Characteristics of Corporate Social Responsibility Indicators

The aim of the study is to investigate a number of characteristics of Corporate Social Responsibility (CSR) indicators that should be adopted by CSR assessment methodologies. For the purpose of this paper, a survey among the Greek companies that belong to FTSE 20 in Athens Exchange (FTSE/Athex-20) has been conducted, as these companies are expected to pioneer in the field of CSR. The results show consensus as regards the characteristics of indicators such as the need for the adoption of general and specific sector indicators, financial and non-financial indicators, the origin and the weight rate. However, the results are contradictory concerning the appropriate number of indicators for the assessment of CSR and the unit of measurement. Finally, the company-s sector is a more important dimension of CSR than the size and the country where the company operates. The purpose of this paper is to standardize the main characteristics of CSR indicators.

Reducing Unplanned Extubation in Psychiatric LTC

Today-s healthcare industries had become more patient-centric than profession-centric, from which the issues of quality of healthcare and the patient safety are the major concerns in the modern healthcare facilities. An unplanned extubation (UE) may be detrimental to the patient-s life, and thus is one of the major indexes of patient safety and healthcare quality. A high UE rate not only defeated the healthcare quality as well as the patient safety policy but also the nurses- morality, and job satisfaction. The UE problem in a psychiatric hospital is unique and may be a tough challenge for the healthcare professionals for the patients were mostly lacking communication capabilities. We reported with this essay a particular project that was organized to reduce the UE rate from the current 2.3% to a lower and satisfactory level in the long-term care units of a psychiatric hospital. The project was conducted between March 1st, 2011 and August 31st, 2011. Based on the error information gathered from varied units of the hospital, the team analyzed the root causes with possible solutions proposed to the meetings. Four solutions were then concluded with consensus and launched to the units in question. The UE rate was now reduced to a level of 0.17%. Experience from this project, the procedure and the tools adopted would be good reference to other hospitals.

Perceptions of Corporate Social Responsibility Concept in Greece

This study attempts to clarify major perspectives of Corporate Social Responsibility (CSR) in the Greek market related to companies that have sufficient CSR. An empirical analysis was undertaken, based on literature review and previous observations and surveys, in order to provide a general analysis of the CSR concept in Greece. The results of Accountability Rating institution were used in order to identify companies that adopt an integrated social responsibility approach. Companies that responded to the survey are both regional and international and belong to different industrial fields. Some of the main survey results reveal: multiple aspects for the CSR concept, weak consensus as regards the importance of stakeholders and benefits from the CSR implementation, the important role of CSR in the decision procedure and CSR practices concerning social issues that affect mostly company-s competitiveness. Sharing companies- experience could address common social issues through CSR best practices and develop new knowledge.

A Trust Model using Fuzzy Logic in Wireless Sensor Network

Adapting various sensor devices to communicate within sensor networks empowers us by providing range of possibilities. The sensors in sensor networks need to know their measurable belief of trust for efficient and safe communication. In this paper, we suggested a trust model using fuzzy logic in sensor network. Trust is an aggregation of consensus given a set of past interaction among sensors. We applied our suggested model to sensor networks in order to show how trust mechanisms are involved in communicating algorithm to choose the proper path from source to destination.

A Hybridization of Constructive Beam Search with Local Search for Far From Most Strings Problem

The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.

A Study of Factors Influencing the Improvement of Technology Business Incubator's Effectiveness: An Explanatory Model

In Both developed and developing countries, governments play a basic role in making policies, programs and instruments which support the development of micro, small and medium enterprises. One of the mechanisms employed to nurture small firms for more than two decades is business incubation. One of the mechanisms employed to nurture small firms for more than two decades is technology business incubation. The main aim of this research was to establish influencing factors in Technology Business Incubator's effectiveness and their explanatory model. Therefore, among 56 Technology Business Incubators in Iran, 32 active incubators were selected and by stratified random sampling, 528 start-ups were chosen. The validity of research questionnaires was determines by expert consensus, item analysis and factor analysis; and their reliability calculated by Cronbach-s alpha. Data analysis was then made through SPSS and LISREL soft wares. Both organizational procedures and entrepreneurial behaviors were the meaningful mediators. Organizational procedures with (P < .01, β =0.45) was stronger mediator for the improvement of Technology Business Incubator's effectiveness comparing to entrepreneurial behavior with (P < .01, β =0.36).

