Search results for: critical features
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8667

Search results for: critical features

5187 Examining Customer Acceptance of Chatbots in B2B Customer Service: A Factorial Survey

Authors: Kathrin Endres, Daniela Greven

Abstract:

Although chatbots are a widely known and established communication instrument in B2C customer services, B2B industries still hesitate to implement chatbots due to the incertitude of customer acceptance. While many studies examine the chatbot acceptance of B2C consumers, few studies are focusing on the B2B sector, where the customer is represented by a buying center consisting of several stakeholders. This study investigates the challenges of chatbot acceptance in B2B industries compared to challenges of chatbot acceptance from current B2C literature by interviewing experts from German chatbot vendors. The results show many similarities between the customer requirements of B2B customers and B2C consumers. Still, due to several stakeholders involved in the buying center, the features of the chatbot users are more diverse but obfuscated at the same time. Using a factorial survey, this study further examines the customer acceptance of varying situations of B2B chatbot designs based on the chatbot variables transparency, fault tolerance, complexity of products, value of products, as well as transfer to live chat service employees. The findings show that all variables influence the propensity to use the chatbot. The results contribute to a better understanding of how firms in B2B industries can design chatbots to advance their customer service and enhance customer satisfaction.

Keywords: chatbots, technology acceptance, B2B customer service, customer satisfaction

Procedia PDF Downloads 99
5186 Automatic Assignment of Geminate and Epenthetic Vowel for Amharic Text-to-Speech System

Authors: Tadesse Anberbir, Bankole Felix, Tomio Takara

Abstract:

In the development of a text-to-speech synthesizer, automatic derivation of correct pronunciation from the grapheme form of a text is a central problem. Particularly deriving phonological features which are not shown in orthography is challenging. In the Amharic language, geminates and epenthetic vowels are very crucial for proper pronunciation, but neither is shown in orthography. In this paper, to proposed and integrated a morphological analyzer into an Amharic Text-to-Speech system, mainly to predict geminates and epenthetic vowel positions and prepared a duration modeling method. Amharic Text-to-Speech system (AmhTTS) is a parametric and rule-based system that adopts a cepstral method and uses a source filter model for speech production and a Log Magnitude Approximation (LMA) filter as the vocal tract filter. The naturalness of the system after employing the duration modeling was evaluated by sentence listening test, and we achieved an average Mean Opinion Score (MOS) 3.4 (68%), which is moderate. By modeling the duration of geminates and controlling the locations of epenthetic vowel, we are able to synthesize good quality speech. Our system is mainly suitable to be customized for other Ethiopian languages with limited resources.

Keywords: amharic, gemination, Speech synthesis, morphology, epenthesis

Procedia PDF Downloads 69
5185 Myers-Briggs Type Index Personality Type Classification Based on an Individual’s Spotify Playlists

Authors: Sefik Can Karakaya, Ibrahim Demir

Abstract:

In this study, the relationship between musical preferences and personality traits has been investigated in terms of Spotify audio analysis features. The aim of this paper is to build such a classifier capable of segmenting people into their Myers-Briggs Type Index (MBTI) personality type based on their Spotify playlists. Music takes an important place in the lives of people all over the world and online music streaming platforms make it easier to reach musical contents. In this context, the motivation to build such a classifier is allowing people to gain access to their MBTI personality type and perhaps for more reliably and more quickly. For this purpose, logistic regression and deep neural networks have been selected for classifier and their performances are compared. In conclusion, it has been found that musical preferences differ statistically between personality traits, and evaluated models are able to distinguish personality types based on given musical data structure with over %60 accuracy rate.

