Reviewerly/exHarmony huggingface dataset:
Modeling Massive Social Network Problem Solving via Network Goal Analysis vs. Social Network Analysis

It is critical for organizations and their members to get questions answered and problems solved in service of objectives and innovation. For this reason, many utilize social input from massive online platforms, such as Google, Facebook, Youtube, and Stack Overflow. We refer to such socially-sourced efforts as social network problem solving (SNPS). This study employed network goal analyses (NGA) to operationalize the answering linkages, which we refer to as goal striving (G) toward question goal nodes. NGA then models the system support (S) linkages to the goal striving. This is hypothesized to generate a distinct network landscape versus traditional social network analyses (SNA). Using Q and A data from the Operations Research community in Stack Overflow, we tested the predictive validity of the G and S distinction on question innovation importance ratings. Controlling for process variables, results confirmed the predictive validity of degree G and S (and G x S moderator) on goal node importance. Degree G also predicted goal node betweenness indicating that strong G behavior results in goal nodes having the shortest paths across the network. As hypothesized, NGA uncovered a more diffuse SNPS system than traditional SNA, thereby providing a new complementary approach to SNPS processes.
Character Design and Interaction - Effects on Social Presence in Virtual Reality

The use of innovative and engaging learning methods in various training contexts (e.g., leadership development) is steadily increasing. Video games have been shown to have positive effects on motivation and learning outcomes through the immersive experience they create, which can be further amplified by Virtual Reality (VR). Crucial to the perception of presence in VR is the acceptance of implemented virtual characters, which can be negatively impacted by the Uncanny Valley (UV) effect. We implemented a typical leadership scenario in VR and in an experimental study with a 2x2 between-subjects design, we examined effects of character design (cartoon vs. semi-realistic) and character interactions (handshake vs. no handshake) on social presence. Results (N = 51) show that interaction effects between character design and character interactions influence the UV (F(1,44) = 7.18, p = 0.01), which in turn impacts perceptions of social presence (F(1,44) = 12.25, p = 0.001). Social presence was especially pronounced when participants encountered the cartoonish character (M = 2.33, SD = .48) compared to the semi-realistic character (M = 1.87, SD = .48). Our findings advance the optimization of character design and interaction in VR implementations, not only for leadership development but training contexts in general.
Working with the API

Up until now, we've started to develop our blog by adding media, content, and the like. Developing our blog in this manner is perfect, but there may come a time when we want to take things further and – to coin a phrase – "spice things up a little."
Effective questions in referential visual dialogue

An interesting challenge for situated dialogue systems is referential visual dialog: by asking questions, the system has to identify the referent to which the user refers to. Task success is the standard metric used to evaluate these systems. However, it does not consider how effective each question is, that is how much each question contributes to the goal. We propose a new metric, that measures question effectiveness. As a preliminary study, we report the new metric for state of the art publicly available models on GuessWhat?!. Surprisingly, successful dialogues do not have a higher percentage of effective questions than failed dialogues. This suggests that a system with high task success is not necessarily one that generates good questions.
Control in the IoT: How to deal with various heterogeneous non-idealities?

In the last decades, in the broad field of Systems and Control several different paradigms have emerged to deal with the control of IoT-enabled cyber-physical systems. Indicative examples include: hybrid behaviour, quantized control, varying delays, safety-criticality, nonlinear control, etc. Although these are typically met together in IoT environments, the research activities have led to disconnected communities, and likewise very specific control techniques, that limit their implementability in a holistic framework. In a real-life IoT control application, these non-idealities take place all together. We will survey the main classes of nonidealities and recent results that link them separately to the quality of performance guarantees for control systems. We will raise the question of how these results can be merged in a holistic IOT-control paradigm.
COVID-19: Revisión de evidencia de una pandemia en evolución

COVID-19 is a new disease, caused by a virus first identified just over 3 months ago, and therefore the evidence is developing and rapidly changing, with dizzying production of scientific literature every day. This review seeks to synthesize the information available to date about certain relevant aspects of the disease, understanding that everything written is subject to change as our knowledge of it advances.
Noise Reduction Framework for Distantly Supervised Relation Extraction with Human in the Loop

Distant supervision is a widely used data labeling method for relation extraction. While aligning knowledge base with the corpus, distant supervision leads to a mass of wrong labels which are defined as noise. The pattern-based denoising model has achieved great progress in selecting trustable sentences (instances). However, the writing of relation-specific patterns heavily relies on expert’s knowledge and is a high labor intensity work. To solve these problems, we propose a noise reduction framework, NOIR, to iteratively select trustable sentences with a little help of a human. Under the guidance of experts, the iterative process can avoid semantic drift. Besides, NOIR can help experts discover relation-specific tokens that are hard to think of. Experimental results on three real-world datasets show the effectiveness of the proposed method compared with state-of-the-art methods.
Arduino-based Charity Box Safety, Tracking, and Counter System

