bluuebunny/crossref_metadata_2025 huggingface dataset:
The Sixth Answer Set Programming Competition
Authors: Gebser Martin , Maratea Marco , Ricca Francesco
Published: July 2018

Answer Set Programming (ASP) is a well-known paradigm of declarative programming with roots in logic programming and non-monotonic reasoning. Similar to other closely related problem-solving technologies, such as SAT/SMT, QBF, Planning and Scheduling, advancements in ASP solving are assessed in competition events. In this paper, we report about the design and results of the Sixth ASP Competition, which was jointly organized by the University of Calabria (Italy), Aalto University (Finland), and the University of Genoa (Italy), in affiliation with the 13th International Conference on Logic Programming and Non-Monotonic Reasoning. This edition maintained some of the design decisions introduced in 2014, e.g., the conception of sub-tracks, the scoring scheme, and the adherence to a fixed modeling language in order to push the adoption of the ASP-Core-2 standard. On the other hand, it featured also some novelties, like a benchmark selection stage classifying instances according to their empirical hardness, and a "Marathon" track where the top-performing systems are given more time for solving hard benchmarks.
Preference-Based Inconsistency Management in Multi-Context Systems
Authors: Eiter Thomas , Weinzierl Antonius
Published: July 2018

Multi-Context Systems (MCS) are a powerful framework for interlinking possibly heterogeneous, autonomous knowledge bases, where information can be exchanged among knowledge bases by designated bridge rules with negation as failure. An acknowledged issue with MCS is inconsistency that arises due to the information exchange. To remedy this problem, inconsistency removal has been proposed in terms of repairs, which modify bridge rules based on suitable notions for diagnosis of inconsistency. In general, multiple diagnoses and repairs do exist; this leaves the user, who arguably may oversee the inconsistency removal, with the task of selecting some repair among all possible ones. To aid in this regard, we extend the MCS framework with preference information for diagnoses, such that undesired diagnoses are filtered out and diagnoses that are most preferred according to a preference ordering are selected. We consider preference information at a generic level and develop meta-reasoning techniques on diagnoses in MCS that can be exploited to reduce preference-based selection of diagnoses to computing ordinary subset-minimal diagnoses in an extended MCS. We describe two meta-reasoning encodings for preference orders: the first is conceptually simple but may incur an exponential blowup. The second is increasing only linearly in size and based on duplicating the original MCS. The latter requires nondeterministic guessing if a subset-minimal among all most preferred diagnoses should be computed. However, a complexity analysis of diagnoses shows that this is worst-case optimal, and that in general, preferred diagnoses have the same complexity as subset-minimal ordinary diagnoses. Furthermore, (subset-minimal) filtered diagnoses and (subset-minimal) ordinary diagnoses also have the same complexity.
Resolving Over-Constrained Temporal Problems with Uncertainty through Conflict-Directed Relaxation
Authors: Yu Peng , Williams Brian , Fang Cheng , Cui Jing , Haslum Patrik
Published: July 2018

Over-subscription, that is, being assigned too many things to do, is commonly encountered in temporal scheduling problems. As human beings, we often want to do more than we can actually do, and underestimate how long it takes to perform each task. Decision makers can benefit from aids that identify when these failure situations are likely, the root causes of these failures, and resolutions to these failures.

In this paper, we present a decision assistant that helps users resolve over-subscribed temporal problems. The system works like an experienced advisor that can quickly identify the cause of failure underlying temporal problems and compute resolutions. The core of the decision assistant is the Best-first Conflict-Directed Relaxation (BCDR) algorithm, which can detect conflicting sets of constraints within temporal problems, and computes continuous relaxations for them that weaken constraints to the minimum extent, instead of removing them completely. BCDR is an extension to the Conflict-Directed A* algorithm, first developed in the model-based reasoning community to compute most likely system diagnoses or reconfigurations. It generalizes the discrete conflicts and relaxations, to hybrid conflicts and relaxations, which denote minimal inconsistencies and minimal relaxations to both discrete and continuous relaxable constraints. In addition, BCDR is capable of handling temporal uncertainty, expressed as either set-bounded or probabilistic durations, and can compute preferred trade-offs between the risk of violating a schedule requirement, versus the loss of utility by weakening those requirements.

