Search results for: neighbor based key sharing

Authors: Abraham Rotich

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The purpose of this study was to determine the effects of relationship banking on the financial performance of SMEs. The paper attempted to establish the link between the constructs of relationship banking and SME performance. The study was guided by relationship lending, relationship monitoring, relationship risk sharing and bundle of products as independent variables while financial performance will be the dependent variable. The study used a quasi experimental design with population being the 620 SMEs who have a relationship banking arrangement with banks in Nairobi. The study used stratified sampling to pick a sample of 235. The population of interest will be the CEOs of the respective companies. The basis of stratification is the sectors in which the SMEs operate in. The study will use a questionnaire to collect data. The questionnaire will have both open and close ended questions. A pilot study will be conducted to test reliability and validity of questionnaire. The data was analyzed using descriptive statistics. Regression analysis was employed to test if there is a relationship between the dependent and the independent variable. The study found evidence that relationship banking positively impacts on financial performance of SMEs. Specifically, the study established that each component of relationship banking in this study i.e relationship lending, monitoring, bundle of products and risk sharing positively affects financial performance.

Keywords: relationship banking, SMEs, financial performance, entrepreneurial orientation

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Authors: Alison Brown

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Through stories, children make sense of their world, see themselves through the eyes of another, and process emotions and lived experiences in a non-threatening and indirect manner. Building on research around the use of narrative techniques with adults and families, this research looked directly at the use of narratives as a therapeutic technique with children in counseling. Based on individual therapy sessions with children over a six-year period, this work of collective case studies tells the story of a practice incorporating children’s narratives, of children’s experiences in writing and sharing their narratives, and of the clinical impact of the use of narratives with children. Not all stories were narratives of success or happiness. Children documented their fears and anger as well as their achievements and hope for the future. What emerged through this study was an awareness of recurring themes in the way children responded to the narrative process and in the benefits and limitations of story writing with children. Consistent with previous studies focusing on narrative work with adults and families, the use of narratives with children provided opportunities for healing, acceptance, developing greater understanding, externalizing, and re-authoring a preferred future. In terms of the children’s experiences in writing and sharing their narratives, consistent themes emerged again, with many children finding the experience cathartic and liberating, empowering and hopeful, but most importantly, an opportunity that allowed them to feel and understand that they were not alone. Whilst a small collection of case studies tells the stories of a limited number of children, it is hoped that this research provides both a model and inspiration for others to explore similar uses of narratives with children. As a greater number of children’s narratives are created, the potential to share and benefit from the many rich stories and experiences of other children becomes more of a reality. Across cultures, economic and social settings, rural and urban environments, and varying family structures, it is important that we hear the voices of our children – ‘In their own words’.

Keywords: narrative therapy children counselling, social, emotional, zone of proximal development, scaffolding

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Authors: Timur Zhukov, Yuko Yamashita

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Music as a product of hedonic consumption has been researched at least since the early 20th century, but little light has been shed on how language affects its consumption process. At the intersection of music consumption, language impact, and consumer behavior, this research explores the influence of language on music consumption in Japan. Its aim is to clarify how listening to music in different languages affects the listener’s purchase intention and sharing intention by conducting a survey where respondents listen to three versions of the same song in different languages in random order. It uses an existing framework that views the flow of music consumption as a combination of responses (emotional response, sensory response, imaginal response, analytical responses) affecting the experiential response, which then affects the overall affective response, followed by the need to reexperience and lastly the purchase intention. In this research, the sharing intention has been added to the model to better fit the modern consumption model (e.g., AISAS). This research shows how positive and negative emotions and imaginal and analytical responses change depending on the language and what impact it has on consumer behavior. It concludes by proposing how modern music businesses can learn from the language differences and cater to the needs of the audiences who speak different languages.

Keywords: AISAS, consumer behavior, first language, music consumption, second language

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Authors: William Li

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Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

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Authors: Nada Mouchfiq, Ahmed Habbani, Chaimae Benjbara

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The security aspect of the IoT occupies a place of great importance especially after the evolution that has known this field lastly because it must take into account the transformations and the new applications .Blockchain is a new technology dedicated to the data sharing. However, this does not work the same way in the different systems with different operating principles. This article will discuss network security using the Blockchain to facilitate the sending of messages and information, enabling the use of new processes and enabling autonomous coordination of devices. To do this, we will discuss proposed solutions to ensure a high level of security in these networks in the work of other researchers. Finally, our article will propose a method of security more adapted to our needs as a team working in the ad hoc networks, this method is based on the principle of the Blockchain and that we named ”MPR Blockchain”.

