The Effect of Religious Tourist Motivation and Satisfaction on Behavioral Intention

In recent years, the Chaoshan area, a special place located in the southeast of Guangdong province in China, actively protects religious heritage and is developing religious tourism, which is attracting many expatriate Chinese who are coming back for travel and to worship. This paper discussed three questions. Firstly, what is the current situation about the different social background of tourists’ motivation, satisfaction and behavioral intention? Secondly, is there a relationship between the motivation, satisfaction and behavioral intention and the different social backgrounds of tourists? Thirdly, what is the relationship between religious tourists’ motivation, satisfaction and behavioral intention? The research methods use a combination of qualitative analysis and quantitative analysis. Qualitative analysis uses the method of observation and interviews. Convenient sampling technique was used for quantitative analysis. The study showed that the different social backgrounds of tourists’ forms diverse cognition and experiences about religious tourism, and their motivations, satisfaction and behavioral intention as tourists vary. Tourists’ motivation and satisfaction has a positive phase relation. Tourists’ motivation with satisfaction as the intervening variable also has a positive phase effect on tourists’ behavior intention. The result shows that religious tourists’ motivations include experiencing a religious atmosphere, and having a rest and recreation. The result also shows that religious tourists want to travel with their family members and friends. While traveling, religious tourists like to talk with Buddhist monks or nuns. Compared to other tourism types, religious tourists have higher expectations about temple environment, traveling experience, peripheral service and temple management.

Development of Innovative Islamic Web Applications

The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Investigating Activity Recognition Using 9-Axis Sensors and Filters in Wearable Devices

In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.

The Impact of Metacognitive Knowledge and Experience on Top Management Team Diversity and Small to Medium Enterprises Performance

The aim of this study is to determine the impact of metacognition on top management team members and firm performance based on full team integration. A survey of 1500 small to medium enterprises (SMEs) was initiated and 140 firms were obtained in this study (with response rate of 9%). The result showed that different metacognitive abilities of managers [knowledge and experience] could enhance team decision-making and problem solving, resulting in greater firm performance. This is a significant finding for SMEs because these organisations have small teams with owner leadership and entrepreneurial orientation.

Applying Transformative Service Design to Develop Brand Community Service in Women, Children and Infants Retailing

This research discussed the various theories of service design, the importance of service design methodology, and the development of transformative service design framework. In this study, transformative service design is applied while building a new brand community service for women, children and infants retailing business. The goal is to enhance the brand recognition and customer loyalty, effectively increase the brand community engagement by embedding the brand community in social network and ultimately, strengthen the impact and the value of the company brand.

Metabolomics Profile Recognition for Cancer Diagnostics

Metabolomics has become a rising field of research for various diseases, particularly cancer. Increases or decreases in metabolite concentrations in the human body are indicative of various cancers. Further elucidation of metabolic pathways and their significance in cancer research may greatly spur medicinal discovery. We analyzed the metabolomics profiles of lung cancer. Thirty-three metabolites were selected as significant. These metabolites are involved in 37 metabolic pathways delivered by MetaboAnalyst software. The top pathways are glyoxylate and dicarboxylate pathway (its hubs are formic acid and glyoxylic acid) along with Citrate cycle pathway followed by Taurine and hypotaurine pathway (the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine, serine, and threonine pathway (the hubs are glycine and L-serine). We studied interactions of the metabolites with the proteins involved in cancer-related signaling networks, and developed an approach to metabolomics biomarker use in cancer diagnostics. Our analysis showed that a significant part of lung-cancer-related metabolites interacts with main cancer-related signaling pathways present in this network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway, and NFKB pathway. These results can be employed for use of metabolomics profiles in elucidation of the related cancer proteins signaling networks.

Developing Rice Disease Analysis System on Mobile via iOS Operating System

This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

The Ethio-Eritrea Claims Commission on Use of Force: Issue of Self-Defense or Violation of Sovereignty

A decision that deals with international disputes, be it arbitral or judicial, has to properly reflect objectivity and coherence with existing rules of international law. This paper shows the decision of the Ethio-Eritrea Claims Commission on the jus ad bellum case is bereft of objectivity and coherence, which contributed a disservice to international law on many aspects. The Commission’s decision that holds Eritrea in contravention to Art 2(4) of the UN Charter based on Ethiopia’s contention is flawed. It fails to consider: the illegitimacy of an actual authority established over contested territory through hostile acts, the proper determination of effectivites under international law, the sanctity of colonially determined boundaries, Ethiopia’s prior firm political recognition and undergirds to respect colonial boundary, and Ethio-Eritrea Border Commission’s decision. The paper will also argue that the Commission confused Eritrea’s right of self-defense with the rule against the non-use of force to settle territorial disputes; wherefore its decision sanitizes or sterilizes unlawful change of territory resulted through unlawful use of force to the effect of advantaging aggressions. The paper likewise argues that the decision is so sacrilegious that it disregards the ossified legal finality of colonial boundaries. Moreover, its approach toward armed attack does not reflect the peculiarity of the jus ad bellum case rather it brings about definitional uncertainties and sustains the perception that the law on self-defense is unsettled.