BCDR has been applied to several decision support applications in different domains, including deep-sea exploration, urban travel planning and transit system management. It has demonstrated its effectiveness in helping users resolve over-subscribed scheduling problems and evaluate the robustness of existing solutions. In our benchmark experiments, BCDR has also demonstrated its efficiency on solving large-scale scheduling problems in the aforementioned domains. Thanks to its conflict-driven approach for computing relaxations, BCDR achieves one to two orders of magnitude improvements on runtime performance when compared to state-of-the-art numerical solvers.
Rationalisation of Profiles of Abstract Argumentation Frameworks: Characterisation and Complexity
Authors: Airiau Stéphane , Bonzon Elise , Endriss Ulle , Maudet Nicolas , Rossit Julien
Published: July 2018

Different agents may have different points of view. Following a popular approach in the artificial intelligence literature, this can be modeled by means of different abstract argumentation frameworks, each consisting of a set of arguments the agent is contemplating and a binary attack-relation between them. A question arising in this context is whether the diversity of views observed in such a profile of argumentation frameworks is consistent with the assumption that every individual argumentation framework is induced by a combination of, first, some basic factual attack-relation between the arguments and, second, the personal preferences of the agent concerned regarding the moral or social values the arguments under scrutiny relate to. We treat this question of rationalisability of a profile as an algorithmic problem and identify tractable and intractable cases. In doing so, we distinguish different constraints on admissible rationalisations, e.g., concerning the types of preferences used or the number of distinct values involved. We also distinguish two different semantics for rationalisability, which differ in the assumptions made on how agents treat attacks between arguments they do not report. This research agenda, bringing together ideas from abstract argumentation and social choice, is useful for understanding what types of profiles can reasonably be expected to occur in a multiagent system.
The Length of Shortest Vertex Paths in Binary Occupancy Grids Compared to Shortest r-Constrained Ones
Authors: Hew Patrick Chisan
Published: July 2018

We study the problem of finding a short path from a start to a goal within a two-dimensional continuous and isotropic terrain that has been discretized into an array of accessible and blocked cells. A classic approach obtains a grid path where each step is along the edge of an accessible cell or diagonally across one. Grid paths suffer from `digitization bias' -- even if two locations have line-of-sight, the minimum travelling cost between them can be greater than the distance along the line-of-sight. In a vertex path, steps are allowed from a cell corner to any other cell corner if they have line-of-sight. While the `digitization bias' is smaller, shortest vertex paths are impractical to find by brute force. Recent research has thus turned to methods for finding short (but not necessarily shortest) vertex paths. To establish the methods' potential utility, we calculate upper bounds on the difference in length between the shortest vertex paths versus the shortest r-constrained ones where an r-constrained path consists of line segments that each traverse at most r rows and at most r columns of cells. The difference in length reduces as r increases -- indeed the shortest vertex paths are at most 1 percent shorter than the shortest 4-constrained ones. This article will be useful to developers and users of short(est) vertex paths algorithms who want to trade path length for improved runtimes in a predictable manner.
Finding A Small Vertex Cover in Massive Sparse Graphs: Construct, Local Search, and Preprocess
Authors: Cai Shaowei , Lin Jinkun , Luo Chuan
Published: July 2018

The problem of finding a minimum vertex cover (MinVC) in a graph is a well known NP-hard combinatorial optimization problem of great importance in theory and practice. Due to its NP-hardness, there has been much interest in developing heuristic algorithms for finding a small vertex cover in reasonable time. Previously, heuristic algorithms for MinVC have focused on solving graphs of relatively small size, and they are not suitable for solving massive graphs as they usually have high-complexity heuristics. This paper explores techniques for solving MinVC in very large scale real-world graphs, including a construction algorithm, a local search algorithm and a preprocessing algorithm. Both the construction and search algorithms are based on low-complexity heuristics, and we combine them to develop a heuristic algorithm for MinVC called FastVC. Experimental results on a broad range of real-world massive graphs show that, our algorithms are very fast and have better performance than previous heuristic algorithms for MinVC. We also develop a preprocessing algorithm to simplify graphs for MinVC algorithms. By applying the preprocessing algorithm to local search algorithms, we obtain two efficient MinVC solvers called NuMVC2+p and FastVC2+p, which show further improvement on the massive graphs.
Decision-Theoretic Planning Under Anonymity in Agent Populations
Authors: Sonu Ekhlas , Chen Yingke , Doshi Prashant
Published: July 2018

We study the problem of self-interested planning under uncertainty in settings shared with more than a thousand other agents, each of which plans at its own individual level. We refer to such large numbers of agents as an agent population. The decision-theoretic formalism of interactive partially observable Markov decision process (I-POMDP) is used to model the agent's self-interested planning. The first contribution of this article is a method for drastically scaling the finitely-nested I-POMDP to certain agent populations for the first time. Our method exploits two types of structure that is often exhibited by agent populations -- anonymity and context-specific independence. We present a variant called the many-agent I-POMDP that models both these types of structure to plan efficiently under uncertainty in multiagent settings. In particular, the complexity of the belief update and solution in the many-agent I-POMDP is polynomial in the number of agents compared with the exponential growth that challenges the original framework.