Keywords: Ad hocs networks, blockchain, MPR, security

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Authors: F. Lhafiane, A. Elbyed, M. Bouchoum

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Reverse Logistics (RL) Process is considered as complex and dynamic network that involves many stakeholders such as: suppliers, manufactures, warehouse, retails, and costumers, this complexity is inherent in such process due to lack of perfect knowledge or conflicting information. Ontologies, on the other hand, can be considered as an approach to overcome the problem of sharing knowledge and communication among the various reverse logistics partners. In this paper, we propose a semantic representation based on hybrid architecture for building the Ontologies in an ascendant way, this method facilitates the semantic reconciliation between the heterogeneous information systems (ICT) that support reverse logistics Processes and product data.

Keywords: Reverse Logistics, information management, heterogeneity, ontologies, semantic web

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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Authors: Hexiong Liu

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Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.

Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy

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Authors: Hatem Hajri, Mohamed-Cherif Rahal

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Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth.

Keywords: ground truth, Hungarian algorithm, lidar Radar data fusion, global nearest neighbor filter

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Authors: Shahadat Uddin, Md Ekramul Hossain, Arif Khan

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The collaboration among physicians during episodes of care for a hospitalised patient has a significant contribution towards effective health outcome. This research aims at improving this health outcome by analysing the attributes of patient-sharing physician collaboration network (PCN) on hospital data. To accomplish this goal, we present a research framework that explores the impact of several types of attributes (such as clique and clan) of PCN on hospitalisation cost and hospital length of stay. We use electronic health insurance claim dataset to construct and explore PCNs. Each PCN is categorised as ‘low’ and ‘high’ in terms of hospitalisation cost and length of stay. The results from the proposed model show that the clique and clan of PCNs affect the hospitalisation cost and length of stay. The clique and clan of PCNs show the difference between ‘low’ and ‘high’ PCNs in terms of hospitalisation cost and length of stay. The findings and insights from this research can potentially help the healthcare stakeholders to better formulate the policy in order to improve quality of care while reducing cost.

Keywords: clique, clan, electronic health records, physician collaboration

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Authors: Ibrahim Ilker Ozyigit, Ertugrul Filiz, Ilhan Dogan

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An in silico analysis of Brachypodium distachyon, Triticum aestivum, Festuca arundinacea, Lolium perenne, Hordeum vulgare subsp. vulgare of the Pooideaea was performed based on complete chloroplast genomes including rbcL coding and trnH-psbA intergenic spacer regions alone to compare phylogenetic resolving power. Neighbor-joining, Minimum Evolution, and Unweighted Pair Group Method with arithmetic mean methods were used to reconstruct phylogenies with the highest bootstrap supported the obtained data from whole chloroplast genome sequence. The highest and lowest values from nucleotide diversity (π) analysis were found to be 0.315813 and 0.043495 in rbcL coding region in chloroplast genome and complete chloroplast genome, respectively. The highest transition/transversion bias (R) value was recorded as 1.384 in complete chloroplast genomes. F. arudinacea-L. perenne clade was uncovered in all phylogenies. Sequences of rbcL and trnH-psbA regions were not able to resolve the Pooideae phylogenies due to lack of genetic variation.

Keywords: chloroplast DNA, Pooideae, phylogenetic analysis, rbcL, trnH-psbA

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Alessandra Rossodivita, Alexei Tikhomirov, Andrey Trufanov, Nikolay Kinash, Olga Berestneva, Svetlana Nikitina, Fabio Casati, Alessandro Visconti, Tommaso Saporito

