Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentence Encoder Video Encoder Frame-Specific Sentence Representation Cross Gating Matching Aggregation Self Interactor Segment Localizer Cross Modal

In this paper, we consider the task of natural language video localization (NLVL): given an untrimmed video and a natural language description, the goal is to localize a segment in the video which semantically corresponds to the given natural language description. We propose a localizing network (LNet), working in an end-to-end fashion, to tackle the NLVL task. We first match the natural sentence and video sequence by cross-gated attended recurrent networks to exploit their fine-grained interactions and generate a sentence-aware video representation. A self interactor is proposed to perform crossframe matching, which dynamically encodes and aggregates the matching evidences. Finally, a boundary model is proposed to locate the positions of video segments corresponding to the natural sentence description by predicting the starting and ending points of the segment. Extensive experiments conducted on the public TACoS and DiDeMo datasets demonstrate that our proposed model performs effectively and efficiently against the state-of-the-art approaches.
Silver nano ink

The invention relates to a silver nano ink, which comprises the following active ingredients in parts by weight: 10-15 parts of pigments, 3-5 parts of Ag powder with average particle size of 100nm, 10-20 parts of carbon black, 30-45 parts of rosin pentaerythrityl ester, 1-2 parts of linseed oil, and 1-3 parts of sodium aryl sulfonate. The ink is good in stability, less in pigment consumption, high in hiding power, full in color, clear in printed images, long in service life, and applicable to industrial production.
Multicultural Counselling A Reader

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Cost Analysis of Poor Quality Using a Software Simulation

The issues of quality, cost of poor quality and factors affecting quality are crucial to maintaining a competitiveness regarding to business activities. Use of software applications and computer simulation enables more effective quality management. Simulation tools offer incorporating the variability of more variables in experiments and evaluating their common impact on the final output. The article presents a case study focused on the possibility of using computer simulation Monte Carlo in the field of quality management. Two approaches for determining the cost of poor quality are introduced here. One from retrospective scope of view, where the cost of poor quality and production process are calculated based on historical data. The second approach uses the probabilistic characteristics of the input variables by means of simulation, and reflects as a perspective view of the costs of poor quality. Simulation output in the form of a tornado and sensitivity charts complement the risk analysis.
Hybrid Multicast-Unicast Video Streaming over Heterogeneous Cellular Networks

The demand for multimedia streaming over mobile networks has been steadily increasing in the past several years. For instance, it has become common for mobile users to stream full TV episodes, sports events, and movies while on the go. Unfortunately, this growth in demand has strained the wireless networks despite the significant increase in their capacities with recent generations. It has also caused a significant increase in the energy consumption at mobile terminals. To overcome these challenges, we first present a novel hybrid unicast and multicast streaming algorithm to minimize the overall energy consumption of mobile terminals as well as the traffic load within cellular networks. Next, we introduce the idea of dynamically configuring cells in mobile networks to form single frequency networks based on the video popularity and user distribution in each cell. We formulate the transmission scheduling problem in such complex networks, and we then present optimal and heuristic solutions to maximize the number of served multimedia streams. Through detailed packet-level simulations, we assess the performance of the aforementioned algorithms with respect to the average service ratio, energy saving, video quality, frame loss rate, initial buffering time, rate of re-buffering events, and bandwidth overhead. Finally, we extend our research to formulate the transmission scheduling problem for adaptive streaming in the emerging heterogeneous cellular networks. We propose an algorithm for the cells in a heterogeneous network to self organize their radio resource allocations in order to minimize the inter-cell interference and increase the average data rate received by mobile terminals. Then we evaluate its performance through extensive simulations of various heterogeneous configurations.
A CIPHER BASED ON THE RANDOM SEQUENCE OF DIGITS IN IRRATIONAL NUMBERS

An encryption method combining a transposition cipher with one-time pad cipher is proposed. The transposition cipher prevents the malleability of the messages and the randomness of one-time pad cipher is based on the normality of "almost" all irrational numbers. Further, authentication and perfect forward secrecy are implemented. This method is quite suitable for communication within groups of people who know one each other in advance, such as mobile chat groups.
Community-Based Program ® S A G E

This article describes a case study of adult learning in a Canadian multisite Community Cardiovascular Hearts in Motion program.The researcher highlights the informal learning of 40 adult participants in this 12-week community-based cardiac rehabilitation/education program in five rural Nova Scotia communities. The effects of this learning and barriers are examined, along with aspects of program design and facilitation that support learning and transformation. The researcher points to the role of emotion in this transformative learning process, and links are made between individual and collective processes in the transformative learning. Transformative learning theorists and health and adult education practitioners can see in this case study how individual and collective health interests can be incorporated into program planning for the community.
Public Manager Requirements of Skills and Training: Importance Rank Analysis Using Composite Indicators

