Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Decay Algorithms for Neural Machine Translation

Neural Machine Translation (NMT) systems require a lot of data to be competitive. For this reason, data selection techniques are used only for finetuning systems that have been trained with larger amounts of data. In this work we aim to use Feature Decay Algorithms (FDA) data selection techniques not only to fine-tune a system but also to build a complete system with less data. Our findings reveal that it is possible to find a subset of sentence pairs, that outperforms by 1.11 BLEU points the full training corpus, when used for training a German-English NMT system .
Novel Cryptographic Algorithm for 4G / LTE-A

LTE (Long Term Evolution) is the fourth generation of mobile communication systems, Novel cryptographic algorithm based on enhancement at RC6 algorithm presented here. Using two parallel RC6 at connect them together with some functions in order to use 256 bit input block instead of 128 bit input block as the usual RC6 . This proposed method makes the encryption decryption process faster, stronger, and more secure against attacks. The algorithm applied to many types of data files, shown in MATLAB how it works. The results are compared with EEA2 (EPS Encryption Algorithm 2) used in LTE as EPS stands for Evolved Packet System.
Solar Geoengineering: Social Science, Legal, Ethical, and Economic Frameworks

Solar geoengineering research in the social sciences and humanities has largely evolved in parallel with research in the natural sciences. In this article, we review the current state of the literature on the ethical, legal, economic, and social science aspects of this emerging area. We discuss issues regarding the framing and futures of solar geoengineering, empirical social science on public views and public engagement, the evolution of ethical concerns regarding research and deployment, and the current legal and economic frameworks and emerging proposals for the regulation and governance of solar geoengineering.
GrETEL. A Tool for Example-Based Treebank Mining

This chapter describes the use of GrETEL for linguistic research. GrETEL is a linguistic search tool that enables users to look up constructions in syntactically annotated corpora or treebanks . It provides online access to the data, allowing users to query a treebank using either an example sentence or an XPath expression in order to look for similar constructions. A major asset of GrETEL is that it enables non-technical users to consult treebanks in a user-friendly way, which is also in line with the main CLARIN goal of applying the results of speech and language technology to research in the humanities and the social sciences. Besides a description of the querying procedure in GrETEL, this chapter presents a selection of research in Dutch syntax and semantics that has been carried out using GrETEL. Furthermore, an overview is given of further developments.
Exploring Participatory Design for Sustainable Landscape for Public Housing Neighborhoods in Singapore

Singapore’s reputation as a green city is largely achieved through political will, strong policies, and effective execution of policies. While greening Singapore for most of the past five decades can be generally described as a public-sector led approach, where citizen engagement was not necessarily the focus, in recent years the public sector is increasingly interested in engaging the community in the planning and design of public green spaces. As this is a nascent movement, there remain considerable gaps in the types, process, and efficacy of participatory design. In this paper, we describe a research project that aims to provide a sustainable landscape design framework—based on the concept of ecosystem services—through a participatory process. Our study focuses on public housing estates, locally referred to as “HDB” (Housing and Development Board) estates, which houses 80% of Singapore’s population in high-rise, high-density towns. We describe the research process, in which we include multiple stakeholders in the planning and design of HDB neighborhood landscapes. They include relevant public agencies, design professionals, residents, and NPOs/NGOs. We also discuss the lessons learned through such a process. Since a participatory approach to landscape design remains to be fully explored in Singapore, we anticipate that this research project could provide valuable insights into the adoption of participatory design in Singapore to promote a more bottom-up approach to the planning and design of public green and open spaces.
Higher education faculty perception of service quality of Pakistan

Faculty serves as stakeholders of higher education institutions (HEIs) and is responsible for knowledge creation and dissemination in society by imparting quality education. With an increase in commercialization of education in Higher Education Institutions more have been an area of concern for HEIs management. Various studies had been done in past on different stakeholders of HEIs and their perception of quality education but the purpose of the current study is to measure the service quality in private HEIs of Lahore, Pakistan by faculty perspective. Quantitative research methods of Principal Component Analysis and Rotated Component Matrix were used in the study. The sample of this study consists of 10 private sectors HEIs having campuses in Lahore. A questionnaire was used to collect primary data from faculty members of private HEIs. The questionnaire consists of 48 items divided into five dimensions of service quality i.e., Reliability, Tangibility, Responsiveness, Assurance and Empathy.204 questionnaires were completely filled and received from the faculty of 10 HEC recognized universities of Lahore. The value of Cronbach Alpha calculated for this study was 0.973. By using Rotated Component Matrix 40 out of 48 items were converged into eight factors as determinants of quality education from faculty’ perception perspective while the remaining eight items having loadings less than 0.5 were not converged. Non converging items direct HEIs management to improve service quality in those ineffective and weak areas of service quality. This research study contributes towards policymakers, budget allocation committees and stakeholders of HEIs in formulating regulations for maintaining a competitive advantage.
Hierarchical feature extraction from spatiotemporal data for cyber-physical system analytics

