shapelet transformation is generally effectively known for classifying time series data. This paper proposes a process of feature extraction that is strong for noise and over-fitting to be applicable in practice. We can extract the feature from the time series data through the proposed algorithm and expect it to be used in various fields such as smart factory.
A Model-Based Approach of Foreground Region of Interest Detection for Video Codecs

Detecting the Region of Interest (ROI) for video clips is a significant and useful technique both in video codecs and surveillance/monitor systems. In this paper, a new model-based detection method is designed which suits video compression codecs by proposing two models: an “inter” and “intra” model. The “inter” model exploits the motion information represented as blocks by global motion compensation approaches while the “intra” model extracts the objects details through objects filtering and image segmentation procedures. Finally, the detection results are formed through a new clustering with fine-tune approach from the “intra” model assisted with the “inter” model. Experimental results show that the proposed method fits well for real-time video codecs and it achieves a good performance both on detection precision and on computing time. In addition, the proposed method is versatile for a wide range of surveillance videos with different characteristics.
TourMAR

The importance of tourism industry as a major contributor to the economic state of countries all around the world has significantly increased. Tourism is not only a major source of employment, but also a catalyst for urban and rural development. The design architecture of the study would integrate tourism data based on the needs of tourist or travelers to mobile augment reality application. The design model of this application is important to make the app more interactive and the user experience is also considered. The use of this technology allows travelers or tourist to retrieve interactive multimodal data about the different tourist destinations. Two major components of the TourMAR application were determined which are the Content Management and Design principle of the MAR. These components are essential to study in this research in order to produce an effective MAR application. The content management enables to address the common problem on tourism data thru the implementation of data integration. The design principles enhanced the development considerations which is anchored on the user perspective that would improve user experience.