snu-aidas/HVMap-dataset huggingface dataset:
Forecasting seasonal time series with computational intelligence: On recent methods and the potential of their combinations

Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce novel methods for multi-step seasonal time series forecasting. All the presented methods stem from computational intelligence techniques: evolutionary artificial neural networks, support vector machines and genuine linguistic fuzzy rules. Performance of the suggested methods is experimentally justified on seasonal time series from distinct domains on three forecasting horizons. The most important contribution is the introduction of a new hybrid combination using linguistic fuzzy rules and the other computational intelligence methods. This hybrid combination presents competitive forecasts, when compared with the popular ARIMA method. Moreover, such hybrid model is more easy to interpret by decision-makers when modeling trended series. 2012 Elsevier Ltd. All rights reserved.
Real-Time Head Orientation from a Monocular Camera Using Deep Neural Network

[1] J. Xiao, S. Baker, I. Matthews, T. Kanade, “Real-Time Combined 2D + 3D Active Appearance Models,” CVPR, pp.535-542, 2004. [2] N. Gourier, D. Hall, J. L. Crowley, “Estimating Face Orientation from Robust Detection of Salient Facial Features”, Proceedings of Pointing 2004, ICPR, International Workshop on Visual Observation of Deictic Gestures, 2004. [3] G. Fanelli, M. Dantone, J. Gall, A. Jssati, L. Van Gool, “Random Forests for Real Time 3D Face Analysis,” IJCV, pp.437-458, 2013. [4] Y. LeCun, R. Bottou, Y. Bengio, P. Haffner, “Gradient-based Learning Applied to Document Recognition,” Proc. IEEE, vol. 86, no. 11, pp.2278-2324, 1998. [5] A. Krizhevsky, I. Sutskever, G. E. Hinton, “ImageNet Classification with Deep Convolutional Neural Networks,” NIPS, pp.1106-1114, 2012. This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (No. 2010-0028680). Proposed Method  Conventional Head Pose Estimation Approaches
Social influence on the use of Clinical Decision Support Systems: Revisiting the Unified Theory of Acceptance and Use of Technology by the fuzzy DEMATEL technique

The aim of study is to examine whether social influence affects medical professionals’ behavioral intention to use while introducing a new Clinical Decision Support System (CDSS). The series of Technology Acceptance Models (TAMs) have been widely applied to examine new technology acceptance by scholars; nevertheless, these models omit system diversity and the user’s profession. On the other hand, causal analysis greatly affects the efficiency of decision-making, and it is usually analyzed by Structural Equation Modeling (SEM); however, the method is often misapplied. This research applies the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique to explore the causal relationship between the significant Unified Theory of Acceptance and Use of Technology (UTAUT) variables. Fuzzy concept is applied to illustrate human vague judgment. It is significant that, in contrary with UTAUT, this study found that social influence does not matter in the behavioral intention to use the CDSS for medical professionals. 2011 Elsevier Ltd. All rights reserved.
Analysis of hidden units in a layered network trained to classify sonar targets

-A neural network learning procedure has been applied to the classification ~/sonar returns [kom two undersea targets, a metal cylinder and a similarly shaped rock. Networks with an intermediate layer ~/ hidden processing units achieved a classification accuracy as high as 100% on a training set of l04 returns. These net~orks correctly classified up to 90.4% of 104 test returns not contained in the training set. This perfi~rmance was better than that of a nearest neighbor classifier, which was 82.7%. and was close to that of an optimal Bayes classifie~ Specific signal features extracted by hidden units in a trained network were identified and related to coding schemes in the pattern of connection strengths between the input and the hidden units. Network perlbrmance and class[/~cation strategy was comparable to that of trained human listeners. Keywords--Learning algorithms, Hidden units. Multilayered neural network, Sonar, Signal processing.
Counterintuitive Behavior of Social Systems