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It is well known that world and national societies are exposed to diverse threats: anthropogenic, technological, and natural. Anthropogenic ones are of greater risks and, thus, attract special interest to researchers within wide spectrum of disciplines in efforts to lower the pertinent risks. Some researchers showed by means of multilayered, complex network models how media promotes the prevention of disease spread. To go further, not only are mass-media sources included in scope the paper suggests but also personificated social bots (socbots) linked according to reflexive theory. The novel scope considers information spread over conscious and unconscious agents while counteracting both natural and man-made threats, i.e., infections and terrorist hazards. Contrary to numerous publications on misinformation disseminated by ‘bad’ bots within social networks, this study focuses on ‘good’ bots, which should be mobilized to counter the former ones. These social bots deployed mixture with real social actors that are engaged in concerted actions at spreading, receiving and analyzing information. All the contemporary complex network platforms (multiplexes, interdependent networks, combined stem networks et al.) are comprised to describe and test socbots activities within competing information sharing tools, namely mass-media hubs, social networks, messengers, and e-mail at all phases of disasters. The scope and concomitant techniques present evidence that embedding such socbots into information sharing process crucially change the network topology of actor interactions. The change might improve or impair robustness of social network environment: it depends on who and how controls the socbots. It is demonstrated that the topological approach elucidates techno-social processes within the field and outline the roadmap to a safer world.

Keywords: complex network platform, counterterrorism, information sharing topology, social bots

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Authors: Pieter Conradie, M. Marina Moller

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Web 2.0 Internet-based technologies have intruded all aspects of human life. Presently, this phenomenon is especially evident in the educational context, with increased disruptive Web 2.0 technology infusions dramatically changing educational practice. The most prominent of these Web 2.0 intrusions can be identified as Massive Open Online Courses (Coursera, EdX), video and photo sharing sites (Youtube, Flickr, Instagram), and Web 2.0 online tools utilize to create Personal Learning Environments (PLEs) (Symbaloo (aggregator), Delicious (social bookmarking), PBWorks (collaboration), Google+ (social networks), Wordspress (blogs), Wikispaces (wiki)). These Web 2.0 technologies have supported the realignment from a teacher-based pedagogy (didactic presentation) to a learner-based pedagogy (problem-based learning, project-based learning, blended learning), allowing greater learner autonomy. No longer is the educator the source of knowledge. Instead the educator has become the facilitator and mediator of the learner, involved in developing learner competencies to support life-long learning (continuous learning) in the 21st century. In this study, the self-regulated learning skills of thirty first-year university learners were explored by utilizing the Online Self-regulated Learning Questionnaire. Implementing an action research method, an intervention was affected towards improving the self-regulation skill set of the participants. Statistical significant results were obtained with increased self-regulated learning proficiency, positively impacting learner performance. Goal setting, time management, environment structuring, help seeking, task (learning) strategies and self-evaluation skills were confirmed as determinants of improved learner success.

Keywords: andragogy, online self-regulated learning questionnaire, self-regulated learning, web 2.0

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Authors: Samipraj Mishra

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Despite the successful implementation of community forestry program, a number of pros and cons have been raised on Terai community forestry in the case of lowland locally called Terai region of Nepal, which is climatically belongs to tropical humid and possessed high quality forests in terms of ecology and economy. The study aims to investigate the local pricing strategy of forest products and its impacts on equitable forest benefit sharing, collection of community fund and carrying out livelihood improvement activities. The study was carried out on six community forests revealed that local people have substantially benefited from the community forests. However, being the region is heterogeneous by socio-economic conditions and forest resources have higher economical potential, the decision of low pricing strategy made by the local people have created inequality problems while sharing the forest benefits, and poorly contributed to community fund collection and consequently carrying out limited activities of livelihood improvement. The paper argued that the decision of low pricing strategy of forest products is counter-productive to promote the equitable benefit sharing in the areas of heterogeneous socio-economic conditions with high value forests. The low pricing strategy has been increasing accessibility of better off households at higher rate than poor; as such households always have higher affording capacity. It is also defective to increase the community fund and carry out activities of livelihood improvement effectively. The study concluded that unilateral decentralized forest policy and decision-making autonomy to the local people seems questionable unless their decision-making capacities are enriched sufficiently. Therefore, it is recommended that empowerment of decision-making capacity of local people and their respective institutions together with policy and program formulation are prerequisite for efficient and equitable community forest management and its long-term sustainability.

