Search results for: poison information services

Authors: Aishrith Rao

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COVID 19 is a pandemic which has resulted in thousands of deaths around the world and a huge impact on the global economy. Testing is a huge issue as the test kits have limited availability and are expensive to manufacture. Using deep learning methods on radiology images in the detection of the coronavirus as these images contain information about the spread of the virus in the lungs is extremely economical and time-saving as it can be used in areas with a lack of testing facilities. This paper focuses on binary classification and multi-class classification of COVID 19 and other diseases such as pneumonia, tuberculosis, etc. Different deep learning methods such as VGG-19, COVID-Net, ResNET+ SVM, Deep CNN, DarkCovidnet, etc., have been used, and their accuracy has been compared using the Chest X-Ray dataset.

Keywords: deep learning, computer vision, radiology, COVID-19, ResNet, VGG-19, deep neural networks

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Authors: S. M. Yasir Arafat

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Driving models are needed by many researchers to improve traffic safety and to advance autonomous vehicle design. To be most useful, a driving model must state specifically what information is needed and how it is processed. So we developed an “Obstacle Avoidance and Detection Autonomous Car” based on sensor application. The ever increasing technological demands of today call for very complex systems, which in turn require highly sophisticated controllers to ensure that high performance can be achieved and maintained under adverse conditions. Based on a developed model of brakes operation, the controller of braking system operation has been designed. It has a task to enable solution to the problem of the better controlling of braking system operation in a more accurate way then it was the case now a day.

Keywords: automobile, obstacle, safety, sensing

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Authors: Ilgin Gökaşar, Saman Ghaffarian

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The need for fast processed big data of transportation ridership (eg., smartcard data) and traffic operation (e.g., traffic detectors data) which requires a lot of computational power is incontrovertible in Intelligent Transportation Systems. Nowadays cloud computing is one of the important subjects and popular information technology solution for data processing. It enables users to process enormous measure of data without having their own particular computing power. Thus, it can also be a good selection for transportation big data processing as well. This paper intends to examine how the cloud computing can enhance transportation big data process with contrasting its advantages and disadvantages, and discussing cloud computing features.

Keywords: big data, cloud computing, Intelligent Transportation Systems, ITS, traffic data processing

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Authors: Priscila A. Bernardes, Marcos E. Buzanskas, Luciana C. A. Regitano, Ricardo V. Ventura, Danisio P. Munari

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The best linear unbiased predictor (BLUP) is a method commonly used in genetic evaluations of breeding programs. However, this approach can lead to higher inbreeding coefficients in the population due to the intensive use of few bulls with higher genetic potential, usually presenting some degree of relatedness. High levels of inbreeding are associated to low genetic viability, fertility, and performance for some economically important traits and therefore, should be constantly monitored. Unreliable pedigree data can also lead to misleading results. Genomic information (i.e., single nucleotide polymorphism – SNP) is a useful tool to estimate the inbreeding coefficient. Runs of homozygosity have been used to evaluate homozygous segments inherited due to direct or collateral inbreeding and allows inferring population selection history. This study aimed to evaluate runs of homozygosity (ROH) and inbreeding in a population of Nelore beef cattle. A total of 814 animals were genotyped with the Illumina BovineHD BeadChip and the quality control was carried out excluding SNPs located in non-autosomal regions, with unknown position, with a p-value in the Hardy-Weinberg equilibrium lower than 10⁻⁵, call rate lower than 0.98 and samples with the call rate lower than 0.90. After the quality control, 809 animals and 509,107 SNPs remained for analyses. For the ROH analysis, PLINK software was used considering segments with at least 50 SNPs with a minimum length of 1Mb in each animal. The inbreeding coefficient was calculated using the ratio between the sum of all ROH sizes and the size of the whole genome (2,548,724kb). A total of 25.711 ROH were observed, presenting mean, median, minimum, and maximum length of 3.34Mb, 2Mb, 1Mb, and 80.8Mb, respectively. The number of SNPs present in ROH segments varied from 50 to 14.954. The longest ROH length was observed in one animal, which presented a length of 634Mb (24.88% of the genome). Four bulls were among the 10 animals with the longest extension of ROH, presenting 11% of ROH with length higher than 10Mb. Segments longer than 10Mb indicate recent inbreeding. Therefore, the results indicate an intensive use of few sires in the studied data. The distribution of ROH along the chromosomes showed that chromosomes 5 and 6 presented a large number of segments when compared to other chromosomes. The mean, median, minimum, and maximum inbreeding coefficients were 5.84%, 5.40%, 0.00%, and 24.88%, respectively. Although the mean inbreeding was considered low, the ROH indicates a recent and intensive use of few sires, which should be avoided for the genetic progress of breed.

