Search results for: context aware computing

Authors: Xunan Huang, Caicai Zhang

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This paper investigated the code-mixing features in Mandarin-English bilingual children in Singapore. First, it examined whether the code-mixing rate was different in Mandarin Chinese and English contexts. Second, it explored the syntactic categories of code-mixing in Singapore bilingual children. Moreover, this study investigated whether morphological information was preserved when inserting syntactic components into the matrix language. Data are derived from the Singapore Bilingual Corpus, in which the recordings and transcriptions of sixty English-Mandarin 5-to-6-year-old children were preserved for analysis. Results indicated that the rate of code-mixing was asymmetrical in the two language contexts, with the rate being significantly higher in the Mandarin context than that in the English context. The asymmetry is related to language dominance in that children are more likely to code-mix when using their nondominant language. Concerning the syntactic categories of code-mixing words in the Singaporean bilingual children, we found that noun-mixing, verb-mixing, and adjective-mixing are the three most frequently used categories in code-mixing in the Mandarin context. This pattern mirrors the syntactic categories of code-mixing in the Cantonese context in Cantonese-English bilingual children, and the general trend observed in lexical borrowing. Third, our results also indicated that English vocabularies that carry morphological information are embedded in bare forms in the Mandarin context. These findings shed light upon how bilingual children take advantage of the two languages in mixed utterances in a bilingual environment.

Keywords: bilingual children, code-mixing, English, Mandarin Chinese

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Authors: Sekkal Nawel

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The Web of Things (WoT), integration of smart technologies from the Internet or network to Web architecture or application, is becoming more complex, larger, and dynamic. The WoT is associated with various elements such as sensors, devices, networks, protocols, data, functionalities, and architectures to perform services for stakeholders. These services operate in the context of the interaction of stakeholders and the WoT elements. Such context is becoming a key information source from which data are of various nature and uncertain, thus leading to complex situations. In this paper, we take interest in the development of intelligent Web services. The key ingredients of this “intelligent” notion are the context diversity, the necessity of a semantic representation to manage complex situations and the capacity to reason with uncertain data. In this perspective, we introduce a multi-layered architecture based on a generic intelligent Web service model dealing with various contexts, which proactively predict future situations and reactively respond to real-time situations in order to support decision-making. For semantic context data representation, we use PR-OWL, which is a probabilistic ontology based on Multi-Entity Bayesian Networks (MEBN). PR-OWL is flexible enough to represent complex, dynamic, and uncertain contexts, the key requirements of the development for the intelligent Web services. A case study was carried out using the proposed architecture for intelligent plant watering to show the role of proactive and reactive contextual reasoning in terms of WoT.

Keywords: smart web service, the web of things, context reasoning, proactive, reactive, multi-entity bayesian networks, PR-OWL

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Authors: Mohammed Agbali, Claudia Trillo, Yusuf Arayici, Terrence Fernando

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The wide-spread adoption of the Smart City concept has introduced a new era of computing paradigm with opportunities for city administrators and stakeholders in various sectors to re-think the concept of urbanization and development of healthy cities. With the world population rapidly becoming urban-centric especially amongst the emerging economies, social innovation will assist greatly in deploying emerging technologies to address the development challenges in core sectors of the future cities. In this context, sustainable health-care delivery and improved quality of life of the people is considered at the heart of the healthy city agenda. This paper examines the Boston innovation landscape from the perspective of smart services and innovation ecosystem for sustainable development, especially in transportation and healthcare. It investigates the policy implementation process of the Healthy City agenda and eHealth economy innovation based on the experience of Massachusetts’s City of Boston initiatives. For this purpose, three emerging areas are emphasized, namely the eHealth concept, the innovation hubs, and the emerging technologies that drive innovation. This was carried out through empirical analysis on results of public sector and industry-wide interviews/survey about Boston’s current initiatives and the enabling environment. The paper highlights few potential research directions for service integration and social innovation for deploying emerging technologies in the healthy city agenda. The study therefore suggests the need to prioritize social innovation as an overarching strategy to build sustainable Smart Cities in order to avoid technology lock-in. Finally, it concludes that the Boston example of innovation economy is unique in view of the existing platforms for innovation and proper understanding of its dynamics, which is imperative in building smart and healthy cities where quality of life of the citizenry can be improved.