Keywords: community forest, livelihood, socio-economy, pricing system, Nepal

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Authors: Seyyed Mohammad Hasheminia, Heoung Jae Chun, Jong Chan Park, Hong Suk Chang

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Composite joints have been getting attention recently due to their high specific mechanical strength to weight ratio that is crucial for structures such as aircrafts and automobiles. In this study on hybrid joints, quasi-static experiments and finite element analysis were performed to investigate the failure mechanism of hybrid composite joint with respect to the joint properties such as the adhesive material, clamping force, and joint geometry. The outcomes demonstrated that the stiffness of the adhesive is the most imperative design parameter. In this investigation, two adhesives with various stiffness values were utilized. Regarding the joints utilizing the adhesive with the lower stiffness modulus, it was observed that the load was exchanged promptly through the adhesive since it was shared more proficiently between the bolt and adhesive. This phenomenon permitted the hybrid joints with low-modulus adhesive to support more prominent loads before failure when contrasted with the joints that utilize the stiffer adhesive. In the next step, the stress share between the bond and bolt as a function of various design parameters was studied using a finite element model in which it was understood that the geometrical parameters such as joint overlap and width have a significant influence on the load sharing between the bolt and the adhesive.

Keywords: composite joints, composite materials, hybrid joints, single-lap joint

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Authors: Ahmed Elzainy, Abir El Sadik, Waleed Al Abdulmonem, Ahmad Alamro, Homaidan Al-Homaidan

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Problem-based learning (PBL) is an educational modality which stimulates critical and creative thinking. PBL has been practiced in the college of medicine, Qassim University, Saudi Arabia, since the 2002s with offline face to face activities. Therefore, crucial technological changes in paperless work were needed. The aim of the present study was to design and implement the digitalization of the PBL activities and to evaluate its impact on students' and tutors’ performance. This approach promoted the involvement of all stakeholders after their awareness of the techniques of using online tools. IT support, learning resources facilities, and required multimedia were prepared. Students’ and staff perception surveys reflected their satisfaction with these remarkable changes. The students were interested in the new digitalized materials and educational design, which facilitated the conduction of PBL sessions and provided sufficient time for discussion and peer sharing of knowledge. It enhanced the tutors for supervision and tracking students’ activities on the Learning Management System. It could be concluded that introducing of digitalization of the PBL activities promoted the students’ performance, engagement and enabled a better evaluation of PBL materials and getting prompt students as well as staff feedback. These positive findings encouraged the college to implement the digitalization approach in other educational activities, such as Team-Based Learning, as an additional opportunity for further development.

Keywords: multimedia in PBL, online PBL, problem-based learning, PBL digitalization

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Authors: Noawanit Songkram

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This paper is a report on the findings of a study conducted on e–learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education. The methodology of this study was R&D research. The subjects were 18 undergraduate students in Faculty of Education, Chulalongkorn University in the academic year of 2013. The research instruments were a problem solving ability assessment, a team learning evaluation form, and an attitude questionnaire. The data was statistically analyzed using mean, standard deviation, one way repeated measure ANOVA and t–test. The research findings discovered the e –learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education consisted of five components:(1) online collaborative tools, (2) active learning activities, (3) creative thinking, (4) knowledge sharing process, (5) evaluation and nine processes which were (1) preparing in group working, (2) identifying interested topic, (3) analysing interested topic, (4) collecting data, (5) concluding idea (6) proposing idea, (7) creating workings, (8) workings evaluation, (9) sharing knowledge from empirical experience.

Keywords: e-learning system, problem solving ability, team leaning, virtual learning environment

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Authors: John M. Lyne, K. Andrea Scott

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In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

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Authors: Balázs Kulcsár

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Few people now doubt the future of the global energy transition. The only question is whether the pace of renewables' penetration will be sufficient to compete with the rate of warming. Dynamic changes are also taking place in the Hungarian electricity system. In addition to nuclear power, which provides the basic electricity supply, the most dynamic is solar power, which is largely small-scale and residential. The emergence of solar power is outlining the emergence of energy production and supply fabric of municipalities. This creates the potential for over-producing municipalities to supply the electricity needs of neighboring settlements with lower production beyond renewables. By taking advantage of this energy sharing, electricity supply based on pure renewables can be achieved more quickly.