Keywords: myers-briggs type indicator, music psychology, Spotify, behavioural user profiling, deep neural networks, logistic regression

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5184 Controlling the Degradation Rate of Biodegradable Mg Implant Using Magnetron-Sputtered (Zr-Nb) Thin Films

Authors: Somayeh Azizi, Mohammad Hossein Ehsani, Amir Zareidoost

Abstract:

In this research, a technique has been developed to reduce the corrosion rate of magnesium (Mg) metal by creating Zr-Nb thin film coatings. In this regard, thin-film coatings of niobium (Nb) zirconium (Zr) double alloy are applied on pure Mg specimens under different processes conditions, such as the change of the substrate temperature, substrate bias, and coating thickness using the magnetron sputtering method. Then, deposited coatings are analyzed in terms of surface features via field-emission scanning electron microscopy (FE-SEM), thin-layer X-ray diffraction (GI-XRD), energy-dispersive X-ray spectroscopy (EDS), atomic force microscopy (AFM), and corrosion tests. Also, nano-scratch tests were carried out to investigate the adhesion of the thin film. The results showed that the (Zr-Nb) thin films could control the degradation rate of Mg in the simulated body fluid (SBF). The nano-scratch studies depicted that the (Zr-Nb) thin films have a proper adhesion with the Mg substrate. Therefore, this technique could be used to enhance the corrosion resistance of bare Mg and could result in improving the performance of the biodegradable Mg implant for orthopedic applications.

Keywords: (Zr-Nb) thin film, magnetron sputtering, biodegradable Mg, degradation rate

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5183 The Assessment of the Comparative Efficiency of Reforms through the Integral Index of Transformation

Authors: Samson Davoyan, Ashot Davoyan, Ani Khachatryan

Abstract:

The indexes (Global Competitiveness Index, Economic Freedom Index, Human Development Index, etc.) developed by different international and non-government organizations in time and space express the quantitative and qualitative features of different fields of various reforms implemented in different countries. The main objective of our research is to develop new methodology that we will use to create integral index based on many indexes and that will include many areas of reforms. To achieve our aim we have used econometric methods (regression model for panel data method). The basis of our methodology is the development of the new integral index based on quantitative assessment of the change of two main parameters: the score of the countries by different indexes and the change of the ranks of countries for following two periods of time. As a result of the usage of methods for analyzes we have defined the indexes that are used to create the new integral index and the scales for each of them. Analyzing quantitatively and qualitatively analysis through the integral index for more than 100 countries for 2009-2014, we have defined comparative efficiency that helps to conclude in which directions countries have implemented reforms more effectively compared to others and in which direction reforms have implemented less efficiently.

Keywords: development, rank, reforms, comparative, index, economic, corruption, social, program

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5182 On the Application and Comparison of Two Geostatistics Methods in the Parameterisation Step to Calibrate Groundwater Model: Grid-Based Pilot Point and Head-Zonation Based Pilot Point Methods

Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

Abstract:

Properly selecting the most suitable and effective geostatistics method in the parameterization step of groundwater modeling is critical to attain a satisfactory model. In this paper, two geostatistics methods, i.e., Grid-Based Pilot Point (GB-PP) and Head-Zonation Based Pilot Point (HZB-PP) methods, were applied in an eogenetic karst catchment and compared using as model performances and computation time the criteria. Overall, the results show that appropriate selection of method is substantial in the parameterization of physically-based groundwater models, as it influences both the accuracy and simulation times. It was found that GB-PP method performed comparably superior to HZB-PP method. However, reflecting its model performances, HZB-PP method is promising for further application in groundwater modeling.

Keywords: groundwater model, geostatistics, pilot point, parameterization step

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5181 Multi-Class Text Classification Using Ensembles of Classifiers

Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

Abstract:

Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

Procedia PDF Downloads 217
5180 Use of Predictive Food Microbiology to Determine the Shelf-Life of Foods

Authors: Fatih Tarlak

Abstract:

Predictive microbiology can be considered as an important field in food microbiology in which it uses predictive models to describe the microbial growth in different food products. Predictive models estimate the growth of microorganisms quickly, efficiently, and in a cost-effective way as compared to traditional methods of enumeration, which are long-lasting, expensive, and time-consuming. The mathematical models used in predictive microbiology are mainly categorised as primary and secondary models. The primary models are the mathematical equations that define the growth data as a function of time under a constant environmental condition. The secondary models describe the effects of environmental factors, such as temperature, pH, and water activity (aw) on the parameters of the primary models, including the maximum specific growth rate and lag phase duration, which are the most critical growth kinetic parameters. The combination of primary and secondary models provides valuable information to set limits for the quantitative detection of the microbial spoilage and assess product shelf-life.