Keywords: computing paradigm, emerging technologies, equitable healthcare, healthy cities, open data, smart city, social innovation

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Authors: Patrick Santos, João Casal, João Santos Luis Varandas, Tiago Alves, Carlos Romeiro, Sérgio Lourenço

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Nowadays, technology makes it possible to, in one hand, communicate with various objects of the daily life through the Internet, and in the other, put these objects interacting with each other through this channel. Simultaneously, with the raise of smartphones as the most ubiquitous technology on persons lives, emerge new agents for these devices - Intelligent Personal Assistants. These agents have the goal of helping the user manage and organize his information as well as supporting the user in his/her day-to-day tasks. Moreover, other emergent concept is the Cloud Computing, which allows computation and storage to get out of the users devices, bringing benefits in terms of performance, security, interoperability and others. Connecting these three paradigms, in this work we propose an architecture for an intelligent system which provides an interface that assists the user on smart environments, informing, suggesting actions and allowing to manage the objects of his/her daily life.

Keywords: internet of things, cloud, intelligent personal assistant, architecture

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Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

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Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

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Authors: Fairouz Fakhfakh, Hatem Hadj Kacem, Ahmed Hadj Kacem

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Cloud computing offers a new model of service provisioning for workflow applications, thanks to its elasticity and its paying model. However, it presents various challenges that need to be addressed in order to be efficiently utilized. The resources provisioning problem for workflow applications has been widely studied. Nevertheless, the existing works did not consider the change in workflow instances while they are being executed. This functionality has become a major requirement to deal with unusual situations and evolution. This paper presents a first step towards the resources provisioning for a dynamic workflow. In fact, we propose a provisioning algorithm which minimizes the overall workflow execution cost, while meeting a deadline constraint. Then, we extend it to support the dynamic adding of tasks. Experimental results show that our proposed heuristic demonstrates a significant reduction in resources cost by using a consolidation process.

Keywords: cloud computing, resources provisioning, dynamic workflow, workflow applications

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: S. Y. Ozkan, S. Taftaf

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This study aims to investigate the possible effects of guerrilla advertising on consumers' attitudes as well as purchase intentions in comparison with traditional advertising. Participants who were over 18 years of age were recruited and completed an online questionnaire. Each participant was randomly assigned to one of the four well-known brand conditions. The study had a within-subjects design where each participant evaluated two advertisements, one guerrilla advertisement, and one traditional advertisement od one respective brand. Participants rated both traditional advertisement and guerrilla advertisement on ad attitude, ad likability, and purchase intention scales. Ad attitude was measured by using both positive and negative adjectives. The hypotheses were tested by paired samples t-test analysis. The results indicated that perceivers were able to differentiate advertisements that include guerrilla techniques and advertisements that include traditional methods from one another. Regardless of the brand manipulation, guerrilla advertisements lead significantly higher positive ad attitude, negative ad attitude, ad likability, and purchase intention compared to traditional advertisements. Therefore, the results showed that while using guerrilla advertising, companies should be aware of any ethical concerns that may emerge in consumers' minds. Present study is one of the rare studies that measures the perceptions of guerrilla and traditional advertisements in an empirical manner in Turkish context, showing that guerrilla advertisements may stimulate negative ad attitudes together with positive ad attitudes, increasing ad likability and purchase intention.