Keywords: autozygosity, Bos taurus indicus, genomic information, single nucleotide polymorphism

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Authors: Sawsen Khlifa, Chiheb AMeur Abid, Belhassan Zouari

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Modular verification approaches have been widely attempted to cope with the well known state explosion problem. This paper deals with the modular verification of modular Petri nets. We propose a reduced version for the modular state space of a given modular Petri net. The new structure allows the creation of smaller modular graphs. Each one draws the behavior of the corresponding module and outlines some global information. Hence, this version helps to overcome the explosion problem and to use less memory space. In this condensed structure, the verification of some generic properties concerning one module is limited to the exploration of its associated graph.

Keywords: distributed systems, modular verification, petri nets, state space explosition

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Authors: I. Gupta, N. Setia

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Introduction. Buyer conduct is a progression of practices or examples that buyers pursue before making a buy. It begins when the shopper ends up mindful of a need or wish for an item, at that point finishes up with the buying exchange. Business visionaries can't generally simply shake hands with their intended interest group people and become more acquainted with them. Research is often necessary, so every organization primarily involves doing continuous research to understand and satisfy consumer needs pattern. Aims and Objectives: The aim of the present study is to examine the different behaviors of the consumer, including pre-purchase, purchase, and post-purchase behavior. Materials and Methods: In order to get results, face to face interview held with 80 people which comprise a larger part of female individuals having upper as well as middle-class status. The prime source of data collection was primary. However, the study has also used the theoretical contribution of many researchers in their respective field. Results: Majority of the respondents were females (70%) from the age group of 20-50. The collected data was analyzed through hypothesis testing statistical techniques such as correlation analysis, single regression analysis, and ANOVA which has rejected the null hypothesis that there is no relation between researching the consumer behavior at different stages and organizational performance. The real finding of this study is that simply focusing on the buying part isn't enough to gain profits and fame, however, understanding the pre, buy and post-buy behavior of consumer performs a huge role in organization success. The outcomes demonstrated that the organization, which deals with the three phases of research of purchasing conduct is able to establish a great brand image as compare to their competitors. Alongside, enterprises can observe customer conduct in a considerably more proficient manner. Conclusion: The analyses of consumer behavior presented in this study is an attempt to understand the factors affecting consumer purchasing behavior. This study has revealed that those corporations are more successful, which work on understanding buying behavior instead to just focus on the selling products. As a result, organizations perform good and grow rapidly because consumers are the one who can make or break the company. The interviews that were conducted face to face, clearly revealed that those organizations become at top-notch whom consumers are satisfied, not just with product but also with services of the company. The study is not targeting the particular class of audience; however, it brings out benefits to the masses, in particular to business organizations.

Keywords: consumer behavior, pre purchase, post purchase, consumer satisfaction

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Authors: Justice Zakhele Msomi

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Nanoparticles of CdFe2O4 with particle size of about 10 nm have been synthesized by high energy ball milling and co-precipitation processes. The synthesis route appears to have some effects on the properties. The compounds have been characterized by X-ray diffraction, Fourier Transform Infrared (FTIR), transmission electron microscopy (TEM), Mössbauer and magnetization measurements. The XRD pattern of CdFe2O4 provides information about single-phase formation of spinel structure with cubic symmetry. The FTIR measurements between 400 and 4000 cm-1 indicate intrinsic cation vibration of the spinel structure. The Mössbauer spectra were recorded at 4 K and 300 K. The hyperfine fields appear to be highly sensitive on particle size. The evolution of the properties as a function of particle size is also presented.

