bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Feedback as Soft Scaffolding on Ongoing Assessment Toward The Quantum Physics Concept Mastery of The Prospective Physics Teachers
Authors: Abdurrahman A. , Saregar A. , Umam R.
Published: July 2018

Many recent studies have reported that feedback plays a very important role in students’ learning outcomes. However, currently, feedback has not been utilized by lecturers and students in the learning process effectively. This study aimed to explore the impact of feedback as a soft scaffolding in the ongoing assessment of Quantum Physics class for the students as prospective Physics teachers. A quasi-experimental design non-equivalent pretest-posttest control group was used to examine the effectiveness of feedback based on ongoing assessment. The results of the study revealed that students who received feedback based on metacognitive and social constructivism on studying Quantum Physics showed better average results compared to students who received traditional feedback based on the cognitivism in the form of correction.
Students’ Errors in Solving Science Reasoning-Domain of Trends in International Mathematics and Science Study (TIMSS)
Authors: Utomo A. P. , Yuana K. , Narulita E. , Fikri K. , Wahono B.
Published: July 2018

This research aims to identify the errors of students’ answers in solving the TIMSS cognitive domain of reasoning. This research was a qualitative descriptive research. A total 259 students from four secondary schools located in rural and urban areas in Jember, East Java participated in a paper and pencil test. Error identification was examined by reducing the result of wrong students’ answer and grouping based on error type of general errors. The results showed that the average percentage of total errors from the four schools were contradicting error of 7.3%, disregarding evidence error of 5.2%, misreading error of 45.7%, and opinion-based judgment error of 40.9%. In conclusion, there were four types of general errors made by students in answering TIMMS test item of reasoning domain with misreading and disregarding evidence as the highest and lowest error, respectively.
Do Physics Textbooks Present the Ideas of Thought Experiments?: A Case in Indonesia
Authors: Bancong H. , Song J.
Published: July 2018

This study sought to check and evaluate whether or not thought experiments presented in the Indonesian physics textbooks can be used as tools to transfer scientific knowledge. This was a descriptive study using Indonesian physics textbooks as the primary sources of data. In this study, we analyzed thirty (30) physics textbooks from Grades 10 to 12 which are widely used both by teachers and students. The results showed that majority of physics textbooks did not mention about thought experiments. Only 6 physics textbooks presented thought experiments at a satisfactory level. The number of physics textbooks that described thought experiments in fair and poor levels are 9 and 5 respectively. The study concludes that Indonesian physics textbooks published from 2009 to 2017 generally lack thought experiments. Many authors of these Indonesian physics textbooks ignored or inadequately present thought experiments. Moreover, 70% of thought experiments mentioned in the physics textbooks were in the fair and poor levels. So, in general, thought experiments presented in the Indonesian physics textbooks cannot be used as an introduction in transferring scientific knowledge to science students.
The Impact of Engineering Design Process in Teaching and Learning to Enhance Students’ Science Problem-Solving Skills
Authors: Syukri M. , Halim L. , Mohtar L. E. , Soewarno S.
Published: July 2018

This study aimed to determine the impact of the integration of engineering design process (asking, imagining, planning, creating and improving) in an electrical & magnetism module to improve problem-solving skills in physics among secondary school students in Aceh, Indonesia. The quasi-experimental study was carried out with 82 form three (age 15 years old) students of a secondary school in Aceh Besar, Indonesia. The first author had randomly chosen two classes as the experimental group and two other classes as the control group. Independent samples t-test analysis was conducted to determine the difference between the physics teaching and learning module which integrated the five steps of engineering design process and the existing commonly used science “Pudak” teaching and learning module. The results of the independent samples t-test analysis showed that the use of the physics teaching and learning module which integrated the five steps of engineering design process was more effective compared to the use of the existing “Pudak” module in increasing the students’ skills in solving physics problems. The findings of the study suggest that the science learning approach is appropriate to be applied in the teaching and learning of science to enhance science problem-solving skills among secondary school students. In addition, it can be used as a guide for teachers on how to implement the integration of the five steps of engineering design process in science teaching and learning practices.
Development of Digital Storytelling-Based Science Teaching Materials to Improve Students’ Metacognitive Ability
Authors: Dewi N. R. , Kannapiran S. , Wibowo S. W. A.
Published: July 2018

This study aims to produce digital-based storytelling teaching materials of natural science that can facilitate the students to be able to explore the object of science learning deeply and to improve their metacognitive ability. This research is development research. The samples used are four teachers and 40 junior high school students. The technique of gathering data employed a testing method, documentation study, and questionnaire. Validation is done to determine the feasibility of teaching materials. The research result of the improvement of students’ metacognitive ability is measured by using the testing method in the form of pretest and posttest. Pretest and posttest data were analyzed by N-gain and t-test of significance. The result of the research shows that the average percentage of validation result of media expert and material expert is 97,70% and 95,16%. According to experts, all developed products are very feasible to use. The results of metacognitive enhancement (N-gain) for levels 1 to 5 respectively were 0.36; 0.56; 0.49; 0.45 and 0.39. The results of significance test showed that the t-count 7.65 and t-table of 2.03 which that the mean improvement of the metacognitive ability of students is significant. Based on the results of this study, it can be concluded that the teaching materials based on digital storytelling are feasible to be used to improve students’ metacognitive ability.
Chemoentrepreneurship with Cooperative Integrated Process Inquiry Strategy to Increase Students' Entrepreneurial Interest and Learning Motivation
Authors: Sumarti S. S. , Aris S. R. S. , Aini R. N.
Published: July 2018

