nils-herrmann/clean_scirepeval huggingface dataset:
Adaptive Feature Fusion via Graph Neural Network for Person Re identification
Venue: ACM Multimedia
Year: 2019

Person Re identification (ReID) targets to identify a probe person appeared under multiple camera views. Existing methods focus on proposing a robust model to capture the discriminative information. However, they all generate a representation by mining useful clues from a given single image, and ignore the intercommunication with other images. To address this issue, we propose a novel network named Feature Fusing Graph Neural Network (FFGNN) which fully utilizes the relationships among the nearest neighbors of the given image, and allows message propagation to update the feature of the node during representation learning. Given an anchor image, the FFGNN firstly obtains its Top K nearest images based on the feature generated by the trained Feature Extracting Network(FEN) We then construct a graph G based on the obtained K+1 images, in which each node represents the feature of an image. The edge of the graph G is obtained by combing the visual similarity and Jaccard similarity between nodes. Within the constructed graph G, FFGNN conducts message propagation and adaptive feature fusion between nodes by iteratively performing graph convolutional operation on the input features. Finally, the FFGNN outputs a robust and discriminative representation which contains the information from its similar images. Extensive experiments on three public person ReID datasets including Market 1501, DukeMTMC ReID, and CUHK03 demonstrate that the proposed model can achieve significant improvement against state of the art methods.
Assessment of the Quality of Mid Day Meal Packaged for Nursery School Children in Ile Ife, Nigeria
Year: 2017

This study identified the kind of food and snacks packaged as mid day meal for nursery school children and determined the magnitude of influence of the children on their parents' choice of school bound mid day in Ile Ife, Nigeria. The study adopted the survey research design and collected relevant information from parents of nursery school children and their classroom teachers. The study observed that there was no synergy of efforts between the parents and teachers of nursery school children in ensuring that food and snacks of good quality were packaged as mid day meal for Ile Ife nursery school children, as Rice with Stew was the most prominent mid day in their launch pack alongside. Biscuits which have less nutritional value and are not balanced diet wise.
Flexible and Transparent Ferroferric Oxide Modified Silver Nanowire Film for Efficient Electromagnetic Interference Shielding
Year: 2020

Transparent and flexible electromagnetic interference (EMI) shielding film is highly desirable due to the fast growing flexible electronics. A silver nanowire (Ag NW) film is considered to be an ideal candidate for a transparent and flexible EMI shielding film but suffers low EMI shielding effectiveness (SE) at high transparency and poor bending durability. Herein, we introduce ferroferric oxide (Fe3O4) into a Ag NW film and demonstrate a robust EMI shielding film, which exhibits SE of 24.9 dB at 8.2 GHz and optical transparency of 90% Fe3O4 exhibits roles of the improved absorption loss for electromagnetic radiation due to its high permeability, the enhanced reflection loss for electromagnetic radiation by increasing the conductivity of Ag NWs film, and the improved stability for the enhanced adhesion of the Ag NW EMI shielding film. Our work provides a facile method for high performance transparent EMI shielding film, which exhibits great potential for protection for electronic devices.
Detecting the Chirp Signals on the Surface of the Transformation Materials GRIN Lens
Venue: 2019 Thirteenth International Congress on Artificial Materials for Novel Wave Phenomena (Metamaterials)
Year: 2019

Part of the optical axis inside a conventional graded index lens is exposed to the surface with the help of transformation optics, with which the chirpiness detection can be more convenient, efficient and precise based on the optical fractional Fourier transform.
Clinical Comparison of Head and Facial Massage and Qiaogong Point Massage as Adjuvant Therapy of Hypertension
Year: 2009

To compare the clinical efficacy of head and facial massage to Qiaogong point massage in adjuvant treatment of hypertension.A total of 64 hypertension patients whose blood pressure had been managed by extended release nifedipine tablets in previous received the head and facial massage and Qiaogong point massage randomly.Clinical symptoms,blood pressure and heart rate before and after treatment were compared.The head and facial massage group had better outcomes in dizziness,headache and irritability improvement(P0.05).On the first day after treatment,the blood pressure reduced more in the Qiaogong point massage group compared to the other group;the situation was turned over after 15 days treatment.No significant difference was found in the change of blood pressure between the 2 groups(P0.05).Conclusion:The Qiaogong point massotherapy has temporary antihypertensive effect,while the head and facial massage has better hypertension and symptom improvement after long time treatment.
PENGARUH KURS VALUTA ASING DAN TINGKAT BAGI HASIL TERHADAP VOLUME DEPOSITO MUDHARABAH USD PADA PERBANKAN SYARIAH (PERIODE JANUARI 2011 MARET 2015)
Year: 2020

