nils-herrmann/clean_scirepeval huggingface dataset:
A Spatial Regional Planning Assessment for Green Development Towards Ecotourism with Use of MCDA/SAW Method (Case Study: Spanish Rural Housings)

In the late 20th century, Spanish rural areas are under increasing pressure of illegal construction sprawls and human movements: the areas are also affecting to its ecological consequences. Particularly, the conflict in ecotourism areas between rapid urban development and environmental conservation urgently needs to be addressed due to their regional geographical characteristics. This paper presents a spatial and sustainable planning approach, identifying rural housings' suitability maps in a case study area, La Vera, Spain. Evaluation criteria determine a spatial data management with a grading system, based on constraints, tourism resource, environmental and social economic criteria that are supporting economic opportunities, environmental conservation, local municipal benefits and efficient management of ecotourism. The method presented herein is an integrated application using the multi criteria decision analysis (MCDA) based on the understanding of all possible aspects and implications, applied for weight coefficients calculation of the criteria according to their impact and sensitivity. Six constraints and twelve criteria were assessed in the process of computation, categorized into four groups. Then, with the assistance of the simple additive weighting (SAW) the final housings' suitability map is assessed for the case study area on grading scale of 0 to 255. Here, it displays that 7.99% of La Vera has a most suitable area for sustainable and resilient housings planning after considering their stable sensitive analysis. Therefore, the proposed planning method and the results measuring regional geographical characteristics can be used for policy and decision making process of sustainable and resilient housing planning towards ecotourism at all government levels and private sectors. Moreover, this approach can extend to similar geographical conditions and situations for verifying suitable housings planning suitability.
Borena Saynt National Park in danger of irreversible loss and community based ecotourism as a panacea

Community based Ecotourism (CBET) has emerged as one of the fastest growing sectors of the tourism market and protected areas are the foundation of it. Despite this trend, it is still at its toddler stage in Ethiopian national parks. This study focuses on the assessment of challenges of Borena Saynt National Park (BSNP) for CBET development. The study met this research aims through an extensive study of relevant literature and the implementation of practical research. The latter was carried out through personal observations, key informant interview and using questionnaires. The findings of the study have portrayed that constraints such as poor infrastructural developments, (roads, campsites, lodges, lack of abundant health facilities, hotels and electricity) lack of well qualified human power, lack of natural buffer zone, serious environmental degradation, very exaggerated shape, being small in size, preference of locals towards traditional use of the parks resources over conservation and development of ecotourism, population growth due to expectations of growth of social services and development around the park, settlement, unfair and against the human rights relocation and compensation system; human wild life conflict; and lack of shopping and commercial facilities are persistent challenges for ecotourism development in the area. The main conclusions drawn from this research were that controlling the challenges the park can be said an open air museum for biodiversity and geological features. Hence, for such a fragile, pristine, and comparatively undisturbed natural areas, ecotourism is a panacea as it could teach the community, help to produce funds for ecological conservation, and enable to directly profit the economic development and political management of native communities, and fosters respect for various cultures and for human rights.  Borena Saynt, Community based Ecotourism, National park, Panacea.
Aromatase inhibitors alone or sequentially combined with tamoxifen in postmenopausal early breast cancer compared with tamoxifen or placebo Meta analyses on efficacy and adverse events based on randomized clinical trials.
Venue: Breast

Tamoxifen (TAM) and aromatase inhibitors (AI) are adjuvant therapy options for postmenopausal women with estrogen receptor positive (ER+ breast cancer. This systematic review of seven randomized controlled studies comparing TAM and AI, and one study comparing extended therapy with an AI with placebo after about 5 years of tamoxifen, aims to assess long term clinical efficacy and adverse events. The literature review was performed according to the principles of the Cochrane Collaboration. The search included common databases up to 2013 01 14. Studies of high or moderate quality were used for grading of evidence. Revman(tm) software was utilized for meta analyses of published data. Disease free survival (DFS) and overall survival (OS) were improved with AI monotherapy compared to TAM with high and moderate quality of evidence respectively. Sequenced therapy with AI TAM (or vice versa) improved DFS compared with TAM with moderate quality of evidence, but did not improve OS (low quality of evidence) However, if only studies on sequenced AI therapy with randomization before endocrine therapy were considered, no improvement of DFS could be found. Fractures are more frequently associated with AI whereas the risk of endometrial cancer and venous thromboembolism are higher with TAM. For cardiovascular events no difference was found between AI (mono or sequenced therapy) and TAM, whereas sequenced therapy compared with AI had lower risk of cardiovascular events (moderate level of evidence) AIs are superior to TAM as adjuvant hormonal therapy for postmenopausal ER positive breast cancer. TAM can be considered for individual patients due to the different toxicity profile compared with AI. Cardiovascular events related to AI treatment deserve further attention.
Detecting Rumors from Microblogs with Recurrent Neural Networks
Venue: IJCAI