Keywords: ferrite, nanoparticles, magnetization, Mössbauer

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Authors: Chukwuka Justus Iwegbu

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Background: A major concern facing the world is providing senior citizens, individuals with disabilities, and other vulnerable groups with high-quality care. This issue is more serious in Nigeria's North Eastern area, where the burden of disease and disability is heavy, and access to care is constrained. This study aims to fill this gap by exploring the roles, challenges and support needs of caregivers, care home management, funding and administration in challenged communities in North Eastern Nigeria. The study will also provide a comprehensive understanding of the current situation and identify opportunities for improving the quality of care and support for caregivers and care recipients in these communities. Methods: A mixed-methods design, including both quantitative and qualitative data collection methods, will be used, and it will be guided by the stress process model of caregiving. The qualitative stage approach will comprise a survey, In-depth interviews, observations, and focus group discussion and the quantitative analysis will be used in order to comprehend the variations between caregiver's roles and care home management. A review of relevant documents, such as care home policies and funding reports, would be used to gather quantitative data on the administrative and financial aspects of care. The data collected will be analyzed using both descriptive statistics and thematic analysis. A sample size of around 200-300 participants, including caregivers, care recipients, care home managers and administrators, policymakers and health care providers, would be recruited. Findings: The study revealed that caregivers in challenged communities in North Eastern Nigeria face significant challenges, including lack of training and support, limited access to funding and resources, and high levels of burnout. Care home management and administration were also found to be inadequate, with a lack of clear policies and procedures and limited oversight and accountability. Conclusion: There is a need for increased investment in training and support for caregivers, as well as a need for improved care home management and administration in challenged communities in North Eastern Nigeria. It also highlights the importance of involving community members in decision-making and planning processes related to care homes and services. The study would contribute to the existing body of knowledge by providing a detailed understanding of the challenges faced by caregivers, care home managers and administrators.

Keywords: caregivers, care home management, funding, administration, challenge communities, North Eastern Nigeria

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Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

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Authors: Huynh Viet Khai, Mitsuyasu Yabe

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The study investigated the economic value of biodiversity attributes that could provide policy-makers reliable information to estimate welfare losses due to biodiversity reductions and analyse the trade-off between biodiversity and economics. In order to obtain the non-market benefits of biodiversity conservation, an indirect utility function and willingness to pay for biodiversity attributes were applied using the approach of choice modelling with the analysis of conditional logit model. The study found that Mekong Delta residents accepted their willingness to pay for VND 913 monthly for a one percent increase in healthy vegetation, VND 360 for an additional mammal species and VND 2,440 to avoid the welfare losses of 100 local farmers.

Keywords: choice modelling, genetic resources, wetland conservation, marginal willingness to pay

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Authors: Sabo Elizabeth

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Cowpea production is presently mainly done with inorganic insecticides, but the growing environmental problems linked with their use and the rising costs of the chemicals are stimulating all categories of stakeholders towards the adoption of less impacting practices. 611 respondents were interviewed between 2008 and 2009. Respondents are young adults and are fairly educated. Awareness is high about insecticide use, but is low for bio-pesticides and resistant varieties. Adoption of inorganic insecticides is related to age, educational level, and contacts with dealers. Low adoption rate for resistant varieties is associated with inadequate information and poor extension service. To adopt IPM techniques with limited health hazards and compatible with the environment, a properly designed extension program is consequently needed.

Keywords: Vigna unguiculata, IPM, bio-pesticides, resistant varieties, extension

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Authors: M. Sumana, K. S. Hareesha

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Secure computations are essential while performing privacy preserving data mining. Distributed privacy preserving data mining involve two to more sites that cannot pool in their data to a third party due to the violation of law regarding the individual. Hence in order to model the private data without compromising privacy and information loss, secure multiparty computations are used. Secure computations of product, mean, variance, dot product, sigmoid function using the additive and multiplicative homomorphic property is discussed. The computations are performed on vertically partitioned data with a single site holding the class value.