With the advent of ubiquitous sensing, robust communication and advanced computation, datadriven modeling is increasingly becoming popular for many engineering problems. Eliminating difficulties of physics-based modeling, avoiding simplifying assumptions and ad hoc empirical models are significant among many advantages of data-driven approaches, especially for large-scale complex systems. While classical statistics and signal processing algorithms have been widely used by the engineering community, advanced machine learning techniques have not been sufficiently explored in this regard. This study summarizes various categories of machine learning tools that have been applied or may be a candidate for addressing engineering problems. While there are increasing number of machine learning algorithms, the main steps involved in applying such techniques to the problems consist in: data collection and pre-processing, feature extraction, model training and inference for decision-making. To support decision-making processes in many applications, hierarchical feature extraction is key. Among various feature extraction principles, recent studies emphasize hierarchical approaches of extracting salient features that is carried out at multiple abstraction levels from data. In this context, the focus of the dissertation is towards developing hierarchical feature extraction algorithms within the framework of machine learning in order to solve challenging cyber-physical problems in various domains such as electromechanical systems and agricultural systems. Furthermore, the feature extraction techniques are described using the spatial, temporal and spatiotemporal data types collected from the systems. The wide applicability of such features in solving some selected real-life domain problems are demonstrated throughout this study.
The Performance of Forecast-Based Monetary Policy Rules

We investigate the performance of forecast-based monetary policy rules using five macroeconomic models that reflect a wide range of views on aggregate dynamics. We identify the key characteristics of rules that are robust to model uncertainty: such rules respond to the one-year ahead inflation forecast and to the current output gap, and incorporate a substantial degree of policy inertia. In contrast, rules with longer forecast horizons are less robust and are prone to generating indeterminacy. In light of these results, we identify a robust benchmark rule that performs very well in all five models over a wide range of policy preferences.
Innovation and welfare: the marriage of an unlikely couple

ABSTRACT Studies on innovation and welfare are seemingly unrelated and, currently, scholars of innovation and welfare form distinctive groups. However, recent developments in the fields of business and psychology suggest that a social safety net and the positive mental assets that can be developed by implementing carefully designed welfare programs may stimulate innovative activities within a country. Further, they are closely connected due to their contribution to economic growth, which forms the central tenet of the discourses on both innovation and welfare. In this context, this study uses the patent applications filed under the Patent Co-operation Treaty and social spending data of 35 Organisation for Economic Co-operation and Development countries for the period 2000–2015 to investigate the effect of welfare on innovation. Contrary to the widespread belief that welfare spending can undermine innovative potential, we argue that welfare can harness a country’s innovative potential and contribute to the country’s long-term growth.
Putting empirically supported treatment into practice: Lessons learned in a children's mental health center.

With the increasing focus on service accountability, there is an urgent need to identify empirically supported treatments (ESTs) and disseminate their use in the daily practice of mental health organizations. This articledescribes the authors' experiences of implementing an EST at a children's mental health center by involving the collaboration of clinicians, administrators, and innovator(s). Initially, a small group of clinicians voluntarily commit to pilot test the EST, with the intention of evaluating the adoption and integration of the treatment model into the organization's full-service delivery system. Using E. M. Rogers's (1995) work on the diffusion of innovations, the current case study example suggests that ESTs can be flexibly and successfully implemented with integrity.
Semantic Description of Activities in Videos

Description of human activities in videos results not only in detection of actions and objects but also in identification of their active semantic relationships in the scene. Towards this broader goal, we present a combinatorial approach that assumes availability of algorithms for detecting and labeling objects and actions, albeit with some errors. Given these uncertain labels and detected objects, we link them into interpretative structures using domain knowledge encoded with concepts of Grenander’s general pattern theory. Here a semantic video description is built using basic units, termed generators, that represent labels of objects or actions. These generators have multiple out-bonds, each associated with either a type of domain semantics, spatial constraints, temporal constraints or image/video evidence. Generators combine between each other, according to a set of pre-defined combination rules that capture domain semantics, to form larger structures known as configurations, which here will be used to represent video descriptions. Such connected structures of generators are called configurations. This framework offers a powerful representational scheme for its flexibility in spanning a space of interpretative structures (configurations) of varying sizes and structural complexity. We impose a probability distribution on the configuration space, with inferences generated using a Markov Chain Monte Carlo-based simulated annealing algorithm. The primary advantage of the approach is that it handles known computer vision challenges – appearance variability, errors in object label annotation, object clutter, simultaneous events, temporal dependency encoding, etc. – without the need for a exponentiallylarge (labeled) training data set.
The effects of service quality and consumer-brand value congruity on hospitality brand loyalty