Keywords: ad attitude, guerrilla advertisement, purchase intention, traditional advertisement

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Authors: Panita Wannapiroon, Noppadon Phumeechanya, Sitthichai Laisema

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This study is the research and development which is intended to: 1) design the ubiquitous cloud learning management system and: 2) assess the suitability of the design of the ubiquitous cloud learning management system. Its methods are divided into 2 phases. Phase 1 is the design of the ubiquitous cloud learning management system, phase 2 is the assessment of the suitability of the design the samples used in this study are work done by 25 professionals in the field of Ubiquitous cloud learning management systems and information and communication technology in education selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. The results showed that the ubiquitous cloud learning management system consists of 2 main components which are: 1) the ubiquitous cloud learning management system server (u-Cloud LMS Server) including: cloud repository, cloud information resources, social cloud network, cloud context awareness, cloud communication, cloud collaborative tools, and: 2) the mobile client. The result of the system suitability assessment from the professionals is in the highest range.

Keywords: learning management system, cloud computing, ubiquitous learning, ubiquitous learning management system

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Authors: Patrick J. Kerpan, Ryan C. Koop, Margaret M. Walker, Chris P. Swan

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The User Datagram Protocol (UDP) multicast is a vital part of data center networking that is being left out of major cloud computing providers' network infrastructure. Enterprise users rely on multicast, and particularly UDP multicast to create and connect vital business operations. For example, UPD makes a variety of business functions possible from simultaneous content media updates, High-Performance Computing (HPC) grids, and video call routing for massive open online courses (MOOCs). Essentially, UDP multicast's technological slight is causing a huge effect on whether companies choose to use (or not to use) public cloud infrastructure as a service (IaaS). Allowing the ‘chatty’ UDP multicast protocol inside a cloud network could have a serious impact on the performance of the cloud as a whole. Cloud IaaS providers solve the issue by disallowing all UDP multicast. But what about enterprise use cases for multicast applications in organizations that want to move to the cloud? To re-allow multicast traffic, enterprises can build a layer 3 - 7 network over the top of a data center, private cloud, or public cloud. An overlay network simply creates a private, sealed network on top of the existing network. Overlays give complete control of the network back to enterprise cloud users the freedom to manage their network beyond the control of the cloud provider’s firewall conditions. The same logic applies if for users who wish to use IPsec or BGP network protocols inside or connected into an overlay network in cloud IaaS.

Keywords: cloud computing, protocols, UDP multicast, virtualization

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Authors: Sanjeev Kumar Appicharla

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This paper presents the results of the modelling and analysis of the European Railway Traffic Management (ERTMS) safety-critical incident to raise awareness of biases in the systems engineering process on the Cambrian Railway in the UK using the RAIB 17/2019 as a primary input. The RAIB, the UK independent accident investigator, published the Report- RAIB 17/2019 giving the details of their investigation of the focal event in the form of immediate cause, causal factors, and underlying factors and recommendations to prevent a repeat of the safety-critical incident on the Cambrian Line. The Systems for Investigation of Railway Interfaces (SIRI) is the methodology used to model and analyze the safety-critical incident. The SIRI methodology uses the Swiss Cheese Model to model the incident and identify latent failure conditions (potentially less than adequate conditions) by means of the management oversight and risk tree technique. The benefits of the systems for investigation of railway interfaces methodology (SIRI) are threefold: first is that it incorporates the “Heuristics and Biases” approach advanced by 2002 Nobel laureate in Economic Sciences, Prof Daniel Kahneman, in the management oversight and risk tree technique to identify systematic errors. Civil engineering and programme management railway professionals are aware of the role “optimism bias” plays in programme cost overruns and are aware of bow tie (fault and event tree) model-based safety risk modelling techniques. However, the role of systematic errors due to “Heuristics and Biases” is not appreciated as yet. This overcomes the problems of omission of human and organizational factors from accident analysis. Second, the scope of the investigation includes all levels of the socio-technical system, including government, regulatory, railway safety bodies, duty holders, signaling firms and transport planners, and front-line staff such that lessons are learned at the decision making and implementation level as well. Third, the author’s past accident case studies are supplemented with research pieces of evidence drawn from the practitioner's and academic researchers’ publications as well. This is to discuss the role of system thinking to improve the decision-making and risk management processes and practices in the IEC 15288 systems engineering standard and in the industrial context such as the GB railways and artificial intelligence (AI) contexts as well.