This paper addresses several social concerns: population trends; quality of urban life; policies for urban growth; and the unexpected, ineffective, or detrimental results often generated by government programs. Society becomes frustrated as repeated attacks on deficiencies in social systems lead only to worse symptoms. Legislation is debated and passed with great hope, but many programs prove to be ineffective. Results are often far short of expectations. Because dynamic behavior of social systems is not understood, government programs often cause exactly the reverse of desired results. The field of system dynamics now can explain how such contrary results happen. Fundamental reasons cause people to misjudge behavior of social systems. Orderly processes in creating human judgment and intuition lead people to wrong decisions when faced with complex and highly interacting systems. Until we reach a much better public understanding of social systems, attempts to develop corrective programs for social troubles will continue to be disappointing. This paper cautions against continuing to depend on the same past approaches that have led to present feelings of frustration. New methods developed over the last 30 years will lead to a better understanding of social systems and thereby to more effective policies for guiding the future. 1 Updated March, 1995. This paper was first copyrighted © 1971 by Jay W. Forrester. It is based on testimony for the Subcommittee on Urban Growth of the Committee on Banking and Currency, U.S. House of Representatives, on October 7, 1970. The original text appeared in the January, 1971, issue of the Technology Review published by the Alumni Association of the Massachusetts Institute of Technology. All figures are taken from World Dynamics by Jay W. Forrester, Productivity Press, Portland, Oregon. 2 Germeshausen Professor Emeritus and Senior Lecturer, Massachusetts Institute of Technology, Cambridge, MA, USA Copyright © 1995 Jay W. Forrester
Random Forests and VGG-NET: An Algorithm for the ISIC 2017 Skin Lesion Classification Challenge

This manuscript briefly describes an algorithm developed for the ISIC 2017 Skin Lesion Classification Competition. In this task, participants are asked to complete two independent binary image classification tasks that involve three unique diagnoses of skin lesions (melanoma, nevus, and seborrheic keratosis). In the first binary classification task, participants are asked to distinguish between (a) melanoma and (b) nevus and seborrheic keratosis. In the second binary classification task, participants are asked to distinguish between (a) seborrheic keratosis and (b) nevus and melanoma. The other phases of the competition are not considered. Our proposed algorithm consists of three steps: preprocessing, classification using VGG-NET [2] and Random Forests [3], and calculation of a final score.
How GaN Power Transistors Drive High-Performance Lidar: Generating ultrafast pulsed power with GaN FETs

Light detection and ranging (lidar) is a versatile light-based remote sensing technology that recently has been the subject of great attention. It has shown up in a number of media venues and has even led to public debate about the engineering choices of a well-known electric car company, Tesla Motors [1]. While this article is not going to enter the fray, it will provide some background on lidar and discuss its strong connection to power electronics technologies.
An Alternative Way to Analyze Workflow Graphs

At the CAiSE conference in Heidelberg in 1999, Wasim Sadiq and Maria Orlowska presented an algorithm to verify workflow graphs [19]. The algorithm uses a set of reduction rules to detect structural conflicts. This paper shows that the set of reduction rules presented in [19] is not complete and proposes an alternative algorithm. The algorithm translates workflow graphs into so-called WF-nets. WF-nets are a class of Petri nets tailored towards workflow analysis. As a result, Petri-net theory and tools can be used to verify workflow graphs. In particular, our workflow verification tool Woflan [21] can be used to detect design errors. It is shown that the absence of structural conflicts, i.e., deadlocks and lack of synchronization, conforms to soundness of the corresponding WF-net [2]. In contrast to the algorithm presented in [19], the algorithm presented in this paper is complete. Moreover, the complexity of this alternative algorithm is given.
Cancer phenotype as the outcome of an evolutionary game between normal and malignant cells