Colloid chemistry learning at SMAN 1 Mijen Demak had a less useful impact as it has not integrated the process of making with the products needed in everyday life. The lesson also did not equip students with the skills in entering the entrepreneurship world. The observation results indicated that the XI IPA1 grade students in SMAN 1 Mijen Demak had low entrepreneurial interest and motivation. This was due to the tedious and less-motivated chemistry learning. Therefore, this study aimed to increase the students' entrepreneurial interest and learning motivation on colloid materials through Integrated Cooperative Inquiry Process strategy. A classroom action research applied in this research consisted of three cycles. Each cycle had several stages which were planning, implementation, observation, and reflection. The data on the students’ entrepreneurial interest and learning motivation were collected through observation and questionnaire. The descriptive analysis was adopted in this research. The data were analysed using the average mastery and proportion. Based on the analysis of cycles I, II and III, the percentage of the students’ entrepreneurship interest increased from 47.64% to 51.17%; 72,16% and 81,10% having 38 students achieved the mastery learning. While the learning motivation increased from 49.55% to 56.08%; 68.21% and 76.32% having 37 students reached the mastery learning. It concluded that the CIPI (Cooperative Integrated Process Inquiry) with CEP (Chemo entrepreneurship) approach could increase the students’ entrepreneurial interest and learning motivation.
The Influence of Android-Based Isomorphic Physics (Forfis) Application on Analogical Transfer and Self-Diagnosis Skill of Students at SMA Negeri 3 Kupang
Authors: Sari D. K. , Supahar S. , Ralmugiz U.
Published: July 2018

This research intended to understand the effect of Isomorphic Physics (FORFIS) application to the analogical transfer and self-diagnosis skill of high school students. The use of Android applications in physics learning has given a considerable influence in improving the various abilities of learners. However, no one has measured the influence of the Android application on the analogical transfer and self-diagnosis skill of students, especially in physics subject. This research type was experimental research of pre-test post-test control group design. The subjects involved in this research were 1 physics teacher and 87 students of SMA Negeri 3 Kupang; 28 students in the experimental class I (G1), 35 students in the experimental class II (G2), and 24 students in the experimental class III (G3). The data obtained were analyzed using the ANOVA Mixed Design method in combination with General Linear Model. The results of the analysis show that the FORFIS application could improve 0.912 or 91.2% of the students’ analogical transfer and self-diagnosis skill. Therefore, the FORFIS application employed in physics learning had a great influence on the improvement of analogical transfer and self-diagnosis skill of high school students.
Studying Natural Science in Elementary School Using NOS-Oriented Cooperative Learning Model with the NHT Type
Authors: Jampel I. N. , Fahrurrozi F. , Artawan G. , Widiana I. W. , Parmiti D. P. , Hellman J.
Published: July 2018

Elementary school students’ achievement in natural science in the academic year of 2015/2016 at Cluster V, Buleleng regency, Bali province was considerably low. An early observation also revealed low motivation, negative attitudes towards teachers, low self-esteem and low confidence in self-capability. Therefore, a breakthrough approach was urgently required to improve the students' performance in natural science learning. The current article aimed at investigating the effects of the (Nature of Science) NOS-oriented cooperative learning model with the Numbered Head Together (NHT) on the elementary school students’ achievement in natural science. The study was a quasi-experimental research adopting the post-test only control group design. The research conducted in elementary schools in Cluster V Buleleng sub-district, Buleleng regency, Bali, Indonesia. The research subject was 137 students in Grade 5 consisting of six classes from  5 elementary schools. The hypothesis was examined using an inferential statistics, the t-test. The results showed that there was a significant difference in the learning results of natural science between the students taught with the NOS-oriented cooperative learning model with the NHT type and those with the conventional learning model (t count = 7,048 >t table = 2,000). The students taught with the NOS-oriented constructive learning model with the NHT type achieved better than those with the conventional learning model. Therefore, it concluded that the NOS-oriented cooperative learning model with the NHT type gave positive effects on the fifth year students’ achievement in natural science learning.
Evaluating gastroenteropancreatic neuroendocrine tumors through microRNA sequencing
Authors: Panarelli Nicole , Tyryshkin Kathrin , Wong Justin Jong Mun , Majewski Adrianna , Yang Xiaojing , Scognamiglio Theresa , Kim Michelle Kang , Bogardus Kimberly , Tuschl Thomas , Chen Yao-Tseng , Renwick Neil
Published: July 2018