Microblogging platforms are an ideal place for spreading rumors and automatically debunking rumors is a crucial problem. To detect rumors, existing approaches have relied on hand crafted features for employing machine learning algorithms that require daunting manual effort. Upon facing a dubious claim, people dispute its truthfulness by posting various cues over time, which generates long distance dependencies of evidence. This paper presents a novel method that learns continuous representations of microblog events for identifying rumors. The proposed model is based on recurrent neural networks (RNN) for learning the hidden representations that capture the variation of contextual information of relevant posts over time. Experimental results on datasets from two real world microblog platforms demonstrate that (1) the RNN method outperforms state of the art rumor detection models that use hand crafted features; (2) performance of the RNN based algorithm is further improved via sophisticated recurrent units and extra hidden layers; (3) RNN based method detects rumors more quickly and accurately than existing techniques, including the leading online rumor debunking services.
Towards Conversational Recommender Systems
Venue: KDD

People often ask others for restaurant recommendations as a way to discover new dining experiences. This makes restaurant recommendation an exciting scenario for recommender systems and has led to substantial research in this area. However, most such systems behave very differently from a human when asked for a recommendation. The goal of this paper is to begin to reduce this gap. In particular, humans can quickly establish preferences when asked to make a recommendation for someone they do not know. We address this cold start recommendation problem in an online learning setting. We develop a preference elicitation framework to identify which questions to ask a new user to quickly learn their preferences. Taking advantage of latent structure in the recommendation space using a probabilistic latent factor model, our experiments with both synthetic and real world data compare different types of feedback and question selection strategies. We find that our framework can make very effective use of online user feedback, improving personalized recommendations over a static model by 25% after asking only 2 questions. Our results demonstrate dramatic benefits of starting from offline embeddings, and highlight the benefit of bandit based explore exploit strategies in this setting.
Gaya Hidup Hedonisme Mahasiswa Fakultas Ekonomi dan Bisnis Universitas Sam Ratulangi di Kota Manado

The hedonism lifestyle of college students to long term harm when someone does not want to accept the process and just want results fast and easy, the lack of mutual respect and quality of the nation's leaders are not concerned with morals, dishonest leadership and lack of concern for others. The problems that occur among somestudents of the Faculty of Economics and business of the University of Sam Ratulangi Manado from the pattern of their lives that is overly consumerist behavior in everyday life, the less learning interests, the wrong guidelines impact on free sex, drinks(alcoholic beverages) LGBT, the study is not completed and the completion of the study too long over 5 years. As for the goals of this research is to analyze the lifestyles of hedonism student faculty of Economics and business of the University of Sam Ratulangi in Manado.Research methods used in this research is qualitative research. Informants in this study is 11 students from the Faculty of Economics and business Unsrat in the city of Manado. Data collection is done by observation and interview. The data analyzed in the reduction of the data, the presentation of the data and conclusions/verification.Results of the study prove that female students hedonism lifestyle change when they hang out with new friends in a lecture. When they see their friends who are very mindful of appearances ranging from hair styles, how to dress, bags are in use, shoes that are in use, the assesoris in wearand branded goods are purchased.Popular culture the Manado manners and religious values have a high experienced a shift for the Association and the student mindset i.e. young people who excessively followed the trend of culture outside, free association, the lack of seriousness in learning
A high efficiency, self powered nonlinear interface circuit for bi stable rotating piezoelectric vibration energy harvesting with nonlinear magnetic force