Keywords: renewable energy, energy geography, self-sufficiency, energy transition

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Authors: Hamed Homaei, Seyed Reza Hejazi, Iraj Mahdavi

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Return policy (RP) is a strategy for supply chain coordination, whereby the retailer returns the unsold products to the manufacturer or the manufacturer offers a credit on unsold products to the retailer at the end of selling season. Early order commitment (EOC) is another efficient mechanism for channel coordination wherein the retailer commits to purchasing from the manufacturer a fixed order quantity a few periods in advance of the regular delivery lead time. This paper studies the coordination issue of a two-level supply chain with one retailer and one manufacturer through combining two mentioned contracts. The main purpose of this paper is to present an analytical model to show that how the contract which is created by combining RP and EOC can improve supply chain performance. Numerical analyses show that the supply chain coordination through mentioned contract in compare with EOC mechanism, can improve supply chain performance under certain ranges of model parameters. Furthermore, some numerical analyses are done to determine the best buyback price in order to achieve maximum cost saving in the supply chain. Finally, a revenue sharing scheme is presented in order to achieve a win-win condition in the supply chain.

Keywords: supply chain coordination, early order commitment, return policy, revenue sharing

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Authors: Chrysoula Mangafa

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Autism is a lifelong condition that affects how individuals interact with others and make sense of the world around them. The two core difficulties associated with autism are difficulties in social communication and interaction, and the manifestation of restricted, repetitive patterns of behaviour. However, children with autism may also have many talents and special interests among which is their affinity with digital technologies. Despite the increasing use of mobile tablets in schools and homes and the children’s motivation in using them, there is limited guidance on how to use the tablets to teach children with autism-specific skills. This study aims to fill this gap in knowledge by providing guidelines about the ways in which iPads and other tablets can be used by parents/carers and their child at home to support the development of social communication skills. Semi-structured interviews with 10 parents of primary school aged children with autism were conducted with the aim to explore their experiences in using mobile devices, such as iPads and Android tablets, and social activities with their children to create opportunities for social communication development. The interview involved questions about the parents’ knowledge and experience in autism, their understanding of social communication skills, the use of technology at home, and their links with the child’s school. Qualitative analysis of the interviews showed that parents used a variety of strategies to boost their child’s social communication skills. Among these strategies were a) the use of communication symbols, b) the use of the child’s special interest as motivator to gain their attention, and c) allowing time to their child to respond. It was also found that parents engaged their child in joint activities such as cooking, role play and creating social stories together on the device. Seven out of ten parents mentioned that the tablet is a motivating tool that can be used to teach social communication skills, nonetheless all parents raised concerns over screen time and their child’s sharing difficulties. The need for training and advice as well as building stronger links with their child’s school was highlighted. In particular, it was mentioned that recommendations would be welcomed about how parents can address their child’s difficulties in initiating or sustaining a conversation, taking turns and sharing, understanding other people’s feelings and facial expressions, and showing interest to other people. The findings of this study resulted in the development of a parents’ guide based on evidence-based practice and the participants’ experiences and concerns. The proposed guidelines aim to urge parents to feel more confident in using the tablet with their child in more collaborative ways. In particular, the guide offers recommendations about how to develop verbal and non-verbal communication, gives examples of tablet-based activities to interact and create things together, as well as it offers suggestions on how to provide a worry-free tablet experience and how to connect with the school.

Keywords: families, perception and cognition in early development, school-age intervention, social development

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Authors: Hanqing Yang, Xiang Meng, Qi Li, Weirong Chen

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The SOC (state of charge) based droop control has limitations on the load power sharing among different energy storage units, due to the line impedance. In this paper, a distributed control strategy for dispersed energy storage units in the DC microgrid based on discrete consensus is proposed. Firstly, a sparse information communication network is built. Thus, local controllers can communicate with its neighbors using voltage, current and SOC information. An average voltage of grid can be evaluated to compensate voltage offset by droop control, and an objective virtual resistance fulfilling above requirement can be dynamically calculated to distribute load power according to the SOC of the energy storage units. Then, the stability of the whole system and influence of communication delay are analyzed. It can be concluded that this control strategy can improve the robustness and flexibility, because of having no center controller. Finally, a model of DC microgrid with dispersed energy storage units and loads is built, the discrete distributed algorithm is established and communication protocol is developed. The co-simulation between Matlab/Simulink and JADE (Java agent development framework) has verified the effectiveness of proposed control strategy.