ABSTRACT This research integrates the congruity and the social identity theories to better understand the consumer-brand relationships. A structural equation modelling approach was used to explore the drivers of brand loyalty in the context of upscale hotels. The findings suggest that the customers are increasingly engaging with the brands that reflect their identity and personal values. The consumer-brand value congruity and the hospitality businesses’ delivery of high service quality were found to be significant antecedents of consumer-brand identification and engagement. Moreover, we reported that consumer-brand identification is a precursor of consumer-brand engagement and brand loyalty. In conclusion, this contribution implies that luxury hotels ought to satisfy their customers’ needs for distinctiveness and self-enhancement whilst exceeding their expectations on service quality. Abbreviations: CBE - Consumer-Brand Engagement; CBI - Consumer-Brand Identification; CA - Conscious Attention; EP - Enthused Participation; SC - Social Connection; BL - Brand Loyalty; VC - Consumer-Brand Value Congruity; SQ - Perceived Service Quality
The Indian Patola: import and consumerism in early-modern Indonesia

Purpose The present paper aims to focus on the Indian influence in the transfer of, the business of and consumer markets for Indian products, specifically, textiles from producers in the South Asian subcontinent to the lands to the east of Bali. This aspect of the influence of Indian products has received some attention in a general but not been sufficiently elucidated with regard to eastern Indonesia. Design/methodology/approach This paper is based on archival research, as well as secondary data, derived from the published sources on early trade in South Asia and the Indian Ocean world. The study includes data about the Vereenigde Oost-Indische Compagnie, a Dutch-owned company, and its textile trade history with India and the Indonesian islands with a special focus on Patola textiles. Narratives and accounts provide an understanding of the Patola, including business development and related elite and non-elite consumption. Findings The paper shows how imported Indian textiles became indigenised in important respects, as shown in legends and myths. A search in the colonial sources demonstrates the role of cloth in gift exchange, alliance brokering and economic network-building in eastern Indonesia, often with important political implications. Research limitations/implications The study combines previous research on material culture and textile traditions with archival data from the early colonial period, thus pointing at new ways to understand the socio-economic agency of local societies. Originality/value Only mapping the purchase and ownership of trading goods to understand consumption is not enough. One must also regard consumption, both as an expression of taste and desire and as a way to reify a community of people.
The future of environmental social work: Looking to community initiatives for models of prevention

ABSTRACT Social work responses to environmental degradation have sought to mitigate harm that has already occurred and create strategies to respond or adapt to environmental hazards. Despite a good deal of literature suggesting the promise of prevention-focused models, social workers have less frequently considered prevention models to address environmental issues. In this manuscript, we consider how communities engaged in environmentally-based prevention work might inform the development of ecosocial work practice. We describe how a prevention-focused agenda, in partnership with communities, can be a promising avenue for ecosocial work practice to address the root causes of environmental degradation and its social impacts.
Media Coverage and the Stock Market Valuation of TARP Participating Banks‡

Abstract We examine the impact of media coverage of the Capital Purchase Program (CPP) under the Troubled Assets Relief Program on the equity market valuation of participating bank holding companies (CPP banks). We document substantial negative coverage of the CPP and its participants over the five quarters following the program's initiation. We find that the extent of negative media coverage about the CPP exerted substantial downward pressure on the stock returns of CPP banks, decreasing their valuation relative to bank holding companies not participating in the program. We show that our findings cannot be explained by differences in the banks’ financial viability at the CPP's initiation, new information about their performance being released to the market after the CPP's initiation or preceding stock returns causing the negative media coverage. Our findings highlight the importance of investor sentiment, as reflected by the tone of media coverage, in banks’ valuation during a period of high uncertainty in financial markets.
The Effect of Smart Mobile Devices Ownership and Usage on Insomnia among Health Trainees in Ghana

