Recommendation

The provision of the same pedagogical and educational methods to all students is pedagogically ineffective. In contrast, more effectively have proved the pedagogical strategies that adapt to the real individual skills of the students. An important innovation in this direction is the Adaptive Educational Systems (AES) that adjust the teaching content on educational needs and students' skills. Effective utilization of these approaches can be enhanced with Artificial Intelligence (AI) and Semantic Web technologies that can increase data generation, access, flow, integration, and comprehension using the very same open standards that drive the World Wide Web (URIs, HTTP, and HTML). This study proposes a novel Adaptive Educational eLearning System (AEeLS) that has the capacity to gather and analyze data from learning repositories and to adapt these to the educational curriculum according to the student skills and experience. It is an innovative hybrid machine learning system that combines a Semi-Supervised Classification method for ontology matching and a Recommendation Mechanism that uses a sophisticated method from neighborhood-based collaborative and content-based filtering techniques, in order to provide a personalized educational environment for each student.

Uncertain times require prompt reflexes to survive and this study is a collaborative reflex to better understand uncertainty and navigate through it. The Coronavirus (Covid-19) pandemic hit hard and interrupted many dimensions of our lives, particularly education. As a response to interruption of education due to the Covid-19 pandemic, this study is a collaborative reaction that narrates the overall view, reflections from the K12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62.7% of the whole world population. In addition to the value of each case by country, the synthesis of this research suggests that the current practices can be defined as emergency remote education and this practice is different from planned practices such as distance education, online learning or other derivations. Above all, this study points out how social injustice, inequity and the digital divide have been exacerbate...

and watch. During the top) service has seen an exponential a growing activity and on this field. In past few Paper, human emotions to provide dynamic content recommen deep list of movies overcome problem in existing method. Keywords When television first came player emerge in the market. with the introduction of the Netflix, Amazon Prime and many other OTT(Over the top) media around provides the has changed the way users interact with video content. films and human emotions. Emotions neurophysiologic pleasure or displeasure. The recent advancement in machine learning, Computer vision and recommendation has achieved studies on computer vision, there is a possibility of improving the quality of Recommendation System whose primary goal is to predict predictions we decide whether to learning have become very popular target their content to a specific audience. they can d The motivation in this work to use emotion technique in recommendation system to generate additional input movie recommendation system a system,

Modelling the diverse desires of users through their economic models for recommendation systems is difficult and essential. Past Techniques utilize successive neural networks to convert the historical experiences of customers across left to right into encoded suggestion models. Recommendation systems in e-commerce are becoming an integral means of making consumers navigate the content accessible. Recommender systems are an important aspect of E-commerce platforms that assist consumers choose products of choice on a wide scale through huge investments. The metadata termed the contextual phrase, that incorporates the reference label, and the description of the quote proves have been used by several authors to locate the relevant research referenced. The lack of a well-established benchmarking dataset and no tool for recommendations that can achieve great efficiency has perhaps made the study challenging. The foundation of mutual marketplace stages in the rental property field is the personalization of recommendation systems. To support people, such a framework provides a valuable tool. The current technique aims to determine the context of the movie plot summary from the given movies using BERT as-a-service and to predict similar movie recommendations.

Content, usability, and aesthetics are core constructs in users' perception and evaluation of websites, but little is known about their interplay in different use phases. In a first study web users (N=330) stated content as most relevant, followed by usability and aesthetics. In study 2 tests with four websites were performed (N=300), resulting data were modeled in path analyses. In this model aesthetics had the largest influence on first impressions, while all three constructs had an impact on first and overall impressions. However, only content contributed significantly to the intention to revisit or recommend a website. Using data from a third study (N=512, 42 websites), we were able to replicate this model. As before, perceived usability affected first and overall impressions, while content perception was important for all analyzed website use phases. In addition, aesthetics also had a small but significant impact on the participants' intentions to revisit or recommend.

The legal norms govern the conduct of the human being but there is no adequate legislation or regulation about the artificial intelligence which is more influenced creation than human in public and private sector all over the world. It is urgent needs of world in international and national level that should be considered appropriate method to govern them in order to solve the future crisis. Our country also is to be prepared to face the problem in legal manner by way of adopting legislation.

Artificial intelligence is broad conceptual term for the technologies and makes it possible to perform like human including decision making, self-driving car, robotic surgical equipment, automated accounting and security system including software performing legal tasks. Therefore, artificial intelligence technology will need to advance creative concept for addressing issues as legal duty, legal protection and liability.

In Sri Lanka, there is an Association for Artificial intelligence which is established in 2000 for non-profit purpose to develop the techniques of the artificial intelligence. Our country is ready to promote these technical skills but there is no law to regulate properly. Section 6 of Intellectual Property Law Act No 36 of 2003 is mentioned about protection for computer programs. It is not enough to deal all the relevant matter of Artificial Intelligence.

Apart from that, there is no more legal provision. Policy makers would not be kept silent until raise the problem and start to think wider manner that would be good for the country to adopt new technology rather than depending on traditional system because the world is busy to find out new things and we have to prepare ourselves to go with them. Otherwise, Sri Lanka will not achieve anything even in technology. Therefore, the legislation for Artificial Intelligence is a present need of society, for that purpose this study will examine the legal status, legal issues, and legal protection especially in the area of Intellectual Property Rights and with the comparative analysis of other countries legislation.