Keywords: accident analysis, AI algorithm internal audit, bounded rationality, Byzantine failures, heuristics and biases approach

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Authors: Tanveer Hussain, Khan Muhammad, Amin Ullah, Mi Young Lee, Sung Wook Baik

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The Big Data generated from distributed vision sensors installed on large scale in smart cities create hurdles in its efficient and beneficial exploration for browsing, retrieval, and indexing. This paper presents a three-folded framework for effective video summarization of such data and provide a compact and representative format of Big Video Data. In the first fold, the paper acquires input video data from the installed cameras and collect clues such as type and count of objects and clarity of the view from a chunk of pre-defined number of frames of each view. The decision of representative view selection for a particular interval is based on fuzzy inference system, acquiring a precise and human resembling decision, reinforced by the known clues as a part of the second fold. In the third fold, the paper forwards the selected view frames to the summary generation mechanism that is supported by a saliency-aware convolution neural network (CNN) model. The new trend of fuzzy rules for view selection followed by CNN architecture for saliency computation makes the multi-view video summarization (MVS) framework a suitable candidate for real-world practice in smart cities.

Keywords: big video data analysis, fuzzy logic, multi-view video summarization, saliency detection

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Authors: Manish Kumar Thakur, Subrata Kumar Ghosh

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Various types of particles found in lubricant may be characterized by their fractal dimension. Some of the available methods are: yard-stick method or structured walk method, box-counting method. This paper presents a review of the developments and progress in fractal dimension computing methods as applied to characteristics the surface of wear particles. An overview of these methods, their implementation, their advantages and their limits is also present here. It has been accepted that wear particles contain major information about wear and friction of materials. Morphological analysis of wear particles from a lubricant is a very effective way for machine condition monitoring. Fractal dimension methods are used to characterize the morphology of the found particles. It is very useful in the analysis of complexity of irregular substance. The aim of this review is to bring together the fractal methods applicable for wear particles.

Keywords: fractal dimension, morphological analysis, wear, wear particles

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Authors: Nalinee Sophatsathit

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The objectives of memorabilia of Suan Sunandha are to develop a general knowledge presentation about the historical royal garden through interactive graphic simulation technique and to employ high-functionality context in enhancing interactive user navigation. The approach infers non-intrusive display of relevant history in response to situational context. User’s navigation runs through the virtual reality campus, consisting of new and restored buildings. A flash back presentation of information pertaining to the history in the form of photos, paintings, and textual descriptions are displayed along each passing-by building. To keep the presentation lively, graphical simulation is created in a serendipity game play so that the user can both learn and enjoy the educational tour. The benefits of this human-computer interaction development are two folds. First, lively presentation technique and situational context modeling are developed that entail a usable paradigm of knowledge and information presentation combinations. Second, cost effective training and promotion for both internal personnel and public visitors to learn and keep informed of this historical royal garden can be furnished without the need for a dedicated public relations service. Future improvement on graphic simulation and ability based display can extend this work to be more realistic, user-friendly, and informative for all.

Keywords: interactive user navigation, high-functionality context, situational context, human-computer interaction

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Authors: Ioanna Koumi

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The aim of the intervention presented is to show the positive effects a mindfulness programme can have on the behaviour of preschoolers (years 4-6). The programme was implemented as part of the psychologist's work in 5 preschool units on the Greek island of Chios. Classroom-based activities of mindfulness were shown and practiced in 5 sessions, in collaboration with teachers, in order to make preschoolers aware of how their brain affects their behaviour, as well as of how they can have more positive behaviours, especially in instances of negative feelings. The outcomes of the intervention were assessed via questionnaire completion before and after the sessions by the teachers, as well as focus groups procedures with students, teachers, and parents. Implications of how mindfulness programmes can also be implemented at home are further discussed. School year in which the programme is being implemented: 2022-23 Intervention method: based on basic mindfulness theory and practice, the 220 students (age 4-6) in 11 classes of the 5 preschools that participated were given lessons of how to become aware of their states of focusing, regulation, attention, emotional situation, as well as body and social situations. Furthermore, the preschoolers were encouraged to make more mindful choices when it came to negative situations and emotions. Assessment method: The school as a caring community Profile II – Questionnaire completed by 20 preschool teachers prior to and after the intervention, Focus group sessions with teachers, students, parents at the end of the intervention Results: the assessment will be completed in May 2023.