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) can be challenging to evaluate histologically. MicroRNAs (miRNAs) are small RNA molecules that often are excellent biomarkers due to their abundance, cell-type and disease stage specificity and stability. To evaluate miRNAs as adjunct tissue markers for classifying and grading well-differentiated GEP-NETs, we generated and compared miRNA expression profiles from four pathological types of GEP-NETs. Using quantitative barcoded small RNA sequencing and state-of-the-art sequence annotation, we generated comprehensive miRNA expression profiles from archived pancreatic, ileal, appendiceal and rectal NETs. Following data preprocessing, we randomly assigned sample profiles to discovery (80%) and validation (20%) sets prior to data mining using machine-learning techniques. High expression analyses indicated that miR-375 was the most abundant individual miRNA and miRNA cistron in all samples. Leveraging prior knowledge that GEP-NET behavior is influenced by embryonic derivation, we developed a dual-layer hierarchical classifier for differentiating GEP-NET types. In the first layer, our classifier discriminated midgut (ileum, appendix) from non-midgut (rectum, pancreas) NETs based on miR-615 and -92b expression. In the second layer, our classifier discriminated ileal from appendiceal NETs based on miR-125b, -192 and -149 expression, and rectal from pancreatic NETs based on miR-429 and -487b expression. Our classifier achieved overall accuracies of 98.5% and 94.4% in discovery and validation sets, respectively. We also found provisional evidence that low- and intermediate-grade pancreatic NETs can be discriminated based on miR-328 expression. GEP-NETs can be reliably classified and potentially graded using a limited panel of miRNA markers, complementing morphological and immunohistochemistry-based approaches to histologic evaluation.
Whole Genome Sequence of the Parasitoid Wasp Microplitis demolitor That Harbors an Endogenous Virus Mutualist
Authors: Burke Gaelen R , Walden Kimberly K O , Whitfield James B , Robertson Hugh M , Strand Michael R
Published: July 2018

Microplitis demolitor (Hymenoptera: Braconidae) is a parasitoid used as a biological control agent to control larval-stage Lepidoptera and serves as a model for studying the function and evolution of symbiotic viruses in the genus Bracovirus. Here we present the M. demolitor genome (assembly version 2.0), with a genome size of 241 Mb, and a N50 scaffold and contig size of 1.1 Mb and 14 Kb, respectively. Using RNA-Seq data and manual annotation of genes of viral origin, we produced a high-quality gene set that includes 18,586 eukaryotic and 171 virus-derived protein-coding genes. Bracoviruses are dsDNA viruses with unusual genome architecture, in which the viral genome is integrated into the wasp genome and is comprised of two distinct components: proviral segments that are amplified, circularized, and packaged into virions for export into the wasp’s host via oviposition; and replication genes. This genome assembly revealed that at least two scaffolds contain both nudivirus-like genes and proviral segments, demonstrating that at least some of these components are near each other in the genome on a single chromosome. The updated assembly and annotation are available in several publicly accessible databases; including the National Center for Biotechnology Information and the Ag Data Commons. In addition, all raw sequence data available for M. demolitor have been consolidated and are available for visualization at the i5k Workspace. This whole genome assembly and annotation represents the only genome-scale, annotated assembly from the lineage of parasitoid wasps that has associations with bracoviruses (the ‘microgastroid complex’), providing important baseline knowledge about the architecture of co-opted virus symbiont genomes.
EKSISTENSI KLINIK IPTEK MINA BISNIS (KIMBis) “PAMISAYA MINA” MENGEMBANGKAN POTENSI PERIKANAN LOKAL KABUPATEN WONOGIRI
Authors: Pramoda Radityo , Muhartono Rizky , Koeshendrajana Sonny
Published: July 2018

Penelitian ini bertujuan mengetahui eksistensi KIMBis Pamisaya Mina dalam memberdayakan masyarakat perikanan di Kabupaten Wonogiri. Analisis kajian dilakukan menggunakan metode kualitatif dan pendekatan studi kasus, yang dipaparkan secara deskriptif. Hasil kajian menunjukkan: (1) KIMBis Pamisaya Mina di Kabupaten Wonogiri telah membentuk inkubator bisnis; (2) kinerja dan eksistensi keberadaan KIMBis Pamisaya Mina sudah dirasakan manfaatnya dan sangat dibutuhkan; (3) sosialisasi yang kurang akibat faktor  jangkauan lokasi. Saran yang dapat diberikan adalah mendorong kelembagaan KIMBis Pamisaya Mina menjadi sebuah asosiasi, bekerja sama dengan otoritas daerah melaksanakan sosialisasi ke seluruh wilayah selingkar Waduk Gajah Mungkur yang belum pernah dijangkau oleh pengurus KIMBis Pamisaya Mina.
KEMITRAAN PEMASARAN RUMPUT LAUT DALAM UPAYA PENGENTASAN KEMISKINAN DI KABUPATEN LOMBOK TIMUR DAN LOMBOK TENGAH, PROVINSI NUSA TENGGARA BARAT
Authors: Suryawati Siti Hajar , Nurlaili Nurlaili , Witomo Cornelia Mirwantini , Zamroni Achmad
Published: July 2018