Parallel synchronized switch harvesting on inductor (P SSHI) circuits have been proved to enhance piezoelectric vibration energy harvesting (PVEH) but the maximum conversion efficiency is obtained only when the voltage across the storage capacitor (VSC) equates to the optimal value. For bi stable rotating PVEH with nonlinear magnetic force in engineering applications, however, the VSC will change greatly when powering real electric loads, thus it is impossible to maintain high conversion efficiency. In order to solve this problem, this paper presents an improved P SSHI circuit with controllable optimal voltage (COV PSSHI) by using a voltage control strategy between the storage capacitor and the electric load. The innovation is to control and maintain the VSC close to the optimal value. Firstly, the COV PSSHI circuit is proposed and its theoretic model is built in detail. Then its average harvested power (AHP) is theoretically derived and AHP of the COV PSSHI circuit is proved to be more than that of a classical P SSHI circuit. In the end, experiments are performed to validate the performance of the COV PSSHI circuit. It can be seen that the COV PSSHI circuit can increase the AHP by factor 1.25 compared with classical P SSHI circuits, which is enough to intermittently power the wireless sensor node. Also power consumption of the voltage control circuit has few effects on the COV PSSHI circuit. In particular, it needs to optimize the envelop capacitor, the parallel inductor and two threshold voltages of the voltage controller in order to implement the COV PSSHI circuit well in practice.
Dynamic safety analysis of process systems using nonlinear and non sequential accident model

Analysis of the safety and reliability of complex engineering systems is becoming challenging and highly demanding. In complex engineering systems, accident causation is a function of nonlinear interactions of several accident contributory factors. Traditional accident models normally use a fault and event trees sequential approach to predict cause consequence relationships, which unable to capture real interaction thus have limited predictability of accident. This paper presents a new non sequential barrier based process accident model. The conditional dependencies among accident contributory factors within prevention barriers are modelled using the Bayesian network with various relaxation strategies, and non sequential failure of prevention (safety) barriers. The modelling of non linear interactions in the model led to significant improvement of the predicted probability of an accident when compared with that of sequential technique. This renders valuable information for process safety management. The proposed accident model is tested on a real life case study from the U.S. Chemical Safety Board.
On cloud security attacks: A taxonomy and intrusion detection and prevention as a service
Venue: J. Netw. Comput. Appl.

Major provisioning of cloud computing is mainly delivered via Software as a Service, Platform as a Service and Infrastructure as a Service. However, these service delivery models are vulnerable to a range of security attacks, exploiting both cloud specific and existing web service vulnerabilities. Taxonomies are a useful tool for system designers as they provide a systematic way of understanding, identifying and addressing security risks. In this research work, Cloud based attacks and vulnerabilities are collected and classify with respect to their cloud models. We also present taxonomy of cloud security attacks and potential mitigation strategies with the aim of providing an in depth understanding of security requirements in the cloud environment. We also highlight the importance of intrusion detection and prevention as a service. Display Omitted Cloud Security Attacks Taxonomy.Cloud Intrusion Detection and Prevention as a Service.Intrusion detection in cloud computing service models.Need for in depth advanced cloud protection systems.
Assessment of Selected Elements of Logistic Customer Service for Management in Transport Enterprises The Multiple Discriminant Analysis

The aim of the paper is the assessment of selected elements of logistic customer service for management as perceived by the recipients of services on example of commercial cargo motor transport enterprises. The surveys of the logistic service level as perceived by the recipients of the services of Polish Silesian Province's commercial cargo motor transport enterprises, carried out using the Servqual method, enabled the quality assessment of the logistic service elements of business entities included in the test sample. Considering the results of classification of the most significant logistic customer service elements at the enterprises under study, an attempt was made to examine the effect of logistic customer service element quality on service correctness, service timeliness, service completeness, service provision promptness, technological advancement of the fleet, and service availability. For the determination of the above mentioned significance, the multiple discriminant analysis was employed. The computations were made using the STATISTICA 10.0 package.
Effect Of E Service Quality On Consumer Interest Buying (Case Study On The Website Korean Denim)

Internet users in Indonesia are increasing, creating an opportunity for business people to do business through e commerc on the company website. Each company would have the marketing strategy to attract consumers, one of them by providing electronic services facility called or e servi ce on the website. Through the role of e service on e commerce, companies can improve quality service through reliability aspect (X1) website design (X2) security privacy (X3) and customer service (X4) to attract consumers interest buying (Y) so that the quality of online services can improve consumer buying interest through the company's website. This research was aimed to analyze the influence of e service quality to consumers buying interest on Korean Denim's website, through purposive sampling of 150 respondents and analyzed by using multiple regression analysis on. The result showed that the e service quality had a positive influence on co nsumers buying interest at 38% with a significance value of 0.000 <0.05) indicating that H1 was accepted and generated the regression equation Y 5,035 0. 440 X1 X2 0.187 0.296 1.820 X3 X4.
Teacher recruitment data analytics using association rule mining in Indian context
Venue: 2016 International Conference on Data Science and Engineering (ICDSE)

