Miracle-dz/UniFAR-FTUs huggingface dataset:
Image compression method and image processing apparatus

The present invention provides an image compression method and an image processing apparatus. The image compression method comprises: dividing an original image into at least one image block; determining a number of color types contained in image data corresponding to each image block; for image blocks whose number of color types is less than or equal to a first threshold, performing compression using a lossless compression algorithm, and obtaining code streams after compression; for image blocks whose number of color types is greater than the first threshold, performing compression using a lossy compression algorithm, and obtaining code streams after compression; combining the code streams obtained after compressing the at least one image block into a unified code stream; and sending the unified code stream to a client. By distinguishing image block types according to the number of color types of each image block, and using the lossy compression algorithm or the lossless compression algorithm to perform encoding compression on image blocks of different types, the present invention can effectively give consideration to reconstruction quality and compression efficiency of a desktop image.
ENHANCED RECONFIGURABLE WEIGHTED ASSOCIATION RULE MINING FOR FREQUENT PATTERNS OF WEB LOGS

Systolic tree structure is a reconfigurable architecture in Field-programmable gate arrays (FPGA) which provide performance advantages. It is used for frequent pattern mining operations. High throughput and cost effective performance are the highlights of the systolic tree based reconfigurable architecture. Frequent pattern mining algorithms are used to find frequently occurring item sets in databases. However, space and computational time requirements are very high in frequent pattern mining algorithms. In the proposed system, systolic tree based hardware mechanism is employed with Weighted Association Rule Mining (WARM) for frequent item set extraction process of the Web access logs. Weighted rule mining is to mine the items which are assigned with weights based on user’s interest and the importance of the items. In the proposed system, weights are assigned automatically to Web pages that are visited by the users. Hence, systolic tree based rule mining scheme is enhanced for WARM process, which fetches the frequently accessed Web pages with weight values. The dynamic Web page weight assignment scheme uses the page request count and span time values. The proposed system improves the weight estimation process with span time, request count and access sequence details. The user interest based page weight is used to extract the frequent item sets. The proposed system will also improve the mining efficiency on sparse patterns. The goal is to drive the mining focus to those significant relationships involving items with significant weights.
The Method of Managing Employee Motivation Based On a Halal Lifestyle

In general, there are various methods of managing motivation that have been adopted by Islamic institutions. Nevertheless, a question remains whether there is any method that can enhance employees’ motivation? What is the role of Islamic law and how can its principles be incorporated in the motivation management method? This needs to be emphasised as some motivation management methods, such as having a reward ceremony, are against Islamic law due to the serving of alcohol and the unethical interaction between male and female employees. In Islam, the issue of halal and haram has been discussed clearly and in detail. Halal in Islam is naturally holistic, as it can be integrated into the entire lifestyle and it is not only limited to aspects of food, dressing and economy but extends to the aspect of employee management. This paper was written with two objectives in mind. The first objective was to identify the method of managing employee motivation that has been applied by the management of Islamic institutions. The second objective was to analyse the method based on a halal lifestyle. This paper work unravelled the answers by using the qualitative approach that applied document analysis. Based on the analysis, it was found that there are three methods of managing employee motivation and these methods are consolidated by the halal aspect to ensure that they are consistent with the Islamic Shari’a. After the questions were answered, this paper tried to clarify to society, especially the management, that halal is not small in scope but it goes even further than that because halal in Islam is holistic, and it needs to be practised in all aspects of a lifestyle.
Resiliency as a predictor of flexibility in coping with stress of cardiac patients

Since cardiovascular diseases remain the main cause of premature mortality in men and women in Poland, it is reasonable to look for factors that protect against these conditions. Psychological resiliency is one of such properties that support adaptation in difficult situations and conducive to adaptation to the disease. The aim of the present study was to analyze the relationship between resiliency and flexibility in coping of cardiac patients and to determine whether resiliency is a predictor of flexibility in coping with stress in this group. In the study the Assessment of Resiliency Scale (SPP-25) and the scale of Flexibility in Coping with Stress (KERS-14) were used. The participants of the study were 120 cardiac patients (72 men and 48 at the The results show that there is a statistically significant relationship between resiliency and flexibility in coping. Each of the resiliency dimensions, as well as the result of the overall resiliency, correlates positively with each of the dimensions of flexibility in coping. The analysis showed that resiliency is an important predictor of a dependent variable – flexible in coping. There is a positive relationship between resiliency and flexibility in coping with stress in cardiac patients. People with a higher intensity of resiliency in comparison to people with lower intensity of resiliency are characterized by greater flexibility in coping with stress. The dimensions of resiliency, in particular ‘Persistence and determination in action’ and ‘Openness to new experiences and sense of humor’, together with the duration of the disease, play a predictive role for flexibility in coping with stress.
The Repayment of Bank Credits Having Financed Investments in the Domar Model