&lt;p&gt;The charity box is a supporting facility that can be used by pilgrims to distribute their infaq. In this modern era, it turns out that the mosque still counts the contents of the charity box manually and uses the usual padlock key for the safety of the charity box. The purpose of this research is to build a system and tool that can simplify the performance of mosque administrators in counting money and maintaining the security of the charity box. ArduinoBased Charity Box Safety, Tracking, and Counter System is a charity box equipped with automatic counting and security features using RFID and GPS. The method used in making this system is the waterfall method. The features in this system are automatic counting and security features using RFID keys, GPS, buzzers, and infrared sensors. This system is also equipped with a notification to the mosque management regarding the amount of money in the charity box and the location of the charity box using GSM / GPRS. From the testing of the system, it was produced that the Arduino-Based Charity Box Safety, Tracing, and Counter System was able to detect banknotes and coins well. The SMS feature also works well where there will be an SMS message regarding the amount of money and location of the charity box. The safety of the charity box is enhanced by using RFID, GPS, buzzers, and infrared sensors. From the user satisfaction test results obtained by the percentage of user satisfaction by 85%, which means the Arduino-Based Charity Box Safety, Tracing, and Counter System is quite attractive to users.&lt;/p&gt;
Cryptocurrencies: Protocols for Consensus

The novel feature of Bitcoin [N + 08] as a currency is that it is designed to be decentralised, i.e., to be run without the use of a central bank, or any centralised point of control.Beyond simply serving as currencies, however, cryptocurrencies like Bitcoin are really protocols for reaching consensus over a decentralised network of users.While running currencies is one possible application of such protocols, one might consider broad swathes of other possible applications.As one example, we have already seen
IMPLIKASI PENERAPAN PRAGMATIK ILMU BAHASA INGGRIS TERHADAP PEMAKNAAN BAHASA INDONESIA DI PERGURUAN TINGGI

This article will discuss Pragmatics in English for understanding Indonesian by studying the origins, contents and main theories of pragmatics which include speech act theory, conversation implication theory and relevance theory, then incorporating it into English teaching in universities to deepen students' knowledge about pragmatic science so as to avoid the use of pragmatic errors and increase students' pragmatic competence. After analyzing the three pragmatic theories based on case studies, it was found that pragmatic theory had an extraordinary impact on the practice of teaching English in tertiary institutions. By introducing relevant pragmatic theories in teaching English in tertiary institutions, it can describe the precise and clear meaning in English-Indonesian communication.
Geostatistical analysis for characterization of groundwater quality in Igbokoda coastal aquifers of Dahomey basin, Nigeria

Thirty one groundwater samples were collected in the study area and were taken to Adekunle Ajasin Research laboratory where each samples were analysed for 27 parameters. Anions were determined by titration, heavy metals by AAS and so, dium and potassium by flame photometer. Geostatistical techniques such as descriptive, correlation coefficient, cluster and factor analyses were used for the interpretation of large and complex hydrogeochemical data obtained from 31 groundwater samples from coastal aquifers in Igbokada area in Dahomey Basin, Nigeria. The purpose was to determine the spatial variability of groundwater and to identify their various sources of pollution. Pollutants in the groundwater are Oil and grease; iron and Mg2+ and Cl- due to saltwater intrusion from Atlantic Ocean. Cluster analysis classified water into three groups, fresh, intermediate and polluted water according their geochemical and location characteristics. There were 4 Factor analysis, factor 1 indicated high loading of magnesium and chloride ions that were responsible for the groundwater pollution and they are likely to be derived from saltwater intrusion, Factor 2, showed high loading of calcium and calcium hardness that were responsible for its temporary hardness. Factor 3, exhibits high loading of Na+ and K+ which may be due to saltwater intrusion, Factor 4, showed high loading of Mn+ and Zn+ which may be derived from ores, and low loading of SO42 . Groundwater here are good for drinking except those in locations 3, 4, 5, 20, 21, 21, 23, and 28 which were polluted and should be discarded for health reasons.
Entity recognition of Chinese bidding announcement title based on deep learning

