Search results for: recognition primed decision

Authors: Bharti Bhandari, Bharati Mehta, Sabyasachi Sircar

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Medical education is advancing in India, with its advancement newer innovations are being incorporated in teaching and assessment methodology. Our study focusses on a teaching innovation that is more student-centric than teacher-centric and is the need of the day. The teaching innovation was carried out in 1st year MBBS students of our institute. Students were assigned control and test groups. Priming was done for the students in the test group with an open-book MCQ based test in a particular topic before delivering formal didactic lecture on that topic. The control group was not assigned any such exercise. This was followed by formal didactic lecture on the same topic. Thereafter, both groups were assessed on the same topic. The marks were compiled and analysed using appropriate statistical tests. Students were also given questionnaire to elicit their views on the benefits of “self-priming”. The mean marks scored in theory assessment by the test group were statistically higher than the marks scored by the controls. According to students’ feedback, the ‘self-priming “process was interesting, helped in better orientation during class-room lectures and better understanding of the topic. They want it to be repeated for other topics with moderate difficulty level. Better performance of the students in the primed group validates the combination of student-centric priming model and didactic lecture as superior to the conventional, teacher-centric methods alone. If this system is successfully followed, the present teacher-centric pedagogy should increasingly give way to student-centric activities where the teacher is only a facilitator.

Keywords: medical education, open-book test, pedagogy, priming

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Authors: Javier Comes Fayos, Isabel RodríGuez Moreno, Sara Bressanutti, Marisol Lila, Angel Romero MartíNez, Luis Moya Albiol

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Given the great impact produced by gender-based violence, its comprehensive approach seems essential. Consequently, research has focused on risk factors for violent behaviour, linking various psychosocial variables, as well as cognitive and neuropsychological deficits with the aggressors. However, studies on affective processing are scarce, so the present study investigates possible emotional alterations in men convicted of gender violence. The participants were 51 aggressors, who attended the CONTEXTO program with sentences of less than two years, and 47 men with no history of violence. The sample did not differ in age, socioeconomic level, education, or alcohol and other substances consumption. Anger, alexithymia and facial recognition of other people´s emotions were assessed through the State-Trait Anger Expression Inventory (STAXI-2), the Toronto Alexithymia Scale (TAS-20) and Reading the mind in the eyes (REM), respectively. Men convicted of gender-based violence showed higher scores on the anger trait and temperament dimensions, as well as on the anger expression index. They also scored higher on alexithymia and in the identification and emotional expression subscales. In addition, they showed greater difficulties in the facial recognition of emotions by having a lower score in the REM. These results seem to show difficulties in different affective areas in men condemned for gender violence. The deficits are reflected in greater difficulty in identifying and expressing emotions, in processing anger and in recognizing the emotions of others. All these difficulties have been related to the use of violent behavior. Consequently, it is essential and necessary to include emotional regulation in intervention programs for men who have been convicted of gender-based violence.

Keywords: alexithymia, anger, emotional processing, emotional recognition, empathy, intimate partner violence

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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Authors: Ying Chuan Wang, Zhang Tao

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The aim of this article intends to explore the differences of well-being of employees in casino hotels before and after the Chinese government began to fight corruption. This researcher also attempted to find out the relationship between work pressure and well-being of employees in gambling workplaces before and after the Chinese government crackdowns the corruption. The category of well-being including life well-being, workplace well-being, and psychological well-being was included for analyzing well-being of employees in gaming workplaces. In addition, the psychological pressure classification was applied into this study and the Job Content Questionnaire (JCQ) would be adopted on investigating employees’ work pressure in terms of decision latitude, psychological demands, and workplace support. This study is a quantitative approach research and was conducted in March 2017. A purposive sampling was used in this study. A total of valid 339 responses were collected and the participants were casino hotel employees. The findings showed that decision latitude was significantly different prior to and after Chinese government crackdowns on corruption. Moreover, workplace support was strongly significantly related to employees’ well-being before Chinese government crackdowns. Decision latitude was strongly significantly related to employees’ well-being after Chinese government crackdowns. The findings suggest that employees’ work pressure affects their well being. In particular, because of workplace supports, it may alleviate employees’ work pressure and affect their perceptions of well-being but only prior to fighting the crackdowns. Importantly, decision latitude has become an essential factor affecting their well-being after the crackdown. It is finally hoped that the findings of this study provide suggestion to the managerial levels of hospitality industries. It is important to enhance employees’ decision latitude. Offering training courses to equip employees’ skills could be a possible way to reduce work pressure. In addition, establishing career path for the employees to pursuit is essential for their self-development and the improvement of well being. This would be crucial for casino hotels’ sustainable development and strengthening their competitiveness.