Tujuan penelitian ini adalah untuk menganalisis pengaruh kurs USD dan tingkat bagi hasil deposito mudharabah USD terhadap volume deposito mudharabah USD pada perbankan syariah. Data yang digunakan pada penelitian ini adalah data bulanan dari Januari 2011 sampai Maret 2015. Penelitian ini menggunakan metode analisis linier regresi berganda dengan menggunakan program komputer SPSS versi 22.0 dan Microsoft Excel 2010. Hasil analisis menunjukkan bahwa secara parsial, kurs USD berpengaruh positf signifikan terhadap volume deposito mudharabah USD, sedangkan tingkat bagi hasil deposito mudharabah USD berpengaruh negatif tidak signifikan. Secara simultan variabel kurs USD dan tingkat bagi hasil deposito mudharabah USD berpengaruh signifikan terhadap volume deposito mudharabah USD. Hal ini dibuktikan dengan nilai sig F 0,000 yang lebih kecil dari signifikansi 5% Kemampuan prediksi dari kedua variabel tersebut terhadap volume deposito mudharabah USD adalah 88,4% sebagaimana ditunjukkan oleh besarnya adjusted R square, sedangkan sisanya 11,6% dipengaruhi oleh faktor lain. Kata Kunci Kurs, Tingkat Bagi Hasil Deposito Mudharabah, Volume Deposito Mudharabah dan Analisis  The purpose of this study was to analyze the influence of the USD exchange rate and the rate for the mudharabah deposit for USD toward the volume of deposit of mudharabah. The data used in this study is the monthly data from January 2011 to March 2015. This study uses linear regression analysis using SPSS version 22.0 and Microsoft Excel 2010. The analysis showed that partially, the USD exchange rate impact positf significantly to the volume of deposits mudaraba USD, while the rate for the deposits of USD mudharabah significant negative effect. Simultaneously, USD rate and deposits of USD mudharabah significantly affect the volume of deposits mudarabah USD. This is evidenced by the value of sig F 0,000 less than the 5% significance. The predictive ability of the variables on the volume of deposits was 88.4% mudharabah USD. As indicated by the adjusted R square, while the remaining 11.6% is influenced by other factors.  kurs, Rate of Profit of Mudharabah Deposit, volume of Deposit, and regresseion analisys
Women and games: technologies of the gendered self
Venue: New Media Soc.
Year: 2007

This study examines how individual differences in the consumption of computer games intersect with gender and how games and gender mutually constitute each other. The study focused on adult women with particular attention to differences in level of play, as well as genre preferences. Three levels of game consumption were identified. For power gamers, technology and gender are most highly integrated. These women enjoy multiple pleasures from the gaming experience, including mastery of game based skills and competition. Moderate gamers play games in order to cope with their real lives. These women reported taking pleasure in controlling the gaming environment, or alternately that games provide a needed distraction from the pressures of their daily lives. Finally, the non gamers who participated in the study expressed strong criticisms about game playing and gaming culture. For these women, games are a waste of time, a limited commodity better spent on other activities.
Innovation collaborative et innovation ouverte caracteristiques de leur mise en oeuvre
Year: 2021

L'innovation ouverte et l'innovation collaborative sont largement repandues dans differentes disciplines, du management a l'economie en passant par les sciences sociales. Ces concepts ont ete developpes en opposition a l'innovation fermee qui promeut des activites internes aux firmes, ne s'appuyant que sur les ressources deja presentes. L'ouverture des frontieres des entreprises permet d'intensifier les collaborations avec divers types d'acteurs, pour soutenir l'innovation a l'interne. Par ailleurs, le degre d'ouverture que les entreprises doivent assurer pour promouvoir les processus d'innovation sont sources de divergence dans plusieurs travaux. De plus, peu de travaux ont etudie la dimension territoriale de l'innovation ouverte. La proximite physique serait une condition necessaire et minimale pour l'innovation, ainsi que d'autres dimensions de la proximite (cognitive et institutionnelle) Les systemes nationaux d'innovation, districts industriels et clusters favorisant la production et circulation de connaissances sont a l'oeuvre et soutenus par des politiques locales, et fleurissent depuis plusieurs decennies. Finalement, l'innovation ouverte favorise une diversite de partenariats qui deviennent possibles, bien que cela engendre aussi des difficultes a differents niveaux entre les entreprises impliquees.
Legal origins and mortgage finance contradictions
Year: 2017

