nils-herrmann/clean_scirepeval huggingface dataset:
Stock Market Index Prediction Using Artificial Neural Network

In this study the ability of artificial neural network (ANN) in forecasting the daily NASDAQ stock exchange rate was investigated. Several feed forward ANNs that were trained by the back propagation algorithm have been assessed. The methodology used in this study considered the short term historical stock prices as well as the day of week as inputs. Daily stock exchange rates of NASDAQ from January 28, 2015 to 18 June, 2015 are used to develop a robust model. First 70 days (January 28 to March 7) are selected as training dataset and the last 29 days are used for testing the model prediction ability. Networks for NASDAQ index prediction for two type of input dataset (four prior days and nine prior days) were developed and validated.
A high efficiency reconfigurable cryptographic processor
Venue: 2016 International Conference on Integrated Circuits and Microsystems (ICICM)

With the significant attention to information security, mobile terminals such as smartphone always be demand for integrating cryptographic processor. In this paper, a high efficiency reconfigurable cryptographic processor is presented. Integrating small amounts of computing units designed by reconfigurable technology and developing instruction level parallelism of different operations in a block and among multiple blocks, the proposed architecture can improve the performance of cryptographic algorithm under the condition of limited resources. The processor was simulated and synthesized in 65nm CMOS process. Experimental results show that the processor is small area and high throughput, and outperforms the state of the art processors in area efficiency.
Bounded Off Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design
Venue: ICML

Successfully recommending personalized course schedules is a difficult problem given the diversity of students knowledge, learning behaviour, and goals. This paper presents personalized course recommendation and curriculum design algorithms that exploit logged student data. The algorithms are based on the regression estimator for contextual multi armed bandits with a penalized variance term. Guarantees on the predictive performance of the algorithms are provided using empirical Bernstein bounds. We also provide guidelines for including expert domain knowledge into the recommendations. Using undergraduate engineering logged data from a post secondary institution we illustrate the performance of these algorithms.
Feature Extraction Techniques for Facial Expression Recognition Systems

Automatic facial expression recognition has become a progressive research area since it plays a major role in human computer interaction. The facial expression recognition finds its major application in areas like social interaction and social intelligence. However it is not an easy task because the facial image, facial occlusion, face color/shape etc. is not easy to deal with. In this paper, various techniques for feature extraction like Gabor filters, Principal Component Analysis (PCA) Local Binary Patterns (LBP) Linear Discriminant Analysis (LDA) DCT, with different classifiers like Support Vector Machine (SVM) and Neural Networks, which are used to recognize human expression in various conditions on different databases are being examined. KeywordsFacial expression, Geometric features, Appearance features, PCA, LBP, Gabor, LDA
Automatic facial expression recognition: A survey based on feature extraction and classification techniques
Venue: 2016 International Conference on ICT in Business Industry Government (ICTBIG)

Facial expression carries information about the emotional and physical state of a human being. In the past few years facial expression recognition has become a promising research area. With the developing robotic era the systems needs intelligence to understand human's behavior. Expression recognition is applied and useful from emoticons to disease detection in medical field. Apart from automated systems the applications include human computer interfaces, human emotion analysis, awareness systems, surveillance and security, medical diagnosis, law enforcement, automated tutoring systems and many more.
Single cell TCRseq: paired recovery of entire T cell alpha and beta chain transcripts in T cell receptors from single cell RNAseq
Venue: Genome Medicine

Accurate characterization of the repertoire of the T cell receptor (TCR) alpha and beta chains is critical to understanding adaptive immunity. Such characterization has many applications across such fields as vaccine development and response, clone tracking in cancer, and immunotherapy. Here we present a new methodology called single cell TCRseq (scTCRseq) for the identification and assembly of full length rearranged V(D)J T cell receptor sequences from paired end single cell RNA sequencing reads. The method allows accurate identification of the V(D)J rearrangements for each individual T cell and has the novel ability to recover paired alpha and beta segments. Source code is available at https:/github.com/ElementoLab/scTCRseq.
Annotation and differential analysis of alternative splicing using de novo assembly of RNAseq data