Keywords: well-being, work pressure, Casino hotels’ employees, gaming workplace

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Authors: Xizhen Zhou, Yanjie Ji

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The charging behavior of drivers provides a reference for the planning and management of charging facilities. Based on the real trajectory data of electric vehicles, this study explored the influence of the surrounding environments of the parking spot on charging decisions. The built environment, the condition of vehicles, and the nearest charging station were all considered. And the mixed binary logit model was used to capture the impact of unobserved heterogeneity. The results show that the number of fast chargers in the charging station, parking price, dwell time, and shopping services all significantly impact the charging decision, while the leisure services, scenic spots, and mileage since the last charging are opposite. Besides, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, residential areas, etc. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. The results provide insights for planning and managing charging facilities.

Keywords: charging decision, trajectory, electric vehicle, infrastructure, mixed logit

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Authors: Wided Khiari, Adel Karaa

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This study aims to establish a typology of Tunisian listed firms according to their corporate governance characteristics and disclosure quality. The paper uses disclosed scores to examine corporate governance practices of Tunisian listed firms. A content analysis of 46 Tunisian listed firms from 2001 to 2010 has been carried out and a disclosure index developed to determine the level of disclosure of the companies. The disclosure quality is appreciated through the quantity and also through the nature (type) of information disclosed. Applying the decision tree method, the obtained tree diagrams provide ways to know the characteristics of a particular firm regardless of its level of disclosure. Obtained results show that the characteristics of corporate governance to achieve good quality of disclosure are not unique for all firms. These structures are not necessarily all of the recommendations of best practices, but converge towards the best combination. Indeed, in practice, there are companies which have a good quality of disclosure, but are not well-governed. However, we hope that by improving their governance system their level of disclosure may be better. These findings show, in a general way, a convergence towards the standards of corporate governance with a few exceptions related to the specificity of Tunisian listed firms and show the need for the adoption of a code for each context. These findings shed the light on corporate governance features that enhance incentives for good disclosure. It allows identifying, for each firm and in any date, corporate governance determinants of disclosure quality. More specifically, and all being equal, obtained tree makes a rule of decision for the company to know the level of disclosure based on certain characteristics of the governance strategy adopted by the latter.

Keywords: corporate governance, disclosure, decision tree, economics

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Authors: Komal Ghafoor, Tauqir Ahmad, Murtaza Hanif, Hira Zaheer

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Assistive technology has been developed to support visually impaired people in their social interactions. Conversation assistive technology is designed to enhance communication skills, facilitate social interaction, and improve the quality of life of visually impaired individuals. This technology includes speech recognition, text-to-speech features, and other communication devices that enable users to communicate with others in real time. The technology uses natural language processing and machine learning algorithms to analyze spoken language and provide appropriate responses. It also includes features such as voice commands and audio feedback to provide users with a more immersive experience. These technologies have been shown to increase the confidence and independence of visually impaired individuals in social situations and have the potential to improve their social skills and relationships with others. Overall, conversation-assistive technology is a promising tool for empowering visually impaired people and improving their social interactions. One of the key benefits of conversation-assistive technology is that it allows visually impaired individuals to overcome communication barriers that they may face in social situations. It can help them to communicate more effectively with friends, family, and colleagues, as well as strangers in public spaces. By providing a more seamless and natural way to communicate, this technology can help to reduce feelings of isolation and improve overall quality of life. The main objective of this research is to give blind users the capability to move around in unfamiliar environments through a user-friendly device by face, object, and activity recognition system. This model evaluates the accuracy of activity recognition. This device captures the front view of the blind, detects the objects, recognizes the activities, and answers the blind query. It is implemented using the front view of the camera. The local dataset is collected that includes different 1st-person human activities. The results obtained are the identification of the activities that the VGG-16 model was trained on, where Hugging, Shaking Hands, Talking, Walking, Waving video, etc.