ABSTRAKModel pengembangan ekonomi kawasan berbasis teknologi adaptif lokasi di Lombok Timur (Lotim) dan Lombok Tengah (Loteng) adalah model yang berbasis kemitraan. Model ini mengakomodir kesepakatan kerjasama berbasis pasar yang melibatkan pembudidaya dan juga pengolah melalui KIMBis Lotim dan Mitra KIMBis Loteng. Pembudidaya sebagai produsen primer komoditi rumput laut dengan  para pengolah yang melakukan proses penambahan nilai melalui kegiatan pengolahan dan pemerintah sebagai regulator, mediator dan fasilitator bagi kedua belah pihak, disertai rincian komitmen dan tanggung jawab pada tiap pihak yang terlibat, untuk menjamin bahwa: (1) pembudidaya menerima bagian nilai (farmer’s share) yang adil dari hasil usahanya; (2) pembudidaya bisa mendapatkan pendapatan rutin; dan (3) pengolah mendapatkan bahan baku dengan kualitas yang sesuai. Sampai akhirnya produk yang dihasilkan diterima oleh konsumen akhir dengan mendapat jaminan produk olahan yang sehat dan harga yang terjangkau. Selain itu implementasi model ini diharapkan dapat meningkatkan kesejahteraan masyarakat di wilayah pesisir khususnya pembudidaya rumput laut, serta mengurangi kerugian karena malpraktek pedagang dalam penentuan harga beli. Title: Marketing Partnership for Poverty Reduction in East Lombok District and Central Lombok, West Nusa Tenggara ProvinceRegional economic development model based on adaptive location technology in East Lombok (Lotim) and Central Lombok (Loteng) is a partnership model. This model accommodates a market-based cooperation agreement involving farmers and processor through KIMBis Lotim and Mitra KIMBis Loteng. Farmers as primary producers of seaweed commodities with processor undertaking additional processingthrough processing and government as regulator, mediator and facilitator for both parties. They work together with commitment and responsibility to each party involved, to ensure: (1) the farmer receives a share (farmer’s share) fair from business results; (2) farmers get routine income; and (3) processor get raw materials with appropriate quality. Until finally the resulting product is accepted by the final consumer with a guaranteed healthy processed products and affordable prices. The implementation of this model is expected to improve the community welfare in coastal areas, especially seaweed farmers, and reducelosses due to malpractice traders in the determination of purchasing price.
Technology Courage: Implications for Faculty Development
Authors: Niebuhr Virginia , Niebuhr Bruce , Rudnicki Anne , Urbani Mary Jo
Published: July 2018

This article was migrated. The article was marked as recommended. Purpose: From a decade of technology-focused faculty development, the authors recognized that academic physicians adopt educational technology at varying rates and with variable confidence. This work is an exploration of the phenomenon of technology courage and how the concept can inform faculty development. Method: Qualitative methods of interpretative phenomenological analysis (IPA) were used. Faculty interviews were transcribed using Google Docs voice typing. Data were analyzed, themes developed, and supportive narratives were identified using IPA methodology. Results: Two themes emerged. The theme of Willingness includes willingness to try, explore, or risk learning a new technology; and willingness to persist in the face of fear or anxiety. The theme of Benefit Evaluation relates to motivators for technology courage, i.e., assessing benefit to self and learners before learning and using a new technology. Conclusions: From a theme analysis, a definition of technology courage has emerged: willingness to try and to persist when using a new technology because of perceived benefit to self and/or others. The authors discuss how further research of the construct might be guided by theoretical frameworks of grit, self-efficacy, teacher identity, and generational learning differences. Recommendations are offered on how the construct of technology courage can be valuable for technology-focused faculty development
Low-Fidelity Haptic Simulation Increases the Transfer of Peripheral Blood Sampling Skills in Novice Medical Students
Authors: Erdmann Thomas Rolf , Oliveira Filho Getúlio Rodrigues de
Published: July 2018

This article was migrated. The article was not marked as recommended. Background: The transfer of skills into clinical practice is a major issue in medical education. This study compared the transfer of skills related to peripheral blood collection between naïve medical students simulation-trained or not before performing on real patients. Methods: 30 novice medical students attended to a lecture addressing peripheral blood collection for laboratory tests. The intervention group trained procedural skills with low-fidelity haptic simulation and role-playing. Controls simulated basic life support. Each student performed six blood sampling attempts in real patients in another occasion. Performance was rated on a scoring checklist. Self-efficacy was measured after the lecture, immediately before and after blood sampling procedures. Results: Success rates were significantly higher in the intervention 82% than in the control group (68%; p = 0.037). Significantly lesser technical errors were observed in the intervention group. Self-efficacy scores increased significantly in both groups after blood collection procedures and correlated significantly with individual success rates (rho = 0.50). Conclusion: An educational intervention consisting of low-fidelity simulation and role-playing added to a lecture-based teaching session on peripheral blood sampling was associated with increased transfer of procedural skills. Self-efficacy was positively associated with individual success rates.
What’s a book club doing at a medical conference?
Authors: Chisolm Margaret , Azzam Amin , Ayyala Manasa , Levine Rachel , Wright Scott
Published: July 2018