Extremism among College and High School Students in Moscow: Diagnostics Features

In this day and age, extremism in various forms of its manifestation is a real threat to the world community, the national security of a state and its territorial integrity, as well as to the constitutional rights and freedoms of citizens. Extremism, as it is known, in general terms described as a commitment to extreme views and actions, radically denying the existing social norms and rules. Supporters of extremism in the ideological and political struggles often adopt methods and means of psychological warfare, appeal not to reason and logical arguments, but to emotions and instincts of the people, to prejudices, biases, and a variety of mythological designs. They are dissatisfied with the established order and aim at increasing this dissatisfaction among the masses. Youth extremism holds a specific place among the existing forms and types of extremism. In this context in 2015, we conducted a survey among Moscow college and high school students. The aim of this study was to determine how great or small is the difference in understanding and attitudes towards extremism manifestations, inclination and readiness to take part in extremist activities and what causes this predisposition, if it exists. We performed multivariate analysis and found the Russian college and high school students' opinion about the extremism and terrorism situation in our country and also their cognition on these topics. Among other things, we showed, that the level of aggressiveness of young people were not above the average for the whole population. The survey was conducted using the questionnaire method. The sample included college and high school students in Moscow (642 and 382, respectively) by method of random selection. The questionnaire was developed by specialists of RUDN University Sociological Laboratory and included both original questions (projective questions, the technique of incomplete sentences), and the standard test Dayhoff S. to determine the level of internal aggressiveness. It is also used as an experiment, the technique of study option using of FACS and SPAFF to determine the psychotypes and determination of non-verbal manifestations of emotions. The study confirmed the hypothesis that in respondents’ opinion, the level of aggression is higher today than a few years ago. Differences were found in the understanding of and respect for such social phenomena as extremism, terrorism, and their danger and appeal for the two age groups of young people. Theory of psychotypes, SPAFF (specific affect cording system) and FACS (facial action cording system) are considered as additional techniques for the diagnosis of a tendency to extreme views. Thus, it is established that diagnostics of acceptance of extreme views among young people is possible thanks to simultaneous use of knowledge from the different fields of socio-humanistic sciences. The results of the research can be used in a comparative context with other countries and as a starting point for further research in the field, taking into account its extreme relevance.

Human Action Recognition System Based on Silhouette

Human action is recognized directly from the video sequences. The objective of this work is to recognize various human actions like run, jump, walk etc. Human action recognition requires some prior knowledge about actions namely, the motion estimation, foreground and background estimation. Region of interest (ROI) is extracted to identify the human in the frame. Then, optical flow technique is used to extract the motion vectors. Using the extracted features similarity measure based classification is done to recognize the action. From experimentations upon the Weizmann database, it is found that the proposed method offers a high accuracy.

Mechanisms in Regulating Language Practices in Electronics Engineering: A Program Plan for Outcomes-Based Education

The underlying principle behind the harmonization in international education does not solely aim for the comparability but also the compatibility of outputs produced. The international standard in the different professions particularly in engineering defines the required graduate attributes to attain suitable qualifications and recognitions. This study described the language practices of the Electronics Engineering students of Bulacan State University, Philippines who will be deployed for their internship program. The purpose of the study was achieved by determining the language proficiency of the students in terms of speaking, listening, reading, and writing, and checking the adherence of the University to the commitment of intensifying community building for the Association of Southeast Asian Nation Vision 2020. The analysis of variance of the variables defined the significance between the causal variables and dependent variables. Thus, this study identified the mechanism that would regulate language practices in the Electronics Engineering program.

Corporate Governance in Network Marketing Organizations: The Role of Ethics and CSR

Corporate Governance (CG) is of utmost importance for running a company ethically. It is essential for the growth and success of the corporation. It is intended to increase the accountability of an organization to the larger context of the business environment. The general principles of CG include and are related to Shareholder recognition, Stakeholder interests, and focus on Corporate Social Responsibility (CSR), Clear Board responsibilities, Ethical behavior, and Business transparency. Network Marketing Organizations (NMOs) focus on marketing through direct-sales using people who are associated with the organization but are not their employees. This paper tries to study the importance of Ethics and CSR in an NMO and suggest a basic guideline for CG in NMO(s). This paper could be used as a basis or starting point for conducting an in-depth research to understand the difference in CG practices between NMO(s) and other organizations and define a standard set of guidelines for CG practice.