Keywords: shelf-life, growth model, predictive microbiology, simulation

Procedia PDF Downloads 188
5179 Towards an Adversary-Aware ML-Based Detector of Spam on Twitter Hashtags

Authors: Niddal Imam, Vassilios G. Vassilakis

Abstract:

After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

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5178 Hardware Error Analysis and Severity Characterization in Linux-Based Server Systems

Authors: Nikolaos Georgoulopoulos, Alkis Hatzopoulos, Konstantinos Karamitsios, Konstantinos Kotrotsios, Alexandros I. Metsai

Abstract:

In modern server systems, business critical applications run in different types of infrastructure, such as cloud systems, physical machines and virtualization. Often, due to high load and over time, various hardware faults occur in servers that translate to errors, resulting to malfunction or even server breakdown. CPU, RAM and hard drive (HDD) are the hardware parts that concern server administrators the most regarding errors. In this work, selected RAM, HDD and CPU errors, that have been observed or can be simulated in kernel ring buffer log files from two groups of Linux servers, are investigated. Moreover, a severity characterization is given for each error type. Better understanding of such errors can lead to more efficient analysis of kernel logs that are usually exploited for fault diagnosis and prediction. In addition, this work summarizes ways of simulating hardware errors in RAM and HDD, in order to test the error detection and correction mechanisms of a Linux server.

Keywords: hardware errors, Kernel logs, Linux servers, RAM, hard disk, CPU

Procedia PDF Downloads 142
5177 The Impact of Shared Culture, Trust and Information Exchange on Satisfaction and Financial Performance: Moderating Effects of Supply Chain Dependence

Authors: Hung Nguyen, Norma Harrison

Abstract:

This paper examines the role supply chain dependence as contingency factors which affect the effectiveness of different critical factors (in terms trust, information exchange and shared culture) in delivering supply chain satisfaction and financial performance. Using the data of 468 manufacturing firms in the Global Manufacturing Research Group, this study shows that supply chain dependence strengthens the positive relationship between shared culture & vision and supply chain satisfaction while dampens the relationship between trust and satisfaction. The study also demonstrates the direct positive effect of satisfaction on financial performance. Supply chain managers were advised to emphasize on the alignments of common understanding, codes, languages, common shared vision and similar cultures.

Keywords: information exchange, shared culture, satisfaction, supply chain dependence

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5176 Harnessing Renewable Energy as a Strategy to Combating Climate Change in Sub Saharan Africa

Authors: Gideon Nyuimbe Gasu

Abstract:

Sub Saharan Africa is at a critical point, experiencing rapid population growth, particularly in urban areas and young growing force. At the same time, the growing risk of catastrophic global climate change threatens to weaken food production system, increase intensity and frequency of drought, flood, and fires and undermine gains on development and poverty reduction. Although the region has the lowest per capital greenhouse gas emission level in the world, it will need to join global efforts to address climate change, including action to avoid significant increases and to encourage a green economy. Thus, there is a need for the concept of 'greening the economy' as was prescribed at Rio Summit of 1992. Renewable energy is one of the criterions to achieve this laudable goal of maintaining a green economy. There is need to address climate change while facilitating continued economic growth and social progress as energy today is critical to economic growth. Fossil fuels remain the major contributor of greenhouse gas emission. Thus, cleaner technologies such as carbon capture storage, renewable energy have emerged to be commercially competitive. This paper sets out to examine how to achieve a low carbon economy with minimal emission of carbon dioxide and other greenhouse gases which is one of the outcomes of implementing a green economy. Also, the paper examines the different renewable energy sources such as nuclear, wind, hydro, biofuel, and solar voltaic as a panacea to the looming climate change menace. Finally, the paper assesses the different renewable energy and energy efficiency as a propeller to generating new sources of income and jobs and in turn reduces carbon emission. The research shall engage qualitative, evaluative and comparative methods. The research will employ both primary and secondary sources of information. The primary sources of information shall be drawn from the sub Saharan African region and the global environmental organizations, energy legislation, policies and related industries and the judicial processes. The secondary sources will be made up of some books, journal articles, commentaries, discussions, observations, explanations, expositions, suggestions, prescriptions and other material sourced from the internet on renewable energy as a panacea to climate change. All information obtained from these sources will be subject to content analysis. The research result will show that the entire planet is warming as a result of the activities of mankind which is clear evidence that the current development is fundamentally unsustainable. Equally, the study will reveal that a low carbon development pathway in the sub Saharan African region should be embraced to minimize emission of greenhouse gases such as using renewable energy rather than coal, oil, and gas. The study concludes that until adequate strategies are devised towards the use of renewable energy the region will continue to add and worsen the current climate change menace and other adverse environmental conditions.