Keywords: homomorphic property, secure product, secure mean and variance, secure dot product, vertically partitioned data

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Authors: Bo Wang

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This paper proposes a method that can estimate PM2.5 by the images of GF-1 Satellite that called WFOV images (Wide Field of View). AOD (Aerosol Optical Depth) over land surfaces was retrieved in Shanghai area based on DDV (Dark Dense Vegetation) method. PM2.5 information, gathered from ground monitoring stations hourly, was fitted with AOD using different polynomial coefficients, and then the correlation coefficient between them was calculated. The results showed that, the GF-1 WFOV images can meet the requirement of retrieving AOD, and the correlation coefficient between the retrieved AOD and PM2.5 was high. If more detailed and comprehensive data is provided, the accuracy could be improved and the parameters can be more precise in the future.

Keywords: remote sensing retrieve, PM 2.5, GF-1, aerosol optical depth

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Authors: Ergham Al Bachir

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This study adopts strategic leadership (Upper Echelons) as the core theory and contextual leadership theory as the research lens. This research asks how the external context impacts strategic leadership effectiveness to achieve the outcomes in pluralistic organizations (PO). The study explores how the context influences the selection of CEOs, top management teams (TMT), and their leadership effectiveness. POs are characterized by the multiple objectives of their top management teams, divergent objectives, multiple strategies, and multiple governing authorities. The research question is explored by means of a qualitative multiple-case study focusing on healthcare, real estate, and financial services organizations. The data sources are semi-structured interviews, documents, and direct observations. The data analysis strategy is inductive and deploys thematic analysis and cross-case synthesis. The findings differentiate between national and international CEOs' delegation of authority and relationship with the Board of Directors. The findings identify the elements of the dynamic context that influence TMT and PO outcomes. The emergent hybrid strategic and contextual leadership framework shows how the different contextual factors influence strategic direction, PO context, selection of CEOs and TMT, and the outcomes in four pluralistic organizations. The study offers seven theoretical contributions to Upper Echelons, strategic leadership, and contextual leadership research. (1) The integration of two theories revealed how CEO’s impact on the organization is complementary to the contextual impact. (2) Conducting this study in the Middle East contributes to strategic leadership and contextual leadership research. (3) The demonstration of the significant contextual effects on the selection of CEOs. (4 and 5) Two contributions revealed new links between the context, the Board role, internal versus external CEOs, and national versus international CEOs. (6 and 7) This study offered two definitions: what accounts for CEO leadership effectiveness and organizational outcomes. Two methodological contributions were also identified: (1) Previous strategic leadership and Upper Echelons research are mainly quantitative, while this study adopts qualitative multiple-case research with face-to-face interviews. (2) The extrication of the CEO from the TMT advanced the data analysis in strategic leadership research. Four contributions are offered to practice: (1) The CEO's leadership effectiveness inside and outside the organization. (2) Rapid turnover of predecessor CEOs signifies the need for a strategic and contextual approach to CEOs' succession. (3) TMT composition and education impact on TMT-CEO and TMT-TMT interface. (4) Multilevel strategic contextual leadership development framework.

Keywords: strategic leadership, contextual leadership, upper echelons, pluralistic organizations, cross-cultural leadership

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Authors: Riofrio Jonathan, Fernandez Guillermo

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Renewable energy represented around 80% of the energy matrix for power generation in Ecuador during 2020, so the deployment of current public policies is focused on taking advantage of the high presence of renewable sources to carry out several electrification projects. These projects are part of the portfolio sent to the United Nations Framework on Climate Change (UNFCCC) as a commitment to reduce greenhouse gas emissions (GHG) in the established national determined contribution (NDC). In this sense, the Ecuadorian Organic Energy Efficiency Law (LOEE) published in 2019 promotes E-mobility as one of the main milestones. In fact, it states that the new vehicles for urban and interurban usage must be E-buses since 2025. As a result, and for a successful implementation of this technological change in a national context, it is important to deploy land surveys focused on technical and geographical areas to keep the quality of services in both the electricity and transport sectors. Therefore, this research presents a technological and energy comparison between a conventional diesel bus and its equivalent E-bus. Both vehicles fulfill all the technical requirements to ride in the study-case city, which is Ambato in the province of Tungurahua-Ecuador. In addition, the analysis includes the development of a model for the energy estimation of both technologies that are especially applied in a highland city such as Ambato. The altimetry of the most important bus routes in the city varies from 2557 to 3200 m.a.s.l., respectively, for the lowest and highest points. These operation conditions provide a grade of novelty to this paper. Complementary, the technical specifications of diesel buses are defined following the common features of buses registered in Ambato. On the other hand, the specifications for E-buses come from the most common units introduced in Latin America because there is not enough evidence in similar cities at the moment. The achieved results will be good input data for decision-makers since electric demand forecast, energy savings, costs, and greenhouse gases emissions are computed. Indeed, GHG is important because it allows reporting the transparency framework that it is part of the Paris Agreement. Finally, the presented results correspond to stage I of the called project “Analysis and Prospective of Electromobility in Ecuador and Energy Mix towards 2030” supported by Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ).