Bidding announcement widely exists in Chinese government procurement websites at all levels in the form of text. Its composition is complex and the number is numerous. Identifying and extracting more concise project names is helpful to improve the ability of website data query and analysis. To solve this problem, this paper proposes a Transformer-att-label model based on deep learning. The model uses Transformer-att for feature extraction. It uses the attention mechanism to replace the original multi-head combination of Transformer, which can improve the recognition effect. And combined with tag embedding, predict the tag semantics of words, and select the tag closest to its semantics for output. The proposed model was tested on the announcement title data set of the Chinese bidding website, and the recognition effect of other mainstream models was compared to verify the effectiveness of the method.
GENDER BIASED IN TEXTBOOK’S PICTURE OF WEST BENGAL BOARD OF PRIMARY EDUCATION

Education prepares future generation to take their due place in the society. It becomes essential that substandard educational goal, materials and method of instruction are not retaining but up to date with the advance of social, cultural, and scientific field. Curriculum is the main root of action that can confirm the supply of effective and efficient human resource for the development of a nation and a progressive society. It helps to generate and to promote among the children’s language ability of listening, speaking, reading, writing, thinking, values, creativity, social interaction, positive attitude and create of atmosphere of co-operation, develop interpersonal relation, create to help academic and social relationship, communication skill for social living .Text books are the direct real and particular manifestation of curriculum and it is a key instructional media which play an important role in the field of education and the child mental and social development. The sense of sight processes the most unique place of providing knowledge of information of the environment suffering us in a most comprehensive and stable way that is why the knowledge gained through a picture of the object, person or event said to be 100 times better, than mere description in word. Picture in the textbook is a one of the main instructional media which help the student to understand the topic easily, it provide the clear structure for student, it influence the student learning and imagination, strength the visual thinking and allowing kids to connect how they reason with what they observed, child link concept with word. Picture shape children mind and help the teacher discussing story and picture help should always make the reading fun and enjoyable and affect on children effective domain and also it has been understood that textbooks are a basic vehicle of socialization, conveying Knowledge, values and also play a significant role in transmitting a society’s culture; it is also a tool for Social change because it disseminates universal values. Textbooks are very needful and potential vehicle for gender equality. The main objective of the study was to describe gender bias present in the textbook’s picture. It is a descriptive study. Through the purposive sampling the text book of class-V namely “BHASA PATH” which is prescribes by West Bengal Board of Primary Education was chosen. The visual content analysis method use for conducting this research paper. The data were analyzed quantitatively though percentage shown by table and graph and qualitatively the researcher give insightful, rational and realistic description of the textbook’s picture. The result of the study shows that gender is unequally presented in this textbook’s picture.
Girl With A Frying Pan

Author(s): Oliynyk, Mariya | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Reliability Engineering for Long-term Deployment of Autonomous Service Robots

Author(s): Wang, Shengye | Advisor(s): Christensen, Henrik I | Abstract: Current service robots perform flawless demos under close human supervision, but they often fail when working autonomously in long-term deployments. This dissertation studies the failures in long-term autonomous service robots and proposes methods to improve their reliability.We built TritonBot, a receptionist and tour-guide robot, as a realistic example to discover the failure modes of a long-term autonomous service robot. TritonBot recognizes people's faces, talks to people, and shows people the labs and facilities in a university building. We deployed TritonBot for hundreds of hours to identify failure modes and common issues on service robots.Following the experience from TritonBot, we designed two reliability engineering methods to improve the robustness of service robots. First, we found software encapsulation and dynamic orchestration streamline development workflows and avoid resource contention in service robots. Software encapsulation allows the developers to pack software into self-contained containers and simplify development workflows, and dynamic orchestration schedules the components on demand to avoid CPU/memory resource contention. We developed Rorg, a Linux container-based scheme to manage software components on service robots. Second, we found simulating a broad spectrum of rare failures at system level exposes design flaws and improves the robustness of service robots. Design errors in robotics are challenging to discover due to the need for extensive and resource-demanding testing. Broad-spectrum system-level failure injection exposes both software- and hardware-related design flaws and assists developers in reproducing rare failures, verifying the fixes, and testing the robustness of a robot system. We implemented RoboVac, an extensible and convenient fault injection framework that works at the system level and covers many failure patterns seen in long-term autonomous service robot deployments.After working with TritonBot for two years and implementing reliability engineering methods, we concluded a few design principles for a long-term autonomous service robot at different levels in the system hierarchy. These design principles guide robust and reliable long-term autonomous service robot designs.We use a set of automated tools, engineering methods, and design principles to build service robots that are available 24x7, and we call it Reliability Engineering for Long-term Deployment of Autonomous Service Robots.
EDUCATIONAL MULTIMODAL DATA MINING AND FUSION THROUGH KNOWLEDGE GRAPHS FOR TOPIC-RELATION EXTRACTION IN STUDY RECOMMENDATIONS