All critical infrastructures around the globe have become an increasing target of cyberattacks day by day. These cyberattacks are significantly concerning the healthcare sector as their primary target [1,2]. The last few years have seen the healthcare sector is undergoing an extraordinary transformation. There is a substantial shift from traditional system procedures towards modern, automated, and complex systems [2]. The outdated IT infrastructure, insecure database approaches, vulnerability systems still exist in most early level healthcare firms. They are not efficient to manage the high amount of data processing, new types of equipment and storage needs. When examining the adoption of Healthcare Information Systems (HIS) in the healthcare industry, the security of patient's data, data of hospital employees and hospital informational data is the most overbearing restrictions to access for the cyber attackers [3]. The study will discuss the critical infrastructure security of the healthcare industry, and threats to healthcare infrastructure and various techniques that can use to prevent happening cyberattacks and how to apply them to the IoT [Internet of Things] based health care sector. The study also focuses on Encryption standards used in the health care sector to defend its infrastructure from cyber threats.

ABSTRAK Pendahuluan:Keamanan dan keselamatan pasien perlu diperhatikan oleh perawat saat memberikan pelayanan kepada pasien. Kesalahan komunikasi antar perawat dalam kerjasama interdisipliner menjadi penyebab lazimnya cedera pasien.Teknik komunikasi yang digunakan untuk menjaga keamanan dan keselamatan pasien adalah dengan teknik SBAR (Situation, Background, Assessment, Recommendation), namun implementasi penggunaan komunikasi SBAR banyak menemui kendala.Tujuan: Penelitian ini untuk mengetahui gambaran penerapan komunikasi SBAR (Situation, Background, Assesment, Recommendation) di RSUD Dr. Soewondo Kendal. Metode: Penelitian ini menggunakan desaindeskriptif exploratifnon hipotesis dengan pendekatancross sectional. Sampel dalam penelitian ini diambil dengan menggunakan Proportionate Stratified Random Sampling sebanyak132 perawat di RSUD Dr. H. Soewondo Kendal. Alat penelitian menggunakan kuesionerkarakteristik, dan kuesioner penerapan komunikasi SBAR yang dianalisis secara univariat.Hasil: Hasil penelitian ini menunjukkan perawat di RSUD Dr. H. Soewondo Kendal sebagian besar menerapkan komunikasi SBAR dengan baik (59,1%), namun tidak secara utuh dalam penerapannya. Pembahasan: Penerapan komunikasi SBAR yang tidak baik adalah tidak menyebutan umur dan tanggal masuk pasien (100%), adanya alergi makanan (22,7%), hasil pemeriksaan laboratorium (51,5%), vital sign (38,6%), kemungkinan masalah atau resiko (10%), mengusulkan dokter untuk melihat kondisi pasien (65,9%), memastikan waktu kedatangan dokter (61,4%). Saran: Peneliti selanjutnya diharapkan mengembangkan variabel-variabel yang berhubungan dengan penerapan komunikasi efektif menggunakan SBAR.

تظهر الدراسات الدولية بشكل مستمر أن سلوك الحركة (النشاط البدني، والسلوك الخامل، والنوم(
التي نقوم بها خلال اليوم تعتبر مؤشرات رئيسية للصحة. ترتبط هذه السلوكيات ببعضها ارتباطاً وثيقاً
ومع ذلك فإن العديد من الإرشادات المتعلقة بالعوامل المرتبطة بالحركة تركز على كل سلوك حركي
منها بشكل منفصل، وهذا غير كافٍ لتطوير وتطبيق التوصيات اللازمة لتحقيق الصحة العقلية والبدنية
والادراكية للمستهدفين. لكن النهج الموحد يأخذ في الاعتبار السلوك الحركي الشامل على مدار 24
ساعة، والذي يتكون من فترات من النشاط البدني والخمول البدني والنوم (مدة النوم).
ولذلك، فإن وجود مصدر واحد شامل يعتبر أكثر كفاءة لتحسين صحة الفرد والوقاية من الأمراض المزمنة
وبالتالي تقليل معدلات الإصابة بالأمراض والوفيات، وقد قدمت منظمة الصحة العالمية WHO
والعديد من الدول الرائدة في هذا المجال مثل كندا، واستراليا، وجنوب أفريقيا إرشادات الحركة ومدة
النوم على مدار 24 ساعة للفئات التالية: السنوات الأولى (من الولادة وحتى 4 سنوات)، الأطفال
والشباب (من 5 – 18 سنة)، البالغين (من 19 – 64 سنة)، كبار السن (65 سنة فما فوق).

With the increase of volume, velocity, and variety of big data, the traditional collaborative filtering recommendation algorithm, which recommends the items based on the ratings from those like-minded users, becomes more and more inefficient. In this paper, two varieties of algorithms for col-laborative filtering recommendation system are proposed. The first one uses the improved k-means clustering technique while the second one uses the improved k-means clustering technique coupled with Principal Component Analysis as a dimensionality reduction method to enhance the recommendation accuracy for big data. The experimental results show that the proposed algorithms have better recommendation performance than the traditional collaborative filtering recommendation algorithm.