Leader-following Consensus Criterion for Multi-agent Systems with Probabilistic Self-delay

This paper proposes a delay-dependent leader-following consensus condition of multi-agent systems with both communication delay and probabilistic self-delay. The proposed methods employ a suitable piecewise Lyapunov-Krasovskii functional and the average dwell time approach. New consensus criterion for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical example showed that the proposed method is effective.

Constraint Based Frequent Pattern Mining Technique for Solving GCS Problem

Generalized Center String (GCS) problem are generalized from Common Approximate Substring problem and Common substring problems. GCS are known to be NP-hard allowing the problems lies in the explosion of potential candidates. Finding longest center string without concerning the sequence that may not contain any motifs is not known in advance in any particular biological gene process. GCS solved by frequent pattern-mining techniques and known to be fixed parameter tractable based on the fixed input sequence length and symbol set size. Efficient method known as Bpriori algorithms can solve GCS with reasonable time/space complexities. Bpriori 2 and Bpriori 3-2 algorithm are been proposed of any length and any positions of all their instances in input sequences. In this paper, we reduced the time/space complexity of Bpriori algorithm by Constrained Based Frequent Pattern mining (CBFP) technique which integrates the idea of Constraint Based Mining and FP-tree mining. CBFP mining technique solves the GCS problem works for all center string of any length, but also for the positions of all their mutated copies of input sequence. CBFP mining technique construct TRIE like with FP tree to represent the mutated copies of center string of any length, along with constraints to restraint growth of the consensus tree. The complexity analysis for Constrained Based FP mining technique and Bpriori algorithm is done based on the worst case and average case approach. Algorithm's correctness compared with the Bpriori algorithm using artificial data is shown.

Greening the Greyfields: Unlocking the Redevelopment Potential of the Middle Suburbs in Australian Cities

Pressures for urban redevelopment are intensifying in all large cities. A new logic for urban development is required – green urbanism – that provides a spatial framework for directing population and investment inwards to brownfields and greyfields precincts, rather than outwards to the greenfields. This represents both a major opportunity and a major challenge for city planners in pluralist liberal democracies. However, plans for more compact forms of urban redevelopment are stalling in the face of community resistance. A new paradigm and spatial planning platform is required that will support timely multi-level and multi-actor stakeholder engagement, resulting in the emergence of consensus plans for precinct-level urban regeneration capable of more rapid implementation. Using Melbourne, Australia as a case study, this paper addresses two of the urban intervention challenges – where and how – via the application of a 21st century planning tool ENVISION created for this purpose.

User Experience Evolution Lifecycle Framework

Perceptions of quality from both designers and users perspective have now stretched beyond the traditional usability, incorporating abstract and subjective concepts. This has led to a shift in human computer interaction research communities- focus; a shift that focuses on achieving user experience (UX) by not only fulfilling conventional usability needs but also those that go beyond them. The term UX, although widely spread and given significant importance, lacks consensus in its unified definition. In this paper, we survey various UX definitions and modeling frameworks and examine them as the foundation for proposing a UX evolution lifecycle framework for understanding UX in detail. In the proposed framework we identify the building blocks of UX and discuss how UX evolves in various phases. The framework can be used as a tool to understand experience requirements and evaluate them, resulting in better UX design and hence improved user satisfaction.