Background:There is variability in the cancer phenotype across individuals: two patients with the same tumour may experience different disease life histories, resulting from genetic variation within the tumour and from the interaction between tumour and host. Until now, phenotypic variability has precluded a clear-cut identification of the fundamental characteristics of a given tumour type.Methods:Using multiple myeloma as an example, we apply the principles of evolutionary game theory to determine the fundamental characteristics that define the phenotypic variability of a tumour.Results:Tumour dynamics is determined by the frequency-dependent fitness of different cell populations, resulting from the benefits and costs accrued by each cell type in the presence of others. Our study shows how the phenotypic variability in multiple myeloma bone disease can be understood through the theoretical approach of a game that allows the identification of key genotypic features in a tumour and provides a natural explanation for phenotypic variability. This analysis also illustrates how complex biochemical signals can be translated into cell fitness that determines disease dynamics.Conclusion:The present paradigm is general and extends well beyond multiple myeloma, and even to non-neoplastic disorders. Furthermore, it provides a new perspective in dealing with cancer eradication. Instead of trying to kill all cancer cells, therapies should aim at reducing the fitness of malignant cells compared with normal cells, allowing natural selection to eradicate the tumour.
Sequential Optimization and Reliability Assessment Method for Efficient Probabilistic Design

Probabilistic design, such as reliability-based design and robust design, offers tool making reliable decisions with the consideration of uncertainty associated with de variables/parameters and simulation models. Since a probabilistic optimization ofte volves a double-loop procedure for the overall optimization and iterative probabili assessment, the computational demand is extremely high. In this paper, the seq optimization and reliability assessment (SORA) is developed to improve the efficien probabilistic optimization. The SORA method employs a single-loop strategy with a s of cycles of deterministic optimization and reliability assessment. In each cycle, op zation and reliability assessment are decoupled from each other; the reliability asses is only conducted after the deterministic optimization to verify constraint feasibility un uncertainty. The key to the proposed method is to shift the boundaries of violated straints (with low reliability) to the feasible direction based on the reliability informati obtained in the previous cycle. The design is quickly improved from cycle to cycle an computational efficiency is improved significantly. Two engineering applications, reliability-based design for vehicle crashworthiness of side impact and the integr reliability and robust design of a speed reducer, are presented to demonstrate the tiveness of the SORA method. @DOI: 10.1115/1.1649968 #
LIPN at SemEval-2017 Task 10: Filtering Candidate Keyphrases from Scientific Publications with Part-of-Speech Tag Sequences to Train a Sequence Labeling Model

This paper describes the system used by the team LIPN in SemEval 2017 Task 10: Extracting Keyphrases and Relations from Scientific Publications. The team participated in Scenario 1, that includes three subtasks, Identification of keyphrases (Subtask A), Classification of identified keyphrases (Subtask B) and Extraction of relationships between two identified keyphrases (Subtask C). The presented system was mainly focused on the use of part-of-speech tag sequences to filter candidate keyphrases for Subtask A. Subtasks A and B were addressed as a sequence labeling problem using Conditional Random Fields (CRFs) and even though Subtask C was out of the scope of this approach, one rule was included to identify synonyms.
Frontomaxillary facial angle in trisomy 21 fetuses at 16-24 weeks of gestation.

OBJECTIVES
To establish a normal range for the frontomaxillary facial (FMF) angle by three-dimensional (3D) ultrasound imaging and to examine the FMF angle in trisomy 21 fetuses at 16-24 weeks of gestation.


METHODS
We measured the FMF angle using 3D volumes of the fetal profile obtained with the transducer parallel to the long axis of the nose and at 45 degrees to the palate, which had been acquired from 150 normal fetuses and 23 fetuses with trisomy 21.


RESULTS
In the normal group there was no significant association between the FMF angle and gestational age; the mean FMF angle was 83.9 degrees (range, 76.9-90.2 degrees ) and the 95(th) centile was 88.5 degrees . In 15 (65.2%) of the fetuses with trisomy 21 the FMF angle was greater than 88.5 degrees . Repeatability studies demonstrated that in 95% of cases the difference between two measurements of FMF angle by the same operator and different operators was less than 5 degrees .