Genome wide analyses reveal that more than 90% of multi exonic human genes produce at least two transcripts through alternative splicing (AS) Various bioinformatics methods are available to analyze AS from RNAseq data. Most methods start by mapping the reads to an annotated reference genome, but some start by a de novo assembly of the reads. In this paper, we present a systematic comparison of a mapping first approach (FaRLine) and an assembly first approach (KisSplice) These two approaches are event based, as they focus on the regions of the transcripts that vary in their exon content. We applied these methods to an RNAseq dataset from a neuroblastoma SK N SH cell line (ENCODE) differentiated or not using retinoic acid. We found that the predictions of the two pipelines overlapped (70% of exon skipping events were common) but with noticeable differences. The assembly first approach allowed to find more novel variants, including novel unannotated exons and splice sites. It also predicted AS in families of paralog genes. The mapping first approach allowed to find more lowly expressed splicing variants, and was better in predicting exons overlapping repeated elements. This work demonstrates that annotating AS with a single approach leads to missing a large number of candidates. We further show that these candidates cannot be neglected, since many of them are differentially regulated across conditions, and can be validated experimentally. We therefore advocate for the combine use of both mapping first and assembly first approaches for the annotation and differential analysis of AS from RNAseq data.
PENGARUH KINERJA MAKROEKONOMI TERHADAP DANA PIHAK KETIGA BANK SYARIAH INDONESIA

This study Aimed to analyze the influence of GDP, SBIS and inflation on third party funds (DPK) in the short term and long term in the period quarterely 2008: 1 until 2014: 4. The variables used are third party funds (DPK) Gross Domestic Product (GDP) inflation, and Bank Indonesia Certificates Sharia (SBIS) Mmethodology used is a method of Error Correction Model (ECM) Before the test of Error Correction Model (ECM) the models must pass the prerequisite test unit root, integration and Co integration. The results showed the models Prerequisites Error Correction Model (ECM) can be used and passed the prerequisite test. The results using methods Error Correction Model (ECM) it was found that the variable inflation does not significantly influence the Third Party Funds (TPF) in the long term. While in the short term inflation is a significant variable to the Third Party Fund (DPK)
Critical Evaluation of Prince2 and Agile Project Management Methodologies for a complex project

Most of major IT projects failed due to its complexity and the project complexity is determined by the intensity of business requirements and its fluctuant nature. Prince2 is the solution for a sophisticated project because of its vast range of stage driven processes which mainly focus on project benefits in each stage. The main objective of Prince2 is breaking the complexity into small parts/stages which can be achieved easily. The seven processes of Prince2 cover the entire project lifecycle including requirement gathering, as is process, development, and product delivery. The seven themes cover major concerns of any project including business case, risk management and quality on deliverables. The seven principles are the seven pillars of Prince2 which sustain its standard. It is understood that the Agile project management methodology is suitable for medium and small scaled projects. The five groups processes of Agile project management intensely focus on development activities and make sure the required product is delivered without any error. It is recommended that Prince2 is certainly suitable for complex projects as a dominant project management methodology, however, Scrum technique can be used for depth IT development as a secondary project management methodology within Prince2.
A Study on Project Management Based on PMBOK and PRINCE2

The Project Management Body of Knowledge (PMBOK) is a group of processes and knowledge fields which are generally accepted as greatest practice within the project management discipline. The PMBOK Guide is also an internationally recognized standard which provides the fundamentals of project management as they apply to a wide range of projects. PRINCE2 is a project management methodology standard in the United Kingdom and Europe. This standard is the required method for all UK government commissioned projects. PRINCE2 is in the public domain and offers best practice guidance on how to manage a project. The aim of this study is to compare PRINCE2 and PMBOK to recognize the characteristics of these best practices in order to provide decision criteria for governments with regard to selecting IT project management methodology.
Comparison of stakeholder management and change management factors in managing successful versus unsuccessful it projects

Shah, Ishita Viren.  Purdue University, May 2016. Comparison of Stakeholder Management and Change Management Factors in Managing Successful Versus Unsuccessful IT Projects.  The purpose of this study is to conduct a meta analysis of published case studies of projects, which are driven by information technology (IT) and are using a formal organizational change management method to manage those changes. It also identifies the common factors that influence the success or failure of a project. Change impacts people directly or indirectly and much of the research proves that people tend to resist change. The study reviews recent research and discusses the evolution of change management and current practices. The study focuses on finding the case studies published in well known journals. It also analysis the factors affecting the change management during the implementation of an IT system being communication and common knowledge, engaging employees and training them about the change and employees' interest for the change. The research concludes that there is gap in Project Management Body of Knowledge (PMBOK) and gives a conceptual model as a recommendation for future research.
Household task demands for quiet and focused behavior facilitate performance by ADHD youth.
Venue: Arquivos de neuro psiquiatria