Keywords: carbon dioxide, climate change, legislation/law, renewable energy

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5175 Heart Ailment Prediction Using Machine Learning Methods

Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

Abstract:

The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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5174 Exploration of Graphite Nano-Particles as Anti-Wear Additive for Performance Enhancement of Oil

Authors: Manoj Kumar Gupta, Jayashree Bijwe

Abstract:

Additives in lubricating oils are the focus of research attention since the further reduction in friction and wear properties of oils would lead to the further saving of tribo-materials and energy apart from improving their efficiency. Remarkable tribo-performance enhancement is reported in the literature due to addition of particles of solid lubricants in lubricating oils; especially that of nano-sizes. In the present work graphite nano-particles (NPs) in various amounts (1, 2, 3 and 4 wt. %) were used to explore the possible anti-wear (AW) performance enhancement in Group III oil. Polyisobutylene succinimide (PIBSI- 1 wt. %) was used as a dispersant for dispersing these NPs and to enhance the stability of these nano-suspensions. It was observed that PIBSI inclusion enhanced the stability of oil almost by eight times. NPs in all amounts enhanced the AW performance of oil considerably. The optimum amount was three wt. %, which led to the highest enhancement under all loads. The extent of benefits, however, were dependent on load. At the lowest (392 N) and highest loads (784 N), the benefits were not profound. At moderate load (588 N), highest improvement (around 60 %) was recorded. The SEM and AFM studies were done on the worn ball surfaces to reveal the detailed features of films transferred and proved useful to correlate the wear performance of oils.

Keywords: dispersant, graphite, nano-lubricant, anti-wear additive

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5173 The Impact of Board Structure to the Roles of Board of Commissioners in Implementing Good Corporate Governance at Indonesian State-Owned Enterprises

Authors: Synthia Atas Sari, Engkos Achmad Kuncoro, Haryadi Sarjono

Abstract:

The purpose of this paper is to examine the impact of reward system which is determined by government over the work of Board of Commissioners in implementing good corporate governance in Indonesian state-owned enterprises. To do so, this study analyses the adequacy of the remuneration, the job attractiveness, and the board commitment and dedication with the remuneration system. Qualitative method used to examine the significant features and challenges to the government policy over the remuneration determination for the board of commissioners to their roles. Data are gathered through semi-structure in-depth interview to the 21 participants over 10 Indonesian stated-owned enterprises and written documents. Findings in this study indicate that government policies over the remuneration system is not effective to increase the performance of board of commissioners in implementing good corporate governance in Indonesian state-owned enterprises due to unattractiveness of the remuneration amount, demotivate active members, and conflict interest over members of the remuneration committee.

Keywords: reward system, board of commissioners, state-owned enterprises, good corporate governance

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5172 Graphene-Based Nanocomposites as Ecofriendly Antifouling Surfaces

Authors: Mohamed S. Selim, Nesreen A. Fatthallah, Shimaa A. Higazy, Zhifeng Hao, Xiang Chen

Abstract:

After the prohibition of tin-based fouling-prevention coatings in 2003, the researchers were directed toward eco-friendly coatings. Because of their nonstick, environmental, and economic benefits, foul-release nanocoatings have received a lot of attention. They use physical anti-adhesion terminology to deter any fouling attachment.Natural bioinspired surfaces have micro/nano-roughness and low surface free energy features, which may inspire the design of dynamic antifouling coatings. Graphene-based nanocomposite surfaces were designed to combat marine-fouling adhesion with ecological as well as eco-friendly effects rather than biocidal solutions. Polymer–graphenenanofiller hybrids are a novel class of composite materials in fouling-prevention applications. The controlled preparation of nanoscale orientation, arrangement, and direction along the composite building blocks would result in superior fouling prohibition. This work representsfoul-release nanocomposite top coats for marine coating applications with superhydrophobicity, surface inertness against fouling adherence, cost-effectiveness, and increased lifetime.