CONCLUSIONS
In the majority of second-trimester fetuses with trisomy 21 the FMF angle is increased.
Antioxidant defense responses: physiological plasticity in higher plants under abiotic constraints

Environmental stresses (salinity, drought, heat/cold, light and other hostile conditions) may trigger in plants oxidative stress, generating the formation of reactive oxygen species (ROS). These species are partially reduced or activated derivatives of oxygen, comprising both free radical $$ ( {\text{O}}_{2}^{\cdot - } ,{\text{OH}} \cdot , {\text{OH}}_{ 2} \cdot ) $$ and non-radical (H2O2) forms, leading to cellular damage, metabolic disorders and senescence processes. In order to overcome oxidative stress, plants have developed two main antioxidants defense mechanisms that can be classified as non-enzymatic and enzymatic systems. The first class (non-enzymatic) consists of small molecules such as vitamin (A, C and E), glutathione, carotenoids and phenolics that can react directly with the ROS by scavenging them. Second class is represented by enzymes among them superoxide dismutase, peroxidase and catalase which have the capacity to eliminate superoxide and hydrogen peroxide. In this review, we have tried to explore the related works, which have revealed the changes in the basic antioxidant metabolism of plants under various abiotic constraints.
The hidden treasure in nursing leadership: informal leaders.

AIM
The goal of the present article was to generate awareness of characteristics of informal leaders in healthcare with the emphasis on nurses in acute care settings. There is limited research or literature regarding informal leaders in nursing and how they positively impact nursing management, the organization and, ultimately, patient care. Identification of nurses with leadership characteristics is important so that leadership development and mentoring can occur within the nursing profession.


BACKGROUND
More than ever, nursing needs energetic, committed and dedicated leaders to meet the challenges of the healthcare climate and the nursing shortage. This requires nurse leaders to consider all avenues to ensure the ongoing profitability and viability of their healthcare facility.


KEY ISSUES
This paper discusses clinical nurses as informal leaders; characteristics of the informal nurse leader, the role they play, how they impact their unit and how they shape the organization.


IMPLICATION FOR NURSING MANAGEMENT
  Informal nurse leaders are an underutilized asset in health care. If identified early, these nurses can be developed and empowered to impact unit performance, efficiency and environmental culture in a positive manner.
Deep Learning based Large Scale Visual Recommendation and Search for E-Commerce

In this paper, we present a unied end-to-end approach to build a large scale Visual Search and Recommendation system for ecommerce. Previous works have targeted these problems in isolation. We believe a more eective and elegant solution could be obtained by tackling them together. We propose a unied Deep Convolutional Neural Network architecture, called VisNet 1, to learn embeddings to capture the notion of visual similarity, across several semantic granularities. We demonstrate the superiority of our approach for the task of image retrieval, by comparing against the state-of-the-art on the Exact Street2Shop [14] dataset. We then share the design decisions and trade-os made while deploying the model to power Visual Recommendations across a catalog of 50M products, supporting 2K queries a second at Flipkart, India’s largest e-commerce company. e deployment of our solution has yielded a signicant business impact, as measured by the conversion-rate.
ontoAGA: Ontology to Support Educational Systems Interoperability

Looking forward to promote the exchange and integration of information in order to build a unique reference model for the universities it is essencial to assure commom concepts of higher education institutions in Brazil. This paper proposes an University Support Management Ontology, named ontoAGA, to help the operation of legacy data in Semantic Web in a standardized manner and to allow the integration of databases with different technologies.To evaluate the research questions two usages cenarios were defined and the results point to the proposal viability. Resumo. Para promover o intercâmbio e a integração de informações de forma a se construir um modelo de referência para as universidades há necessidade de se estruturar conceitos comuns às instituições de ensino superior no Brasil. Este artigo propõe uma ontologia, no domínio da gestão acadêmica nas universidades, denominada ontoAGA, para ajudar a exploração de dados legados na web Semântica de forma padronizada e para possibilitar a integração de bases de dados de diferentes tecnologias. Para avaliação das questões de pesquisa foram definidos dois cenários de uso, cujos resultados apontam para a viabilidade da proposta.
Robust Real-time Object Detection

This paper describes a visual object detection framework that is capable of processing images extremely rapidly while achieving high detection rates. There are three key contributions. The first is the introduction of a new image representation called the “Integral Image” which allows the features used by our detector to be computed very quickly. The second is a learning algorithm, based on AdaBoost, which selects a small number of critical visual features and yields extremely efficient classifiers [6]. The third contribution is a method for combining classifiers in a “cascade” which allows background regions of the image to be quickly discarded while spending more computation on promising object-like regions. A set of experiments in the domain of face detection are presented. The system yields face detection performace comparable to the best previous systems [18, 13, 16, 12, 1]. Implemented on a conventional desktop, face detection proceeds at 15 frames per second.
Efficacy of Topical Combination of 0.25% Finasteride and 3% Minoxidil Versus 3% Minoxidil Solution in Female Pattern Hair Loss: A Randomized, Double-Blind, Controlled Study.