This article was migrated. The article was marked as recommended. The prevalence of burnout among physicians in the United States now exceeds 50%, with many physicians feeling isolated and lacking in a sense of community. Book clubs among colleagues may be one way to foster community and restore joy to medicine. The authors introduced two book clubs at the annual meetings of the Society for General Internal Medicine (SGIM) and the Association for Academic Psychiatry (AAP). Response rates for completed surveys for the SGIM and AAP book clubs were 71% and 86%, respectively. About half of the book club participants were already members of a book club, and had read an average of 10 non-medical books in the past year. Eighty-one percent reported the discussions had "a lot" or "tremendous" impact on their learning, and that they would be "likely" or "very likely" to look for a non-medical book in the future as a resource to assist in their professional growth. Sixty-seven percent said they would be "likely" or "very likely" to organize their own book club. Participants listed the "most enjoyable and/or impactful non-medical book read in past year." Survey responses speak to the impact of book club participation on attendees' professional growth, learning, and recognition of overall value of reading non-medical books. These findings support the role of the humanities in professional development to encourage physicians to challenge assumptions, tolerate ambiguity, appreciate cultural influences, and honor the unique perspectives of our patients. In the increasingly complex and challenging work environment of academic health centers, faculty must find mechanisms to maintain workplace meaning and prevent burnout. Reading a book prior to attending one's annual professional society meeting and participating in thoughtful discussions was enjoyable and useful. When facilitators are thoughtfully prepared to guide conversations, professional growth can result in useful insights related to academic practices and pursuits.
The use of gamification to teach in the nursing field
Authors: Castro Talita Candida , Gonçalves Luciana Schleder
Published: July 2018

ABSTRACT Objectives: To investigate whether the course offer with elements of gamification contributes to the formation of competences in Informatics in Nursing; and evaluate it based on teaching and learning criteria and content structure. Method: Exploratory, applied and technological innovation research, with a qualitative and quantitative approach, developed at a university in the southern region of the country between February and November 2016. Participants were professors (5) and nursing students (10). Results: The adoption of gamification was considered an interesting and innovative approach, as an alternative to traditional practices and applicable to Nursing teaching. In the quantitative analysis, it was observed that the course contemplates the set of evaluated criteria. Final considerations: Gamification contributes to the formation of competences among Nursing students for positively influencing the teaching-learning process. It can be understood as one more resource in the teaching work with a view to student motivation and meaningful learning.
Assessment of the care process with orthotics, prosthetics and special materials
Authors: Moraes Clayton dos Santos , Rabin Eliane Goldberg , Viégas Karin
Published: July 2018

ABSTRACT Objective: to assess potential failures in the care process with orthotics, prosthetics and special materials in a high-complexity hospital. Method: an intervention study conducted from March to October 2013. This process was assessed with the Failure Mode and Effects Analysis (FMEA) service tool. The data were analysed according to the risk and the corrective measures were defined. Results: no failure was classified as high risk and the corrective measures indicated as low and moderate risk had the following improvement initiatives suggested: standardize the material records in the information system; create a specific form to require materials; hire specialized technical personnel and create a continuous education program. Conclusion: all the suggested initiatives were implemented and helped to reduce the assistance risks for patients due to failures in this process. The actions increase safety levels and provide higher quality of service.
Stress of nursing students in clinical simulation: a randomized clinical trial
Authors: Boostel Radamés , Felix Jorge Vinícius Cestari , Bortolato-Major Carina , Pedrolo Edivane , Vayego Stela Adami , Mantovani Maria de Fátima
Published: July 2018

ABSTRACT Objective: To evaluate and compare the perception of stressors by nursing students before and after a high-fidelity clinical simulation or conventional laboratory practice class. Method: This is a randomized clinical trial conducted with 52 nursing students. Both groups had theoretical classes about cardiothoracic physical examination, followed by practice class in skill laboratory. In addition, the experimental group took part in a high-fidelity simulation scenario. Stressors were evaluated before and after class, with the application of KEZKAK questionnaire. Results: The experimental group was significantly more worried about six factors related to lack of competence and to interpersonal relationships (p < 0.05), while the control group was significantly more worried about being in contact with suffering (p = 0.0315). Conclusion: The simulation affects students’ perception of stressors and promotes their self-evaluation and critical thinking regarding the responsibility that comes with their learning.
Discursive archaeology: constituting knowledge of militant nurses in trade associations
Authors: Almeida Deybson Borba de , Silva Gilberto Tadeu Reis da , Freitas Genival Fernandes de , Padilha Maria Itayra , Almeida Igor Ferreira Borba de
Published: July 2018