Analysis of Noise Level Effects on Signal-Averaged Electrocardiograms

Noise level has critical effects on the diagnostic performance of signal-averaged electrocardiogram (SAECG), because the true starting and end points of QRS complex would be masked by the residual noise and sensitive to the noise level. Several studies and commercial machines have used a fixed number of heart beats (typically between 200 to 600 beats) or set a predefined noise level (typically between 0.3 to 1.0 μV) in each X, Y and Z lead to perform SAECG analysis. However different criteria or methods used to perform SAECG would cause the discrepancies of the noise levels among study subjects. According to the recommendations of 1991 ESC, AHA and ACC Task Force Consensus Document for the use of SAECG, the determinations of onset and offset are related closely to the mean and standard deviation of noise sample. Hence this study would try to perform SAECG using consistent root-mean-square (RMS) noise levels among study subjects and analyze the noise level effects on SAECG. This study would also evaluate the differences between normal subjects and chronic renal failure (CRF) patients in the time-domain SAECG parameters. The study subjects were composed of 50 normal Taiwanese and 20 CRF patients. During the signal-averaged processing, different RMS noise levels were adjusted to evaluate their effects on three time domain parameters (1) filtered total QRS duration (fQRSD), (2) RMS voltage of the last QRS 40 ms (RMS40), and (3) duration of the low amplitude signals below 40 μV (LAS40). The study results demonstrated that the reduction of RMS noise level can increase fQRSD and LAS40 and decrease the RMS40, and can further increase the differences of fQRSD and RMS40 between normal subjects and CRF patients. The SAECG may also become abnormal due to the reduction of RMS noise level. In conclusion, it is essential to establish diagnostic criteria of SAECG using consistent RMS noise levels for the reduction of the noise level effects.

The e-DELPHI Method to Test the Importance Competence and Skills: Case of the Lifelong Learning Spanish Trainers

The lifelong learning is a crucial element in the modernization of European education and training systems. The most important actors in the development process of the lifelong learning are the trainers, whose professional characteristics need new competences and skills in the current labour market. The main objective of this paper is to establish an importance ranking of the new competences, capabilities and skills that the lifelong learning Spanish trainers must possess nowadays. A wide study of secondary sources has allowed the design of a questionnaire that organizes the trainer-s skills and competences. The e-Delphi method is used for realizing a creative, individual and anonymous evaluation by experts on the importance ranking that presents the criteria, sub-criteria and indicators of the e-Delphi questionnaire. Twenty Spanish experts in the lifelong learning have participated in two rounds of the e- DELPHI method. In the first round, the analysis of the experts- evaluation has allowed to establish the ranking of the most importance criteria, sub-criteria and indicators and to eliminate the least valued. The minimum level necessary to reach the consensus among experts has been achieved in the second round.

The Weight of Corporate Social Responsibility Indicators in Measurement Procedure

The Corporate Social Responsibility (CSR) performance has garnered significant interest during the last two decades as numerous methodologies are proposed by Social Responsible Investment (SRI) indexes. The weight of each indicator is a crucial component of the CSR measurement procedures. Based on a previous study, the appropriate weight of each proposed indicator for the Greek telecommunication sector is specified using the rank reciprocal weighting. The Kendall-s Coefficient of Concordance and Spearman Correlation Coefficient non-parametric tests are adopted to determine the level of consensus among the experts concerning the importance rank of indicators. The results show that there is no consensus regarding the rank of indicators in most of stakeholders- domains. The equal weight for all indicators could be proposed as a solution for the lack of consensus among the experts. The study recommends three different equations concerning the adopted weight approach.

eLearning Tools Evaluation based on Quality Concept Distance Computing. A Case Study

Despite the extensive use of eLearning systems, there is no consensus on a standard framework for evaluating this kind of quality system. Hence, there is only a minimum set of tools that can supervise this judgment and gives information about the course content value. This paper presents two kinds of quality set evaluation indicators for eLearning courses based on the computational process of three known metrics, the Euclidian, Hamming and Levenshtein distances. The “distance" calculus is applied to standard evaluation templates (i.e. the European Commission Programme procedures vs. the AFNOR Z 76-001 Standard), determining a reference point in the evaluation of the e-learning course quality vs. the optimal concept(s). The case study, based on the results of project(s) developed in the framework of the European Programme “Leonardo da Vinci", with Romanian contractors, try to put into evidence the benefits of such a method.