Keywords: dataset, visually impaired person, natural language process, human activity recognition

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Authors: Rodrigo C. Belleza, Jr., Roselyn A. Maaño, Karl Patrick E. Camota, Darwin Kim Q. Bulawan

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Eyes are an essential and conspicuous organ of the human body. Human eyes are outward and inward portals of the body that allows to see the outside world and provides glimpses into ones inner thoughts and feelings. Inevitable blindness and visual impairments may result from eye-related disease, trauma, or congenital or degenerative conditions that cannot be corrected by conventional means. The study emphasizes innovative tools that will serve as an aid to the blind and visually impaired (VI) individuals. The researchers fabricated a prototype that utilizes the Microsoft Kinect for Windows and Arduino microcontroller board. The prototype facilitates advanced gesture recognition, voice recognition, obstacle detection and indoor environment navigation. Open Computer Vision (OpenCV) performs image analysis, and gesture tracking to transform Kinect data to the desired output. A computer vision technology device provides greater accessibility for those with vision impairments.

Keywords: algorithms, blind, computer vision, embedded systems, image analysis

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Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

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Authors: Umut Erksan Senalp

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The aim of this study is to examine the link between firm level productivity heterogeneity and firm’s decision to export. Thus, we test the self selection hypothesis which suggests only more productive firms self select themselves to export markets. We analyze UK manufacturing sector by using firm-level data for the period 2003-2011. Although our preliminary results suggest that exporters outperform non-exporters when we pool all manufacturing industries, when we examine each industry individually, we find that self-selection hypothesis does not hold for each industries.

Keywords: total factor productivity, firm heterogeneity, international trade, decision to export

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Authors: Juliana Barcelos Cordeiro, Khashayar Mahani, Farbod Farzan, Mohsen A. Jafari

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Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  

Keywords: energy consumption forecasting, energy efficiency, load disaggregation, pattern recognition approach

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Authors: Ian A. McCulloh, Madelaine Zinser, Jesse Patsolic, Michael Ramos

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Recommender systems are a common artificial intelligence (AI) application. For any given input, a search system will return a rank-ordered list of similar items. As users review returned items, they must decide when to halt the search and either revise search terms or conclude their requirement is novel with no similar items in the database. We present a statistically designed experiment that investigates the impact of similarity ratings on human judgement to conclude a search item is novel and halt the search. 450 participants were recruited from Amazon Mechanical Turk to render judgement across 12 decision tasks. We find the inclusion of ratings increases the human perception that items are novel. Percent similarity increases novelty discernment when compared with star-rated similarity or the absence of a rating. Ratings reduce the time to decide and improve decision confidence. This suggests the inclusion of similarity ratings can aid human decision-makers in knowledge search tasks.

Keywords: ratings, rankings, crowdsourcing, empirical studies, user studies, similarity measures, human-centered computing, novelty in information retrieval

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Authors: Matthias Nnadi

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Using samples of 250 large listed firms by market capitalization in China and Hong Kong, we conducted empirical test to determine the impact of regulatory environment on reporting quality following IFRS convergence using three financial reporting measures; earning management, timely loss recognition and value relevance. Our results indicate that accounting data are more value relevant for Hong Kong listed firms than the Chinese A-share firms. The empirical results for timely loss recognition further reveal that there is a larger coefficient estimate on bad news earnings, which suggests that Chines A-share firms are more likely to report losses in a timely manner. The results support the evidence that substantial convergence of IFRS can improve financial reporting quality in a regulated environment such as China. This further supports the expectation that IFRS are relevant to China and has positive effect on its accounting practice and quality.

Keywords: reporting, quality, earning, loss, relevance, financial, China, Hong Kong

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Authors: Nazif Fuat Turkmen

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Domestic violence is the most common form of violence that risks the health and psychological well-being of victims and its witnesses. Psychology as a scientific field has made contributions in research, exploration, assessment, intervention, and prevention of domestic violence. The present study will be exploring the level of recognition of Turkish Cypriots on domestic violence and their understanding about it in general terms. While discussing the level of awareness of Turkish Cypriots on domestic violence and the effects of this level of awareness on the general well-being of the members of the society, the most common types of domestic violence as well as how Turkish Cypriots recognize and interpret these different types will be explored. The participants consisted of 224 Turkish Cypriots; 48.4% (n= 109) were female, 51.1% (n=115) were male. For the purpose of the study, a 28-item questionnaire was prepared and used for data collection. According to the results, there is a strong relationship between the education level of the respondents and their awareness on domestic violence. The study shows that cultural approaches on child rearing effect people’s recognition of violence in general and awareness on domestic violence in particular.