Keywords: foul-release nanocoatings, graphene-based nanocomposite, polymer, nanofillers

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5171 Predicting Customer Purchasing Behaviour in Retail Marketing: A Research for a Supermarket Chain

Authors: Sabri Serkan Güllüoğlu

Abstract:

Analysis can be defined as the process of gathering, recording and researching data related to products and services, in order to learn something. But for marketers, analyses are not only used for learning but also an essential and critical part of the business, because this allows companies to offer products or services which are focused and well targeted. Market analysis also identify market trends, demographics, customer’s buying habits and important information on the competition. Data mining is used instead of traditional research, because it extracts predictive information about customer and sales from large databases. In contrast to traditional research, data mining relies on information that is already available. Simply the goal is to improve the efficiency of supermarkets. In this study, the purpose is to find dependency on products. For instance, which items are bought together, using association rules in data mining. Moreover, this information will be used for improving the profitability of customers such as increasing shopping time and sales of fewer sold items.

Keywords: data mining, association rule mining, market basket analysis, purchasing

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5170 SnSₓ, Cu₂ZnSnS₄ Nanostructured Thin Layers for Thin-Film Solar Cells

Authors: Elena A. Outkina, Marina V. Meledina, Aliaksandr A. Khodin

Abstract:

Nanostructured thin films of SnSₓ, Cu₂ZnSnS₄ (CZTS) semiconductors were fabricated by chemical processing to produce thin-film photoactive layers for photocells as a prospective lowest-cost and environment-friendly alternative to Si, Cu(In, Ga)Se₂, and other traditional solar cells materials. To produce SnSₓ layers, the modified successive ionic layer adsorption and reaction (SILAR) technique were investigated, including successive cyclic dipping into Na₂S solution and SnCl₂, NaCl, triethanolamine solution. To fabricate CZTS layers, the cyclic dipping into CuSO₄ with ZnSO₄, SnCl₂, and Na₂S solutions was used with intermediate rinsing in distilled water. The nano-template aluminum/alumina substrate was used to control deposition processes. Micromorphology and optical characteristics of the fabricated layers have been investigated. Analysis of 2D-like layers deposition features using nano-template substrate is presented, including the effect of nanotips in a template on surface charge redistribution and transport.

Keywords: kesterite, nanotemplate, SILAR, solar cell, tin sulphide

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5169 Spatial Correlation of Channel State Information in Real Long Range Measurement

Authors: Ahmed Abdelghany, Bernard Uguen, Christophe Moy, Dominique Lemur

Abstract:

The Internet of Things (IoT) is developed to ensure monitoring and connectivity within different applications. Thus, it is critical to study the channel propagation characteristics in Low Power Wide Area Network (LPWAN), especially Long Range Wide Area Network (LoRaWAN). In this paper, an in-depth investigation of the reciprocity between the uplink and downlink Channel State Information (CSI) is done by performing an outdoor measurement campaign in the area of Campus Beaulieu in Rennes. At each different location, the CSI reciprocity is quantified using the Pearson Correlation Coefficient (PCC) which shows a very high linear correlation between the uplink and downlink CSI. This reciprocity feature could be utilized for the physical layer security between the node and the gateway. On the other hand, most of the CSI shapes from different locations are highly uncorrelated from each other. Hence, it can be anticipated that this could achieve significant localization gain by utilizing the frequency hopping in the LoRa systems by getting access to a wider band.

Keywords: IoT, LPWAN, LoRa, effective signal power, onsite measurement

Procedia PDF Downloads 149
5168 Green Marketing and Sustainable Development: Challenges and Opportunities

Authors: Guru P. S. Rangasamy

Abstract:

In the cutting edge period of globalization, it has turned into a test to keep the clients and also shoppers in overlay and even keep our regular habitat safe and that is the greatest need of the time. Purchasers are likewise mindful of the ecological issues like a dangerous atmospheric deviation and the effect of natural contamination. Green showcasing is a marvel which has created specific critical in the present day advertise and has risen as an imperative idea in India, as in different parts of the creating and created world and is viewed as an essential procedure of encouraging practical improvement. In this exploration paper, primary accentuation has been made of idea, need, and significance of green promoting. It investigates the principle issues in reception of green showcasing hones. The paper portrays the present situation of Indian market and investigates the difficulties and openings organizations have with green advertising, why organizations are receiving it and eventual fate of green promoting and presumes that green showcasing is something that will consistently develop in both practice and request.