Keywords: preschool, mindfulness training, self-awareness, social-emotional development

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Authors: Asmaa El Harat, Toumi Hicham, Youssef Baddi

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This survey delves into the complex realm of Internet of Things (IoT) security, highlighting the urgent need for effective cybersecurity measures as IoT devices become increasingly common. It explores a wide array of cyber threats targeting IoT devices and focuses on mitigating these attacks through the combined use of deep learning and machine learning algorithms, as well as edge and cloud computing paradigms. The survey starts with an overview of the IoT landscape and the various types of attacks that IoT devices face. It then reviews key machine learning and deep learning algorithms employed in IoT cybersecurity, providing a detailed comparison to assist in selecting the most suitable algorithms. Finally, the survey provides valuable insights for cybersecurity professionals and researchers aiming to enhance security in the intricate world of IoT.

Keywords: internet of things (IoT), cybersecurity, machine learning, deep learning

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Authors: Ahmad Mohsin, Syda Fatima, Falak Nawaz, Aman Ullah Khan

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Selection of an appropriate architectural style is vital to the success of target web service under development. The nature of architecture design and selection for service-oriented computing applications is quite different as compared to traditional software. Web Services have complex and rigorous architectural styles to choose. Due to this, selection for accurate architectural style for web services development has become a more complex decision to be made by architects. Architectural style selection is a multi-criteria decision and demands lots of experience in service oriented computing. Decision support systems are good solutions to simplify the selection process of a particular architectural style. Our research suggests a new approach using DSS for selection of architectural styles while developing a web service to cater FRs and NFRs. Our proposed DSS helps architects to select right web service architectural pattern according to the domain and non-functional requirements. In this paper, a rule base DSS has been developed using CLIPS (C Language Integrated Production System) to support decisions using multi-criteria requirements. This DSS takes architectural characteristics, domain requirements and software architect preferences for NFRs as input for different architectural styles in use today in service-oriented computing. Weighted sum model has been applied to prioritize quality attributes and domain requirements. Scores are calculated using multiple criterions to choose the final architecture style.

Keywords: software architecture, web-service, rule-based, DSS, multi-criteria requirements, quality attributes

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Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib‎

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In order to support the continued growth, critical latency of ‎IoT ‎applications, and ‎various obstacles of traditional data centers, ‎mobile edge ‎computing (MEC) has ‎emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. ‎By adopting a MEC structure, IoT applications could be executed ‎locally, on ‎an edge server, different fog nodes, or distant cloud ‎data centers. However, we are ‎often ‎faced with wanting to optimize conflicting criteria such as ‎minimizing energy ‎consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge ‎devices and trying to ‎keep ‎high performance (reducing ‎response time, increasing throughput and service availability) ‎at the same ‎time‎. Achieving one goal may affect the other, making task offloading (TO), ‎resource allocation (RA), and service placement (SP) complex ‎processes. ‎It is a nontrivial multi-objective optimization ‎problem ‎to study the trade-off between conflicting criteria. ‎The paper provides a survey on different TO, SP, and RA recent multi-‎objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications‎.