BACKGROUND
The relationship between female pattern hair loss (FPHL) and androgenic hormones is not well established, but some evidence indicates oral finasteride may be efficacious in FPHL. Use of a topical formulation has been proposed to minimize unwanted effects.


OBJECTIVES
Our objective was to compare the efficacy and safety of topical 0.25% finasteride combined with 3% minoxidil solution and 3% minoxidil solution as monotherapy in the treatment of FPHL.


METHODS
This was a prospective, randomized, double-blind study in 30 postmenopausal women with FPHL. Each participant was randomized to receive either topical 0.25% finasteride combined with topical 3% minoxidil or topical 3% minoxidil solution as monotherapy for 24 weeks. To determine efficacy, the hair density and diameter was measured and global photographic assessment was conducted at baseline and 8, 16, and 24 weeks. Side effects and serum dihydrotestosterone levels were also evaluated.


RESULTS
By 24 weeks, hair density and diameter had increased in both groups, and finasteride/minoxidil was significantly superior to minoxidil solution in terms of hair diameter (p = 0.039). No systemic side effects were reported. However, serum dihydrotestosterone levels in the finasteride/minoxidil group significantly decreased from baseline (p = 0.016).


CONCLUSION
A topical combination of 0.25% finasteride and 3% minoxidil may be a promising option in the treatment of FPHL with an additional benefit of increasing hair diameter. Nevertheless, as it may be absorbed percutaneously, it should be reserved for postmenopausal women.


TRIAL REGISTRATION
clinicaltrials.in.th; identifier TCTR20160912002.
Exercise treatment for major depression: maintenance of therapeutic benefit at 10 months.

OBJECTIVE
The purpose of this study was to assess the status of 156 adult volunteers with major depressive disorder (MDD) 6 months after completion of a study in which they were randomly assigned to a 4-month course of aerobic exercise, sertraline therapy, or a combination of exercise and sertraline.


METHODS
The presence and severity of depression were assessed by clinical interview using the Diagnostic Interview Schedule and the Hamilton Rating Scale for Depression (HRSD) and by self-report using the Beck Depression Inventory. Assessments were performed at baseline, after 4 months of treatment, and 6 months after treatment was concluded (ie, after 10 months).


RESULTS
After 4 months patients in all three groups exhibited significant improvement; the proportion of remitted participants (ie, those who no longer met diagnostic criteria for MDD and had an HRSD score <8) was comparable across the three treatment conditions. After 10 months, however, remitted subjects in the exercise group had significantly lower relapse rates (p = .01) than subjects in the medication group. Exercising on one's own during the follow-up period was associated with a reduced probability of depression diagnosis at the end of that period (odds ratio = 0.49, p = .0009).


CONCLUSIONS
Among individuals with MDD, exercise therapy is feasible and is associated with significant therapeutic benefit, especially if exercise is continued over time.
Design and Validation of Computer Protocols

This report aims at giving a short overview on rank function analysis of authentication protocols concentrating on the results of Schneider in [4] and Heather in [2]. Therefore it shows a standard form of protocol implementation in CSP, shows how authentication properties can be captured as trace specifications, gives basic definitions necessary to reason about the unbounded set of messages, reformulates the central rank function theorem and restates it proof. Additionally it gives hints on applying this approach to verify secrecy protocols as well, a short overview on tool support available and some hints on interesting properties of rank functions. This report will use notations introduced in earlier reports [11-16] throughout and only reintroduce notations where they are considered vital.