In the Domar model, based on the Keynesian multiplier theory, investment generates savings. Therefore, savings cannot fund investments, at least ex ante . Investments have first to be financed by bank credit, hence the question on their repayment. In this article, we suppose that investments are financed by bank credits issued on several periods, as it typically takes years for firms to reimburse their investment debt. What we then obtain is that, in order to avoid an overproduction crisis, the rate of capital accumulation has to gradually rise throughout a growth phase. This result paves the way to a theory of cycles based on the repayment of bank credits.
Promoting Improved Infant and Young Child Feeding: Evidence from a Field Experiment in Ethiopia

Unhealthy diet with very low dietary diversity is prevalent among young children in the developing world, which increases the risk of chronic undernutrition. Such suboptimal child-feeding behaviors are partly due to mothers’ lack of nutritional knowledge, income, or both. This study implemented a clustered randomized experiment in Ethiopia to examine the effects of nutrition behavior change communication (BCC) and food vouchers on child-feeding behaviors and child growth. We find that BCC increases knowledge on infant and young child feeding and improves children’s dietary quality significantly, while food vouchers alone do not. The impacts on improved child-feeding behaviors are largest for those treated by both BCC and food vouchers, and we find evidence for stunting reduction in this group.
Design Concept for Thule Luggage - A Flexible Solution for Traveling with Multiple Bags

During travels, people want to be able to move fast and smooth from point A to point B. Thereby, many people can relate to the struggles which occur when carrying several belongings simultaneously. This master’s thesis was performed in collaboration with Thule Sweden AB and the purpose was to develop a design concept which would make it easier to travel with a wheeled luggage in combination with a secondary bag such as a laptop bag or handbag. The design process started off with benchmarking competitors and their solutions to similar problems followed by a user study including observations of travelers and their habits, interviews and user journeys. From this, key findings were gathered and served as foundation for the identification of user needs, creating of personas and for decomposing the problem into the most important functions. Based on these, a large number of concepts were produced in a first concept generation phase through brainstorming, sketching and parallel prototyping. The concepts were evaluated and one was chosen to be elaborated in a second concept generation phase. The final concept is called Thule Unite and is a feature which enables fast and easy attachment of a secondary bag onto a wheeled luggage. The solution consists of a bar, equipped with two elastic bands, integrated into the wheeled luggage and does not interfere with the design of the luggage nor its fixed- and telescopic handle. When using Thule Unite the user places their secondary bag on top of the wheeled luggage, pulls the bar over and around the bag and the telescopic tubes and then releases it. The bar is pulled against the telescopic tubes by the elastic bands which are at the same time pressing the secondary bag towards the wheeled luggage. Thule Unite allows fastening of various types and sizes of secondary bags and is easily managed with only one hand. The concept aim travelers who are not willing to compromise in the choice of their personal everyday bag. The functional and minimalistic design of the concept would fit into a Thule wheeled luggage and achieve the company’s mission to help people transport the things they care for safely, easily and in style.
Online news coverage of female perpetrators during the October 2015 wave of violence of the Israeli–Palestinian conflict

Based on the authors’ understanding regarding the effect of ethnocentric coverage, on one hand, and the tendency of the media to cover female perpetrators differently, on the other, the current study aimed to examine how leading Israeli news websites (N = 1,832) covered female versus male perpetrators during the October 2015 wave of violence. Their goal was to examine if differences between the coverage of female and male perpetrators exist, or if all perpetrators are grouped together and depicted as a single common enemy. In other words, they sought to understand the intersection of two journalistic tendencies: (1) does the ethnocentric frame hold consistently, or (2) do gender considerations overpower the consistent ethnocentric frame? Findings indicate that there were significant differences in how male and female perpetrators were covered by the media. Articles regarding female perpetrators included more information about their personal, familial and mental states than for males. Moreover, more information was given regarding female perpetrators’ motives, which were mostly ideological. Unlike in previous studies, the authors failed to find an emphasis on female perpetrators’ physical appearance. A possible explanation may come from the dominance of the ethnic framing exemplified by the Israeli media.
An Investigation of Term Weighting and Feature Selection Methods for Sentiment Analysis

