Reviewerly/exHarmony huggingface dataset:
A Hybrid Data Reduction and Knowledge Extraction Algorithm for Quality Prediction

Background: With the explosive growth of the manufacturing data, the manufacturing enterprises paid more and more attention to dealing with the manufacturing big data. The manufacturing big data also can be summarized as "5Vs”, volume, variety, velocity, veracity and value. Recently, the researchers are focused on proposing better knowledge discovery algorithms to handling the manufacturing big data. Objective: The high dimensional data can be reduced from two directions. The one was the dimension reduction. It makes the data set simple and overcome the problem of curse dimensionality. This method reduced the data set form the data width. Methods: We proposed a hybrid data reduction and knowledge extraction algorithm (HDRKE) for quality prediction. There are 5 steps in the algorithm: Step 1: Data preprocessing; Step 2: Dimension reduction; Step 3: Extract SVs by SVM; Step 4: Extract rules from the subset; Step 5: Prediction by the rules extracted in step 3. Results: The presented HDRKE method reduced the data scales from the data dimensions and the data attributions. Then, the prediction method was used on the subset of reduced data. At last, the HDRKE method was applied to a enterprise sample, the validation of the method can be validated on the enterprise sample. Conclusion: Quality prediction and control was an important procedure in manufacturing. The HDRKE algorithm was a novel method based on the attribution reduction and dimensionality reduce. The data set simplified from double direction made the data set easily to calculate. The HDRKE method also proposed a new thought of decision rules extracting on the low-embeddings. The HDRKE method also applied to a manufacturing instance and proved its validity.
INTERPRETIVE INVESTIGATION OF THE USE OF AUGMENTED REALITY IN FAMILY ENVIRONMENT WITHIN CHILDREN'S PLAY THROUGH THE OPTICS OF QUALITATIVE METHODOLOGY

INTERPRETIVE INVESTIGATION OF THE USE OF AUGMENTED REALITY IN FAMILY ENVIRONMENT WITHIN CHILDREN'S PLAY THROUGH THE OPTICS OF QUALITATIVE METHODOLOGY
Algebraic attack on Zhang-Wang digital signature algorithm

Zhang and Wang presented a variety of digital signature scheme neither using message redundancy nor one-way hash function. There are many different varieties of attacks on Zhang-Wang’s algorithm, such as forgery attack, two’s complement vulnerability, misused precedence of operator and probability analysis of parameters so on. In this paper the authors will show the algebraic attack on Zhang-Wang’s algorithm. We believe it is necessary one-way hash function or message recovery on their scheme.
Educación y postconflicto: Bajo una mirada de pedagogía crítica, empoderamiento y emancipación.

This article aims to present a critical reflection on the possibilities and opportunities that teachers have in a specific context called Education for the Post-Conflict in Colombia. At first, emancipation is discussed as an opportunity for the transformation of educational roles. Then, the importance of the “empowerment pedagogy” is stated, based on critical thinking, as a crucial factor in the repair of the social bonds. Finally, a pedagogical proposal emerges to materialize the reflections on this subject.
Corporate Anti-Corruption Policy and MNE Location Strategy:The Contingent Role of Investment Motive

This study examines the impact of corporate anti-corruption policies on MNEs’ foreign investment strategy. We argue that self-regulatory measures against corruption will reduce the propensity of a firm investing in countries with high levels of corruption. We also propose that the differences in foreign investment motives and firms’ operating experience will moderate the deterrent effect of anti-corruption policies. Our analysis of overseas production investments by Japanese firms (2011–2017) supports our main theoretical predictions. We find that firms that had implemented policies to curtail corruption and bribery were less likely to enter countries where corruption was prevalent. However, the deterrent effect diminished when a new subsidiary had an efficiency-seeking purpose or when the parent firm had accumulated extensive operating experience in other corrupt markets. In contrast, the deterrent effect was more prominent when a new subsidiary had a competence-creating purpose. These results not only directly contribute to the research on control of corruption in international business, but also have implications for research on corporate self-regulation more generally.
Design of Intelligent Medicine Box for Elderly People Based on Context Awareness and FAST Theory

Abstract Based on context awareness and FAST (Function Analysis System Technique) theory, this paper explored the needs of elderly users and designed an intelligent medicine box for them to provide more comprehensive health services. It defined context through context analysis method, combined four context factors to obtain human-machine interaction model, and built a functional tree through the FAST theory to analyze product design factors and functional transformation forms. Finally, this paper established a product shape matrix upon functional combination and human-machine relationship, and selected the best design scheme. Through a practical application to a case, the validity of context awareness and FAST theory hybrid approach and their technical feasibility and effectiveness was demonstrated, and an accurate mapping relationship between objective product performance and user needs was formed.
A scalable real-time many-shadowed-light rendering system