Introduction: Quality of sleep is an essential need of humans especially the young and the old. A good night or good sleep is a great determinant of one’s ability to function effectively and efficiently during the daytime events. Objective: The main objective of this study is to ascertain the effect of the use of smart mobile devices on sleep quality that may lead to insomnia. It verifies whether the frequent use of smart mobile devices have any effects on sleeping habits that lead to any sleeping disorder. Method: A cross-sectional study design was used to assess the evidence of relationship between smart mobile device usage and sleep duration, subjective sleep quality, daytime sleepiness, and sleep quality index, of respondents as well as their demographic characteristics. The Pittsburgh University Sleep Quality Index was used to determine the score of respondents’ sleep quality level. The research was conducted in Ghana among Health Trainees from different programmes of study comprising a sample of 490 students. Pilot study was conducted with 200 trainees from a similar Nurses’ Training College . Results: Primary insomnia was the most prevalent sleep disorder among the respondents and this formed the majority of the respondents. There was evidence of a linear by linear relationship between the frequency of the number of smart mobile devices usage and respondents with insomnia. Conclusion: The sleep quality worsens leading to insomnia with increasing addiction of smart mobile devices usage.
Netzob : un outil pour la rétro-conception de protocoles de communication

In this paper, we present Netzob, an opensource tool which supports the expert in its operations of reverse engineering, evaluation and simulation of communication protocols. Its main goals are to help security evaluators to assess the robustness of proprietary or unknown protocols implementation, simulate realistic communications to test third-party products (IDS, firewalls, etc.) or even create an open source implementation of a proprietary or unknown protocol. Netzob supports the expert in a semi-automatic manner. It includes the necessaries to passively learn the vocabulary of a protocol and to actively infer its grammar. In addition, it integrates a stochastic and statefull model to represent any statefull communication protocol. The definition of the model can be shared and loaded in a dedicated component of Netzob, its simulator. Therefore, it becomes easy to simulate multiple actors (servers and clients) which communicate according to the infered protocol, and to apply advanced fuzzing.
Unconstrained Segue Navigation for an Immersive Virtual Reality Experience

Virtual reality (VR) is a rapidly growing field that has got innovative applications. Two main forms of VR content can be identified in the current applications --computer generated 3D models and adaptations of real world scenarios using digital imagery and video. However, real world adaptations are quite restrictive when it comes to interaction. These restrictions are due either to large storage needs, or to high computational needs, required to generate dynamic intermediate views. Thus, solutions through which real world simulation could be achieved in immersive and interactive VR environments are not available. The research presented in this paper is intended to provide a high degree of interaction to users who engage in immersive VR experiences related to real world adaptations. The solution offered is a navigable grid map of spherical panoramas, which uses a three stage approach. Firstly, intermediate views among spheres are approximated using novel mechanisms. Secondly, an optimization strategy is introduced based on visual locality in which the areas with a higher probability of immediate interaction are given more prominence for quality during rendering. Thirdly, smooth segue transition is achieved through a machine learning backed gesture input system. The three approaches when combined together allow for an intuitive virtual experience while ensuring optimal resource utilization.
Development of Chunk Size and Capacity as a Predictor of Working Memory in Hindi Speaking Typically Developing Children

Working memory is a temporary information storage system which facilitates spontaneous retrieval of information for day-today usage. It has been also defined as the few temporarily active thoughts [1,2]. These thoughts are assumed to be controlling the behaviors through active memory representation. Working memory is used in mental tasks, such as language comprehension (for example, retaining ideas from early in a sentence to be combined with ideas later on), problem solving (in arithmetic, carrying a digit from the ones to the tens column while remembering the numbers), and planning (determining the best order in which to visit the bank, library and grocery). Working memory capacity has considered as outcome of storage and processing together [1-3]. Individual difference in WM capacity may be exhibited owing to developmental changes in processing ability and gradual increase in storage capacity. Apart from the global development during early childhood development of working memory is extremely crucial to ensure age appropriate cognitive-communicative growth. It is now well-known that the capacity of working memory broadly defined increases with age in childhood. Many studies indicate that working memory capacity varies among people, predicts individual differences in intellectual ability, and changes across the life span [4]. Enhancement in Wm capacity with increasing age may also be contributed to increase in speed and proficiency of covert verbal rehearsal skill [5-9]. It is not yet clear though which aspects of working memory account for this increasing capacity. Perhaps the most fundamental distinction that can be drawn is between the storage function of working memory and the processes that affect how working memory is used. Chunk of working memory has been defined as the number of meaningful units of information stored temporarily [10]. Words, numbers, events letters etc are examples of chunk. These chunks facilitate immediate and serial recall of words or events. Working memory in children can be investigated by measuring the number of specific information or chunks stored and the size or length of each chunk at a particular time [11]. The contextual knowledge of the person