While exploiting structure helps mitigate the curse of many agents, the well-known curse of history that afflicts I-POMDPs continues to challenge scalability in terms of the planning horizon. The second contribution of this article is an application of the branch-and-bound scheme to reduce the exponential growth of the search tree for look ahead. For this, we introduce new fast-computing upper and lower bounds for the exact value function of the many-agent I-POMDP. This speeds up the look-ahead computations without trading off optimality, and reduces both memory and run time complexity. The third contribution is a comprehensive empirical evaluation of the methods on three new problems domains -- policing large protests, controlling traffic congestion at a busy intersection, and improving the AI for the popular Clash of Clans multiplayer game. We demonstrate the feasibility of exact self-interested planning in these large problems, and that our methods for speeding up the planning are effective. Altogether, these contributions represent a principled and significant advance toward moving self-interested planning under uncertainty to real-world applications.
AND/OR Branch-and-Bound on a Computational Grid
Authors: Otten Lars , Dechter Rina
Published: July 2018

We present a parallel AND/OR Branch-and-Bound scheme that uses the power of a computational grid to push the boundaries of feasibility for combinatorial optimization. Two variants of the scheme are described, one of which aims to use machine learning techniques for parallel load balancing. In-depth analysis identifies two inherent sources of parallel search space redundancies that, together with general parallel execution overhead, can impede parallelization and render the problem far from embarrassingly parallel. We conduct extensive empirical evaluation on hundreds of CPUs, the first of its kind, with overall positive results. In a significant number of cases parallel speedup is close to the theoretical maximum and we are able to solve many very complex problem instances orders of magnitude faster than before; yet analysis of certain results also serves to demonstrate the inherent limitations of the approach due to the aforementioned redundancies.
Coordinating Measurements in Uncertain Participatory Sensing Settings
Authors: Zenonos Alexandros , Stein Sebastian , Jennings Nicholas R.
Published: July 2018

Environmental monitoring allows authorities to understand the impact of potentially harmful phenomena, such as air pollution, excessive noise, and radiation. Recently, there has been considerable interest in participatory sensing as a paradigm for such large-scale data collection because it is cost-effective and able to capture more fine-grained data than traditional approaches that use stationary sensors scattered in cities. In this approach, ordinary citizens (non-expert contributors) collect environmental data using low-cost mobile devices. However, these participants are generally self-interested actors that have their own goals and make local decisions about when and where to take measurements. This can lead to highly inefficient outcomes, where observations are either taken redundantly or do not provide sufficient information about key areas of interest. To address these challenges, it is necessary to guide and to coordinate participants, so they take measurements when it is most informative. To this end, we develop a computationally-efficient coordination algorithm (adaptive Best-Match) that suggests to users when and where to take measurements. Our algorithm exploits probabilistic knowledge of human mobility patterns, but explicitly considers the uncertainty of these patterns and the potential unwillingness of people to take measurements when requested to do so. In particular, our algorithm uses a local search technique, clustering and random simulations to map participants to measurements that need to be taken in space and time. We empirically evaluate our algorithm on a real-world human mobility and air quality dataset and show that it outperforms the current state of the art by up to 24% in terms of utility gained.
On the Equivalence between Assumption-Based Argumentation and Logic Programming
Authors: Caminada Martin , Schulz Claudia
Published: July 2018

Assumption-Based Argumentation (ABA) has been shown to subsume various other non-monotonic reasoning formalisms, among them normal logic programming (LP). We re-examine the relationship between ABA and LP and show that normal LP also subsumes (flat) ABA. More precisely, we specify a procedure that given a (flat) ABA framework yields an associated logic program with almost the same syntax whose semantics coincide with those of the ABA framework. That is, the 3-valued stable (respectively well-founded, regular, 2-valued stable, and ideal) models of the associated logic program coincide with the complete (respectively grounded, preferred, stable, and ideal) assumption labellings and extensions of the ABA framework. Moreover, we show how our results on the translation from ABA to LP can be reapplied for a reverse translation from LP to ABA, and observe that some of the existing results in the literature are in fact special cases of our work. Overall, we show that (flat) ABA frameworks can be seen as normal logic programs with a slightly different syntax. This implies that methods developed for one of these formalisms can be equivalently applied to the other by simply modifying the syntax.
Corpus-Level Fine-Grained Entity Typing
Authors: Yaghoobzadeh Yadollah , Adel Heike , Schuetze Hinrich
Published: July 2018

Extracting information about entities remains an important research area. This paper addresses the problem of corpus-level entity typing, i.e., inferring from a large corpus that an entity is a member of a class, such as "food" or "artist". The application of entity typing we are interested in is knowledge base completion, specifically, to learn which classes an entity is a member of. We propose FIGMENT to tackle this problem. FIGMENT is embedding-based and combines (i) a global model that computes scores based on global information of an entity and (ii) a context model that first evaluates the individual occurrences of an entity and then aggregates the scores.