In this paper, we present a new shadow rendering system, with a number of novel design to support large amount of shadowed lights in a large virtual environment, with real-time performance on mainstream GPUs.
PENGEMBANGAN MEDIA AUDIOVISUAL BAHASA KRAMA ASPEK KETERAMPILAN MENYIMAK PADA MATA PELAJARAN BAHASA JAWA KELAS IV DI SEKOLAH DASAR

This research is motivated by facts in the field, the use of Javanese language manners increasingly makes it difficult for students to understand the stories read so students are less interested in learning to listen to cultural environment stories, teaching materials for listening only come from books so there is no variation in learning, and teacher limitations. in developing media due to lack of time. The purpose of the study (1) was to know the process of developing audiovisual media in the language of aspects of listening skills in fourth grade Javanese language subjects in elementary school; (2) to find out the feasibility of audiovisual media in the language of aspects of listening skills in fourth grade Javanese language subjects in elementary school.  This research model is Research and Development (R & D) from Sugiyono, with research procedures up to step nine, namely: potential and problems, data collection, product design, product validation, design revisions, product trials, product revisions, usage trials, and final product revisions. The subject of this study was fourth grade students at Tanjungsari Elementary School. Data collection techniques using questionnaires, interviews and observations. Analysis of research data using qualitative descriptive techniques and descriptive statistics. The results of the study showed the quality of audiovisual media in the category of Good. These results were obtained from the results of 89% media expert calculations, 90% material experts, and 94% learning experts. While in terms of the feasibility of audiovisual media included in the category of Good / Very Worthy. This was obtained from a small group trial of 95.2% and a large group trial of 98.80%. The average of all assessments scored 93.24% with the category Good / Very Worthy.
Novelty Messages Filtering for Multi Agent Privacy-preserving Planning

In multi-agent planning, agents jointly compute a plan that achieves mutual goals, keeping certain information private to the individual agents. Agents’ coordination is achieved through the transmission of messages. These messages can be a source of privacy leakage as they can permit a malicious agent to collect information about other agents’ actions and search states. In this paper, we investigate the usage of novelty techniques in the context of (decentralised) multiagent privacy-preserving planning, addressing the challenges related to the agents’ privacy and performance. In particular, we show that the use of novelty based techniques can significantly reduce the number of messages transmitted among agents, better preserving their privacy and improving their performance. An experimental study analyses the effectiveness of our techniques and compares them with the state-ofthe-art. Finally, we evaluate the robustness of our approach, considering different delays in the transmission of messages as they would occur in overloaded networks, due for example to massive attacks or critical situations.
Seaberg – jazzpionjär med gotländska rötter

Short biography of the Swedish American clarinetist Artie Seaberg (1904–1957) who played with the Original Dixieland Jazz Band 1920–1925.
Η συμβολή του βιβλίου χωρίς λέξεις στην ανάπτυξη της σημασιολογικής ικανότητας στη δεύτερη/ξένη γλώσσα

This article develops the question of the contribution of wordless narratives in foreign language teaching and the effective use of image in speech improvement and semantic competence. In particular, the interest of this work focuses on how wordless picturebooks promote the development of the semantic competence of students as independent and competent users of a foreign language and, at the same time, how a wordless narrative can contribute to the development of literacy. In the context of this problematic, we will examine the contribution of wordless picturebooks to control the organization of meaning according to the three levels of reading (denotation, connotation, interpretation), as well as the development of related teaching activities enhancing understanding and interpretation skills and improving production skills.
QUERY OPTIMIZATION WITH WEIGHTED FISH SCHOOL SEARCH IN ONTOLOGICAL DATABASE WITH APPLICATION OF BOINFORMATICS

Making queries from large ontological database has a severe problem of generating query plans as it is made in form of left tree search form. This restricts the querying for composite applications and speed of acquiring query results. In such a scenario the most prominent approach is to optimise the indexing of graph nodes in ontological database and many evolutionary and particle of swarm optimisation (PSO)-based approach had already been attempted. However, loss of diversity and unanticipated convergence causes the solution to remain sub-optimal. In this study we present a weighted fish school searching-based query optimisation technique owing to its scalability and self control functioning with the application of bioinformatics. It creates probabilistic logic-based weight system for the fish school search in a hierarchical tree form which results in increased accuracy when put in comparison with standard PSO-based methods and its other variants.
A New Multiple Information Fusion Approach for Astronomical Navigation using Markov Random Field algorithm