ABSTRACT Objective: To analyze the constituting knowledge of militant nurses in trade associations. Method: Historical research, based on the oral history method, with a qualitative approach carried out with 11 nurses who are/were militants for professional issues since the 1980s in the state of Bahia. The data collected through semi-structured interviews were organized in the software n-vivo 10 and analyzed based on dialectical hermeneutics. Results: We identified pedagogical, administrative, public health, sociological, and trade union background knowledge as constituent of militant individuals. Final considerations: The constituting knowledge of militant nurses are inscribed in the Social Sciences, distanced from biomedical knowledge and power, pointing at ways for structuring nursing curricula. We identified the Brazilian Association of Nursing as a space for political formation.
Robust Local Search for Solving RCPSP/max with Durational Uncertainty
Authors: Fu N. , Lau H.C. , Varakantham P. , Xiao F.
Published: July 2018

Scheduling problems in manufacturing, logistics and project management have frequently been modeled using the framework of Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max). Due to the importance of these problems, providing scalable solution schedules for RCPSP/max problems is a topic of extensive research. However, all existing methods for solving RCPSP/max assume that durations of activities are known with certainty, an assumption that does not hold in real world scheduling problems where unexpected external events such as manpower availability, weather changes, etc. lead to delays or advances in completion of activities. Thus, in this paper, our focus is on providing a scalable method for solving RCPSP/max problems with durational uncertainty. To that end, we introduce the robust local search method consisting of three key ideas: (a) Introducing and studying the properties of two decision rule approximations used to compute start times of activities with respect to dynamic realizations of the durational uncertainty; (b) Deriving the expression for robust makespan of an execution strategy based on decision rule approximations; and (c) A robust local search mechanism to efficiently compute activity execution strategies that are robust against durational uncertainty. Furthermore, we also provide enhancements to local search that exploit temporal dependencies between activities. Our experimental results illustrate that robust local search is able to provide robust execution strategies efficiently.
Learning and Reasoning with Action-Related Places for Robust Mobile Manipulation
Authors: Stulp F. , Fedrizzi A. , Mösenlechner L. , Beetz M.
Published: July 2018

We propose the concept of Action-Related Place (ARPlace) as a powerful and flexible representation of task-related place in the context of mobile manipulation. ARPlace represents robot base locations not as a single position, but rather as a collection of positions, each with an associated probability that the manipulation action will succeed when located there. ARPlaces are generated using a predictive model that is acquired through experience-based learning, and take into account the uncertainty the robot has about its own location and the location of the object to be manipulated.

When executing the task, rather than choosing one specific goal position based only on the initial knowledge about the task context, the robot instantiates an ARPlace, and bases its decisions on this ARPlace, which is updated as new information about the task becomes available. To show the advantages of this least-commitment approach, we present a transformational planner that reasons about ARPlaces in order to optimize symbolic plans. Our empirical evaluation demonstrates that using ARPlaces leads to more robust and efficient mobile manipulation in the face of state estimation uncertainty on our simulated robot.
The CQC Algorithm: Cycling in Graphs to Semantically Enrich and Enhance a Bilingual Dictionary
Authors: Flati T. , Navigli R.
Published: July 2018

Bilingual machine-readable dictionaries are knowledge resources useful in many automatic tasks. However, compared to monolingual computational lexicons like WordNet, bilingual dictionaries typically provide a lower amount of structured information, such as lexical and semantic relations, and often do not cover the entire range of possible translations for a word of interest. In this paper we present Cycles and Quasi-Cycles (CQC), a novel algorithm for the automated disambiguation of ambiguous translations in the lexical entries of a bilingual machine-readable dictionary. The dictionary is represented as a graph, and cyclic patterns are sought in the graph to assign an appropriate sense tag to each translation in a lexical entry. Further, we use the algorithm's output to improve the quality of the dictionary itself, by suggesting accurate solutions to structural problems such as misalignments, partial alignments
and missing entries. Finally, we successfully apply CQC to the task of synonym extraction.
Counting-Based Search: Branching Heuristics for Constraint Satisfaction Problems
Authors: Pesant G. , Quimper C. , Zanarini A.
Published: July 2018

Designing a search heuristic for constraint programming that is reliable across problem domains has been an important research topic in recent years. This paper concentrates on one family of candidates: counting-based search. Such heuristics seek to make branching decisions that preserve most of the solutions by determining what proportion of solutions to each individual constraint agree with that decision. Whereas most generic search heuristics in constraint programming rely on local information at the level of the individual variable, our search heuristics are based on more global information at the constraint level. We design several algorithms that are used to count the number of solutions to specific families of constraints and propose some search heuristics exploiting such information. The experimental part of the paper considers eight problem domains ranging from well-established benchmark puzzles to rostering and sport scheduling. An initial empirical analysis identifies heuristic maxSD as a robust candidate among our proposals.eWe then evaluate the latter against the state of the art, including the latest generic search heuristics, restarts, and discrepancy-based tree traversals. Experimental results show that counting-based search generally outperforms other generic heuristics.
Learning to Win by Reading Manuals in a Monte-Carlo Framework
Authors: Branavan S.R.K. , Silver D. , Barzilay R.
Published: July 2018

