Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of executive share ownership and private hedging on executive stock option exercise and values.

Executives can substantially increase the subjective value of their stock options by hedging optimally with an imperfectly correlated traded asset, even if trades are costly, because of the reduction in their cost of unhedged risk. Through the effect on their exercise strategy, this also increases the options’ cost to shareholders. Subjective values, exercise thresholds and shareholders’ objective values thus depend on unhedgeable (idiosyncratic) as well as total risk. All differ from their perfect market equivalents more for larger unhedgeable risk, grant sizes and executive ownership levels. If shares are retained on exercise, unhedgeable risk increases optimal exercise thresholds; if sold, thresholds decrease. Objective values always decrease with unhedgeable risk.
SHORT TEXT INFERENCE USING ENHANCED STRING SEMANTICS

The cryptography is created by obtaining AN in-depth neural network, that is trained on texts symbolized by word-count vectors (bag-of word representation). unfortunately, the conclusion result's texts for instance searches, tweets, or news titles, such representations inadequate to capture the linguistics. bunch short texts (for example news titles) by their which means could be a difficult task. The linguistics hashing approach encodes usually| this can be often within the text within the compact code. Thus, to tell if 2 texts have similar meanings, we tend to merely check whether or not they have similar codes. To cluster short texts by their meanings, we tend to advise to incorporate a lot of linguistics signals to short texts. significantly, for each term inside the short text, we've got its ideas and co-occurring terms inside the probabilistic understanding base to boost fast text. additionally, we tend to introduce a simplified deep learning network comprised of the 3-layer stacked auto-encoders for linguistics hashing. Comprehensive experiments show, with elevated linguistics signals, our simplified deep learning model has the capability to capture the linguistics of short texts, which will facilitate various applications as well as short text retrieval, classification, and general purpose text process.
A technique to identify some typical radio frequency interference using support vector machine

In this paper, we present a technique to automatically identify some typical radio frequency interference from pulsar surveys using support vector machine. The technique has been tested by candidates. In these experiments, to get features of SVM, we use principal component analysis for mosaic plots and its classification accuracy is 96.9%; while we use mathematical morphology operation for smog plots and horizontal stripes plots and its classification accuracy is 86%. The technique is simple, high accurate and useful.
Residual stress provides significant strengthening and ductility in gradient structured materials

ABSTRACT Residual stress exists extensively in biological and engineering structures. Here we report that residual stress can be engineered to significantly enhance the strength and ductility of gradient materials. In-situ synchrotron experiments revealed that the strongest strain hardening occurred in the layer with the highest compressive residual stress in a gradient structure. This layer remained elastic longer than adjacent layers during tension, producing high hetero-deformation induced stress to increase strength and enhancing work hardening even after the disappearance of the compressive stress to increase ductility. This finding provides a new paradigm for designing gradient structures for superior mechanical properties. IMPACT STATEMENT We show that compressive residual stress layer in SMAT-processed gradient material produces hetero-deformation induced hardening, which played a major role in improving strength and ductility. GRAPHICAL ABSTRACT
Prospective Modelling of Residential Space Cooling Diffusion in France

Residential space cooling receives increasing attention in energy demand models, due to the considerable share of buildings’ energy consumption it already represents in hot countries and its strong growth in mild climate countries such as France. Reliable estimates and predictions of market diffusion of cooling equipment are an essential part of such models. They require ownership and installation data from households, which is rarely collected in European countries. Existing European models are thus calibrated with data from the USA to account for variation due to climate and adjusted based on average household income. They assume that lower purchasing power may entirely explain the difference between the two continents and that similar level of market diffusion will be attained as wealth increases further. This usually implies eye watering growth rates in the coming decades when climate change and economic growth are considered. Survey data from France, Spain and the USA allows us to test this assumption and to propose a new model for France based on openly available data (cooling degree-days and GNI at purchasing power parity). This is likely to also be a more accurate model for other European countries. The evolution of cooling degree-days is predicted based on climate change scenarios. We identify the differences compared to the USA - those taken into account by the model and those due to other factors. It is found that significant variation exists which cannot be accounted for by the model variables, particularly in colder climates. Likely causes are attributed to "cultural" factors and the use of reversible heat pumps. We demonstrate the usefulness of US survey data and argue for the need of increased and better data collection for space cooling in Europe.
Corporate Social Responsibility (CSR) of MNCs in Bangladesh: A Study on Nestlé Bangladesh Limited