Each of the two proposed models has specific properties. For the global model, learning high-quality entity representations is crucial because it is the only source used for the predictions. Therefore, we introduce representations using the name and contexts of entities on the three levels of entity, word, and character. We show that each level provides complementary information and a multi-level representation performs best. For the context model, we need to use distant supervision since there are no context-level labels available for entities. Distantly supervised labels are noisy and this harms the performance of models. Therefore, we introduce and apply new algorithms for noise mitigation using multi-instance learning. We show the effectiveness of our models on a large entity typing dataset built from Freebase.
Bisimulations on Data Graphs
Authors: Abriola Sergio , Barceló Pablo , Figueira Diego , Figueira Santiago
Published: July 2018

Bisimulation provides structural conditions to characterize indistinguishability from an external observer between nodes on labeled graphs. It is a fundamental notion used in many areas, such as verification, graph-structured databases, and constraint satisfaction. However, several current applications use graphs where nodes also contain data (the so called "data graphs"), and where observers can test for equality or inequality of data values (e.g., asking the attribute 'name' of a node to be different from that of all its neighbors). The present work constitutes a first investigation of "data aware" bisimulations on data graphs. We study the problem of computing such bisimulations, based on the observational indistinguishability for XPath ---a language that extends modal logics like PDL with tests for data equality--- with and without transitive closure operators. We show that in general the problem is PSpace-complete, but identify several restrictions that yield better complexity bounds (coNP, PTime) by controlling suitable parameters of the problem, namely the amount of non-locality allowed, and the class of models considered (graphs, DAGs, trees). In particular, this analysis yields a hierarchy of tractable fragments.
Cycles and Intractability in a Large Class of Aggregation Rules
Authors: Zwicker William S.
Published: July 2018

We introduce the (j,k)-Kemeny rule -- a generalization of Kemeny's voting rule that aggregates j-chotomous weak orders into a k-chotomous weak order. Special cases of (j,k)-Kemeny include approval voting, the mean rule and Borda mean rule, as well as the Borda count and plurality voting. Why, then, is the winner problem computationally tractable for each of these other rules, but intractable for Kemeny? We show that intractability of winner determination for the (j,k)-Kemeny rule first appears at the j=3, k=3 level. The proof rests on a reduction of max cut to a related problem on weighted tournaments, and reveals that computational complexity arises from the cyclic part in the fundamental decomposition of a weighted tournament into cyclic and cocyclic components. Thus the existence of majority cycles -- the engine driving both Arrow's impossibility theorem and the Gibbard-Satterthwaite theorem -- also serves as a source of computational complexity in social choice.
Viewpoint: A Critical View on Smart Cities and AI
Authors: Inclezan Daniela , Pradanos Luis I.
Published: July 2018

AI developments on smart cities, if not critical, risk making a flawed urban model more efficient. Instead, we suggest that AI should challenge the mainstream techno-optimistic approach to solving urban problems by dialoguing with other academic fields, questioning the dominant urban paradigm, and creating transformative solutions. We claim that doing differently, rather than doing better, may be smarter for cities and the common good.

This article is part of the special track on AI and Society.
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents
Authors: Machado Marlos C. , Bellemare Marc G. , Talvitie Erik , Veness Joel , Hausknecht Matthew , Bowling Michael
Published: July 2018

The Arcade Learning Environment (ALE) is an evaluation platform that poses the challenge of building AI agents with general competency across dozens of Atari 2600 games. It supports a variety of different problem settings and it has been receiving increasing attention from the scientific community, leading to some high-profile success stories such as the much publicized Deep Q-Networks (DQN). In this article we take a big picture look at how the ALE is being used by the research community. We show how diverse the evaluation methodologies in the ALE have become with time, and highlight some key concerns when evaluating agents in the ALE. We use this discussion to present some methodological best practices and provide new benchmark results using these best practices. To further the progress in the field, we introduce a new version of the ALE that supports multiple game modes and provides a form of stochasticity we call sticky actions. We conclude this big picture look by revisiting challenges posed when the ALE was introduced, summarizing the state-of-the-art in various problems and highlighting problems that remain open.
On the Behavior of Convolutional Nets for Feature Extraction
Authors: Garcia-Gasulla Dario , Parés Ferran , Vilalta Armand , Moreno Jonatan , Ayguadé Eduard , Labarta Jesús , Cortés Ulises , Suzumura Toyotaro
Published: July 2018