Domain knowledge is crucial for effective performance in autonomous control systems. Typically, human effort is required to encode this knowledge into a control algorithm. In this paper, we present an approach to language grounding which automatically interprets text in the context of a complex control application, such as a game, and uses domain knowledge extracted from the text to improve control performance. Both text analysis and control strategies are learned jointly using only a feedback signal inherent to the application. To effectively leverage textual information, our method automatically extracts the text segment most relevant to the current game state, and labels it with a task-centric predicate structure. This labeled text is then used to bias an action selection policy for the game, guiding it towards promising regions of the action space. We encode our model for text analysis and game playing in a multi-layer neural network, representing linguistic decisions via latent variables in the hidden layers, and game action quality via the output layer. Operating within the Monte-Carlo Search framework, we estimate model parameters using feedback from simulated games. We apply our approach to the complex strategy game Civilization II using the official game manual as the text guide. Our results show that a linguistically-informed game-playing agent significantly outperforms its language-unaware counterpart, yielding a 34% absolute improvement and winning over 65% of games when playing against the built-in AI of Civilization.
Modeling Social Causality and Responsibility Judgment in Multi-Agent Interactions
Authors: Mao W. , Gratch J.
Published: July 2018

Social causality is the inference an entity makes about the social behavior of other entities and self. Besides physical cause and effect, social causality involves reasoning about epistemic states of agents and coercive circumstances. Based on such inference, responsibility judgment is the process whereby one singles out individuals to assign responsibility, credit or blame for multi-agent activities. Social causality and responsibility judgment are a key aspect of social intelligence, and a model for them facilitates the design and development of a variety of multi-agent interactive systems. Based on psychological attribution theory, this paper presents a domain-independent computational model to automate social inference and judgment process according to an agents causal knowledge and observations of interaction. We conduct experimental studies to empirically validate the computational model. The experimental results show that our model predicts human judgments of social attributions and makes inferences consistent with what most people do in their judgments. Therefore, the proposed model can be generically incorporated into an intelligent system to augment its social and cognitive functionality.
Riffled Independence for Efficient Inference with Partial Rankings
Authors: Huang J. , Kapoor A. , Guestrin C.
Published: July 2018

Distributions over rankings are used to model data in a multitude of real world settings such as preference analysis and political elections. Modeling such distributions presents several computational challenges, however, due to the factorial size of the set of rankings over an item set. Some of these challenges are quite familiar to the artificial intelligence community, such as how to compactly represent a distribution over a combinatorially large space, and how to efficiently perform probabilistic inference with these representations. With respect to ranking, however, there is the additional challenge of what we refer to as human task complexity  users are rarely willing to provide a full ranking over a long list of candidates, instead often preferring to provide partial ranking information.

Simultaneously addressing all of these challenges  i.e., designing a compactly representable model which is amenable to efficient inference and can be learned using partial ranking data  is a difficult task, but is necessary if we would like to scale to problems with nontrivial size. In this paper, we show that the recently proposed riffled independence assumptions cleanly and efficiently address each of the above challenges. In particular, we establish a tight mathematical connection between the concepts of riffled independence and of partial rankings. This correspondence not only allows us to then develop efficient and exact algorithms for performing inference tasks using riffled independence based represen- tations with partial rankings, but somewhat surprisingly, also shows that efficient inference is not possible for riffle independent models (in a certain sense) with observations which do not take the form of partial rankings. Finally, using our inference algorithm, we introduce the first method for learning riffled independence based models from partially ranked data.
Algorithms for Generating Ordered Solutions for Explicit AND/OR Structures
Authors: Ghosh P. , Sharma A. , Chakrabarti P.P. , Dasgupta P.
Published: July 2018

We present algorithms for generating alternative solutions for explicit acyclic AND/OR structures in non-decreasing order of cost. The proposed algorithms use a best first search technique and report the solutions using an implicit representation ordered by cost. In this paper, we present two versions of the search algorithm -- (a) an initial version of the best first search algorithm, ASG, which may present one solution more than once while generating the ordered solutions, and (b) another version, LASG, which avoids the construction of the duplicate solutions. The actual solutions can be reconstructed quickly from the implicit compact representation used. We have applied the methods on a few test domains, some of them are synthetic while the others are based on well known problems including the search space of the 5-peg Tower of Hanoi problem, the matrix-chain multiplication problem and the problem of finding secondary structure of RNA. Experimental results show the efficacy of the proposed algorithms over the existing approach. Our proposed algorithms have potential use in various domains ranging from knowledge based frameworks to service composition, where the AND/OR structure is widely used for representing problems.
Avoiding and Escaping Depressions in Real-Time Heuristic Search
Authors: Hernandez C. , Baier J. A.
Published: July 2018