The article CSR of MNCs in Bangladesh scrutinizes how multinational companies conduct corporate social responsibility (CSR) in Bangladesh. The purpose of the study is to observe the framework of CSR areas and contribution to those areas by the Nestlé Bangladesh Limited. It considers the structure of CSR in the business of Bangladesh, which is now globally a vital issue for the development of society. It explains the systems of adopting CSR by the MNCs in Bangladesh, we can begin to see what implications arise from the fact that CSR is a financially developed nations’ concept. Developing country like Bangladesh is considered lagging behind in its understanding and adoption of CSR practices. Generally corporations do not expose their policies. This article tried to explore current practices of CSR by the leading MNC like Nestlé Bangladesh Limited which is operating its business activities proudly for the long since.
Temporal, Spatial, and Annual Variation in the Occurrence of Molt-Migrant Passerines in the Mexican Monsoon Region

Abstract. Adults of several species of western North American passerines are known to migrate to the Mexican monsoon region to undergo molt from July to October before continuing migration to their wintering grounds in the neotropics, but little is known about the biology and habitat requirements of these birds on their molting grounds. Therefore we established 13 banding stations during the monsoon seasons of 2007 and 2008 in southeastern Arizona, central Sonora, and central Sinaloa. We studied the spatial and temporal occurrence of 10 previously known and 9 new species of molt migrants on the molting grounds. In many of these species most or all individuals appeared to undertake molt migration but in others it appeared to be limited to a small proportion of the population, underscoring that molt migration must be defined at the level of the individual rather than of the population. Our results suggest that during the drier 2007 monsoon season molt migrants sought out riparian habitats, whereas in the wetter 2008 season, when the flush of vegetation was greater, they were more widely distributed in drier habitats. Site fidelity to molting grounds was virtually zero, significantly less than site fidelity to banding stations on breeding and winter grounds. Our results suggest that molt migration to the Mexican monsoon region is a stochastic or plastic process, substantially influenced by individual choices related to variation in weather and the preceding breeding season. Our study also emphasizes the need to conserve a mosaic of habitats in the monsoon region appropriate for molting birds.
Work incentives and the cost of redistribution via tax-transfer reforms under constrained labor supply

Using information on desired and actual hours of work, we formulate a discrete choice model of constrained labor supply. Using the German Socio-Economic Panel and the microsimulation model STSM, we find that hours and participation elasticities are substantially smaller than those in the conventional model. We evaluate two reforms for Germany. Both redistribute to the working poor. The first reform is financed through an increase in the effective marginal tax rate for welfare recipients, the second through an increase in taxes. The first reform is desirable with equal weights, the second if the social planner has substantial redistributive taste.
The Use of D2RQ in the Integration of Development Tools

The aim of the article is to present an approach to the integration of heterogeneous data sets from independent computer systems. The article presents the use of integration by means of the virtualization of data sets in a consistent semantic graph. The integration was carried out in accordance with the ATOM methodology, which had been worked out earlier, using the D2QR tool. The tool is presented in the paper as a representative of a class of tools for integrating multiple heterogeneous data sources into one coherent data space. The article describes the experience of using the various options of D2RQ for integration of data sources and different approaches to the issues related to semantic integration. The authors also presented their modification of the tool and suggestions for its improvement. The research and experience are directly related to the CCMODE project (Common Criteria compliant Modular Open IT security Development Environment).
Komparasi Sistem Remunerasi Pada Tiga Perguruan Tinggi Negeri Badan Hukum (PTNbh)

ABSTRACTThe research objective is to analyze the suitability of the design of the remuneration system in three PTNbh with preparation stages and principles of remuneration and evaluate the system of socialization and information systems used in the application of the remuneration of the three PTNbh. This research was conducted in three PTNbh located in Jakarta (PTNbh X), West Java (PTNbh Y) and East Java (PTNbh Z) using primary data obtained from in-depth interviews and secondary data derived from the literature, previous research, laws and regulations, government regulations and decrees that are relevant to the implementation of the remuneration of PTNbh. This study used a descriptive approach qualitative analysis benchmarking method. In the preparation of the remuneration system, which first assigned PTNbh not follow the stages of preparation with good remuneration, whereas previously PTNbh derived from State BLU more likely to obey the principle and the preparation of their remuneration has been prepared in detail based on the principles of remuneration and government regulations.ABSTRAKPenelitian ini bertujuan untuk menganalisis kesesuaian rancangan sistem remunerasi di tiga PTNbh dengan tahapan dan prinsip penyusunan remunerasi dan mengevaluasi sistem sosialisasi serta sistem informasi yang digunakan dalam penerapan remunerasi pada tiga PTNbh. Penelitian ini dilakukan di tiga PTNbh yang berada di DKI Jakarta (PTNbh X), Jawa Barat (PTNbh Y) dan Jawa Timur (PTNbh Z) dengan menggunakan data primer yang diperoleh dari wawancara mendalam serta data sekunder yang berasal dari studi pustaka, penelitian terdahulu, peraturan pemerintah yang berlaku dan surat keputusan yang relevan dengan penerapan remunerasi pada PTNbh. Penelitian ini menggunakan pendekatan deskriptif kualitatif dengan metode analisis patok duga. Dalam penyusunan sistem remunerasi, PTNbh yang lebih dulu ditetapkan belum mengikuti tahapan penyusunan remunerasi dengan baik, sedangkan PTNbh yang sebelumnya berasal dari PTN BLU cenderung lebih taat azas dan penyusunan remunerasinya sudah disusun dengan detil berdasarkan prinsip-prinsip remunerasi dan peraturan pemerintah.
Mechanisms of trust for different modes of welfare service provision