Keywords: culture, domestic violence, health psychology, public health, Turkish Cypriots, violence

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Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Mojtaba Sadeghi, Farshid Baniassadi, Hamed Kashani

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One of the challenging issues faced by seismic retrofitting consultants and employers is quick decision-making on the demolition or retrofitting of a structure at the current time or in the future. For this reason, the existing models proposed by researchers have only covered one of the aspects of cost, execution method, and structural vulnerability. Given the effect of each factor on the final decision, it is crucial to devise a new comprehensive model capable of simultaneously covering all the factors. This study attempted to provide an integrated framework that can be utilized to select the most appropriate earthquake risk mitigation solution for buildings. This framework can overcome the limitations of current models by taking into account several factors such as cost, execution method, risk-taking and structural failure. In the newly proposed model, the database and essential information about retrofitting projects are developed based on the historical data on a retrofit project. In the next phase, an analysis is conducted in order to assess the vulnerability of the building under study. Then, artificial neural networks technique is employed to calculate the cost of retrofitting. While calculating the current price of the structure, an economic analysis is conducted to compare demolition versus retrofitting costs. At the next stage, the optimal method is identified. Finally, the implementation of the framework was demonstrated by collecting data concerning 155 previous projects.

Keywords: decision making, demolition, construction management, seismic retrofit

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Authors: Cherouk Amr Yassin

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This study aims to provide insight into consumer decision-making, which has become very complicated to understand and predict in the existing world of sustainable development. The deficiency of a good understanding of the tourist's perception and attitude toward sustainable development in the tourism industry may impede the ability of organizations to build a sustainable marketing orientation and may negatively influence predicted consumer response. Therefore, this research paper adds further insights into the attitude toward recommended eco-friendly hotel advertisements and their effect on the purchase intention of eco-friendly services. Structural equational modeling was completed to realize the effects of the variables under investigation. The findings revealed that consumer decision-making in choosing eco-friendly hotels is affected by the positive attitude toward sustainable development ads, influenced by informativeness and credibility as values perceived by eco-friendly hotels. This study provides practical implications for tourism, marketers, hotel managers, promoters, and consumers.

Keywords: attitude, consumer behavior, consumer decision making, eco-friendly hotels, perception, the tourism industry

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Authors: Narong Anurak

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The objective of this research was to study Brand Position Communication Channel in Brand Building in Rajabhat University Affecting Decision Making of Higher Education from of qualitative research and in-depth interview with executive members Rajabhat University and also quantitative by questionnaires which are personal data of students, study of the acceptance and the finding of the information of Rajabhat University, study of pattern or Brand Position Communication Channel affecting the decision making of studying in Rajabhat University and the result of the communication in Brand Position Communication Channel. It is found that online channel and word of mount are highly important and necessary for education business since media channel is a tool and the management of marketing communication to create brand awareness, brand credibility and to achieve the high acclaim in terms of bringing out qualified graduates. Also, off-line channel can enable the institution to survive from the high competition especially in education business regarding management of the Rajabhat University. Therefore, Rajabhat University has to communicate by the various communication channel strategies for brand building for attractive student to make decision making of higher education.

Keywords: brand position, communication channel, Rajabhat University, higher education

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Authors: Haiqiao Du, Qian Wang, Shuwei Wang, Jianan Li