This study evaluated the associations among symptoms of attention deficit/hyperactivity disorder (ADHD) and of oppositional defiant disorder (ODD) in children and adolescents' performance in household tasks and assistance provided by caregivers. Parents of children from 6 to 14 years old with ADHD (n 67) were interviewed with the Children Helping Out: Responsibilities, Expectations, and Supports (CHORES) instrument. Significant correlations were found between symptoms of ODD and assistance in self care tasks (r 0.31; p 0.01) symptoms of hyperactivity correlated with assistance in self care (r 0.30, p 0.01) and family care (r 0.25, p 0.04) tasks. Age was directly associated with the number of tasks performed by children and inversely related to the assistance provided by caregivers. A greater number of ODD symptoms resulted in more household assistance from caregivers. Characteristics of ODD symptoms, such as disobedience and hostility in the face of authority, may limit these children in accessing household tasks by their own initiative, requiring assistance from caregivers.
Ask Me Anything: Free Form Visual Question Answering Based on Knowledge from External Sources
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

We propose a method for visual question answering which combines an internal representation of the content of an image with information extracted from a general knowledge base to answer a broad range of image based questions. This allows more complex questions to be answered using the predominant neural network based approach than has previously been possible. It particularly allows questions to be asked about the contents of an image, even when the image itself does not contain the whole answer. The method constructs a textual representation of the semantic content of an image, and merges it with textual information sourced from a knowledge base, to develop a deeper understanding of the scene viewed. Priming a recurrent neural network with this combined information, and the submitted question, leads to a very flexible visual question answering approach. We are specifically able to answer questions posed in natural language, that refer to information not contained in the image. We demonstrate the effectiveness of our model on two publicly available datasets, Toronto COCO QA [23] and VQA  and show that it produces the best reported results in both cases.
Gun Violence: A Public Health and Nursing Concern.
Venue: Journal of perianesthesia nursing official journal of the American Society of PeriAnesthesia Nurses

ONE MORE SENSELESS tragedy Orlando, FL joins numerous cities San Bernadino, CA; Newtown, CT; Littleton, CO; Aurora, CO; Blacksburg, VA; Roseburg, OR; Tucson, AZ; and others in a club which no one wants to join. It was predictable that after the shock and concern for families of the dead that the country would be embroiled in a political tug of war over the 2nd Amendment and right to own guns with one side debating the folly of any kind of further restraints on gun ownership and the other side debating the folly of availability of assault like weapons to the everyday person. I will not be able to solve the political debate, but I can no longer remain silent. Part of the ASPAN Perianesthesia Standards for Ethical Practice demands responsibility to patients and advocacy for nursing, patients, and families.
Statistical power of intensity and feature based similarity measures for registration of multimodal remote sensing images
Venue: Remote Sensing

This paper investigates performance characteristics of similarity measures (SM) used in image registration domain to discriminate between aligned and not aligned reference and template image (RI and TI) fragments. The study emphasizes registration of multimodal remote sensing images including optical to radar, optical to DEM, and radar to DEM scenarios. We compare well known area based SMs such as Mutual Information, Normalized Correlation Coefficient, Phase Correlation, and feature based SM using SIFT and SIFT OCT descriptors. In addition, a new SM called logLR based on log likelihood ratio test and parametric modeling of a pair of RI and TI fragments by the Fractional Brownian Motion model is proposed. While this new measure is restricted to linear intensity change between RI and TI (assumption somewhat restrictive for multimodal registration) it takes explicitly into account noise properties of RI and TI and multivariate mutual distribution of RI and TI pixels. Unlike other SMs, distribution of logLR measure for the null hypothesis does not depend on registration scenario or fragments size and follows closely chi squared distribution according to Wilks's theorem. We demonstrate that a SM utility for image registration purpose can be naturally represented in (True Positive Rate, Positive Likelihood Rate) coordinates. Experiments on real images show that overall the logLR SM outperforms the other SMs in terms of area under the ROC curve, denoted AUC. It also provides the highest Positive Likelihood Rate for True Positive Rate values below 0.4 0.6. But for certain registration problem types, logLR can be second or third best after MI or SIFT SMs.
Factors Affecting Non Teaching Staff Development in Kenyan Universities