Sentiment analysis automatically classifies the opinions in a document. Therefore, sentiment analysis has many useful applications such as opinionated web search and automatic analysis of reviews. In this study, our aim is to show the effects of feature weighting and feature selection methods for the sentiment analysis from Turkish review documents. Feature selection reduces feature vector size by eliminating redundant or irrelevant features to improve classification accuracy. In this study, we use three popular term weighting methods (i.e., term presence, term frequency, term frequency and inverse document frequency-tf*idf) and two feature selection methods (i.e., Chi-square and Query Expansion Ranking-QER) and perform experiments to show their effects. The experimental results show that the classification performance improves when Query Expansion Ranking feature selection method is used with tf*idf term weighting method.
Advanced Fiber Reinforced Self-Healing Ceramics for Middle Range Temperature

The availability of TiC healing agent has been evaluated in low temperature self-healing behavior of Al2O3 based self-healing ceramics. For this purpose, some technical issues to actualize the advanced fiber-reinforced self-healing ceramics containing TiC based interlayer as healing agent were discussed. Especially, the mechanical matching between the matrix and the interlayer was focused. Moreover, the self-healing behavior of the advanced shFRC containing the optimized TiC based healing agent was investigated. As a result, 30 vol% TiC-70 vol% Al2O3 interlayer was confirmed to be the optimized healing agent in the self-healing ceramics, and the self-healing ceramics was found to enable to attain the perfect healing at 600°C within 10 min. And we succeeded in prototype production of fiber-reinforced self-healing ceramics for low pressure turbine blade.
Accessing Virtual Social Worlds: A Unique Methodology for Research in New Media Spaces

Qualitative research into contemporary media engagement is particularly challenged by the complexity and diversity of today’s media channels. Further, the very conception of media is rapidly changing: social activities have become closely linked with media engagement. As media saturation in everyday life continues to expand, the study of everyday “practices” in “ordinary people’s lives,” or habitus, to use Bourdieu's term (1980), constitutes social identity and thus an important object for media research. I offer a reconceptualization of media engagement as a participatory media culture and outline a unique methodological approach developed for the study of this culture in new media spaces. The methodology incorporated use of a laptop to record and analyze the auto-ethnographic reports and actions of a panel of respondents. As an example of an outcome using this methodology, an extensive taxonomy of web sites is outlined, which can be helpful in disaggregating data on new media practices for media research. The methodology could be adapted widely to many disciplines interested in the everyday practices of media engagement. Received 25 November 2013; Revised 10 February 2014; Accepted 28 February 2014
Multi-match Packet Classification Scheme Combining TCAM with an Algorithmic Approach

Packet classification is one of the essential functionalities of Internet routers in providing quality of service. Since the arrival rate of input packets can be tens-of-millions per second, wirespeed packet classification has become one of the most challenging tasks. While traditional packet classification only reports a single matching result, new network applications require multiple matching results. Ternary content-addressable memory (TCAM) has been adopted to solve the multi-match classification problem due to its ability to perform fast parallel matching. However, TCAM has a fundamental issue: high power dissipation. Since TCAM is designed for a single match, the applicability of TCAM to multi-match classification is limited. In this paper, we propose a cost- and energy-efficient multi-match classification architecture that combines TCAM with a tuple space search algorithm. The proposed solution uses two small TCAM modules and requires a single-cycle TCAM lookup, two SRAM accesses, and several Bloom filter query cycles for multimatch classifications.
Evolutionary algorithm application to medium voltage power system restoration

The voltage quality is one of the most important issue in power system. The distribution network has to keep up with the growing consumption and increasing reliability requirements. In many cases supply disturbance is caused by faults on medium voltage distribution networks. Throughout system restoration many switching operation are needed, figuring out the optimal ones is a demanding task. In this paper a genetic algorithm based method is proposed, which can reduce the outage time in those areas where supply can be restored while the repairing is carried out on the failed section.
Affective Impression: Sentiment-Awareness POI Suggestion via Embedding in Heterogeneous LBSNs