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Purpose: The aim is to evaluate the effect of cochlear implantation (CI) in patients with unilateral hearing loss, with a view to providing data support for the selection of therapeutic interventions for patients with single-sided deafness (SSD)/asymmetric hearing loss (AHL) and the broadening of the indications for CI. Methods: The study subjects were patients with unilateral hearing loss who underwent cochlear implantation surgery in our hospital in August 2022 and were willing to cooperate with the test and were divided into 2 groups: SSD group and AHL group. The enrolled patients were followed up for hearing level, tinnitus changes, speech recognition ability, sound source localization ability, and quality of life at five-time points: preoperatively, and 1, 3, 6, and 12 months after postoperative start-up. Results: As of June 30, 2024, a total of nine patients completed follow-up, including four in the SSD group and five in the AHL group. The mean postoperative hearing aid thresholds on the CI side were 31.56 dB HL and 34.75 dB HL in the two groups, respectively. Of the four patients with preoperative tinnitus symptoms (three patients in the SSD group and one patient in the AHL group), all showed a degree of reduction in Tinnitus Handicap Inventory (THI) scores, except for one patient who showed no change. In both the SSD and AHL groups, the sound source localization results (expressed as RMS error values, with smaller values indicating better ability) were 66.87° and 77.41° preoperatively and 29.34° and 54.60° 12 months after postoperative start-up, respectively, which showed that the ability to localize the sound source improved significantly with longer implantation time. The level of speech recognition was assessed by 3 test methods: speech recognition rate of monosyllabic words in a quiet environment and speech recognition rate of different sound source directions at 0° and 90° (implantation side) in a noisy environment. The results of the 3 tests were 99.0%, 72.0%, and 36.0% in the preoperative SSD group and 96.0%, 83.6%, and 73.8% in the AHL group, respectively, whereas they fluctuated in the postoperative period 3 months after start-up, and stabilized at 12 months after start-up to 99.0%, 100.0%, and 100.0% in the SSD group and 99.5%, 96.0%, and 99.0%. Quality of life was subjectively evaluated by three tests: the Speech Spatial Quality of Sound Auditory Scale (SSQ-12), the Quality-of-Life Bilateral Listening Questionnaire (QLBHE), and the Nijmegen Cochlear Implantation Inventory (NCIQ). The results of the SSQ-12 (with a 10-point score out of 10) showed that the scores of preoperative and postoperative 12 months after start-up were 6.35 and 6.46 in the SSD group, while they were 5.61 and 9.83 in the AHL group. The QLBHE scores (100 points out of 100) were 61.0 and 76.0 in the SSD group and 53.4 and 63.7 in the AHL group for the preoperative versus the postoperative 12 months after start-up. Conclusion: Patients with unilateral hearing loss can benefit from cochlear implantation: CI implantation is effective in compensating for the hearing on the affected side and reduces the accompanying tinnitus symptoms; there is a significant improvement in sound source localization and speech recognition in the presence of noise; and the quality of life is improved.

Keywords: single-sided deafness, asymmetric hearing loss, cochlear implant, unilateral hearing loss

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Authors: Alexander N. Savostyanov, Tatyana A. Dolgorukova, Elena A. Esipenko, Mikhail S. Zaleshin, Margherita Malanchini, Anna V. Budakova, Alexander E. Saprygin, Yulia V. Kovas

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The present study compared spectral-power indexes and cortical topography of brain activity in a sample characterized by different levels of trait and mathematical anxiety. 52 healthy Russian-speakers (age 17-32; 30 males) participated in the study. Participants solved an error recognition task under 3 conditions: A lexical condition (simple sentences in Russian), and two numerical conditions (simple arithmetic and complicated algebraic problems). Trait and mathematical anxiety were measured using self-repot questionnaires. EEG activity was recorded simultaneously during task execution. Event-related spectral perturbations (ERSP) were used to analyze spectral-power changes in brain activity. Additionally, sLORETA was applied in order to localize the sources of brain activity. When exploring EEG activity recorded after tasks onset during lexical conditions, sLORETA revealed increased activation in frontal and left temporal cortical areas, mainly in the alpha/beta frequency ranges. When examining the EEG activity recorded after task onset during arithmetic and algebraic conditions, additional activation in delta/theta band in the right parietal cortex was observed. The ERSP plots reveled alpha/beta desynchronizations within a 500-3000 ms interval after task onset and slow-wave synchronization within an interval of 150-350 ms. Amplitudes of these intervals reflected the accuracy of error recognition, and were differently associated with the three (lexical, arithmetic and algebraic) conditions. The level of trait anxiety was positively correlated with the amplitude of alpha/beta desynchronization. The level of mathematical anxiety was negatively correlated with the amplitude of theta synchronization and of alpha/beta desynchronization. Overall, trait anxiety was related with an increase in brain activation during task execution, whereas mathematical anxiety was associated with increased inhibitory-related activity. We gratefully acknowledge the support from the №11.G34.31.0043 grant from the Government of the Russian Federation.