Deep neural networks are representation learning techniques. During training, a deep net is capable of generating a descriptive language of unprecedented size and detail in machine learning. Extracting the descriptive language coded within a trained CNN model (in the case of image data), and reusing it for other purposes is a field of interest, as it provides access to the visual descriptors previously learnt by the CNN after processing millions of images, without requiring an expensive training phase. Contributions to this field (commonly known as feature representation transfer or transfer learning) have been purely empirical so far, extracting all CNN features from a single layer close to the output and testing their performance by feeding them to a classifier. This approach has provided consistent results, although its relevance is limited to classification tasks. In a completely different approach, in this paper we statistically measure the discriminative power of every single feature found within a deep CNN, when used for characterizing every class of 11 datasets. We seek to provide new insights into the behavior of CNN features, particularly the ones from convolutional layers, as this can be relevant for their application to knowledge representation and reasoning. Our results confirm that low and middle level features may behave differently to high level features, but only under certain conditions. We find that all CNN features can be used for knowledge representation purposes both by their presence or by their absence, doubling the information a single CNN feature may provide. We also study how much noise these features may include, and propose a thresholding approach to discard most of it. All these insights have a direct application to the generation of CNN embedding spaces.
Optical loss induced by metal electrodes in a polymer optical waveguide for optical sensor
Authors: Zhang Jia-Wei , Xue Guo-An , Cui Yan-Chen , Liu Rui-Tong
Published: July 2018

Optical electric field sensors have received significant attention in recent years for their potential in a broad range of applications. There are many literatures about the optical electric field sensors, but only a few reports focus on the optical losses. In this paper, an analysis model is developed for the design of the electrode of a polymer electro-optic modulator in an optical electric field sensor. The optical losses due to the electrode are presented for different core waveguide thickness and cladding refractive indices. It also had been found that the optical loss due to electrode absorption will depend not only on the cladding layer but also on the core waveguide thickness. At the same time, the thickness of the cladding layer and core waveguide can be chosen freely by adjusting the refractive index of the polymer materials and keeping the optical losses to be less than 0·1 dB/cm. The results will be helpful for the design of a polymer electro-optic modulator in an optical electric field sensor.
Thermal behavior and light transmittance of PLLA nucleated using strontium phenylmalonate
Authors: Cai Yanhua , Zhao Lisha
Published: July 2018

Adding functional additives in the poly(l-lactic acid) (PLLA) matrix to develop high-performance modified biodegradable polymers is of great interest. Therefore, in this work, strontium phenylmalonate (SrPA), as an organic–inorganic hybrid material, was prepared through a neutralization reaction to evaluate its influence on the crystallization behavior, melting behavior, thermal stability and light transmittance of PLLA. The non-isothermal crystallization behavior, for all PLLA/SrPA samples, showed that the SrPA loading and variations in cooling rate significantly influenced the non-isothermal crystallization of PLLA; 5 wt% SrPA exhibited the best crystallization-accelerating capability for PLLA. However, the effects of the set final melt temperature used on the non-isothermal crystallization were negligible, resulting from the minimal difference in solubility of SrPA in the PLLA matrix in the temperature range of 170–210°C. The results from X-ray diffraction measurements and melting behavior further demonstrated the crystallization-accelerating role of SrPA for PLLA. Thermal stability measurements indicated that the incorporation of SrPA did not change the thermal decomposition behavior of PLLA, but the onset decomposition temperature decreased with increasing SrPA concentration. The addition of SrPA led to a significant decrease in light transmittance.
Seismic uplift resistance of circular plate anchors in sand
Authors: Sahoo Jagdish Prasad , Ganesh R.
Published: July 2018

In the present study, theoretical solutions have been developed for computing the vertical seismic uplift resistance of a shallow buried horizontal circular plate anchor in sand with the incorporation of shear transfer at the interface of the anchor plate and overlying sand during an earthquake. The analysis was performed by employing the kinematic theorem of limit analysis based on a pseudo-static approach, with the assumption of a simple rigid wedge collapse mechanism in the form of an inverted frustum with cross-section changing from circular at the anchor level to an elliptical shape at any level just above the anchor. The effect of seismic body forces on the uplift capacity of the circular anchor is evaluated in terms of dimensionless seismic factors Sq and Sγ due to the components of surcharge pressure and soil unit weight, respectively. An increase in the magnitude of seismic acceleration leads to a continuous reduction in uplift resistance; a significant decrease in the uplift resistance was found to occur for the case with the consideration of shear at the interface between the anchor top surface and the soil as compared to that without any shear.
Automated Quality Assurance of Educational Testing
Authors: Doneva Rositsa , Gaftandzhıeva Silvia , Totkov George
Published: July 2018

This paper presents a study on known approaches for quality assurance of educational test and test items. On its basis a comprehensive approach to the quality assurance of online educational testing is proposed to address the needs of all stakeholders (authors of online tests, teachers, students, experts, quality managers, etc.). According to the proposed approach is developed an original software application Test Quality Evaluation (TQE) for the automation of the stakeholders’ activities for quality assurance of educational tests throughout the whole lifecycle. The application retrieves and provides analysis of data from online tests conducted and specially designed surveys for quality evaluation of educational tests by students and experts. It allows tracking and evaluating the quality of educational tests in real time and provides the related quantitative data in different levels of generalization – in the level of a separate educational test, of educational tests of an entire course, or educational tests of a subject area. The software application has been put under real-time testing for quality evaluation of educational tests, included in e-learning courses from different subject areas that prove its applicability.
Effectiveness of Integrated Primary and Behavioral Healthcare
Authors: Lenz A. Stephen , Dell'Aquila Julia , Balkin Richard S.
Published: July 2018