Keywords: environmental pollution, green marketing, globalization, global warming, sustainable development

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5167 Interpreting Some Transformational Aspects of Pentatonicism in Post-tonal Chinese Music on Dual Interval Space

Authors: Man-Ching Yu

Abstract:

In Chinese music, pentatonic collection is central in constituting all the harmonic and melodic elements; most of the traditional Chinese musicians particularly emphasize the importance of the smoothness between pentatonic collections when one collection modulates to another collection, articulating the roles of the pentatonic common tones. On the contrary, in post-tonal Chinese music the central features of the pentatonic modulations tend to reflect a larger number of semitonal relationships with a lesser number of common tones. This paper offers an analytical account of the transformations between pentatonic collections that arise in post-tonal Chinese music by adopting the methodology of the Tonnetz, in particular, Dual Interval Space (DIS), to elaborate and reexamine pentatonicism by focusing on the transformations between pentatonic elements, especially semitonal motion and common tones. In the essay, various pentatonic passages will be analyzed by means of DIS for highlighting the transformation of the collections. It will be shown that the pentatonic collections that are in semitonal, third, and augmented fourth relationships exhibit the maximum number of semitonal shifts.

Keywords: tonnetz, pentatonicism, post-tonal Chinese music, dual interval space, transformation

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5166 Definition and Core Components of the Role-Partner Allocation Problem in Collaborative Networks

Authors: J. Andrade-Garda, A. Anguera, J. Ares-Casal, M. Hidalgo-Lorenzo, J.-A. Lara, D. Lizcano, S. Suárez-Garaboa

Abstract:

In the current constantly changing economic context, collaborative networks allow partners to undertake projects that would not be possible if attempted by them individually. These projects usually involve the performance of a group of tasks (named roles) that have to be distributed among the partners. Thus, an allocation/matching problem arises that will be referred to as Role-Partner Allocation problem. In real life this situation is addressed by negotiation between partners in order to reach ad hoc agreements. Besides taking a long time and being hard work, both historical evidence and economic analysis show that such approach is not recommended. Instead, the allocation process should be automated by means of a centralized matching scheme. However, as a preliminary step to start the search for such a matching mechanism (or even the development of a new one), the problem and its core components must be specified. To this end, this paper establishes (i) the definition of the problem and its constraints, (ii) the key features of the involved elements (i.e., roles and partners); and (iii) how to create preference lists both for roles and partners. Only this way it will be possible to conduct subsequent methodological research on the solution method.     

Keywords: collaborative network, matching, partner, preference list, role

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5165 Minimum Ratio of Flexural Reinforcement for High Strength Concrete Beams

Authors: Azad A. Mohammed, Dunyazad K. Assi, Alan S. Abdulrahman

Abstract:

Current ACI 318 Code provides two limits for minimum steel ratio for concrete beams. When concrete compressive strength be larger than 31 MPa the limit of √(fc')/4fy usually governs. In this paper shortcomings related to using this limit was fairly discussed and showed that the limit is based on 90% safety factor and was derived based on modulus of rupture equation suitable for concretes of compressive strength lower than 31 MPa. Accordingly, the limit is nor suitable and critical for concretes of higher compressive strength. An alternative equation was proposed for minimum steel ratio of rectangular beams and was found that the proposed limit is accurate for beams of wide range of concrete compressive strength. Shortcomings of the current ACI 318 Code equation and accuracy of the proposed equation were supported by test data obtained from testing six reinforced concrete beams.