To reconceptualize the role and profile of public managers, a survey has been designed and performed in collaboration with the National Association of the Municipalities of Italy (Veneto region). Public managers and in particular municipal directors were asked to rate the importance of various requirements of skills and training for their job. The aim of the paper is to understand how municipal directors rank requirements of skills and training from the least to the most important one. Preference ratings are combined using composite indicators. The outcome of a composite indicator depends on normalization, aggregation and weighting of partial indicators. Therefore the robustness of results is under question. To address this issue, an uncertainty analysis on the ranking of skill and training requirements has been performed. Three uncertainty factors have been considered: normalization, aggregation and weighting. It is shown that the uncertainty analysis allows a better understanding of the problem.
Strength prediction model for cement mortar made with waste LDPE plastic as fine aggregate

Non-biodegradable aggregate prepared from low density polyethylene (LDPE) plastic was used as partial replacement for sand in cement mortar. Various volumetric fractions of 0, 5, 10, 20, 30, 40, 50, and 60% sand were replaced using ground LDPE waste plastic. Mortar mixtures of 1:3 cement to fine aggregate were prepared at various water/cement ratios of 0.45, 0.50, 0.55 and 0.60, then used to cast 50 mm cubes and 40 × 40 × 160 mm prisms. It was found that strength reduces significantly as the proportion of LDPE in mortar increases, however, mixtures containing 50–60% LDPE satisfy the strength criteria for masonry mortars. Based on experimental data, a model was proposed for predicting the compressive strength of mortars containing waste plastics. The model’s validation gave generally accurate predictions for the strengths of mortars made using different types of plastics.
IDENTIFICATION OF ELASTIC PARAMETERS OF LAMINATED CARBON FIBER PLATES USING EXPERIMENTAL MODAL ANALYSIS

The aim of this work is to create an experimental-numerical technique for elastic parameters identification of laminated polymer composites using experimental modal analysis. The object of this research is laminated carbon fiber reinforced composite based on an equally strong carbon fabric and epoxy binder. Experimental determination of natural frequencies and corresponding vibration modes was performed using 3D scanning laser vibrometry. The finite element calculation and quasi-random search optimization technique can be effectively used to solve the identification problem. The evaluation by independent experiments showed that the error of the natural frequencies, determined from the obtained elasticity characteristics, lies within 5%. The described technique can be recommended for determining of elasticity parameters necessary for calculating the modal characteristics of structure elements made from laminated carbon fiber.
Compact Representation of High-Dimensional Data for Large-Scale Image Search

Approximate Nearest Neighbor (ANN) search has been an active research problem across many fields in computer science including computational geometry, data mining, information retrieval, and computer vision. The problem is especially important for high-dimensional and large-scale cases due to the efficiency requirement by many practical applications. Traditional hierarchical approaches including the kd-trees have been used for low-dimensional data, however, these techniques are not scalable to high-dimensional data. Hence compact code representations of high-dimensional data have been actively studied recently, since they can provide efficient similarity search and are suitable for handling large scale databases. In this dissertation, two compact representations of high-dimensional data and search scheme based on the compact codes are proposed: 1) Spherical Hashing and 2) Distance Encoded Product Quantization. In the Spherical Hashing, a novel hypersphere-based hashing functions are proposed to map more spatially coherent data into a binary code compared to hyperplane-based methods. We also propose a new binary code distance function tailored for our hypersphere-based binary code encoding scheme, and an efficient iterative optimization process to achieve both balanced partitioning for each hashing function and independence between hashing functions. Furthermore, we generalize the Spherical Hashing to support various similarity measures define by kernel functions. We also propose a novel compact code encoding scheme that distributes the available bit budget to encode both the cluster index and the quantized distance between point and its cluster center in the Distance Encoded Product Quantization (DPQ). We also propose two different distance metrics tailored to the Distance Encoded Product Quantization. All the proposed schemes are extensively evaluated against the state-of-the-art techniques with various large-scale benchmarks consisting of high-dimensional image descriptors. This dissertation includes two ongoing works: 1) shortlist computation in the inverted file and 2) tag-driven feature learning. In the first ongoing work, a distance estimator based on the orthogonality property in a high-dimensional space is proposed. We also propose a distance aware indexing method and a shortlist construction scheme using the distance estimator. In the second work we learn an image feature from a large-scale tagged image database. Specifically, we define pseudo classes from the tag information and train a neural network for those pseudo classes.
Search Interfaces for Integrating Crowdsourced Code Snippets within Development Environments