Keywords: mobile edge computing, multi-objective optimization, artificial ‎intelligence ‎approaches, task offloading, resource allocation, ‎ service placement

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Authors: Chiung-Hui Chen

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With advancements in science and technology, the concept of the Internet of Things (IoT) has gradually developed. The development of the intelligent environment adds intelligence to objects in the living space by using the IoT. In the smart environment, when multiple users share the living space, if different service requirements from different users arise, then the context-aware system will have conflicting situations for making decisions about providing services. Therefore, the purpose of establishing a communication and negotiation mechanism among objects in the intelligent environment is to resolve those service conflicts among users. This study proposes developing a decision-making methodology that uses “Event Agents” as its core. When the sensor system receives information, it evaluates a user’s current events and conditions; analyses object, location, time, and environmental information; calculates the priority of the object; and provides the user services based on the event. Moreover, when the event is not single but overlaps with another, conflicts arise. This study adopts the “Multiple Events Correlation Matrix” in order to calculate the degree values of incidents and support values for each object. The matrix uses these values as the basis for making inferences for system service, and to further determine appropriate services when there is a conflict.

Keywords: internet of things, intelligent object, event agents, negotiation mechanism, degree of similarity

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Authors: Olanrewaju Kafayat, O., Salman Kabir, K.

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The role of organic agriculture in providing food and income is now gaining wider recognition (Van Elzakker et al 2007). The increasing public concerns about food safety issues on the use of fertilizers, pesticide residues, growth hormones, GM organisms, and increasing awareness of environmental quality issues have led to an expanding demand for environmentally friendly products (Thompson, 1998; Rimal et al., 2005). As a result national governments are concerned about diet and health, and there has been renewed recognition of the role of public policy in promoting healthy diets, thus to provide healthier, safer, more confident citizens (Poole et al., 2007), With these benefits, a study into organic vegetables is very vital to all the major stakeholders. This study analyzed the willingness of consumers to pay for organic vegetables in Oyo state, Nigeria. Primary data was collected with the aid of structured questionnaire administered to 168 respondents. These were selected using multistage random sampling. The first stage involved the selection two (2) ADP zones out of the three (3) ADP zones in Oyo state, The second stage involved the random selection of two (2) local government areas each out of the two (2) ADP zones which are; Ibadan South West and Ogbomoso North and random selection of 4 wards each from the local government areas. The third stage involved random selection of 42 household each from of the local government areas. Descriptive statistics, the principal component analysis, and the logistic regression were used to analyze the data. Results showed 55 percent of the respondents were female while 80 percent were  50 years. 74 percent of the respondents agreed that organic vegetables are of better quality. 31 percent of the respondents were aware of organic vegetables as against 69 percent who were not aware. From the logistic model, educational attainment, amount spent on organic vegetables monthly, better quality of organic vegetables and accessibility to organic vegetables were significant and had a positive relationship on willingness to pay for organic vegetable. The variables that were significant and had a negative relationship with WTP are less attractiveness of organic vegetables and household size of the respondents. This study concludes that consumers with higher level of education were more likely to be aware and willing to pay for organic vegetables than those with low levels of education, the study therefore recommends creation of awareness on the relevance of consuming organic vegetables through effective marketing and educational campaigns.

Keywords: consumers awareness, willingness to pay, organic vegetables, Oyo State

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Authors: Kalat P. Duniya

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A number of technologies expected to increase maize productivity have been introduced by several research programs at national and international level. To this end, the study sought to identify the factors influencing adoption intensity of certified maize varieties. The data used were obtained from a sample household survey of 406 maize farmers, conducted in the northern guinea savannah of Nigeria through multistage stratified sampling, structured questionnaire. A triple hurdle model was adopted to estimate the determinants of adoption intensity; considering awareness, adoption, and intensity as three separate stages. The result showed that the drivers of farmers’ awareness, adoption, and intensity of usage may not necessarily be the same, and where they are, not of the same magnitude and direction. However, factors which were found to be statistically significant were age, education, membership of association and frequency of extension advice. In addition, awareness and adoption of the technologies were likely to be increased with male respondents. Farmers that were members of either community organizations or cooperative organizations had a higher tendency of being aware and adopting certified maize seed varieties. It was also discovered that though some of the farmers were fully aware of the existence of some certified maize varieties, majority lacked detailed knowledge and technical know-how. There is a need for creation of awareness through an excellent trained extension and restructuring of the educational sector to improve on the adoption process as well as improve maize productivity in the country.