Teaching English to Engineers: Between English Language Teaching and Psychology

Teaching English to Engineers is part of English for Specific Purposes, a domain which is under the attention of English students especially under the current conditions of finding jobs and establishing partnerships outside Romania. The paper will analyse the existing textbooks together with the teaching strategies they adopt. Teaching English to Engineering students can intersect with domains such as psychology and cultural studies in order to teach them efficiently. Textbooks for students of ESP, ranging from those at the Faculty of Economics to those at the Faculty of Engineers, have shifted away from using specialized vocabulary, drills for grammar and reading comprehension questions and toward communicative methods and the practical use of language. At present, in Romania, grammar is neglected in favour of communicative methods. The current interest in translation studies may indicate a return to this type of method, since only translation specialists can distinguish among specialized terms and determine which are most suitable in a translation. Engineers are currently encouraged to learn English in order to do their own translations in their own field. This paper will analyse the issue of the extent to which it is useful to teach Engineering students to do translations in their field using cognitive psychology applied to language teaching, including issues such as motivation and social psychology. Teaching general English to engineering students can result in lack of interest, but they can be motivated by practical aspects which will help them in their field. This is why this paper needs to take into account an interdisciplinary approach to teaching English to Engineers.

Stereotypical Motor Movement Recognition Using Microsoft Kinect with Artificial Neural Network

Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Impact of Gold and Silver Nanoparticles on Terrestrial Flora and Microorganisms

Despite the rapid nanotechnology progress and recognition, its potential impact in ecosystems and health of humans is still not fully known. In this paper, the study of ecotoxicological dangers of nanomaterials is presented. By chemical reduction method, silver (AgNPs) and gold (AuNPs) nanoparticles were synthesized, characterized and used in experiments to examine their impact on microorganisms (Escherichia coli, Staphylococcus aureus and Candida albicans) and terrestrial flora (Phaseolus vulgaris and Lepidium sativum). The results collected during experiments with terrestrial flora show tendentious growth stimulations caused by gold nanoparticles. In contrast to these results, silver nanoparticle solutions inhibited growth of beans and garden cress, compared to control samples. The results obtained from experiments with microorganisms show similarities with ones collected from experiments with terrestrial plants. Samples treated with AuNPs of size 13 nm showed stimulation in the growth of the colonies compared with 3,5 nm size nanoparticles.

Disaggregating and Forecasting the Total Energy Consumption of a Building: A Case Study of a High Cooling Demand Facility

Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  

Medical Image Edge Detection Based on Neuro-Fuzzy Approach

Edge detection is one of the most important tasks in image processing. Medical image edge detection plays an important role in segmentation and object recognition of the human organs. It refers to the process of identifying and locating sharp discontinuities in medical images. In this paper, a neuro-fuzzy based approach is introduced to detect the edges for noisy medical images. This approach uses desired number of neuro-fuzzy subdetectors with a postprocessor for detecting the edges of medical images. The internal parameters of the approach are optimized by training pattern using artificial images. The performance of the approach is evaluated on different medical images and compared with popular edge detection algorithm. From the experimental results, it is clear that this approach has better performance than those of other competing edge detection algorithms for noisy medical images.

A Practical and Efficient Evaluation Function for 3D Model Based Vehicle Matching

3D model-based vehicle matching provides a new way for vehicle recognition, localization and tracking. Its key is to construct an evaluation function, also called fitness function, to measure the degree of vehicle matching. The existing fitness functions often poorly perform when the clutter and occlusion exist in traffic scenarios. In this paper, we present a practical and efficient fitness function. Unlike the existing evaluation functions, the proposed fitness function is to study the vehicle matching problem from both local and global perspectives, which exploits the pixel gradient information as well as the silhouette information. In view of the discrepancy between 3D vehicle model and real vehicle, a weighting strategy is introduced to differently treat the fitting of the model’s wireframes. Additionally, a normalization operation for the model’s projection is performed to improve the accuracy of the matching. Experimental results on real traffic videos reveal that the proposed fitness function is efficient and robust to the cluttered background and partial occlusion.

Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments

Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

The Emotions in Consumers’ Decision Making: Review of Empirical Studies

This paper explores, in depth, the idea that emotions are present in all consumer decision making processes, meaning that purchase decisions have never been purely cognitive or as they traditionally have been defined, rational. Human beings, in all kinds of decisions, has "always" used neural systems related to emotions along with neural systems related to cognition, regardless of the type of purchase or the product or service in question. Therefore, all purchase decisions are, at the same time, cognitive and emotional. This paper presents an analysis of the main contributions of researchers in this regard.