ii Acknowledgements iii Statement of Originality iv Chapter 1 Introduction 1 1.1 Motivation 2 1.1.1 Direct Answers 2 1.1.2 Integrating Code Snippet Search into the IDE 3 1.2 Problem Statement 4 1.3 Contributions 5 1.4 Organization of the Thesis 7 Chapter 2 Crowdsourcing Programming 8 2.1 Crowdsourcing Human-Based Computation 8 2.2 Crowdsourced Human-Based Computation 9 2.2.1 Non-Competitive Direct Motivation Tasks 9 2.2.1.1 Image Labeling Games 9 2.2.1.2 News Aggregation Websites 11 2.2.1.3 Wikipedia 12 2.2.1.4 Analysis 14 2.2.2 Non-Competitive Indirect Motivation Tasks 16 2.2.2.1 reCAPTCHA 16 2.2.2.2 Online Surveys with Participation Incentives 18 2.2.2.3 Volunteers 19 2.2.2.4 Analysis 20
A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem Name :

Machine learning algorithms often have many hyper-parameters that can be tuned to improve empirical performance. However, manually exploring the complex hyperparameter search spaces is tedious and cannot guarantee to find satisfactory outcomes. Recently, Bayesian optimization techniques for solving hyper-parameters optimization problem have shown substantial improvements, while also exposing some limitations. It is often the case that some hyper-parameters of a learning algorithm have a dependency on the values of other hyper-parameters or some conditions. These are called conditional hyper-parameters. Furthermore, this case can be expanded to include the choice of algorithm, resulting in the so-called combined algorithm selection and hyperparameter optimization problem. In this thesis, we propose three strategies to extend Bayesian optimization to deal with such a hierarchical search space with conditional inputs, based on a state-of-the-art algorithm MiP-EGO [1]. We first evaluate MiP-EGO without conditional inputs on benchmark problems, and then empirically compare our proposed strategies with other methods on an algorithm configuration scenario. The results show MiP-EGO and its new variants can compete with other state-of-the-art methods, and they are promising for configuring and selecting learning algorithms in practice.
Research and Analysis of Neural Field Global Architecture and Increase Ability

As a new theory that came into being in 1990's, information geometry introduces differential geometry method in computer neural science, provides a useful tool for the research of neural networks and information theory, and presents new breakthrough in the research of brain information transformation mechanism Based on information geometry, the global invariant properities of non linear space consisting of neural network models are studied The disintegration ability of the complex neural field architecture is analyzed and proved Finally, a knowledge increasable neural network model is presented The research helps to discover and understand the structure, transformation and locating mechanism of human's recognition system, stimulate the further neutral network (NN) research, and promote the research level of the connectionist model It also provides important theoretical basis for the understanding of neural network ensembles
Quantum Machine Learning with Superposition of Causal Order

Since first introduced by Richard P. Feynman in 1981 in his epochal-making speech on quantum computation [1], tremendous progress has already been made in both theory and physical realization. Along the line of research, many algorithms was proposed and gained public attention although they were only of pure theoretical interests in 90s when created. Examples include the well-known Shor’s algorithm, a quantum algorithm which factorizes a large integer into its prime factors [2], and the Grovers search algorithm [2] which was later extended to a general scheme called amplitude amplification [3]. The Shor’s algorithm surprised the public for it not only demonstrated the potential of quantum computer to provide exponential speedup against their classical counterpart, but it overthrew some most widely used public-key cryptography schemes such as RSA scheme [2]. The latter one, though offers only quadratic speedup, has been proven extremely useful, since searching problem are often important building blocks of other much more complicated algorithms [2].
Electoral politics and patron-client relations : The impediment to electoral development in PNG

This article explores the role of elections and application to Papua New Guinea (PNG). The relationship between candidate and the voter is explored from the PNG perspective, to shed light on the voting behavior of citizens and candidates approaches. Exploring deeper into this relationship between voter and candidate, the link between patron-client relations can be found. The article examines how this relationship later becomes a barrier to effective electoral development. Primary to this is the influence of the patron-client relationship upon decision making, allocation of resources, benefits etc., rather than sound development of policy at the electoral level as political investments impede electoral development. In the PNG context such politicking has greatly hindered progressive development, due to investments made to shore up political support rather than for sound administrative effectiveness.
Multiple Index Comprehensive Evaluation With time Series of Public Corporations