Keywords: adoption, awareness, maize farmers, Nigeria, regression

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Authors: Mythri Kukkaje

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Information about the social and psychological contexts that operate as a breeding ground for perpetrators of violence against women in India is scarce. To understand the social and psychological contexts that form the bases of violent behaviour in male-perpetrators against women, interviews were conducted with 13 men above the age of 18 years, who were convicted for their crimes against women. Using thematic analysis, the nurturance and the social background of the perpetrators, determined by their social relationships, the socio-economic status, the extent of substance abuse, the history of experiencing and witnessing violence and their cultural context, were found to define the social context. The nature and the psychological background of the perpetrators determined by the thoughts and beliefs regarding gender and violence, the motivation behind their violent behaviour and a few specific personality traits were found to define the psychological context. These factors on their own, as well as an interaction between them, could be responsible for varying degrees of violence against women.

Keywords: perpetrator, psychological, social, violence against women

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Authors: Roman Snytsar

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Pseudo-random numbers are often used in scientific computing such as the Monte Carlo Simulations or the Quantum Inspired Optimization. Requirements for a parallel random number generator running in the modern multi-core vector environment are more stringent than those for sequential random number generators. As well as passing the usual quality tests, the output of the parallel random number generator must be verifiable and reproducible throughout the concurrent execution. We propose a family of vectorized Permuted Congruential Generators. Implementations are available for multiple modern vector modern computer architectures. Besides demonstrating good single core performance, the generators scale easily across many processor cores and multiple distributed nodes. We provide performance and parallel speedup analysis and comparisons between the implementations.

Keywords: pseudo-random numbers, quantum optimization, SIMD, parallel computing

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Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker

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In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

Keywords: admissions, algorithms, cloud computing, differentiation, fog computing, levelling, machine learning

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Authors: Pin-Hua Chou

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MACAN (Museum of Modern and Contemporary Art in Nusantara) is a new private art museum in Jakarta, Indonesia. Facing challenges of rapidly changing social, cultural environments, MACAN is responding by devoting themselves to not only presenting famous international artists but also constructing the context of artists from Indonesia by interdisciplinary education and cultural exchange. This paper discusses the exhibitions, collections and the activities of MACAN. The purpose of this museum is to make people aware of the dialogue between local and international artist, and also Indonesia’s own art history. Yet how they build up the cultural consciousness for their audience inside and outside Indonesia? What strategy or method do they adapt to enhance general understanding of their own history and the relation between Indonesia and the world through their exhibition? MACAN has tried to convey their mission by every action they took since its opening (2017). The discussion begins with the premise that the initiative of MACAN offers us a new vision to better understand how a modern and contemporary art museum can make an effort to connect art with cultural identity and stimulate the awareness of recognition in Indonesia. This paper will adopt a case study, curator interview, and document analysis. Last but not least, the paper seeks to contribute towards the narrative of its first exhibition Art Turns, World Turns, Exploring the collection of the MACAN, as well as the possibility of raising audience’s cultural consciousness by a variety of public programs.

Keywords: contemporary art museum, challenges for art museum curators today, culture heritage, museum collections and exhibitions