Keywords: high altitude cities, energy planning, NDC, e-buses, e-mobility

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Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

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Authors: Byron Joseph A. Hallar, Annjeannette Alain D. Galang, Maria Visitacion N. Gumabay

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One of the unique challenges provided by the twenty-first century to Philippine higher education is the utilization of Big Data. The higher education system in the Philippines is generating burgeoning amounts of data that contains relevant data that can be used to generate the information and knowledge needed for accurate data-driven decision making. This study examines the status, relevance and future of Big Data and Analytics in Philippine higher education. The insights gained from the study may be relevant to other developing nations similarly situated as the Philippines.

Keywords: big data, data analytics, higher education, republic of the philippines, assessment

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Authors: M. Sedlmajer, J. Zach, J. Hroudova, P. Rovnaníkova

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There are several possibilities of reducing the required amount of cement in concrete production. Natural zeolite is one of the raw materials which can partly substitute Portland cement. The effort to reduce the amount of Portland cement used in concrete production is brings both economical as well as ecological benefits. The paper presents the properties of concrete containing natural zeolite as an active admixture in the concrete which partly substitutes Portland cement. The properties discussed here bring information about the basic mechanical properties and frost resistance of concrete containing zeolite. The properties of concretes with the admixture of zeolite are compared with a reference concrete with no content of zeolite. The properties of the individual concretes are observed for 360 days.

Keywords: concrete, zeolite, compressive strength, modulus of elasticity, durability

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Authors: Rinat Gabbay-Benziv, Merav Ben-Natan, Ariel Roguin, Benyamine Abbou, Anna Ofir, Adi Klein, Dikla Dahan-Shriki, Mordechai Hallak, Boris Kessel, Mickey Dudkiewicz

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Introduction: Over recent decades, technology has become integral to healthcare, with electronic health records and advanced medical equipment now standard. However, this reliance has made healthcare systems increasingly vulnerable to ransomware attacks. On October 13, 2021, Hillel Yaffe Medical Center experienced a severe ransomware attack that disrupted all IT systems, including electronic health records, laboratory services, and staff communications. The attack, carried out by the group DeepBlueMagic, utilized advanced encryption to lock the hospital's systems and demanded a ransom. This incident caused significant operational and patient care challenges, particularly impacting the obstetrics department. Objective: The objective is to describe the challenges facing the obstetric division following a cyberattack and discuss ways of preparing for and overcoming another one. Methods: A retrospective descriptive study was conducted in a mid-sized medical center. Division activities, including the number of deliveries, cesarean sections, emergency room visits, admissions, maternal-fetal medicine department occupancy, and ambulatory encounters, from 2 weeks before the attack to 8 weeks following it (a total of 11 weeks), were compared with the retrospective period in 2019 (pre-COVID-19). In addition, we present the challenges and adaptation measures taken at the division and hospital levels leading up to the resumption of full division activity. Results: On the day of the cyberattack, critical decisions were made. The media announced the event, calling on patients not to come to our hospital. Also, all elective activities other than cesarean deliveries were stopped. The number of deliveries, admissions, and both emergency room and ambulatory clinic visits decreased by 5%–10% overall for 11 weeks, reflecting the decrease in division activity. Nevertheless, in all stations, there were sufficient activities and adaptation measures to ensure patient safety, decision-making, and workflow of patients were accounted for. Conclusions: The risk of ransomware cyberattacks is growing. Healthcare systems at all levels should recognize this threat and have protocols for dealing with them once they occur.