Heuristics used for solving hard real-time search problems have regions with depressions. Such regions are bounded areas of the search space in which the heuristic function is inaccurate compared to the actual cost to reach a solution. Early real-time search algorithms, like LRTA*, easily become trapped in those regions since the heuristic values of their states may need to be updated multiple times, which results in costly solutions. State-of-the-art real-time search algorithms, like LSS-LRTA* or LRTA*(k), improve LRTA*'s mechanism to update the heuristic, resulting in improved performance. Those algorithms, however, do not guide search towards avoiding depressed regions. This paper presents depression avoidance, a simple real-time search principle to guide search towards avoiding states that have been marked as part of a heuristic depression. We propose two ways in which depression avoidance can be implemented: mark-and-avoid and move-to-border. We implement these strategies on top of LSS-LRTA* and RTAA*, producing 4 new real-time heuristic search algorithms: aLSS-LRTA*, daLSS-LRTA*, aRTAA*, and daRTAA*. When the objective is to find a single solution by running the real-time search algorithm once, we show that daLSS-LRTA* and daRTAA* outperform their predecessors sometimes by one order of magnitude. Of the four new algorithms, daRTAA* produces the best solutions given a fixed deadline on the average time allowed per planning episode. We prove all our algorithms have good theoretical properties: in finite search spaces, they find a solution if one exists, and converge to an optimal after a number of trials.
Domain and Function: A Dual-Space Model of Semantic Relations and Compositions
Authors: Turney P. D.
Published: July 2018

Given appropriate representations of the semantic relations between carpenter and wood and between mason and stone (for example, vectors in a vector space model), a suitable algorithm should be able to recognize that these relations are highly similar (carpenter is to wood as mason is to stone; the relations are analogous). Likewise, with representations of dog, house, and kennel, an algorithm should be able to recognize that the semantic composition of dog and house, dog house, is highly similar to kennel (dog house and kennel are synonymous). It seems that these two tasks, recognizing relations and compositions, are closely connected. However, up to now, the best models for relations are significantly different from the best models for compositions. In this paper, we introduce a dual-space model that unifies these two tasks. This model matches the performance of the best previous models for relations and compositions. The dual-space model consists of a space for measuring domain similarity and a space for measuring function similarity. Carpenter and wood share the same domain, the domain of carpentry. Mason and stone share the same domain, the domain of masonry. Carpenter and mason share the same function, the function of artisans. Wood and stone share the same function, the function of materials. In the composition dog house, kennel has some domain overlap with both dog and house (the domains of pets and buildings). The function of kennel is similar to the function of house (the function of shelters). By combining domain and function similarities in various ways, we can model relations, compositions, and other aspects of semantics.
Plan-based Policies for Efficient Multiple Battery Load Management
Authors: Fox M. , Long D. , Magazzeni D.
Published: July 2018

Efficient use of multiple batteries is a practical problem with wide and growing application. The problem can be cast as a planning problem under uncertainty. We describe the approach we have adopted to modelling and solving this problem, seen as a Markov Decision Problem, building effective policies for battery switching in the face of stochastic load profiles.

Our solution exploits and adapts several existing techniques: planning for deterministic mixed discrete-continuous problems and Monte Carlo sampling for policy learning. The paper describes the development of planning techniques to allow solution of the non-linear continuous dynamic models capturing the battery behaviours. This approach depends on carefully handled discretisation of the temporal dimension. The construction of policies is performed using a classification approach and this idea offers opportunities for wider exploitation in other problems. The approach and its generality are described in the paper.

Application of the approach leads to construction of policies that, in simulation, significantly outperform those that are currently in use and the best published solutions to the battery management problem. We achieve solutions that achieve more than 99% efficiency in simulation compared with the theoretical limit and do so with far fewer battery switches than existing policies. Behaviour of physical batteries does not exactly match the simulated models for many reasons, so to confirm that our theoretical results can lead to real measured improvements in performance we also conduct and report experiments using a physical test system. These results demonstrate that we can obtain 5%-15% improvement in lifetimes in the case of a two battery system.
Generating Extractive Summaries of Scientific Paradigms
Authors: Qazvinian V. , Radev D. R. , Mohammad S. M. , Dorr B. , Zajic D. , Whidby M. , Moon T.
Published: July 2018

Researchers and scientists increasingly find themselves in the position of having to quickly understand large amounts of technical material. Our goal is to effectively serve this need by using bibliometric text mining and summarization techniques to generate summaries of scientific literature. We show how we can use citations to produce automatically generated, readily consumable, technical extractive summaries. We first propose C-LexRank, a model for summarizing single scientific articles based on citations, which employs community detection and extracts salient information-rich sentences. Next, we further extend our experiments to summarize a set of papers, which cover the same scientific topic. We generate extractive summaries of a set of Question Answering (QA) and Dependency Parsing (DP) papers, their abstracts, and their citation sentences and show that citations have unique information amenable to creating a summary.