EDUCATIONAL MULTIMODAL DATA MINING AND FUSION THROUGH KNOWLEDGE GRAPHS FOR TOPIC-RELATION EXTRACTION IN STUDY RECOMMENDATIONS
Managing Software Project Risks (Implementation Phase) with Proposed Stepwise Regression Analysis Techniques

Regardless how much effort we put for the success of software projects, many software projects have very high failure rate and risks are everywhere in life. Risk is not always avoidable, but it is controllable. The aim of this paper is to present new techniques by which we can study the impact of different risk management techniques and different risk factors on software development projects. The new technique uses the stepwise regression to managing the risks in a software project and reducing risk with software process improvement. Top ten software risk factors (Implementation phase) and thirty control factors were presented to respondents. The results show that all risks in software projects were important in software project manager perspective, whereas all controls are used most of time, and often. These tests were performed using regression analysis to compare the controls to each of the risk factors to determine if they are effective in mitigating the occurrence of each risk factor and selecting best model. We referred the risk management techniques were mitigated on ten top software risk factors in Table XLVI. The study has been conducted on a group of software project managers. Successful project risk management will greatly improve the probability of project success.
Automatic modeling for Chinese ontology of safety risk knowledge in subway construction projects

Subway construction projects are usually large in scale, complex in technology, and long in cycle. These characteristics will make it difficult to share and reuse knowledge of safety risk in subway construction (SRSC). This paper develops a preliminary Chinese ontology automatic modeling tool (COAMT) to support the automatic acquisition of SRSC. First, SRSC is divided into 4 unified classes, namely, human behavior risks, equipment risks, environment risks, and organizational management risks, and the text information is used to collect knowledge. Then the information is preprocessed by natural language processing technology to obtain the asserted text information. Finally, the obtained assertions are added to the ontology with the support of cognitive operations, and the ontology is continuously expanded or modified to update the ontology knowledge base. In this paper, the COAMT can promote knowledge sharing and reuse between engineers and computer applications, and solve the problems of low efficiency and error-prone by manual modeling.
Self-Cultivation Methodology of Engineering Students and Its Application in the NEW ERA

In the New Era of Socialism with Chinese Characteristics, engineering college students face the practical needs of further improving their service will and capability.Selfcultivation can help this goal, because it has special advantages such as considering the student's internal world comprehensively, gradually cultivating moral qualities, and making students improve themselves as they wish, only if it is done faithfully and wholeheartedly.Therefore, based on practical experience, by integrating relevant theories and methods of the traditional Chinese culture excellence, Marxist philosophy, and psychology, we have established a modern methodology of the self-cultivation system for engineering college students, which taking a closed loop of self-perception and practice-testing as its core.This methodology starts from ideological concepts tested by long Chinese history, takes the improvement of physical, mental, academic, and social relations as the testing goal, and with method of guide-but-not-push, to promote the overall moral and humanistic quality of students.The application of this methodology has benefited both teachers and students, which will also expedite the creative transformation and innovative development of traditional Chinese culture excellence.
Some Statistical Applications of Generative Neural Networks

We present some examples of how the field of statistics can benefit from the Deep Learning movement.First, using generative neural networks (GNNs), we are now able to produce quasi Monte Carlo samples from "almost any" copula model.For example, we can do this even for mixtures of copulas with singular components.Second, using GNNs, we can now model and, most importantly, forecast multivariate time series without having to restrict ourselves to using only a few parametric copula families to describe the underlying multivariate dependence.We have empirical evidence that a better dependence model does indeed translate into better forecasts.(This is joint work with Marius Hofert and Avinash Prasad.)
BCK-codes Based on a Parity Check Matrix

Hamming codes are of primary concern in information theory and its applications. Despite a number of researches that have been conducted on such codes and their characterizations, dealing with the properties of previously introduced codes in a BCK-algebraic framework has not been considered in earl ier works. This paper investigates a code constructed based on BCK-algebraic models and proposes an algorithm corresponding to the presented code. It is noticeable that the suggested rendered algorithm is also established on the basis of the elements of a BCK-algebra. In fact, both the Hamming distance and dimension, associated with the presented code, can be estimated through a BCK-algebra structure due to the mechanism of its algorithm which is heavily dependent on the parity check matrix. In addition, the way in which the codes are designed contributes substantially to classification of them and to extract greater number of their attributes compared to the previous works. The highlight of the proposed method is that the number of atoms of the BCK-algebra plays a key role in calculation of the Hamming distance and dimension of these codes. Moreover, the obtained codes possess specified and recognizable Hamming distance which are essential in performing error-correcting, error-detecting and decoding tasks.
SJSU Research Guides: Library Research Scholars Program (LRSP): Welcome & About LRSP

This website provides information on the San Jose State University Library Research Scholars Program (LRSP).