A meta-analysis was completed to identify the degree of effectiveness of the integrated primary and behavioral healthcare (IPBH) paradigm for decreasing commonly occurring mental health symptoms. A systematic search strategy yielded 36 randomized controlled trials whose treatment effects were synthesized using statistical procedures to account for error associated with participant and study characteristics. Findings indicated that IPBH was superior to treatment as usual at end-of-treatment (g = −0.38 to −0.24; k = 39) and longest follow-up intervals (g = −0.40 to −0.24; k = 29). Moderator analyses revealed that number of treatment team providers and number of behavioral health sessions integrated into IPBH were the strongest predictors of treatment effect. Our findings support the position that mental health counselors are well suited to enhance the mental health of individuals within primary care settings. Suggestions are provided for promoting best practices and magnifying treatment effect.
Adverse Childhood Experiences, Brain Development, and Mental Health: A Call for Neurocounseling
Authors: Navalta Carryl P. , McGee Lesley , Underwood Jolene
Published: July 2018

The Adverse Childhood Experiences (ACE) Study provided compelling evidence that abuse, neglect, and other ACEs are the most potent risk factors for the development of health, mental health, and substance use problems. Such negative health-related outcomes parallel the cumulative exposure of the developing brain to the stress response, with resulting impairment in multiple brain structures and functions. Collectively, these sequelae can manifest during childhood, adolescence, or adulthood. We and others have posited that counseling and other psychotherapeutic interventions need to address the individual’s multilayered ecology (i.e., biological, psychological, social, cultural/contextual). Neurocounseling can provide a heuristic framework to more effectively assess, conceptualize, and counsel people with a history of ACEs. We provide an update of the clinical neuroscience of ACEs and its implications for counseling, including how contemporary interventions (e.g., mindfulness) can potentially have positive benefits for such individuals.
Usage of E-Journals by the Users of Central University of Orissa, Koraput: An Analysis with INFISTATS (Usage Statistics Portal for e-Resource) for the Period 2012-2016
Authors: Pradhan Bijayananda
Published: July 2018

Central University of Orissa is getting 8500+ e –journals from e-ShodhSindhu consortia of INFLIBNET. The University was established by the Government of India, MHRD in the year 2009. However, the University is getting e-resources through consortia from the year 2012 onwards. To assess the usage of these e-journals by the users of Central University of Orissa, the author analyzed the statistics using INFISTAT of INFLIBNET. It was found that there are certain resources which are being utilized more by the users, which reflects the popularity of the journals as well as the publisher. The study also shows the trend and statistics of usage by month, by year, by databases, and by journals, etc.
Harvesting of Additional Metadata Schema into DSpace through OAI-PMH: Issues and Challenges
Authors: Das Anup , Sutradhar B.
Published: July 2018

The focus of this paper is to present a manual for harvesting added metadata schema elements from data provider repository through PAI-PMH. Here we have attempted to extend the ability of DSpace as well as the OAI-PMH to host or share other metadata schema elements e.g. LRMI, IEEE-LOM, ETD etc. DSpace, by default, is capable of importing and exporting only Dublin Core metadata; but DSpace has the capability by which one can define his own submission form and expose customized fields to OAI-PMH request. This paper attempts to provide a guideline to a DSpace administrator to accommodate different metadata schema as well as enhancing the Interoperable capability between Data provider and Service provider repository for Importing and Exporting customized metadata Schema. This is an important concern as Institutions have different types of content and have implemented metadata schema and elements appropriate to their content.
Integrating HASSET Thesaurus with ICSSR Data Service
Authors: Pandya Miteshkumar
Published: July 2018

This article studies effective use of thesaurus which provides access to wide range of subject keywords and pick right one which is best suited to describe the dataset being indexed. The article provides brief information on ICSSR Data Service followed by aims and objectives. It also elaborates need for the integrating thesaurus with a data input worksheet of the online databases. It also enlists steps of assigning subject keywords to a dataset being indexed in the repository.
Cited and Citing Pattern of Open Access Journals: A Pilot Study with Selected Indian Journals of Physics- Chemistry-Mathematics
Authors: Kumar Chaubey Ajay , Mukherjee Bhaskar
Published: July 2018