This study aims to examine why Ghana has English legal origins (hypothesised as a legal framework that promotes financial development) but has not developed a well functioning mortgage finance market.  The authors adopt the institutional autopsy approach developed by Milhaupt and Pistor (2008) This study is not a cross country study but a historical examination of Ghana's mortgage finance regulatory framework. The institutional autopsy framework considers the iterative process of change in a system and allows for context specific system analysis.  The authors note that for a long period of about 68 years (1940 2008) some of the legal rules regulating mortgage finance were not typical of the hypothesised characteristics of the English common law tradition. These rules, including, interest rate controls, excessive entry barriers, loan default guarantee discriminations and complex foreclosure procedures, tended to inadequately protect creditors. In the context of the history of military rule and law making, judicial discretion that could have promoted legal efficiency and strengthened contract enforcement was also limited. During this period, the legal system demonstrated a concentrated and coordinative character. New legislation in the form of the Home Mortgage Finance Act 2008 (Act 770) attempts to resolve some of these bottlenecks and improve creditor rights protection.  The study focuses solely on how the legal institution affects creditor protection and mortgage finance in Ghana.  Policy wise, the study deepens the understanding of the channels through which the law affects the development of mortgage finance.  To the best of the authors' knowledge, the methodology used (institutional autopsy) is novel in the context of analysing mortgage finance.
An optimization method for control parameters of underwater gliders considering energy consumption and motion accuracy
Year: 2021

Energy consumption and motion accuracy are both important performance metrics for underwater gliders, which are closely related to the glider control parameters values. For the above two performance metrics, we study a multi objective optimization method to determine the control parameters values that make the glider have the better performance. Here the control parameters include the net buoyancy adjustment amount and the movable internal mass block translation amount. The basis of the optimization method is the dynamic model of the glider. Based on the dynamic model established by us, the evaluation parameter of energy utilization rate is deduced, and it reflects the ideal voyage range produced by 1 kJ energy. Besides, the evaluation parameter of motion accuracy is defined by the mean and standard deviation of the glider motion error in uncertain current. Next, the flow, which is used for calculating the above two evaluation parameters under the same set of control parameters values, is proposed. Based on the above flow and the radial basis function neural network, we fit surrogate models to participate in the optimization calculation to improve the efficiency. Here the optimization objectives are to maximize the energy utilization rate and minimize the glider motion error simultaneously. Then, we obtain the Pareto optimal set containing many sets of control parameters values by using the non dominated sorting genetic algorithm II. Finally, the selection rule of control parameters values is shown by an example. This research can be used for determining the appropriate control parameters values of underwater gliders in actual application.
Indian Stock Market Prediction Using Machine Learning and Sentiment Analysis
Year: 2019

Stock market is a very volatile in deterministic system with vast number of factors influencing the direction of trend on varying scales and multiple layers. Efficient Market Hypothesis (EMH) states that the market is unbeatable. This makes predicting the uptrend or downtrend a very challenging task. This research aims to combine multiple existing techniques into a much more robust prediction model which can handle various scenarios in which investment can be beneficial. Existing techniques like sentiment analysis or neural network techniques can be too narrow in their approach and can lead to erroneous outcomes for varying scenarios. By combing both techniques, this prediction model can provide more accurate and flexible recommendations. Embedding technical indicators will guide the investor to minimize the risk and reap better returns.
Spatial Versus Social Mismatch: The Strength of Weak Ties
Year: 2011

The aim of this paper is to provide a new mechanism based on social interactions explaining why distance to jobs can have a negative impact on workers' labor market outcomes, especially ethnic minorities. Building on Granovetter's idea that weak ties are superior to strong ties for providing support in getting a job, we develop a model in which workers who live far away from jobs tend to have less connections to weak ties. Because of the lack of good public transportation in the US, it is costly (both in terms of time and money) to commute to business centers to meet other types of people who can provide other source of information about jobs. If distant minority workers mainly rely on their strong ties, who are more likely to be unemployed, there is then little chance of escaping unemployment. It is therefore the separation in both the social and physical space that prevents ethnic minorities finding a job.
AI Powered Blockchain A Decentralized Secure Multiparty Computation Protocol for IoV
Venue: IEEE INFOCOM 2020 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
Year: 2020

The rapid advancements in autonomous technologies have paved way for vehicular networks. In particular, Vehicular Ad hoc Network (VANET) forms the basis of the future of Intelligent Transportation System (ITS) ITS represents the communication among vehicles by acquiring and sharing the data. Though congestion control is enhanced by Internet of Vehicles (IoV) there are various security criteria where entire communication can lead to many security and privacy challenges. A blockchain can be deployed to provide the IoV devices with the necessary authentication and security feature for the transfer of data. Blockchain based IoV mechanism eliminates the single source of failure and remains secure at base despite having strong security, the higher level layers and applications are susceptible to attacks. Artificial Intelligence (AI) has the potential to overcome several vulnerabilities of current blockchain technology. In this paper, we propose an AI Powered Blockchain which provides auto coding feature for the smart contracts making it an intelligent contract. Moreover, it speeds up the transaction verification and optimises energy consumption. The results show that intelligent contracts provide higher security compared to smart contracts considering range of different scenarios.
The nature of ethical entrepreneurship in tourism
Year: 2017