Autonomous navigation is one of the key technologies to ensure the implementation of deep space exploration mission. Astronomical angle measurement information and stellar spectral velocity measurement information are usually used to estimate the real-time navigation state. According to the characteristics and requirements of deep space navigation, this paper proposes a novel method for information fusing using Markov Random Field approach, which integrates the navigation information including angle measurement, velocity measurement and combination of angle and velocity measurement, to realize continuous autonomous, real-time and high-precision navigation of deep space exploration. Considering the background of Mars exploration engineering mission, the observability and precision of the navigation method are analysed. The simulation results show that the method based on Markov Random Field can greatly improve the observability of the navigation system, effectively suppress the influence of measurement error, further improve the accuracy of navigation estimation, enhance the reliability of the navigation system, and provide a new technical approach to realize the high precision autonomous navigation of deep space exploration.
Forecasting GDP in ASIAN Countries Using Relevant Vector Machines

The relevance vector machine(RVM) is applied to predict  GDP, the highly important measurement of national economic growth, of some ASEAN countries (Malaysia, Thailand and Singapore) for comparison with the autoregressive model (AR(p)). The results show that RVM dominates the AP(p) model by measuring the error (MAE, MAPE, MSE and RMSE) from both training data and validation data.
Assessing K-Nearest Neighbours Algorithm for Simple, Interpretable Time-to-Event Survival Predictions Over a Range of Simulated Datasets

Survival prediction is a key task in medicine. Existing models are based on statistical techniques, such as the Cox models and there is limited work on the application of machine learning. In this paper we demonstrate that the K-Nearest Neighbour algorithm can be used for survival prediction. We show that its performance is as good as that of standard techniques, and that it provides a clear interpretation of the results. We show that pre-processing methods improve performance, and evaluate the performance across 20 different datasets with differing properties to show that the model performs well under various conditions. For low event rate datasets we show that KNN can outperform the Cox model.
The Effect of Information Technology - Based Game on Fifth Graders’ Critical Thinking Skill

This study aims to describe the effect of information technology-based game media on critical thinking skill of fifth graders on social studies subject under the theme of the Indonesia’s struggle for independence.
Interpretable Patient Trajectories from Temporally Annotated Health Records

By a trajectory, in the medical world, we mean the sequence of clinical events that occur to a patient in some time frame, as implicitly stored in patients' Electronical Health Records. A set of trajectories can be summarized in a trajectory graph, whose paths contain the most common trajectories followed by patients. The graph contains events on its nodes and the edges indicate the temporal relations. Previous works on building trajectory graphs only allow for one event at each node, and conversely for an event type to appear in only one node, thus losing information and potentially mixing different groups of patients. Here we develop a procedure to extract the trajectory graphs that goes beyond both limitations, thus more accurately reflecting the original dataset. In addition, it is close to a notion of patient state which clinicians use intuitively, facilitating interpretation. We evaluate the procedure on two real-world datasets, one related to diagnostics at hospital admissions, and the other on prescriptions in intensive care units, with reasonable and potentially useful results. The method is described here in the medical context only, but it is of general applicability for sequences of events.
A Rich-label Constituency Tree for Constituency Parsing

In this paper, we propose to improve the performance of constituency parsing by incorporate information from dependency trees. Our main contribution is a simple method to combine the information in the two type of trees, which is able to resolve discrepancies between them. This results in a new method to improve constituency parsing performance that is orthogonal to exiting methods, such as using pre-trained word vectors and using external training data. With existing dependency tree conversion tools and exiting constituency parsers, we show by experiment that our method achieves performance on top of a state-of-the-art constituency parser.
Operationalizing “public debates” across digitized heterogeneous mass media datasets in the development and use of the Media Suite

In this paper, we propose a methodological operationalization of “public debates” as we focus on the research process of CLARIAH research pilot Debate Research Across Media (DReAM). In this pilot, heterogeneous datasets (of digitized print and audiovisual media) were made search-able with tools of the CLARIAH Media Suite, using the leveled research approach that we coined previously (combining distant and close reading) to do historical public debate analysis. The qualitative research interest in public debates on drugs and regulation is historical, but in order to bridge the gap between distant and close reading of the combined digital datasets, a number of insights from media studies is taken into consideration. The natures of the different media, the type of analysis and focus on the source material itself, and the necessity to combine historical expertise with a sensibility towards discursive relations are all considered before we argue that the accommodation of this approach in the Media Suite helps the researcher to gain an improved understanding of historical public debates in mass media.
Гибридная система управления движением безэкипажного судна в заданную точку