Location-based social networks (LBSNs) add geographical information into traditional social networks and link people’s virtual and physical lives. As an important application of LBSNs, point-of-interest (POI) suggestion has become an important method to help users explore interesting and attractive locations in LBSNs. The main problems of POI suggestion include data sparsity and cold start, which have been paid much attention by existing techniques. There are two major challenges which can greatly influence the performance of suggestion accuracy. One is the fuzzy boundary between sentiments, i.e., the fine distinction between sentiments makes it difficult to classify words and texts after word-sentiment mapping operation. The other challenge is the unreliability of data quality represented by similarity metrics, which relies on data integrity and path reachability of a heterogeneous network. To cope with the above two challenges, we present a novel framework called Community-based Sentiment Extraction and Network Embedding for POI Recommendation (CENTER) for suggesting impressive POIs to a specific user in an effective fashion. The CENTER framework contains two essential techniques: (1) a latent probabilistic generative model called Community-based Sentiment Extraction (CSE), which can accurately capture the sentiments from review content in LBSNs by taking into consideration the characteristics of social communities. The parameters of the CSE model can be inferred effectively by the Gibbs sampling method. The primary sentiments are obtained based on the distribution of sentiments; (2) a network embedding model called Sentiment-aware Nework Embedding for POI Recommendation (SNER) is employed to learn the representation of the factors including POIs, users and textual sentiments in a low-dimensional embedding space. The joint training is utilized to alternatively sample all sets of edges in a heterogeneous information network. Extensive experiments were conducted on two large-scale real datasets, in order to evaluate the performance of the proposed CENTER framework. The results demonstrate that CENTER is superior to the state-of-the-art baseline methods in the effectiveness and efficiency of POI suggestion.
Multi-Objective Neighborhood Search Algorithm Based on Decomposition for Multi-Objective Minimum Weighted Vertex Cover Problem

The multi-objective minimum weighted vertex cover problem aims to minimize the sum of different single type weights simultaneously. In this paper, we focus on the bi-objective minimum weighted vertex cover and propose a multi-objective algorithm integrating iterated neighborhood search with decomposition technique to solve this problem. Initially, we adopt the decomposition method to divide the multi-objective problem into several scalar optimization sub-problems. Meanwhile, to find more possible optimal solutions, we design a mixed score function according to the problem feature, which is applied in initializing procedure and neighborhood search. During the neighborhood search, three operators ( A d d , D e l e t e , S w a p ) explore the search space effectively. We performed numerical experiments on many instances, and the results show the effectiveness of our new algorithm (combining decomposition and neighborhood search with mixed score) on several experimental metrics. We compared our experimental results with the classical multi-objective algorithm non-dominated sorting genetic algorithm II. It was obviously shown that our algorithm can provide much better results than the comparative algorithm considering the different metrics.
Some Propositions to Improve the Prediction Capability of Word Confidence Estimation for Machine Translation

—Word Confidence Estimation (WCE) is the task of predicting the correct and incorrect words in the MT output. Dealing with this problem, this paper proposes some ideas to build a binary estimator and then enhance its prediction capability. We integrate a number of features of various types (system-based, lexical, syntactic and semantic) into the conventional feature set, to build our classifier. After the experiment with all features, we deploy a " Feature Selection " strategy to filter the best performing ones. Next, we propose a method that combines multiple " weak " classifiers to build a strong " composite " classifier by taking advantage of their complementarity. Experimental results show that our propositions helped to achieve a better performance in term of F-score. Finally, we test whether WCE output can play any role in improving the sentence level confidence estimation system.
Group Key Establishment Scheme Using Wireless Channel Status

Broadcast-based wireless communication is vulnerable to sniffing and eavesdropping by adversaries. Hence, wireless network security mechanisms have relied on cryptographic algorithms to protect information and support confidentiality. We propose a group key establishment scheme for secure wireless multicast services without a key management center. The proposed scheme exploits wireless channel reciprocity and generates an identical secret key among group users by steering pilot phase. We analyze and evaluate performance of the proposed scheme. Our results give an insight to determine transmit power strength and phase quantization-level according to the number of group users and group key size.
A Comparison between Directly Connected and MPPT Connected Solar Powered Water Pumping System using PMDC Motor

This paper represents a comparative analysis of two photovoltaic pumping systems. To study the performance of the Maximum Power Point Tracking (MPPT) system, two models were simulated using Matlab/Simulink and the performance of a directly connected photovoltaic (SPV) pumping system was compared to an MPPT connected SPV pumping system at various levels of solar irradiance. The MPPT system maximizes overall system efficiency, but makes the system complex compared to the directly connected SPV pumping system. Instead of the conventional boost converter the MPPT system contains a buck converter to maintain overall system voltage at the lower levels required by the permanent magnet DC (PMDC) motor. For simplicity, the MPPT controller follows the perturbation and observation (P & O) algorithm and controls the buck converter to maximize overall system efficiency at various levels of solar irradiance. The PMDC motor provides high weight-to-torque density, better speed control, low inertia, and lower losses compared to induction and the conventional DC motor. The comparative analysis shows that the MPPT connected SPV system is more efficient than the directly connected SPV system for water pumping purposes using a PMDC motor.