Keywords: ransomware attack, healthcare cybersecurity, obstetrics challenges, IT system disruption

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Authors: Shaban Guma, Naim Bajcinca

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We propose an event-triggered algorithm for the solution of a distributed optimization problem by means of the projected subgradient method. Thereby, we invoke an OFDMA resource allocation scheme by applying an event-triggered sensitivity analysis at the access point. The optimal resource assignment of the subcarriers to the involved wireless nodes is carried out by considering the sensitivity analysis of the overall objective function as defined by the control of vehicle clusters with respect to the information exchange between the nodes.

Keywords: consensus, cross-layer, distributed, event-triggered, multi-vehicle, protocol, resource, OFDMA, wireless

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Authors: Yali Liu, Maria Avello Iturriagagoitia

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Background: Fitness applications (apps) are one of the most popular mobile health (mHealth) apps. These apps can help prevent/control health issues such as obesity, which is one of the most serious public health challenges in the developed world in recent decades. Compared with the traditional intervention like face-to-face treatment, it is cheaper and more convenient to use fitness apps to interfere with physical activities and healthy behaviors. Nevertheless, fitness applications apps tend to have high abandonment rates and low levels of user engagement. Therefore, maintaining the endurance of users' usage is challenging. In fact, previous research shows a variety of strategies -goal-setting, self-monitoring, coaching, etc.- for promoting fitness and health behavior change. These strategies can influence the users’ perseverance and self-monitoring of the program as well as favoring their adherence to routines that involve a long-term behavioral change. However, commercial fitness apps rarely incorporate these strategies into their design, thus leading to a lack of engagement with the apps. Most of today’s mobile services and brands engage their users proactively via push notifications. Push notifications. These notifications are visual or auditory alerts to inform mobile users about a wide range of topics that entails an effective and personal mean of communication between the app and the user. One of the research purposes of this article is to implement the application of behavior change strategies through push notifications. Proposes: This study aims to better understand the influence that effective use of push notifications combined with the behavioral change strategies will have on users’ engagement with the fitness app. And the secondary objectives are 1) to discuss the sociodemographic differences in utilization of push notifications of fitness apps; 2) to determine the impact of each strategy in customer engagement. Methods: The study uses a combination of the Consumer Engagement Theory and UTAUT2 based model to conduct an online survey among current users of fitness apps. The questionnaire assessed attitudes to each behavioral change strategy, and sociodemographic variables. Findings: Results show the positive effect of push notifications in the generation of consumer engagement and the different impacts of each strategy among different groups of population in customer engagement. Conclusions: Fitness apps with behavior change strategies have a positive impact on increasing users’ usage time and customer engagement. Theoretical experts can participate in designing fitness applications, along with technical designers.

Keywords: behavioral change, customer engagement, fitness app, push notification, UTAUT2

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Authors: Belbaly Nassim

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Virtual teams (VT) initiatives, in which teams are geographically dispersed and communicate via modern computer-driven technologies, have attracted increasing attention from researchers and professionals. The growing need to examine how to balance and optimize VT is particularly important given the exposure experienced by companies when their employees encounter globalization and decentralization pressures to monitor VT performance. Hence, organization is regularly limited due to misalignment between the behavioral capabilities of the team’s dispersed competences and knowledge capabilities and how trust issues interplay and influence these VT dimensions and the effects of such exchanges. In fact, the future success of business depends on the extent to which VTs are managing efficiently their dispersed expertise, skills and knowledge to stimulate VT creativity. Transactive memory system (TMS) may enhance VT creativity using its three dimensons: knowledge specialization, credibility and knowledge coordination. TMS can be understood as a composition of both a structural component residing of individual knowledge and a set of communication processes among individuals. The individual knowledge is shared while being retrieved, applied and the learning is coordinated. TMS is driven by the central concept that the system is built on the distinction between internal and external memory encoding. A VT learns something new and catalogs it in memory for future retrieval and use. TMS uses the role of information technology to explain VT behaviors by offering VT members the possibility to encode, store, and retrieve information. TMS considers the members of a team as a processing system in which the location of expertise both enhances knowledge coordination and builds trust among members over time. We build on TMS dimensions to hypothesize the effects of specialization, coordination, and credibility on VT creativity. In fact, VTs consist of dispersed expertise, skills and knowledge that can positively enhance coordination and collaboration. Ultimately, this team composition may lead to recognition of both who has expertise and where that expertise is located; over time, the team composition may also build trust among VT members over time developing the ability to coordinate their knowledge which can stimulate creativity. We also assess the reciprocal relationship between TMS dimensions and VT creativity. We wish to use TMS to provide researchers with a theoretically driven model that is empirically validated through survey evidence. We propose that TMS provides a new way to enhance and balance VT creativity. This study also provides researchers insight into the use of TMS to influence positively VT creativity. In addition to our research contributions, we provide several managerial insights into how TMS components can be used to increase performance within dispersed VTs.