Keywords: dispersed energy storage units, discrete consensus algorithm, state of charge, communication delay

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Authors: Muhammad Ali Khan

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Although most Muslims are aware that Riba is a great sin in Islamic Shariah, they still do not find themselves inclined toward Islamic banking for their financial needs/activities/requirements. The main purpose of this research work is to analyse the general trend of people's views and miss conceptions among them regarding Islamic Banking and therefore suggest promoting Islamic banking. Scholars believe that Islamic finance is more stable than conventional banking because of the nature of its banking practices, which are based on real assets or partnerships. This is why Islamic banking is growing fastly worldwide, particularly in the wake of global financial crisis. Even though the scope of Islamic banking is expanding on a daily basis yet, it is not gaining the popularity it deserves. Islam declares war against Allah and his last messenger Hazrat Muhammad (PBUM) as it is a great sin and strictly forbids all interest-based transactions. Holy Quran revealed, O you who believe, do not eat up the amounts acquired through Riba (interest), doubled and multiplied. Fear Allah, so that you may be successful. Therefore a, true Muslim who believe in Judgement day always make all efforts in their life to avoid gambling and other speculative activities like Riba for themselves and their loved ones. If a Muslim does not fight against Riba to protect himself and his family, then his faith is meaningless. Allah issues warnings at numerous places in the holy Quran regarding Riba and its sin. Thus, Islamic banking is an alternative banking system where banking transactions are based on Islamic principles. The major component of Islamic Banking is Profit and loss sharing (PLS), as well as ensuring economic justice and equity.

Keywords: Islamic banking, Riba, interest, financial crises

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Authors: Supannee Chaiumporn

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This article is to introduce the meaning and form of social quality moving process as indicated by members of two suburb communities with different social and cultural contexts. The form of social quality moving process is very significant for the community and social development, because it will make the people living together with sustainable happiness. This is a qualitative study involving 30 key-informants from two suburb communities. Data were collected though key-informant interviews, and analyzed using logical content description and descriptive statistics. This research found that on the social quality component, the people in both communities stressed the procedure for social quality-making. This includes the generousness, sharing and assisting among people in the communities. These practices helped making people to live together with sustainable happiness. Living as a family or appear to be a family is the major social characteristic of these two communities. This research also found that form of social quality’s moving process of both communities stress relation of human and nature; “nature overpower humans” paradigm and influence of religious doctrine that emphasizes relations among humans. Both criteria make the form of social’s moving process simple, adaptive to nature and caring for opinion sharing and understanding among each other before action. This form of social quality’s moving process is composed of 4 steps; (1) awareness building, (2) motivation to change, (3) participation from every party concerned (4) self-reliance.

Keywords: social quality, form of social quality moving process, happiness, different social and cultural context

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Authors: F. Varga, Z. Liber, J. Jakše, A. Turudić, Z. Šatović, I. Radosavljević, N. Jeran, M. Grdiša