The recruitment of good teachers is crucial for educational institutions to provide quality education, thereby moulding the students to face challenges of tomorrow. Traditional approaches may fail to choose the right teachers for the right job. In this paper, we apply association rule mining on engineering college teachers data to elicit hidden relationships among the characteristics of the teachers. We use 1992 teachers data collected from AICTE mandatory disclosure documents for our investigation. The study helps the college administration to develop recruitment and HR policies to enhance quality of research, teaching and learning. The study brings out various recommendations for improved research output, patents, awards, R D grants and book publications.
A Content Analysis of English Textbook "When English Rings a Bell" Used in First Grade Junior High School Base on Curriculum 2013

Mansyurah Sadiqah, 2016, A Content Analysis of English Textbook "When English Rings a bell" Used in First Grade Junior High School Based on curriculum 2013, "skripsi" of English education at Faculty of Tarbiyah and Teachers' Training of Syarif Hidayatullah State Islamic University Jakarta, 2016.
How would you like to be rewarded? Relating the Big Five personality traits with reward contingency in a cognitive training puzzle game
Venue: 2016 IEEE International Conference on Serious Games and Applications for Health (SeGAH)

Rewards in serious games have had a long and at times contentious history about their effect on intrinsic motivation, with contradictory findings about whether they are detrimental to intrinsic motivation or not. While recent research suggests that rewards can be beneficial, the effect of reward contingency on motivation is still unclear. The link between player personality and different motivations to play games, and the differing reward preferences arising from the different motivations suggests that personality could moderate the effect of a reward contingency on intrinsic motivation. Knowing this effect could help in better leveraging rewards to make motivating serious games. Two studies, therefore, were conducted to investigate the relationship between personality and reward contingency. In Study 1, 60 participants played a block matching puzzle game that can train executive functions, with each participant randomly assigned to one of three conditions: performance contingent rewards, which gave rewards after achieving a specific performance level, task contingent rewards, which gave rewards simply for completing a task, and no reward condition. Big Five personality traits values of the participants were assessed and related to their intrinsic motivation and performance using a linear regression model. A different combination of the five traits significantly predicted motivation and performance in each condition, with the performance contingent condition yielding significantly higher enjoyment and performance than the other conditions. The efficacy of the linear model was tested in a follow up Study 2, where 30 participants played the same puzzle game, with half the participants given performance contingent rewards, and the other half being assigned a reward contingency that would maximize their intrinsic motivation and performance based on the model obtained in Study 1. Enjoyment and competence subscales of intrinsic motivation, and performance, were significantly higher in the group that received a personality based contingency as compared to the one that always received performance contingent rewards. The present study highlights the role of personality in moderating the effect of different reward contingencies on motivation and performance, and could explain the contradictory findings of existing research. The results demonstrate that serious games can be made more motivating and performance oriented by using appropriately chosen reward contingency.
To Green or Not to Green: A Political, Economic and Social Analysis for the Past Failure of Green Logistics

The objective of green logistics has thus far failed. For example, the share of greenhouse gas emissions by the transportation and logistics sector in Europe rose from 16.6% in 1990 to 24.3% in 2012. This article analyzes the reasons behind this failure by drawing on political, economic and business as well as social motivations and examples. At the core of this analysis are the established theorems of the Jevons paradox and the median voter (Black, Downs) in combination with time distorted preferences of voters and consumers. Adding to the hurdles of green logistics are the problems of short term political programs and decisions versus long term business investments in transportation and logistics. Two cases from Germany are outlined regarding this political "meddling through" with a recent 2015 truck toll decision and the support for electric trucks and vehicles. Finally, the article proposes two ways forward: public control and restriction of carbon raw materials (coal, oil) as well as public investment in low emission transport infrastructure or biofuels as the more feasible and likely alternative.
Robust ellipse detection with Gaussian mixture models
Venue: Pattern Recognit.

The Euclidian distance between Gaussian Mixtures has been shown to be robust to perform point set registration (Jian and Vemuri, 2011) We propose to extend this idea for robustly matching a family of shapes (ellipses) Optimisation is performed with an annealing strategy, and the search for occurrences is repeated several times to detect multiple instances of the shape of interest. We compare experimentally our approach to other state of the art techniques on a benchmark database for ellipses, and demonstrate the good performance of our approach. HighlightsWe extend the framework based on L2 to estimate a parametric family of curves.We propose a non isotropic and multidimensional modeling for the density functions.We propose a method for detecting multiple instances of an ellipse.