Keywords: virtual team creativity, transactive memory systems, specialization, credibility, coordination

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Authors: Thomas Benson

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Smart cities have been heralded as multi-faceted entities which utilise information and communication technologies to enhance citizen participation. The purpose of this paper is to outline authoritative definitions of smart cities and citizen participation and investigate smart city citizen-centrism rhetoric by examining urban governance and citizen participation processes. Drawing on extant literature and official city government documents and websites, Singapore (Singapore) and Tokyo (Japan) are chosen as comparable smart city case studies. For the smart city to be truly realised, this paper concludes that smart cities must do more to incorporate genuine citizen participation mechanisms.

Keywords: citizen participation, smart cities, urban governance, Singapore, Tokyo

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Authors: Xuzhen Yang, Yan Shan, Yabo Ding, Keke DIao, Yanjun Zhang, Yijia Huang

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Purpose: Our aim is to understand the unique experiences of patients with peritoneal dialysis and how they deal with issues brought on by disease and dialysis. Patients and Methods: Semi-structured interview was designed to collect information, and inpatients with peritoneal dialysis in a university-based tertiary hospital in the central province of China were purposively chosen as interviewees. The content analysis method was used to analyze the data. Results: Nine patients participated in the study, and three themes and eight subthemes were generated. Conclusion: Patients using peritoneal dialysis encounter numerous challenges and problems in the process of disease and dialysis, and they took attempt to cope with them well to adapt to living with peritoneal dialysis.

Keywords: peritoneal dialysis, experience, patient, coping strategy

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Authors: Omar Said Almushyt

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Quality management, in all countries all over the world, has become recently necessary to face challenges among companies. Software companies in KSA suffer from two problems, namely, low customer satisfaction, and low product quality. Implementation of quality management for a software company can solve these problems, by improving the quality of products and enhancing customer satisfaction. This will lead the company to be competitive. Introducing quality management system onto system analysis followed by system design and finally implementing that system can achieve these goals. Results of the present work showed that the proposed method can increase both the product quality by 10 % and the customer satisfaction by 20 %.

Keywords: quality, management, software, information engineering

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Authors: Jacolien Barnard, Corlia Van Heerden