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Dalmatian pyrethrum (Tanacetum cinerariifolium (Trevir.) Sch. Bip.; Asteraceae), a source of the commercially dominant plant insecticide pyrethrin, is a species endemic to the eastern Adriatic. Genetic diversity of T. cinerariifolium was previously studied using amplified fragment length polymorphism (AFLP) markers. However, microsatellite markers (single sequence repeats - SSRs) are more informative because they are codominant, highly polymorphic, locus-specific, and more reproducible, and thus are most often used to assess the genetic diversity of plant species. Dalmatian pyrethrum is an outcrossing diploid (2n = 18) whose large genome size and high repeatability have prevented the success of the traditional approach to SSR markers development. The advent of next-generation sequencing combined with the specifically developed method recently enabled the development of, to the author's best knowledge, the first set of SSRs for genomic characterization of Dalmatian pyrethrum, which is essential from the perspective of plant genetic resources conservation. To evaluate the effectiveness of the developed SSR markers in genetic differentiation of Dalmatian pyrethrum populations, a preliminary genetic diversity study was conducted on 30 individuals from three geographically distinct natural populations in Croatia (northern Adriatic island of Mali Lošinj, southern Adriatic island of Čiovo, and Mount Biokovo) based on 12 SSR loci. Analysis of molecular variance (AMOVA) by randomization test with 10,000 permutations was performed in Arlequin 3.5. The average number of alleles per locus, observed and expected heterozygosity, probability of deviations from Hardy-Weinberg equilibrium, and inbreeding coefficient was calculated using GENEPOP 4.4. Genetic distance based on the proportion of common alleles (DPSA) was calculated using MICROSAT. Cluster analysis using the neighbor-joining method with 1,000 bootstraps was performed with PHYLIP to generate a dendrogram. The results of the AMOVA analysis showed that the total SSR diversity was 23% within and 77% between the three populations. A slight deviation from Hardy-Weinberg equilibrium was observed in the Mali Lošinj population. Allele richness ranged from 2.92 to 3.92, with the highest number of private alleles observed in the Mali Lošinj population (17). The average observed DPSA between 30 individuals was 0.557. The highest DPSA (0.875) was observed between several pairs of Dalmatian pyrethrum individuals from the Mali Lošinj and Mt. Biokovo populations, and the lowest between two individuals from the Čiovo population. Neighbor-joining trees, based on DPSA, grouped individuals into clusters according to their population affiliation. The separation of Mt. Biokovo clade was supported (bootstrap value 58%), which is consistent with the previous study on AFLP markers, where isolated populations from Mt. Biokovo differed from the rest of the populations. The developed SSR markers are an effective tool for assessing the genetic diversity and structure of natural Dalmatian pyrethrum populations. These preliminary results are encouraging for a future comprehensive study with a larger sample size across the species' range. Combined with the biochemical data, these highly informative markers could help identify potential genotypes of interest for future development of breeding lines and cultivars that are both resistant to environmental stress and high in pyrethrins. Acknowledgment: This work has been supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.) insecticidal potential’- (PyrDiv) (IP-06-2016-9034) and by project KK.01.1.1.01.0005, Biodiversity and Molecular Plant Breeding, at the Centre of Excellence for Biodiversity and Molecular Plant Breeding (CoE CroP-BioDiv), Zagreb, Croatia.

Keywords: Asteraceae, genetic diversity, genomic SSRs, NGS, pyrethrum, Tanacetum cinerariifolium

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Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

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Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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Authors: Yuanxiang Miao

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This paper aims to examine the perceptual features of couchsurfers on a new hospitality tourism platform, the free homestay website couchsurfing. As a local host, the author has accepted 61 couchsurfers in Kyoto, Japan, and attempted to figure out couchsurfers' characteristics on perception by hosting them. Moreover, the methodology of this research is mainly based on in-depth interviews, by talking with couchsurfers, observing their behaviors, doing questionnaires, etc. Five dominant perceptual features of couchsurfers were identified: (1) Trusting; (2) Meeting; (3) Sharing; (4) Reciprocity; (5) Worries. The value of this research lies in figuring out a deeper understanding of the perceptual features of couchsurfers, and the author indeed hosted and stayed with 61 couchsurfers from 30 countries and areas over one year. Lastly, the author offers practical suggestions for future research.

Keywords: couchsurfing, depth interview, hospitality tourism, perceptual features

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Authors: Tasawar Ashraf

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The paper argues that the European Union’s securitized recourse to migration management which is lacking on the principle of solidarity has enhanced the sufferings of the asylum seekers by influencing the asylum policies of the non-EU states in the Eastern Mediterranean. The research critically analyses the development of the Turkish Asylum Policy and advocates that due to extraordinary burden of refugees and conceivable chances of getting EU membership, Turkey is developing its asylum policy essentially on the footprints of the EU. Such political and economic domination of the EU are resulting in the development of broader securitized migration zone in the EU and MENA region. Therefore, this paper critically analyses two interconnected issues, i.e., securitization of the migration in the EU and MENA region and the deficiency of the principle of solidarity and burden sharing in the European Agenda on Migration and how it reflects on Turkish asylum policy. This paper suggests that the EU must adopt a more generous resettle scheme ensuring the division of the refugee burden on all member and regional states by considering different political, social, and economic factors. Only such corporation can increase the pool of refugee hosting states by collaborating with the regional states to develop their asylum systems in accordance with international law.

Keywords: European Agenda on Migration (EAM), EU, Middle East and North Africa (MENA), Treaty on the Functioning of the European Union (TFEU)

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Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

Procedia PDF Downloads 219