Keywords: concrete beam, compressive strength, minimum steel ratio, modulus of rupture

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5164 Feature Extractions of EMG Signals during a Constant Workload Pedaling Exercise

Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

Abstract:

Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: electromyographic feature extraction, muscle status, pedaling exercise, relaxation segment

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5163 Learning for the Future: Flipping English Language Learning Classrooms for Future

Authors: Natarajan Hema, Tamilarasan Karunakaran

Abstract:

Technology is remodeling the process of teaching and learning. An inflection point is faced where technological interventions are rewiring learning process in formal classrooms. Employment depends on dynamic learning capability. Transforming the functionalities of teaching-learning-assessment through innovation is needed to modify the roles of teacher to enabler and learner to the dynamic learner. This makeover is vital for English language teaching where English is acquired as a skill, exercised as ability and get stabilized as a competence. This reshaping could be achieved through providing autonomy to participants of learning. This paper explores parameters and components aiding such a transformation. The differentiated responsibilities and other critical learning support systems are projected as viable options. New age teaching practices are studied for feasibilities to aid transformation and being put forth an inter-operable teaching-learning system for a learner-centric ELT classrooms. LOTUS model developed by the authors is also studied for its inclusiveness to promote skill acquisition.

Keywords: ELT methodology, communicative competence, skill acquisition , new age teaching

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5162 Between Riots and Protests: A Structural Approach to Urban Environmental Uprisings in China

Authors: Zi Zhu

Abstract:

The last decade has witnessed increasing urban environmental uprisings in China, as thousands of citizens swarmed into streets to express their deep concerns about the environmental threat and public health through various collective actions. The prevalent western approaches to collective actions, which usually treat urban riots and social movements as distinct phenomenon, have plagued an adequate analysis of the urban environmental uprisings in China. The increasing urban environmental contention can neither be categorized into riots nor social movements, as they carry the features of both: at first sight, they are spontaneous, disorganized and disruptive with an absence of observable mobilization process; however, unlike riots in the west, these collective actions conveyed explicit demand in a mostly non-destructive way rather than a pure expression of frustration. This article proposes a different approach to urban environmental uprisings in China which concerns the diminishing boundaries between riots and social movements and points to the underlying structural causes to the unique forms of urban environmental contention. Taking the urban anti-PX protests as examples, this article analyzes the societal and political structural environment faced by the Chinese environmental protesters and its influence on the origin and development of their contention.

Keywords: urban environmental uprisings, China, anti-PX protests, opportunity structure

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5161 Metamorphic Computer Virus Classification Using Hidden Markov Model

Authors: Babak Bashari Rad

Abstract:

A metamorphic computer virus uses different code transformation techniques to mutate its body in duplicated instances. Characteristics and function of new instances are mostly similar to their parents, but they cannot be easily detected by the majority of antivirus in market, as they depend on string signature-based detection techniques. The purpose of this research is to propose a Hidden Markov Model for classification of metamorphic viruses in executable files. In the proposed solution, portable executable files are inspected to extract the instructions opcodes needed for the examination of code. A Hidden Markov Model trained on portable executable files is employed to classify the metamorphic viruses of the same family. The proposed model is able to generate and recognize common statistical features of mutated code. The model has been evaluated by examining the model on a test data set. The performance of the model has been practically tested and evaluated based on False Positive Rate, Detection Rate and Overall Accuracy. The result showed an acceptable performance with high average of 99.7% Detection Rate.

Keywords: malware classification, computer virus classification, metamorphic virus, metamorphic malware, Hidden Markov Model

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5160 Fast Prediction Unit Partition Decision and Accelerating the Algorithm Using Cudafor Intra and Inter Prediction of HEVC

Authors: Qiang Zhang, Chun Yuan

Abstract:

Since the PU (Prediction Unit) decision process is the most time consuming part of the emerging HEVC (High Efficient Video Coding) standardin intra and inter frame coding, this paper proposes the fast PU decision algorithm and speed up the algorithm using CUDA (Compute Unified Device Architecture). In intra frame coding, the fast PU decision algorithm uses the texture features to skip intra-frame prediction or terminal the intra-frame prediction for smaller PU size. In inter frame coding of HEVC, the fast PU decision algorithm takes use of the similarity of its own two Nx2N size PU's motion vectors and the hierarchical structure of CU (Coding Unit) partition to skip some modes of PU partition, so as to reduce the motion estimation times. The accelerate algorithm using CUDA is based on the fast PU decision algorithm which uses the GPU to make the motion search and the gradient computation could be parallel computed. The proposed algorithm achieves up to 57% time saving compared to the HM 10.0 with little rate-distortion losses (0.043dB drop and 1.82% bitrate increase on average).