On the Move to Semantic Web Services

Semantic Web services will enable the semiautomatic and automatic annotation, advertisement, discovery, selection, composition, and execution of inter-organization business logic, making the Internet become a common global platform where organizations and individuals communicate with each other to carry out various commercial activities and to provide value-added services. There is a growing consensus that Web services alone will not be sufficient to develop valuable solutions due the degree of heterogeneity, autonomy, and distribution of the Web. This paper deals with two of the hottest R&D and technology areas currently associated with the Web – Web services and the Semantic Web. It presents the synergies that can be created between Web Services and Semantic Web technologies to provide a new generation of eservices.

Protein Secondary Structure Prediction Using Parallelized Rule Induction from Coverings

Protein 3D structure prediction has always been an important research area in bioinformatics. In particular, the prediction of secondary structure has been a well-studied research topic. Despite the recent breakthrough of combining multiple sequence alignment information and artificial intelligence algorithms to predict protein secondary structure, the Q3 accuracy of various computational prediction algorithms rarely has exceeded 75%. In a previous paper [1], this research team presented a rule-based method called RT-RICO (Relaxed Threshold Rule Induction from Coverings) to predict protein secondary structure. The average Q3 accuracy on the sample datasets using RT-RICO was 80.3%, an improvement over comparable computational methods. Although this demonstrated that RT-RICO might be a promising approach for predicting secondary structure, the algorithm-s computational complexity and program running time limited its use. Herein a parallelized implementation of a slightly modified RT-RICO approach is presented. This new version of the algorithm facilitated the testing of a much larger dataset of 396 protein domains [2]. Parallelized RTRICO achieved a Q3 score of 74.6%, which is higher than the consensus prediction accuracy of 72.9% that was achieved for the same test dataset by a combination of four secondary structure prediction methods [2].

Consensus on Climate Change Adaptation among Government and Populace

Observations and long-term trends indicate that climate change impacts would be significant and affects Taiwan directly and severely. Taiwan engages not only in mitigation, but also in adaptation. However, there are cognitive gaps on adaptation between government and populace. Besides, a vision of zero-carbon and renewable energy 100% will be adopted in future. Therefore, the objectives of this article are to 1) hold a National Forum for knowing differences between the strategies of zero-carbon and renewable energy 100% and cognitions of general populace, and 2) plan a clear roadmap for the vision, strategy, and measures. In this forum, we set 5 group topics, 5 presumed themes, and issues mentioned review for concluding the critical issues. Finally, there are 4 strategies and 14 critical issues which correlate with the vision and strategy of government and the cognition of the general populace.

A Finite-Time Consensus Protocol of the Multi-Agent Systems

According to conjugate gradient algorithm, a new consensus protocol algorithm of discrete-time multi-agent systems is presented, which can achieve finite-time consensus. Finally, a numerical example is given to illustrate our theoretical result.

A Survey: Clustering Ensembles Techniques

The clustering ensembles combine multiple partitions generated by different clustering algorithms into a single clustering solution. Clustering ensembles have emerged as a prominent method for improving robustness, stability and accuracy of unsupervised classification solutions. So far, many contributions have been done to find consensus clustering. One of the major problems in clustering ensembles is the consensus function. In this paper, firstly, we introduce clustering ensembles, representation of multiple partitions, its challenges and present taxonomy of combination algorithms. Secondly, we describe consensus functions in clustering ensembles including Hypergraph partitioning, Voting approach, Mutual information, Co-association based functions and Finite mixture model, and next explain their advantages, disadvantages and computational complexity. Finally, we compare the characteristics of clustering ensembles algorithms such as computational complexity, robustness, simplicity and accuracy on different datasets in previous techniques.