Keywords: anxiety, EEG, lexical and numerical error-recognition tasks, alpha/beta desynchronization

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Authors: Taju Mohammednur, Tesfaye Megersa, Karta Kaske

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Coffee is an economically important cash crop in Ethiopia. However, the conditions under which coffee seeds are dried and processed significantly affect the seedling quality and productivity. The objective of this study was to evaluate the effect of pre-sowing treatments and drying methods on the physiological quality of coffee seeds and seedlings. The study included two coffee varieties (74110, 75227), two drying conditions (under-shade drying room, open sun), and five durations of seed hydro priming (6, 8, 18, 24 hours, and an untreated control). Factorial combinations of the three factors were laid out in a Completely Randomized Design of three replications. Results indicated that the highest germination percentage (91%), emergence rate (90%), and seedling vigor index-I (2236 cm %) were recorded for seeds dried under-shade drying room. In contrast, the lowest values of germination percentage, emergence rate, and vigor index were observed for seeds dried under open sun. There was a significant difference in seed germination based on hydro priming time, with the highest germination percentage (83%) recorded for seeds soaked for 6 hours, followed by 24 hours (83%). The lowest germination percentage (77%) was recorded for un-soaked seeds. In conclusion, drying seeds under shade is better for coffee seed quality, and hydro priming has improved seedling vigor. However, further investigation into seed priming methods and preservation techniques for primed seeds is necessary to improve coffee seed quality.

Keywords: coffee, germination, seed drying, seed longevity, seed priming

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Authors: Sham Kidane, Fitsum Gaim, Ibrahim Abdella, Sirak Asmerom, Yoel Ghebrihiwot, Simon Mulugeta, Natnael Ambassager

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The lack of annotated datasets is a bottleneck to the progress of NLP in low-resourced languages. The work presented here consists of large-scale annotated datasets and models for the named entity recognition (NER) system for the Tigrinya language. Our manually constructed corpus comprises over 340K words tagged for NER, with over 118K of the tokens also having parts-of-speech (POS) tags, annotated with 12 distinct classes of entities, represented using several types of tagging schemes. We conducted extensive experiments covering convolutional neural networks and transformer models; the highest performance achieved is 88.8% weighted F1-score. These results are especially noteworthy given the unique challenges posed by Tigrinya’s distinct grammatical structure and complex word morphologies. The system can be an essential building block for the advancement of NLP systems in Tigrinya and other related low-resourced languages and serve as a bridge for cross-referencing against higher-resourced languages.

Keywords: Tigrinya NER corpus, TiBERT, TiRoBERTa, BiLSTM-CRF

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Authors: Gunnar Oskarsson, Gudjon Helgi Egilsson

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Due to globalization, small and medium-sized enterprises (SME) increasingly offer their products and services in foreign markets. The main reasons are either to compensate for a decreased market share in their home market or to exploit opportunities in foreign markets, which are becoming less distant and better accessible than before. International markets are particularly important for companies located in a small economy and offering specialized products. Although more accessible, entering international markets is both expensive and difficult. In order to select the most appropriate markets, it is, therefore, important to gain an insight into the factors that have an impact on success, or potential failure. Although there has been a reasonable volume of research into the theory of internationalization, there is still a need to gain further understanding of the decision-making process of SMEs in small economies and the most important characteristics that distinguish between success and failure. The main objective of this research is to enhance knowledge on the internationalization of SMEs, including the drivers for the decision to internationalize, and the most important factors contributing to success in their internationalization activities. A qualitative approach was found to be most appropriate for this kind of research, with the objective of gaining a deeper understanding and discovering factors which impact a company’s decision-making and potential success. In-depth interviews were conducted with 14 companies in different industries located in Iceland, a country extensively dependent on export revenues. The interviews revealed several factors as drivers of internationalization and, not surprisingly, the most frequently mentioned source of motivation was that the local market is inadequate to maintain a sustainable operation. Good networking relationships were seen as a particular priority for potential success, searching for new markets was mainly carried out through the internet, although sales exhibitions and sales trips were also considered important. When it comes to the final decision as to whether a market should be considered for further analysis, economy, labor cost, legal environment, and cultural barriers were the most common factors to be weighted. The ultimate answer to successful internationalization, however, is largely dependent on a coordinated and experienced management team. The main contribution of this research is offering an insight into factors affecting decision-making in the internationalization process of SMEs, based on the opinion and experience of managers of SMEs in a small economy.