ABSTRACT Welfare services are an important channel for building institutional trust. But does it matter if the service is publicly or privately provided? Using SEM on individual data from public and private schools in Sweden, the authors test how the provision mode moderates the effects of positive and negative school experiences on trust in government. The results show that students’ perceptions of teacher fairness are dependent on provision mode. Negative experiences are associated with decreased trust in government only in private schools. Positive experiences didn’t affect trust. Thus, the use of private providers may provide greater challenges for maintaining institutional trust
Compact antenna arrays for efficient direction of arrival estimation

In recent years, a modern topic that has received major attention in diverse areas of research is the miniaturization of communication and non-communication devices. Society has demanded increasingly smaller and more compact equipments that allow for mobility with lower level of effort. Fields of research that have recently demanded compactness of devices include radio emitter localization, and more specifically, the localization in terms of Direction of Arrival (DoA), also referred to as direction finding. Applications for direction finding include RADAR systems, channel sounding, satellite navigation, and security applications, among others. High-resolution direction finding systems include a receiving array of antennas responsible to capture the impinging signals and feed the output to a DoA estimator. Miniaturization of such systems is accomplished by optimizing the antenna array with respect to the total volume occupied. There are two possible outcomes of array miniaturization: reduced size and lighter individual sensors or placement of elements in the array closer together. The second solution for compactness implies inter-element spacing smaller than half of the free-space wavelength, giving rise to stronger mutual coupling in the array, which causes adverse effects such as radiated far-fields pattern distortion, reduced bandwidth, and power and polarization mismatch. The contribution of this thesis is to show how the impairment that arises from strong electromagnetic interaction between neighboring elements in compact arrays affects the antenna capabilities for direction finding. We propose a solution to decouple and match compact antenna arrays, which is based on an eigenmode decomposition approach for the design of Decoupling and Matching Networks (DMN) comprised of distributed elements. We demonstrate the benefits of using the proposed DMN, to restore impairment caused by compactness, for direction finding of emitters in diverse scenarios. With the aim of evaluating and optimizing antenna arrays for direction finding based applications, we propose a workbench that connects the antenna design parameters to performance metrics for DoA estimation. Although the proposed decoupling and matching technique significantly enhances the direction finding performance of compact arrays, the frequency bandwidth may still be a limiting factor. This thesis contributes to this issue by proposing a multiband antenna array comprised of sub-arrays optimized for different frequencies. As an outlook, we evaluate wideband antenna arrays comprised of magnetic loops with respect to DoA estimation acuracy and discuss possible solutions for matching and decoupling over a wide frequency bandwidth.
Query Expansion Using Conceptual Knowledge in Computer Science

Traditional information retrieval systems retrieve documents based on keyword based matching, thereby incapable to provide results according to user information needs. These systems do not consider the semantic relationships among the user query keywords, thus cannot interpret the query context accurately. Query Expansion technique enhances the performance of information retrieval process by expanding user query with relevant meaningful concepts. Ontology represents semantics of a domain, and emerges as an important resource for query expansion. In this paper, we propose a query expansion framework based on conceptual knowledge derived from ontology in the domain of computer science. The system prototype results show good average precision percentage of 89.2% over keyword based search.
Visualising student satisfaction