This study is designed to assess the disciplinary difference of cited-citing references of Indic origin open access journals namely Indian Journal of Pure and Applied Physics (IJPAP), Journal of Chemical Science (JCS) and Indian Journal of Pure and Applied Mathematics (IJPAM) in terms of source, authorship, subject diversity, accessibility, citation-age, quantity & citinglife. The sample size consist of 23 issues, 277 articles, 7004 cited references and 2349 citing sources of these 3 journals. While for cited reference, we download reference list of every published article from the official website of the journals, for citing reference, we explore Google Scholar and Scopus both to identify maximum number of citing source during April 2017. Results show that for internet enabled OA articles there is no acceleration of citing behavior; rather, on the contrary, a significant trend is revealed for an increase in authors’ citing somewhat older references. Significant main effects point also at more cited references was of journal articles and was of Indic origin; however, more citing reference was of foreign original journals. Both for cited-citing reference joint authorship were predominant. In spite of the fact that present study considered only open access articles for analysis, results indicates that PCM authors mostl
Assessing India’s Contribution to the Scholarly Publications of Asiatic Region
Authors: Dutta Anirban , Jana Sibsankar
Published: July 2018

This write-up represents the fundamentals of SCImago Journal and Country Ranking in terms of its scope, role in scientometrics study, and the important elements of different types of scientometrics indicators. It attempts to achieve some fundamental objectives of scientometrics, like: 1. ensure access to articles published in different R&D literature at national and global level, 2. reflect and represent true picture of scholarly contribution, research, scientific productivity at national and global level, and 3. have an authentic tool/ground for effective, efficient and rigorous evaluation of scholarly works. The SJR2 indicator takes into account not only the prestige of the citing scientific journal but also its closeness to the cited journal using the cosine of the angle between the vectors of the two journals’ co-citation. To eliminate the size effect, the accumulate prestige is divided by the fraction of the journal’s citable documents, thus eliminating the decreasing tendency of this type of indicator and giving meaning to the scores.
Information Use Behaviour of Engineering Students: A Case Study
Authors: Subhash Reddy B. , Krishnamurthy M.
Published: July 2018

Study of information use is an important aspect of understanding the end users’ behaviour. This study is aimed at understanding the information use behavior of postgraduate engineering students in an institute of technology. The data for this study was collected through an online survey of 130 postgraduate engineering students belonging to various disciplines. The study reveals the frequency of library visit, the purpose of visiting the library, types of facilities, services and library resources used by the students. Data on strategy for searching documents sources, user’s opinion, and user satisfaction with print and e-resources were also collected. The study shows that most of the students are satisfied with library facilities.
Assessing Digital Literacy of Undergraduate Students of the Faculty of Arts, University of Dhaka
Authors: Akter Mahfuza , Haque Enamul
Published: July 2018

The aim of this study is to assess the digital literacy of undergraduate students of Arts faculty at the University of Dhaka, and to determine their strengths and weaknesses. Generally, it was found that students had limited skills in digital literacy, as it is not a part of their academic course curriculum. This study urges the incorporation of a digital literacy program in the course curriculum that will make the students digitally more literate. The study represents the viewpoint of undergraduate students of Arts faculty in Digital Literacy program and provides some insights into students’ knowledge of digital literacy and the importance they attach to digital literacy education.
An Empirical Study on the Asymmetric Behavior of Scientometric Indicator for Journal: A Comparative Evaluation of SJR and H-Index
Authors: Kalita Deepjyoti , Sai Baba M. , Deka Dipen
Published: July 2018

Scimago Journal Rank (SJR) is a size independent measure of journal evaluation where citation coming from quality journals carries more value than citations from ordinary journals and h-index, used as a metrics for author impact when initially introduced, is now a day’s used for journal evaluation in major citation databases like Scopus, Google scholar etc. Both the indicators follow different methods of calculation. SJR is a prestige based measure where the scholarly value of incoming citations matters most than its quantity, while h-index is a quantity based measure where the amount of incoming citations plus the number of published paper both matters. The current study tries to identify how the ranking value of journals changes when compared with the two indicators. The issue was addressed by taking the context of Indian journals indexed in Scopus. Even though the process of calculation for both the indicators is different, it is expected that their ultimate result is same i.e. ranking quality journals at top. The findings of ranking of quality journals represent strikingly different result given by both the indices. The dissimilarity in measure is tested using z-test for two sample means for median difference. Also the biasness of the indicators towards time and subject domains is tested on a raw count.
Identification of Important E-Journals from Article(S) Sought by the Users: An Analysis of Access Denied Usage Report
Authors: Rajendiran P. , Pattnaik J. K.
Published: July 2018