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Effective and accessible consensual dispute resolution and in particular alternative dispute resolution, are central to consumer protection legislation. In this regard, the Consumer Protection Act 68 of 2008 (CPA) of South Africa is no exception. Due to the nature of consumer disputes, alternative dispute resolution (in theory) is an effective vehicle for the adjudication of disputes in a timely manner avoiding overburdening of the courts. The CPA sets down as one of its core purposes the provision of ‘an accessible, consistent, harmonized, effective and efficient system of redress for consumers’ (section 3(1)(h) of the CPA). Section 69 of the Act provides for the enforcement of consumer rights and provides for the National Consumer Commission to be the Central Authority which streamlines, adjudicates and channels disputes to the appropriate forums which include Alternative Dispute Resolution Agents (ADR-agents). The purpose of this paper is to analyze the regulation of these enforcement and redress mechanisms with particular focus on the Central Authority as well as the ADR-agents and their crucial role in successful and efficient adjudication of disputes in South Africa. The South African position will be discussed comparatively with the European Union (EU) position. In this regard, the European Union (EU) Directive on Alternative Dispute Resolution for Consumer Disputes (2013/11/EU) will be discussed (The ADR Directive). The aim of the ADR Directive is to solve contractual disputes between consumers and traders (suppliers or businesses) regardless of whether the agreement was concluded offline or online or whether or not the trader is situated in another member state (Recitals 4-6). The ADR Directive provides for a set of quality requirements that an ADR body or entity tasked with resolving consumer disputes should adhere to in member states which include regulatory mechanisms for control. Transparency, effectiveness, fairness, liberty and legality are all requirements for a successful ADR body and discussed within this chapter III of the Directive. Chapters III and IV govern the importance of information and co-operation. This includes information between ADR bodies and the European Commission (EC) but also between ADR bodies or entities and national authorities enforcing legal acts on consumer protection and traders. (In South Africa the National Consumer Tribunal, Provincial Consumer Protectors and Industry ombuds come to mind). All of which have a responsibility to keep consumers informed. Ultimately the papers aims to provide recommendations as to the successfulness of the current South African position in light of the comparative position in Europe and the highlight the importance of proper regulation of these redress and enforcement institutions.

Keywords: alternative dispute resolution, consumer protection law, enforcement, redress

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Authors: Nora Alomar, Bianca Alexandra Stefa, Saleh Bazi

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This research uncovers the determinants that drive millennial consumers to adhere to product return of fast-fashion products purchases via e-commerce and what effects it has on consumer experience and satisfaction. Online consumption has skyrocketed, with e-commerce being the only, most reliable, and safe method of shopping during and post Covid-19. It has been noted customers are demanding a wide variety of product characteristics and a generous optimal return policy. The authors have selected to examine millennial consumers as they are digital natives and have an affinity for researching, reading product reviews, and shopping online, with a great spending power due to a higher disposable income in comparison to other generations. A multi-study approach is adopted, where study one (interviews, sample of 20 respondents) investigates the factors that drive product return, and study two (PLS-SEM, sample of 250 respondents) looks into the relationships of product return management against behavioral outcomes by having the generated factors (from study one) as moderators. Five themes are generated from study one (return policies, product characteristics, delivery lead time, seasonality, product trial & overspending). The authors identify that two out of the five factors (seasonality, product trial & overspending) have not been highlighted by the literature. The paper examines 11 hypotheses, where 10 are supported. Findings highlight the quality of the product return management influences the overall millennial customer experience and satisfaction. Findings also indicate that product return management was identified to have a significant negative effect on customer experience. Additionally, seasonality has a significant but negative moderation, which means increasing seasonality decreases the relationship between product return management and customer experience and satisfaction. Results highlight that return policies have a significant negative influence on the relationship between returning a product and customer experience and satisfaction. Moreover, product characteristics are also identified to have a significant negative influence on the relationship between returning a product and customer experience and satisfaction. This study further examines the influence of the factors on direct e-commerce websites and third-party e-commerce websites. Findings showcase a strong statistical significance for the increased rate of return of fast-fashion products on third-party websites. This paper aids practitioners in taking strategic decisions related to return management, to improve the quality of logistical services and, in turn, increase profitability.

Keywords: customer experience, customer satisfaction, e-commerce, fast-fashion, product returns

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

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The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Amir Davood Elmi

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From the earliest light microscope to the most innovative X-ray imaging techniques, all of them have refined and improved our knowledge about the organization and composition of living tissues. The old techniques are time consuming and ultimately destructive to the tissues under the examination. In recent few decades, thanks to the boost of technology, non-destructive visualization techniques, such as X-ray computed tomography (CT), magnetic resonance imaging (MRI), selective plane illumination microscopy (SPIM), and optical projection tomography (OPT), have come to the forefront. Among these techniques, CT is excellent for mineralized tissues such as bone or dentine. In addition, CT it is faster than other aforementioned techniques and the sample remains intact. In this article, applications, advantages, and limitations of micro-CT is discussed, in addition to some information about micro-CT of soft tissue.

Keywords: Micro-CT, hard tissue, bone, attenuation coefficient, rapid prototyping

Procedia PDF Downloads 146