The aim of the study is elaboration of control algorithms for an unmanned vessel movement in uncertain environments. The mathematical model of the unmanned vessel is based on the equa-tions of motion of a solid body. In the article three modes of movement are considered. The first mode is a terminal movement to a given point. The second mode is homing in a given area of the point. The third mode is obstacle avoiding. It is necessary to ensure smooth transients. Base multi-mode controller is designed by the position-path attitude of a movement control. In this study a novel algorithm of the references calculation is proposed. The algorithm changes the mode in a planning level. The low level single controller is used for the considered modes of a vessel motion. In the mode of terminal control a vessel velocity reference is calculated as function of the distance to the homing point and the given time of movement. A problem of terminal control is solved as a problem of weak terminal control. A weak terminal control problem introduces the error of a vessel homing. This error eliminates a singularity at the homing point. In the homing mode the vessel velocity reference is calculated as function of the distance to the homing point. The vessel velocity reference is the proportional function of the distance to the homing point. In the obstacle avoiding mode the vessel yaw is corrected by additional component. This component is solution of the addi-tional differential equation. The solution is stable if distance from the vessel to the obstacle is more than the safety distance. The solution is unstable if distance from the vessel to the obstacle is less than the safety distance. Composition of the different modes is made by fuzzy logics algo-rithms. Developed fuzzy logics based algorithms smooth the transients, and eliminate the singular-ity at the homing point. Asymptotical stability of the origin of the closed control system is proved. Presented results are demonstrated by simulation. Developed algorithms are implemented in the control system of mini vessel.
Measuring the Effect of Packet Corruption Ratio on Quality of Experience (QoE) in Video Streaming

The volume of Internet video traffic which consists of downloaded or streamed video from the Internet is projected to increase from 42,029PB monthly in 2016 to 159,161PB monthly, in 2021, representing a 31% increase in the Compound Annual Growth Rate (CAGR).The market for mobile network operators is unpredictable, fast-paced and very competitive.End users now have more options when choosing service providers.With superior network Quality of Experience (QoE), service providers can increase margins by charging more for better quality.Packet corruption occurs when the receiver cannot correctly decode transmitted bits.This study identified the threshold at which the QoE of video streaming services became unacceptable due to the effect of packet corruption.In this paper, several experiments were carried out on video streaming services, creating disturbances to evaluate the user satisfaction level using the mean opinion scores.Network Emulator (NetEm) tool was used to create the packet corruption experienced during the video sessions and the QoE for different packet corruption percentages was established.From the experiments conducted, we found that user QoE decreased as the Packet Corruption Ratio (PCR) increased.With knowledge of the effect of the PCR, service providers can ensure that the PCR is kept within acceptable limits from end-to-end and this will ultimately lead to superior QoE from end users, which will in turn translate to improved subscriber base and profitability.
Scramble and Transform: An Image Data Hiding Technique

Security is the most important concern in steganography which means hiding from visual or statistical attacks. Current steganography methods usually embed the secret data in the spatial or transform domains. Modern steganalysis methods extract features from different possible domains in which the data is hidden. To provide a high secure steganography method, this paper proposes to hide data in a secret domain. The secret domain is achieved by scrambling the image in the spatial domain and then applying integer wavelet transform. The message bits are embedded in the LSBs of randomly selected wavelet coefficients. Applying inverse wavelet transform and unscrambling, the stego image in the spatial domain is obtained. Experimental results were carried out on BOSSbase 1.01 database, and the results are compared against LSB matching (LSBM), highly undetectable stego (HUGO) and spatial embedding of universal wavelet residual distortion (S-UNIWARD) steganographic methods.
ARMS: A Developing Metadata Standard for Describing Astrobiology Research Products

These presentation slides introduce the Astrobiology Resource Metadata Standard (ARMS), a new metadata standard under development at NASA Ames Research Center, in conjunction with the Astrobiology Habitable Environments Database (AHED) project. The intent of this standard is to enable uniform, internet-based search and discovery of astrobiology 'resources', i.e. virtually any product of astrobiology research, including datasets, physical samples, software, publications, websites, images, video, presentations, etc. The current draft of ARMS defines 16 different metadata properties used to describe a given resource, including routine information such as name, resource type, description, personnel, funding, and related publications. But the true power in ARMS lies in four astrobiology-specific pieces of metadata: field site location enables geospatially-restricted search for resources using placenames or geospatial coordinates; research theme associates resources with one of six broad areas of astrobiological research (as identified in the 2015 NASA Astrobiology Strategy document); astrobiology disciplines captures the set of science disciplines most relevant to creation or use of resources; and finally, astrobiology keywords characterize resources in much in the same summarizing way that journal article keywords describe publications. An initial draft of the ARMS standard is being prepared for circulation to the astrobiology community for feedback and revision.