This article examines ethical entrepreneurship in tourism by developing a Weberian Ideal Type Construct for an ethical tourism entrepreneur, and thereby deeper understanding of ethical tourism entrepreneurship. This research contributes to the extremely scarce literature at the academic juncture of ethics, tourism and entrepreneurship, which is significant as tourism is characterised by entrepreneurial idiosyncrasies with ethical challenges. The study is methodologically rooted in Personal Construct Theory. The qualitative findings from 15 semi structured interviews with entrepreneurs, who have been commended for their ethical business conduct, show that ethical entrepreneurship in tourism is based on intuitionism, care and relationships, future orientation, humility and benevolence as key virtues. These findings challenge the more traditional views of entrepreneurial attributes, such as egoism, risk taking and opportunism.
Effect of Vacuum Microwave Drying on the Quality and Storage Stability of Strawberries
Year: 2016

The aim of this study was to determine how vacuum assisted microwave drying (VMD, 50C, 6 kPa for 3 h) affects the quality attributes and shelf life of dehydrated strawberries. Changes of quality attributes such as color, texture, and rehydration, shrinkage, polyphenol contents, antioxidant activity, and physicochemical and sensory properties were assessed after VMD. Vacuum packed, dehydrated strawberries were stored at 20C in the dark for 6 months. Decay of anthocyanins, flavonoids and polyphenols, and antioxidant activity was determined and modeled according to first order kinetics. VMD resulted to minimum color difference. Texture changed by increased mechanical resistance and stiffness, and decreased toughness after VMD. Sensory attributes were between 3.5 and 4.3 on 5 point intensity hedonic scale. Anthocyanins were the most unstable components in strawberries after VMD and storage, assessing the strawberry shelf life to 68 days. Finally, VMD is a promising technology that can be used to maintain fruit quality and extend shelf life. Practical Applications Drying is particularly important for handling and distribution of agricultural products with high moisture content and limited shelf life such as fruits and vegetables. The main objective of drying is to reduce moisture content to a level where microbial spoilage and deteriorative chemical reactions of agricultural products are minimal. However, the degradation of nutrients in food during convective hot air drying results to quality loss. Therefore, new drying equipment and drying techniques have to be designed and studied. Vacuum assisted microwave drying is an emerging dehydration method that may be efficient to preserve quality characteristics of food and additionally leads to shorten effective drying time. The purpose of this study was to determine the effects of vacuum assisted microwave drying and subsequent product storage on the quality attributes and shelf life of strawberry fruits. This preservation technique may avoid freezing or refrigeration of fruit.
Combining self organizing neural nets with multivariate statistics for efficient color image retrieval
Venue: Comput. Vis. Image Underst.
Year: 2006

An efficient novel strategy for color based image retrieval is introduced. It is a hybrid approach combining a data compression scheme based on self organizing neural networks with a nonparametric statistical test for comparing vectorial distributions. First, the color content in each image is summarized by representative RGB vectors extracted using the Neural Gas network. The similarity between two images is then assessed as commonality between the corresponding representative color distributions and quantified using the multivariate Wald Wolfowitz test. Experimental results drawn from the application to a diverse collection of color images show a significantly improved performance (approximately 10 15% higher) relative to both the popular, simplistic approach of color histogram and the sophisticated, computationally demanding technique of Earth Mover's Distance.
A Visual Rule Generation Tool for SWRL
Venue: RuleML+RR
Year: 2020

The number of applications relying on representing knowledge through ontologies and interactions through rules has grown significantly in the past years. The knowledge acquisition needed for ontology engineering requires input from domain experts, which can lack computing and knowledge modeling skills. In this paper, we present a generic visual programming tool for generating SWRL rules for OWL ontologies. The developed web application allows ontology developers and domain experts alike to easily create SWRL rules. By interacting with a simple graphical user interface, the users can specify the antecedents and consequents of SWRL rules by combining ontology entities and applying restrictions on them. Different control features, such as implicit variable handling, are implemented, which only enables rule creation options that maintain the correct SWRL syntax and maintain correct semantics. Consistency is ensured by allowing the users to review the generated rules and their effects before actually applying them to the ontology.
Unsupervised feature learning for audio classification using convolutional deep belief networks
Venue: NIPS
Year: 2009

In recent years, deep learning approaches have gained significant interest as a way of building hierarchical representations from unlabeled data. However, to our knowledge, these deep learning approaches have not been extensively studied for auditory data. In this paper, we apply convolutional deep belief networks to audio data and empirically evaluate them on various audio classification tasks. In the case of speech data, we show that the learned features correspond to phones/phonemes. In addition, our feature representations learned from unlabeled audio data show very good performance for multiple audio classification tasks. We hope that this paper will inspire more research on deep learning approaches applied to a wide range of audio recognition tasks.