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Authors: Dianah Kitiabi

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This study examines the experiences of graduate international students in Study Abroad (SA) in order to understand the evolution of their second language (L2) skills during the period of their sojourn abroad. The study documents students’ perspectives through analysis of interview data situated within the context of their overall SA experience. Based on a phenomenological approach, the study focuses on a sample of nine graduate students with at least one year of SA experience. Gass & Mackey’s (2007) interaction approach and Vygotsky’s (1962) sociocultural theory help frame the study within the discourse of second language acquisition (SLA) in SA, such as to highlight the effects of SA on L2 skills of advanced-level learners. The findings of the study are first presented as individual case vignettes where students’ interpretations of their personal experiences are described in entirety, followed by an analysis across the cases that highlight emergent themes. The results of this study show that the linguistic outcomes of international students studying abroad are highly individualized. Although students reported to have improved some of their L2 skills, they also reported a lack of improvement in other L2 skills, most of which differed by case. What emerges is that besides contextual factors, students’ pre-program exposure to L2, interactions with NSs, frequency of L2 use in context, and personal beliefs contribute to their linguistic gains in SA.

Keywords: context, interaction, second language acquisition, study abroad

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Authors: Jekaterina Novikova, Leon Watts

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In the emerging world of human-robot interaction, people and robots will interact socially in real-world situations. This paper presents the results of an experimental study probing the interaction between situational context and emotional body language in robots. 34 people rated video clips of robots performing expressive behaviours in different situational contexts both for emotional expressivity on Valence-Arousal-Dominance dimensions and by selecting a specific emotional term from a list of suggestions. Results showed that a contextual information enhanced a recognition of emotional body language of a robot, although it did not override emotional signals provided by robot expressions. Results are discussed in terms of design guidelines on how an emotional body language of a robot can be used by roboticists developing social robots.

Keywords: social robotics, non-verbal communication, situational context, artificial emotions, body language

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Authors: Yousra Drissi

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This research explores language teacher identity in a multilingual context where both teachers and students come from different linguistic backgrounds. It seeks to understand how teachers perceive themselves as language teachers in this context in relation to different influencing factors, both internal and external. This study is being conducted due to the importance of language teacher identity (LTI) in the university context, which is being neglected in the present literature (in an attempt to address the gap in the present literature). The broader aim of this study is to bring attention to language teacher identity along with the different influencing elements which can either promote or hinder its development. In this research, we are using the sociocultural theory and post-structural theory. This research uses the mixed methods approach to collect and analyse relevant data. A structured survey was distributed to language teachers from different universities around Algeria, followed by in-depth interviews. Results are supposed to show the different points in self-perception that these teachers share or differ in. they will also help us identify the different internal and external factors that can be of influence. However, the results of this research can be used by institutions as well as decision-makers to better understand university teachers and help them improve their teaching practices by empowering their language teacher identity, starting from teacher education programs to continuous teacher development programs.

Keywords: identity, language teacher identity, multilingualism, university teacher

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Authors: Alemaw Kefale, Aramde Fetene, Hayal Desta

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This study analyzed the users' and experts' views on the green space quality and planning models in Debre Berhan (DB) and Debre Markos (DM) cities in Ethiopia. A questionnaire survey was conducted on 350 park users (148 from DB and 202 from DM) to rate the accessibility, size, shape, vegetation cover, social and cultural context, conservation and heritage, community participation, attractiveness, comfort, safety, inclusiveness, and maintenance of green spaces using a Likert scale. A key informant interview was held with 13 experts in DB and 12 in DM. Descriptive statistics and tests of independence of variables using the chi-square test were done. A statistically significant association existed between the perception of green space quality attributes and users' occupation (χ² (160, N = 350) = 224.463, p < 0.001), age (χ² (128, N = 350) = 212.812, p < 0.001), gender (χ² (32, N = 350) = 68.443, p < 0.001), and education level (χ² (192, N = 350) = 293.396, p < 0.001). 61.7 % of park users were unsatisfied with the quality of urban green spaces. The users perceived dense vegetation cover as "good," with a mean value of 3.41, while the remaining were perceived as "medium with a mean value of 2.62 – 3.32". Only quantitative space standards are practiced as a green space planning model, while other models are unfamiliar and never used in either city. Therefore, experts need to be aware of and practice urban green models during urban planning to ensure that new developments include green spaces to accommodate the community's and the environment's needs.

Keywords: urban green space, quality, users and experts, green space planning models, Ethiopia

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