The study was carried out to investigate the factors that affect non teaching staff development in campuses of Kenyan universities. In light of theoretical literature reviewed and empirical studies related to employee development, the research focused on the five sub variables considered in this study, namely work environment facilities available, technology development, staff training and development, policies and work systems (infrastructure) and number of non teaching staff working in campuses. Literature review was conducted to identify what other researchers have done in the areas of staff development and open to further understanding of their precious contribution to this area of study. The research study was carried out in Mt. Kenya region. Out of sixteen campuses in Mt. Kenya region four were randomly selected. A cross section survey random sampling was used to select the population through of different cadre of middle level non academic staff in various sections in the four campuses. A sample of 30 participants were used which is 20% of population study. Data was collected through questionnaires administered through drop and pick by the researcher and personal interview were conducted where possible. The Questionnaires were screened for completeness. Inferential statistics method was used to analyze the data collected. Data analysis, interpretation and presentation by use of tables, pie charts and bar graphs was done. Correlation analysis and hypothesis testing was done to test the strength of association of variables.
Scanning LIDAR in Advanced Driver Assistance Systems and Beyond: Building a road map for next generation LIDAR technology
Venue: IEEE Consumer Electronics Magazine

Advanced driver assistance systems (ADASs) are accelerating the growth of infrared (IR) devices used in automotive applications. Some of these are well known applications, such as ambient light sensing, steering wheel sensors, and rain sensors. However, many new technologies for ADASs, such as LIDAR, driver monitoring, adaptive beam, and matrix lighting, are still in the early evolution phase of the product life cycle.  1 provides a snapshot of some of the IR devices from OSRAM Opto Semiconductors (Regensburg, Germany) and the applications for which they can be used.
Sustainable value propositions: Framework and implications for technology suppliers

Advances in sustainable purchasing put pressure on firms to evaluate and demonstrate the sustainability of their products and services. In this paper, we coin the term sustainable value proposition develop a process framework for building sustainable value propositions, and illustrate its application with two technology intensive offerings. By integrating the literature on sustainable marketing and customer value propositions with life cycle assessment methodologies, we build a process framework that can be applied to demonstrate and evaluate the economic, environmental and social benefits of industrial products and services. The framework comprises 1) identification of potential impacts, 2) identification of key value creation mechanisms, 3) choosing key indicators, 4) life cycle modeling, and 5) life cycle value demonstration. Through two case studies, we examine the development of sustainable value propositions in two industry sectors: metallurgical and automotive. The results highlight the value provided to customers through the combination of direct economic benefits and derivative benefits of reduced environmental and social impacts. Our paper contributes to the growing field of sustainable marketing by offering guidelines on how to integrate sustainability with the marketing and purchasing of technology intensive offerings. In addition, we offer guidelines for how to construct sustainable value propositions that resonate with customers.
Methods for the management of distributed electricity networks using software agents and market mechanisms: A survey

Significant research efforts are being devoted to the development of distributed electricity networks that aim to facilitate the gradual integration of manageable loads and distributed energy resources. These environments are conceived as self managed, enclosed areas of the distribution network that integrates many of the technologies and information systems that will be part of the future Smart Grid. Both the new scheme and devices are expected to offer users presence in the grid operation so that their preferences and interests are relevant. To this end, the management system has been frequently proposed in form of an electronic market in which producers and consumers exchange energy blocks so that the consumption and production are continuously balanced. As the state of the art reflects, intelligent agents are an suitable technology for building energy management systems in which users participate actively in an intelligent and autonomous manner. This document presents a review of the most relevant works that tackle the safe and effective management of distributed electricity networks through autonomous software agents that negotiate on behalf of customers. This document presents a discussion of the suitability of the most relevant works, highlighting those that are most promising, and identifying the issues that are still necessary to reinforce in future research.
Applications of Intelligent Agents in Health Sector A Review
Venue: Int. J. E Health Medical Commun.

Health sector is a growing field and health conscience has been a major concern for everyone. Particularly in the health care sector, Information and communication Technology, enabled devices like Smart phones, Tablet PC, Sensors, RFID etc are predominantly used for ease of access and use towards decision processing. So looking into expectations of making devices smarter and intelligent enough for health care application, there has been a growing interest in the use of Software agents in health care application. This Survey paper predominantly concentrates on showing the usage and application of intelligent agent technology in health care sector pertaining to hospital search appointment, patient health monitoring and mobile health record, with a thorough literature review and appropriate screenshots necessary.