The paper first points out some questions in conventional static synthetical evaluation.Based on static efficiency evaluation and change of it, a new method of multiple index synthetical evaluation with time series of public coporations in considered,which is composed of principal component analysis and ideal point method.Afterwards an example about dynamic synthetical evaluation for public corporations in electrical field is used to illuminate the use of the proposed method.
Exclusion from school in Scotland and across the
 UK
 : Contrasts and questions

This article draws on findings from the first cross‐national study of school exclusion in the four jurisdictions of the UK. It casts new light on the crucial aspects of children's education that lead to school exclusion. It investigates the reasons for the UK disparities, as well as the policy and practice in place. The focus of this article is on a detailed analysis of the policy context in Scotland, where official permanent exclusion reduced to an all‐time low of just five cases in 2014/15. This is much lower than in Northern Ireland and Wales and in stark contrast to England, where exclusions have increased substantially since 2012. Our analysis seeks to understand Scotland's success in reducing exclusion and offers new insight into the ways in which national policies and local factors more generally shape schools and their practices and the consequent impacts for children and young people more broadly in the UK.
1 Measuring the Impact of Person-Environment Fit between Career Commitment and Organizational Citizenship Behavior

This paper has two research objectives. Firstly, analyze the relationship between Person-Environment fit and employees’ career commitment; secondly, analyze the relationship between Person-Environment fit and employees’ organizational citizenship behavior. The target of this study was the employees of International Cooperation and Development Fund (ICDF) which is a non-profit organization (NPO’s) in Taiwan. A quantitative research design was used. 92 questionnaires were handed out and 75 valid responses were received. The study shows three important findings. The first finding indicates Person-Organization fit, Person-Job fit, and PersonGroup fit have a significant influence on employees’ career commitment and organizational citizenship behavior; the second finding shows that Person-Person fit has a significant influence on employees’ organizational citizenship behavior, however does not have a significant influence on employees’ career commitment; the third finding indicates Person-Vocation fit have no significant influence on employees’ career commitment and organizational citizenship behavior. This paper shows that it is important that not only International Cooperation Development Fund in Taiwan but also other Non-Profit organizations pay close attention to the Person-Environment fit which can directly affect the employees’ career commitment and organizational citizenship behavior.
The complex spirals of engagement and communication: A case study about the communicative roles of co-workers in a corporate incubator

Recently, engagement and communication have started to be researched from a coworker-perspective. Yet, this study problematizes that most research in strategic communication and employee engagement still takes a managerial perspective and lacks critical and complex assessments. This case study therefore aims to analyze coworkers' perceptions of their communicative roles as team members, co-leaders and ambassadors and its communication challenges in a corporate incubator set in Sweden. Based on this, the study strives to understand how employee engagement is both a product and a producer of communication. The empirical material was collected in 15 semi-structured interviews throughout five weeks. Analyzing the findings with a meta-perspective of CCO (Communication Constitutes Organization), it was shown that coworkers perceive the communicative roles differently. More importantly, the results indicated that communication and engagement do not necessarily follow positive linear directions, but rather take complex turns shaped like spirals when studied with CCO. This study contributes with further understanding of how stronger engagement and professional autonomy can be products of both lengthy and limited communication, but also weak ambiguous results with no clear guidance. On the other hand, can employee engagement produce a high-qualitative communication but paradoxically distraction and information overload as well.
The Incomplete Democracy and the Onset of War, Causes and Consequences: A Case Study of Syria

The war is not essentially the absence of peace but the incomplete performances of key components and determinants of a sovereign state. In this contemporary international relation, state interaction revolves around the dependency of both friends and foes to gain vital national interests. Different states face wars in different scenarios based on their domestic manufacturing and the concepts of state building to tackle the destructions and upcoming worst-case scenario. Apart from political leadership, there has always been an external factor that plays a systemicrole to disrupt the peace and stability of the state. In order to understand that particular factor, the author has applied the Mansfield and Jack Snyder’s scholarly idea of incomplete democracy that outbreak the war to help further understand the ongoing Syrian crisis.The main focus of this article is to understand and evaluate the democracy as systemic factor that is playing a significant role to an unending war in Syria even today. The weak and fragile political institutions accompanied by international pressure to overthrow the Assad’s autocratic regime adds more fuel to fire not only for the peace and stability of the middle eastern but also dispersed among the European countries as refugee’s crisis. The author claims that, democracy as a systemic factor doesn’t mean complete efficient form of government to satisfy the needs and demands of a common citizen. It further brings more destructions and devastations that a state can never expect in this globalized world.