Counting Online Usage of Networked Electronic Resources (COUNTER), JR2 (Journal Report 2) - access denied to fulltext articles by month, journal, and category; for the year 2016 and 2017 studied. This paper tries to identify what other e-journal sources apart from current licensed one, that the users looked online to meet day-to-day information requirements. The JR2 usage data downloaded from 13 e-journals platform / content provider for the purpose and analyzed data. This analysis found most frequently paper(s) sought e-journals, year, platform, and publisher wise number of access denied papers during the year 2016 and 2017. It also explored number of e-journals from which at least a full text document tried to download. Bradford’s law of scattering applied to find core journals and found 23 e-journals based on JR2 access denied usage data. The study feels that like other methods and techniques employed by library and information professionals, the JR2 usage data analysis also an important tool to identify the best out of the best resources and help to bridge the gap in serials collection.
Analysis of Stress in Construction Monitoring of Long - Span Concrete Bridge
Authors: Li Jianwei
Published: July 2018

In order to improve the quality of the relevant construction development activities and effectively meet the special requirements of the design and construction of large span concrete bridges, the safety, effectiveness and economy of the bridge are fully enhanced. In this paper, the spatial structure of the long span concrete bridge is very special. As well as environmental adaptability, technical staff should be based on the development of large and span concrete bridge construction activities of the actual needs of large-span concrete bridge for scientific design and planning, but also the construction technology application activities for scientific supervision. The purpose of this paper is to explore the scientific and efficient application of stress monitoring in the construction process of large span concrete bridge under the guidance of the relevant theory of construction from the perspective of stress monitoring, so as to ensure the accuracy of construction activities and promote the development of bridge orderly development.
Foundation Pit Support and Construction of Luneng Real Estate S - 20 Commercial Building
Authors: Song Xueli , Xu Xiudong , Wang Lange , Yang Huajun
Published: July 2018

With the gradual improvement of urban construction, urban construction land increasingly tense, the lack of land caused by the formation of expensive land premium. Alterations and new construction is basically plug-in embedded, the original underground, the building on the protection of the building is also increasingly diverse and complex, the construction is also increasing the difficulty. The safe use of existing facilities and the safety of construction are problems that must be addressed in urban construction.
The Evolution of Public Transport Policy in Hong Kong since 1981
Authors: Li Zhe
Published: July 2018

Counting only the usable land, the population in Hong Kong is as dense as 34,000 people per square kilometer, and it has a highly efficient multi-modal public transport system. According to the experience of Hong Kong public transit system, highly reputable public transport services reveals that the the viability and sustainability of mass transit railways depend very much on accompanying transport policies and land development strategies. The ways to reduce traffic congestion from supply measures to demand management and change the transit mode from vehicle to railway are both based on Hong Kong’s actual situation. Finally this article emphasis on sustainable transport is a great experience which needs research with more in-depth thinking, and the evolution of public transport policy in Hong Kong is a good inspiration for the public transit development in the other great cities in the world.
Development of Finite Element Solver for Welding Analysis
Authors: Khan Abid Ali , Shahid Farzeen , Qamar Ihtzaz
Published: July 2018

Welding is a process of joining the similar or different metals. Improper welding process leads to inaccuracies and misalignments of structural members, causing high cost and delays in work. Therefore, it is essential to predict the temperature field during welding process. Different techniques can be used to predict the temperature field, which may lead to structure distortion. The present study aims to develop a finite element solver for transient heat conduction analysis. The final solution is calculated from the assumed solution and compared with the numerical computations. The solver is then modified for use of moving heat source. The modification comprise, change in governing equations with the inclusion of phase change. The moving heat source continuously increases the temperature during motion. When the heat source completes a pass, model is allowed to cool down in order to study the temperature distribution during cooling.
Bending and Vibration Analysis of Curved FG Nanobeams via Nonlocal Timoshenko Model
Authors: Hosseini Seyyed Amirhosein , Rahmani Omid
Published: July 2018

The bending and vibration behavior of a curved FG nanobeam using the nonlocal Timoshenko beam theory is analyzed in this paper. It is assumed that the material properties vary through the radius direction.  The governing equations were obtained using Hamilton principle based on the nonlocal Timoshenko model of curved beam. An analytical approach for a simply supported boundary condition is conducted to analyze the vibration and bending of curved FG nanobeam. In the both mentioned analysis, the effect of significant parameter such as opening angle, the power law index of FGM, nonlocal parameter, aspect ratio and mode number are studied. The accuracy of the solution is examined by comparing the results obtained with the analytical and numerical results published in the literatures.
Study on Maintenance and Management Measures of Municipal Drainage System
Authors: Huang Peitao , Zhang Ming , Zhang Xiao , An Yuning , Lu Weiming
Published: July 2018

With the continuous development of China's modern economy, it has greatly promoted the pace of the process of urbanization. In the construction of urban infrastructure, municipal drainage system occupies the main position, it can clear the city water, beautify the city, and create a comfortable living environment. In order to play the role of the municipal drainage system to the extreme, the relevant departments should put the drainage system's maintenance and management into practice, and find out the problem and solve it in time. Based on the operation of municipal drainage system, this paper discusses the problems encountered in the maintenance and management of drainage system, and puts forward effective solutions to the problems.