Student satisfaction is an important metric used in teaching and education, and is used in most educational institutions. There are many ways to measure student satisfaction (Elliott, 2002), however student satisfaction is often given as both a numerical score on a Likert scale as well as a text comment which contains further information. Although the numerical scores are often used, the free text comment is an invaluable source of information, often providing further pointers towards possible teaching enhancements. In this study, we explore the use of machine learning techniques to visualise student satisfaction. This visualisation will be exploited in the context of the following 2 research questions, 1. How can we use visual representations of comments to examine student satisfaction? 2. What impact can this have for educators? Using a dataset of over 20 subjects, many student comments and reviews were available for analysis. Primarily, using an analysis method called Latent Dirichlet Allocation (LDA) (Blei, et al., 2003), topics can be extracted from these comments about subjects. Sentiment analysis is then used to find the positivity and negatively of certain comments. Using the approach mentioned, comments from two subjects were analysed to demonstrate the capability of the process. For each subject, two figures were generated, one about the subject, and one focussing on a keyword or topic of interest. Both figures contain 9 automatically determined keywords as the focus of the plot. For each keyword, the length of the bar represents the frequency of keywords. The positive and negative sentiment is also represented on the same figure. From these figures, the reader can identify keywords related to a particular positive or negative sentiment. In this work, we have shown a process which automatically analyses and produces a visual representation for student satisfaction. The produced visuals can be used by lecturers, subject coordinators or managers to compare and review several subjects at once. As a lecturer, you would not need to know how this system works, but have access to student feedback. With the student feedback, these plots can be automatically generated. The visualisations can lead to quick detection of both positive and negative aspects within a subject, thus prompting appropriate action.
Fuzzy Clustering Based Approach to Network Traffic Classification and Anomaly Detection

— In this work, we develop network traffic classification and anomaly detection methods based on traffic time series analysis using fuzzy clustering. We compare four fuzzy clustering techniques using different dimensionality reduction methods and validity indices to work out an effective anomaly detection algorithm. The effectiveness of the proposed classification system is evaluated on traffic data with and without traffic attack components.
Taws:Table Assisted Walk Strategy in Clone Attack Detection

Wireless Sensor Networks (WSNs) deployed in the destructive atmosphere are susceptible to clone attacks. Clone attack in wireless sensor network is a complicated problem because it deployed in hostile environments, and also the nodes could be physically compromised by an adversary. For valuable clone attack detection, the selection criteria play an important role in the proposed work. In this paper, it has been classified the existing detection schemes regarding device type, detection methodologies, deployment strategies and detection ranges and far explore various proposals in deployment based selection criteria category. And also this paper provides a review of detection methodology based on various clone attack detection techniques. It is also widely agreed that clones should be detected quickly as possible with the best optional. Our work is exploratory in that the proposed algorithm concern with table assisted random walk with horizontal and vertical line, frequent level key change and revokes the duplicate node.Our simulation results show that it is more efficient than the detection criteria in terms of security feature, and in detection rate with high resiliency. Specifically, it concentrates on deployment strategy which includes grid based deployment technique. These all come under the selection criteria for better security performance. Our protocol analytically provides effective and clone attack detection capability of robustness.
Practical Usability in XP Software Development Processes

—This paper describes the experiences made and lessons learned in an Extreme Programming (XP) software development project. We investigate the potential of XP to produce user experience-optimized products by including HCI experts in the team. We relate the software development method to user-centered design instruments and propose solutions to different user experience integration problems. Additionally, the practicability of different HCI instruments regarding solving those problems is examined. The analyzed instruments and methods are: user studies, personas, usability tests, user experience expert evaluations, and extended unit tests. The conclusion provides tips and tricks for practitioners.
Mason: Real-time NBA Matches Outcome Prediction

The National Basketball Association (NBA) is the most popular basketball league in the world. The world-wide mighty high popularity to the league leads to large amount of interesting and challenging research problems. Among them, predicting the outcome of an upcoming NBA match between two specific teams according to their historical data is especially attractive. With rapid development of machine learning techniques, it opens the door to examine the correlation between statistical data and outcome of matches. However, existing methods typically make predictions before game starts. In-game prediction, or real-time prediction, has not yet been sufficiently studied. During a match, data are cumulatively generated, and with the accumulation, data become more comprehensive and potentially embrace more predictive power, so that prediction accuracy may dynamically increase with a match goes on. In this study, I design game-level and player-level features based on realtime data of NBA matches and apply a machine learning model to investigate the possibility and characteristics of using real-time prediction in NBA matches.
Facilitated analysis of large data sets by interactive visualisation

In biological research analysis of large data sets, such as RNA-seq gene expression, often involves visualisation of thousands of data points and associated database query. Static charts produced by traditional tools lack the ability to reveal underlying information, and separated database query is laborious and involves a lot of manual effort. Interactive charting is able to make the data transparent but the use of visualisation tools often requires certain programming skills, which hinders most academic users. We present here an open-source chart editor for interactive visualisation, which is designed for academic users with no programming experience. It can not only visualise the data in an interactive way, but also link the data points to external databases, by which the user can save a lot of manual effort. We believe that interactive visualisation using such tools will facilitate analysis of large data sets as well as presenting and interpreting the data.