Keywords: internationalization, success factors, small and medium-sized enterprises (SMEs), drivers, decision making

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Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

Abstract:

The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

Procedia PDF Downloads 138

Authors: Phang Moon Leng

Abstract:

Automated Early Warning Scores is a newly developed clinical decision tool that is used to streamline and improve the process of obtaining a patient’s vital signs so a clinical decision can be made at an earlier stage to prevent the patient from further deterioration. This technology provides immediate update on the score and clinical decision to be taken based on the outcome. This paper aims to study the use of an automated early warning score system on whether the technology has assisted the hospital in early detection and escalation of clinical condition and improve patient outcome. The hospital adopted the Modified Early Warning Scores (MEWS) Scoring System and MEWS Clinical Response into Philips IntelliVue Guardian Automated Early Warning Score equipment and studied whether the process has been leaned, whether the use of technology improved the usage & experience of the nurses, and whether the technology has improved patient care and outcome. It was found the steps required to obtain vital signs has been significantly reduced and is used more frequently to obtain patient vital signs. The number of deaths, and length of stay has significantly decreased as clinical decisions can be made and escalated more quickly with the Automated EWS. The automated early warning score equipment has helped improve work efficiency by removing the need for documenting into patient’s EMR. The technology streamlines clinical decision-making and allows faster care and intervention to be carried out and improves overall patient outcome which translates to better care for patient.

Keywords: automated early warning score, clinical quality and safety, patient safety, medical technology

Procedia PDF Downloads 178

Authors: Dinamarie Fonzone

Abstract:

Employer-sponsored health insurance (ESI) strategic decision-making processes rely on financial analysis to guide leadership in choosing plans that will produce optimal organizational spending outcomes. These financial decision-making methods have not abated ESI costs. Previously unrecognized external social determinants, the impact on ESI plan spending, and other organizational strategies are emerging and are important considerations for organizational decision-makers and change management practitioners. The purpose of thisstudy is to examine the relationship between the social determinants of health (SDoH), employer-sponsored health insurance (ESI) plans, andthe unintended consequence of health inequity. A quantitative research design using selectemployee records from an existing employer human capital management database will be analyzed. Statistical regressionmethods will be used to study the relationships between certainSDoH (employee income, neighborhood geographic living area, and health care access) and health plan utilization, cost, and chronic disease prevalence. The discussion will include an application of the social gradient of health theory to the study findings, organizational transformation through changes in ESI decision-making mental models, and the connection of ESI health inequity to organizational development and changediversity, equity, and inclusion strategies.

Keywords: employer-sponsored health insurance, social determinants of health, health inequity, mental models, organizational development, organizational change, social gradient of health theory

Procedia PDF Downloads 108

Authors: Cansu Kandemir, Marco Franchino

Abstract:

To attain sustainability goals, the manufacturing industries must assess and improve their processes, adopt the latest technologies, and ensure minimal environmental impact. Ongoing debates claim that the definition of sustainability and its assessment is vague. Companies struggle with understanding which processes they should prioritise and necessitate a methodology to aid decision-making. For that reason, our investigation focused on defining a prioritisation guide to help to manufacture engineers identify areas of a facility to prioritise de-carbonisation efforts based on existing sources of data. The authors at the University of Sheffield Advanced Manufacturing Research Centre (AMRC) worked with a range of major businesses, including Food and Drink (Moy Park), Automotive (Nissan), Aerospace and Defence (BAE, Meggitt, Leonardo, and GKN) and Technology (Accenture and Intellium AI). Collected information has been integrated into a prioritisation guide framework that helps process comparison and decision-making. The framework developed in this study aims to ensure that companies have guidance on where to focus their efforts whilst striving to fulfil their environmental and societal obligations.