Keywords: HEVC, PU decision, inter prediction, intra prediction, CUDA, parallel

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5159 “A Built-In, Shockproof, Shit Detector”: Major Challenges and Peculiarities of Translating Ernest Hemingway’s Short Stories Into Georgian

Authors: Natia Kvachakidze

Abstract:

Translating fiction is a complicated and multidimensional issue. However, studying and analyzing literary translations is not less challenging. This becomes even more complex due to the existence of several alternative translations of one and the same literary work. However, this also makes the research process more interesting at the same time. The aim of the given work is to distinguish major obstacles and challenges translators come across while working on Ernest Hemingway’s short fiction, as well as to analyze certain peculiarities and characteristic features of some existing Georgian translations of the writer’s work (especially in the context of various alternative versions of some well-known short stories). Consequently, the focus is on studying how close these translations come to the form and the context of the original text in order to see if the linguistic and stylistic characteristics of the original author are preserved. Moreover, it is interesting not only to study the relevance of each translation to the original text but also to present a comparative analysis of some major peculiarities of the given translations, which are naturally characterized by certain strengths and weaknesses. The latter is at times inevitable, but in certain cases, there is room for improvement. The given work also attempts to humbly suggest certain ways of possible improvements of some translation inadequacies, as this can provide even more opportunities for deeper and detailed studies in the future.

Keywords: Hemingway, short fiction, translation, Georgian

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5158 Student Experiences in Online Doctoral Programs: A Critical Review of the Literature

Authors: Nicole A. Alford

Abstract:

The study of online graduate education started just 30 years ago, with the first online graduate program in the 1990s. Institutions are looking for ways to increase retention and support the needs of students with the rapid expansion of online higher education due to the global pandemic. Online education provides access and opportunities to those who otherwise would be unable to pursue an advanced degree for logistical reasons. Thus, the objective of the critical literature review is to survey current research of student experiences given the expanding role of online doctoral programs. The guiding research questions are: What are the personal, professional, and student life practices of graduate students who enrolled in a fully online university doctoral program or course? and How do graduate students who enrolled in a fully online doctoral program or course describe the factors that contributed to their continued study? The systematic literature review was conducted employing a variety of databases to locate articles using key Boolean terms and synonyms within three categories of the e-learning, doctoral education, and student perspectives. Inclusion criteria for the literature review consisted of empirical peer-reviewed studies with original data sources that focused on doctoral programs and courses within a fully online environment and centered around student experiences. A total of 16 articles were selected based on the inclusion criteria and systemically analyzed through coding using the Boote and Beile criteria. Major findings suggest that doctoral students face stressors related to social and emotional wellbeing in the online environment. A lack of social connection, isolation, and burnout were the main challenges experienced by students. Students found support from their colleagues, advisors, and faculty to persist. Communities and cohorts of online doctoral students were found to guard against these challenges. Moreover, in the methods section of the articles, there was a lack of specificity related to student demographics, general student information, and insufficient detail about the online doctoral program. Additionally, descriptions regarding the experiences of cohorts and communities in the online environment were vague and not easily replicable with the given details. This literature review reveals that doctoral students face social and emotional challenges related to isolation and the rigor of the academic process and lean on others for support to continue in their studies. Given the lack of current knowledge about online doctoral students, it proves to be a challenge to identify effective practices and create high-retention doctoral programs in online environments. The paucity of information combined with the dramatic transition to e-learning due to the global pandemic can provide a perfect storm for attrition in these programs. Several higher education institutions have transitioned graduate studies online, thus providing an opportunity for further exploration. Given the new necessity of online learning, this work provides insight into examining current practices in online doctoral programs that have moved to this modality during the pandemic. The significance of the literature review provides a springboard for research into online doctoral programs as the solution to continue advanced education amongst a global pandemic.

Keywords: e-learning, experiences, higher education, literature review

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