25 research outputs found

    An effective hotel recommendation system through processing heterogeneous data

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    Recommendation systems have recently gained a lot of popularity in various industries such as entertainment and tourism. They can act as filters of information by providing relevant suggestions to the users through processing heterogeneous data from different networks. Many travelers and tourists routinely rely on textual reviews, numerical ratings, and points of interest to select hotels in cities worldwide. To attract more customers, online hotel booking systems typically rank their hotels based on the recommendations from their customers. In this paper, we present a framework that can rank hotels by analyzing hotels’ customer reviews and nearby amenities. In addition, a framework is presented that combines the scores generated from user reviews and surrounding facilities. We perform experiments using datasets from online hotel booking platforms such as TripAdvisor and Booking to evaluate the effectiveness and applicability of the proposed framework. We first store the keywords extracted from reviews and assign weights to each considered unigram and bigram keywords and, then, we give a numerical score to each considered keyword. Finally, our proposed system aggregates the scores generated from the reviews and surrounding environments from different categories of the facilities. Experimental results confirm the effectiveness of the proposed recommendation framework

    Financial threat, hardship and distress predict depression, anxiety and stress among the unemployed youths: a Bangladeshi multi-cities study

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    Introduction: Unemployment has a contributory role in the development of mental health problems and in Bangladesh there is increasing unemployment, particularly among youth. Consequently, the present study investigated depression, anxiety, and stress among recent graduates in a multi-city study across the country. Methods: A cross-sectional study was conducted among 988 Bangladeshi graduate jobseekers in six major cities of the country between August to November 2019. The measures included socio-demographics and life-style factors, study and job-related information, Economic Hardship Questionnaire, Financial Threat Scale, Financial Well-Being Scale, and Depression Anxiety Stress Scale-21. Results: Depression, anxiety and stress rates among the present sample were 81.1% (n=801), 61.5% (n=608) and 64.8% (n=640) respectively. Factors related to gender, age, socio-economic conditions, educational background, lack of extra-curricular activities, and high screen activity were significant risk factors of depression, anxiety, and stress. Structural equation modeling indicated that (while controlling for age, daily time spent on sleep study, and social media use), financial threat was moderately positively related to depression, anxiety, and stress. Financial hardship was weakly positively associated with depression, anxiety, and stress, whereas financial wellbeing was weakly negatively associated with depression, anxiety, and stress. Limitations: Due to the nature of the present study (i.e., cross-sectional study) and sampling method (i.e., convenience sampling), determining causality between the variables is not possible. Conclusions: The present results emphasized the important detrimental role of financial troubles on young people's mental health by showing that financial problems among unemployed youth predict elevated psychiatric distress in both men and women

    Understanding the Predictors of Rural Customers’ Continuance Intention toward Mobile Banking Services Applications during the COVID-19 Pandemic

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    The purpose of this study is to examine the antecedents of customers’ continuance intention to use mobile banking services applications (MBSAs) during the COVID-19 pandemic. Grounding on the Technology Acceptance Model, Theory of Planned Behavior, and Cognitive Load Theory, an integrated conceptual framework was proposed and tested incorporating psychological factors (i.e., cyberchondria, perceived anxiety) and situational factors (i.e., social distance, institutional support). Data were collected from 250 rural customers and analyzed with Structural Equation Modeling. The results showed that subjective norms, perceived ease of use, social distance, attitudes, cyberchondria, and institutional support influenced users’ continuance intention. Moreover, the results showed that perceived anxiety, subjective norms, perceived ease of use, and perceived usefulness influenced users’ attitudes. Besides, the findings suggested that attitudes mediate the influence of subjective norms, usefulness, ease of use, and social distance on users’ intention. This study is unique in terms of investigating pandemic-specific psychological and situational factors in explaining consumers’ continuance intention. Therefore, the service providers and professionals should be cautious in designing MBSAs so that consumers’ usage behaviors may not vary during an unprecedented situation (e.g., COVID-19). The theoretical and practical implications were discussed

    High-performance work systems and job engagement: The mediating role of psychological empowerment

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    Drawing on the social exchange theory, this study aimed to investigate the mediating role of psychological empowerment in the relationship between high-performance work systems and job engagement. Data collected from 287 employees in a large manufacturing organization was analyzed using structural equation modeling and hierarchical regression analysis. The results showed that perceived high-performance work systems and psychological empowerment positively influenced job engagement. The results of the study also revealed that psychological empowerment mediated the influence of high-performance work systems on job engagement. The results further suggest that organizational human resources systems impact job engagement through psychological empowerment. The theoretical contribution and managerial implications have been thoroughly discussed in this paper

    Advantages of Using Paclitaxel in Combination with Oncolytic Adenovirus Utilizing RNA Destabilization Mechanism

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    Oncolytic virotherapy is a novel approach to cancer therapy. Ad-fosARE is a conditionally replicative adenovirus engineered by inserting AU-rich elements (ARE) in the 3'-untranslated region of the E1A gene. In this study, we examined the oncolytic activity of Ad-fosARE and used it in a synergistic combination with the chemotherapeutic agent paclitaxel (PTX) for treating cancer cells. The expression of E1A was high in cancer cells due to stabilized E1A-ARE mRNA. As a result, the efficiency of its replication and cytolytic activity in cancer cells was higher than in normal cells. PTX treatment increased the cytoplasmic HuR relocalization in cancer cells, enhanced viral replication through elevated E1A expression, and upregulated CAR (Coxsackie-adenovirus receptor) required for viral uptake. Furthermore, PTX altered the instability of microtubules by acetylation and detyrosination, which is essential for viral internalization and trafficking to the nucleus. These results indicate that PTX can provide multiple advantages to the efficacy of Ad-fosARE both in vitro and in vivo, and provides a basis for designing novel clinical trials. Thus, this virus has a lot of benefits that are not found in other oncolytic viruses. The virus also has the potential for treating PXT-resistant cancers

    Autonomous Driving Vehicle System using LiDAR sensor

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    An overview of light detection and ranging (LiDAR) sensor technology for autonomous vehicles is presented in this paper. The sensor called LiDAR sensors is a key component of autonomous driving’s for the upcoming generation as an assistance function. LiDAR technology is discussed, including its characteristics, a technical overview, prospects as well as limitations in relation to other sensors available in the industry. Comparison and comment on sensor quality are based on factory parameters. The basic components of a LiDAR system from the laser transmitter to the beam scanning mechanism are explained
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