Keywords: decision making, sustainability, carbon emissions, manufacturing

Procedia PDF Downloads 61

Authors: Khaled M. Ali, M. A. Abdel-Hamid, Ayman A. Mostafa

Abstract:

Objective: Safety and efficacy of Ahmed glaucoma valve implantation for the management of uveitis induced glaucoma evaluated on the five dogs with uncontrollable glaucoma. Materials and Methods: Ahmed Glaucoma Valve (AGV®; New World Medical, Rancho Cucamonga, CA, USA) is a flow restrictive, non-obstructive self-regulating valve system. Preoperative ocular evaluation included direct ophthalmoscopy and measurement of the intraocular pressure (IOP). The implant was examined and primed prior to implantation. The selected site of the valve implantation was the superior quadrant between the superior and lateral rectus muscles. A fornix-based incision was made through the conjunectiva and Tenon’s capsule. A pocket is formed by blunt dissection of Tenon’s capsule from the episclera. The body of the implant was inserted into the pocket with the leading edge of the device around 8-10 mm from the limbus. Results: No post operative complications were detected in the operated eyes except a persistent corneal edema occupied the upper half of the cornea in one case. Hyphaema was very mild and seen only in two cases which resolved quickly two days after surgery. Endoscopical evaluation for the operated eyes revealed a normal ocular fundus with clearly visible optic papilla, tapetum and retinal blood vessels. No evidence of hemorrhage, infection, adhesions or retinal abnormalities was detected. Conclusion: Ahmed glaucoma valve is safe and effective implant for treatment of uveitic glaucoma in dogs.

Keywords: Ahmed valve, endoscopy, glaucoma, ocular fundus

Procedia PDF Downloads 587

Authors: Xuan Linh Nguyen, Tien Yin Chou, Yao Min Fang, Feng Cheng Lin, Thanh Van Hoang, Yin Min Huang

Abstract:

In Vietnam, land use planning is the most important and powerful tool of the government for sustainable land use and land management. Nevertheless, many of land use planning locations are facing protests from surrounding households due to environmental impacts. In addition, locations are planned completely based on the subjective decisions of planners who are unsupported by tools or scientific methods. Hence, this research aims to assist the decision-makers in evaluating the rationality of planning locations by developing a Spatial Decision Support System (SDSS) using approaches of Geographic Information System (GIS)-based technology, Analytic Hierarchy Process (AHP) multi-criteria-based technique and Fuzzy set theory. An ArcGIS Desktop add-ins named SDSS-LUPA was developed to support users analyzing data and presenting results in friendly format. The Fuzzy-AHP method has been utilized as analytic model for this SDSS. There are 18 planned locations in Hung Ha district (Thai Binh province, Vietnam) as a case study. The experimental results indicated that the assessment threshold higher than 0.65 while the 18 planned locations were irrational because of close to residential areas or close to water sources. Some potential sites were also proposed to the authorities for consideration of land use planning changes.

Keywords: analytic hierarchy process, fuzzy set theory, land use planning, spatial decision support system

Procedia PDF Downloads 379

Authors: Mui Joo Tang, Eang Teng Chan

Abstract:

Advertising is commonly used to foster sales and reputation of an institution. It is at first the growth of print advertising that has increased the population and number of periodicals of newspaper and its circulation. The rise of Internet and online media has somehow blurred the role of media and advertising though the intention is still to reach out to audience and to increase sales. The relationship between advertising and audience on a product purchase through persuasion has been developing from print media to online media. From the changing media environment and audience, it is the concern of this research to study the impact of online advertising to such a relationship cycle. The content of online advertisements is much of text, multimedia, photo, audio and video. The messages of such content format may indeed bring impacts to its audience and its credibility. This study is therefore reflecting the effectiveness of online advertisement and its influences on generation Y in their purchasing behavior. This study uses Media Dependency Theory to analyze the relationship between the impact of online advertisement and media usage pattern of generation Y. Hierarchy of Effectiveness Model is used as a marketing communication model to study the effectiveness of advertising and further to determine the impact of online advertisement on generation Y in their purchasing decision making. This research uses online survey to reach out the sample of generation Y. The results have shown that online advertisements do not affect much on purchase decision making even though generation Y relies much on the media content including online advertisement for its information and believing in its credibility. There are few other external factors that may interrupt the effectiveness of online advertising. The very obvious influence of purchasing behavior is actually derived from the peers.

Keywords: generation Y, purchase decision, print media, online advertising, persuasion

Procedia PDF Downloads 527