Recent statistics and available data show that Saudi Arabia is one of the countries with the lowest levels of physical activity and the highest levels of sedentary behavior, as well as a lack of sufficient
sleep. The absence of national guidelines on physical activity, sedentary behavior, and sleep duration that incorporate cultural differences have prompted the development of the Saudi 24-Hour-Movement guidelines. Promoting physical activity has been on the agenda of the Saudi
government and other national organizations over the past two decades and is a priority of the Saudi Vision 2030 goals.

Uncertain times require prompt reflexes to survive and this study is a collaborative reflex to better understand uncertainty and navigate through it. The Coronavirus (Covid-19) pandemic hit hard and interrupted many dimensions of our lives, particularly education. As a response to interruption of education due to the Covid-19 pandemic, this study is a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population. In addition to the value of each case by country, the synthesis of this research suggests that the current practices can be defined as emergency remote education and this practice is different from planned practices such as distance education, online learning or other derivations. Above all, this study points out how social injustice, inequity and the digital divide have been exacerbat...

Uncertain times require prompt reflexes to survive and this study is a collaborative reflex to better understand uncertainty and navigate through it. The Coronavirus (Covid-19) pandemic hit hard and interrupted many dimensions of our lives, particularly education. As a response to interruption of education due to the Covid-19 pandemic, this study is a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population. In addition to the value of each case by country, the synthesis of this research suggests that the current practices can be defined as emergency remote education and this practice is different from planned practices such as distance education, online learning or other derivations. Above all, this study points out how social injustice, inequity and the digital divide have been exacerbat...

Uncertain times require prompt reflexes to survive and this study is a collaborative reflex to better understand uncertainty and navigate through it. The Coronavirus (Covid-19) pandemic hit hard and interrupted many dimensions of our lives, particularly education. As a response to interruption of education due to the Covid-19 pandemic, this study is a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population. In addition to the value of each case by country, the synthesis of this research suggests that the current practices can be defined as emergency remote education and this practice is different from planned practices such as distance education, online learning or other derivations. Above all, this study points out how social injustice, inequity and the digital divide have been exacerbat...

Uncertain times require prompt reflexes to survive and this study is a collaborative reflex to better understand uncertainty and navigate through it. The Coronavirus (Covid-19) pandemic hit hard and interrupted many dimensions of our lives, particularly education. As a response to interruption of education due to the Covid-19 pandemic, this study is a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population. In addition to the value of each case by country, the synthesis of this research suggests that the current practices can be defined as emergency remote education and this practice is different from planned practices such as distance education, online learning or other derivations. Above all, this study points out how social injustice, inequity and the digital divide have been exacerbat...

8th International Conference on Data Mining and Applications (DMAP 2022) provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Data mining and Applications.

Uncertain times require prompt reflexes to survive and this study is a collaborative reflex to better understand uncertainty and navigate through it. The Coronavirus (Covid-19) pandemic hit hard and interrupted many dimensions of our lives, particularly education. As a response to interruption of education due to the Covid-19 pandemic, this study is a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population. In addition to the value of each case by country, the synthesis of this research suggests that the current practices can be defined as emergency remote education and this practice is different from planned practices such as distance education, online learning or other derivations. Above all, this study points out how social injustice, inequity and the digital divide have been exacerbat...

This paper focuses on open public policies that are related to youth employment and hence to human capital or skills training. From the objective of this study, it is important to recognize that debates around public development policies, focused on external openness and youth employment, have always existed in both developed and underdeveloped countries. Inspired by all these debates, we were able to develop our hypothesis and, subsequently, an adequate methodology to verify them. This shows a causality between the variables: external openness, employment and qualifying training or public policy. Thus, we will start from the neoclassical economic theory that relates production, capital, and employment to develop our econometric model. We, therefore, found that it is appropriate to use VAR (value at risk) modeling to analyze the interrelationship between the variables: open access, human capital and employment. The data come from the World Bank, specifically from the "World Development Indicators" , which has earned us a longitudinal sectional study over the period from 1979 to 2014. It uses Word and Excel software to ensure the processing of our data as well as Eviews for the analysis of our data. In this way, we arrive at the result and the recommendations according to which it is necessary to upgrade the GESP (strategy documents for growth and employment in Cameroon). In their elaboration in August 2009, they were focused on the global economic crisis in providing, among other things, appropriate responses to the problems raised by the so-called crisis. This has also placed growth and employment in Cameroon at the center of their actions. To this end, the integration of young people should start from public policies according to the sectors of news and concerns of the jobs of subcontracting and the jobs of transition. It insists on the formations qualifying and, in the long run, the auto employment of the young people.

"The research studied the factors that affect consumers’ behavioural intention towards apparel stores. Three different aspects of behavioural intention were examined: consumers’ purchase intention (PI), willingness to pay more (WPAY), and brand recommendation (RECM). Specifically the authors propose a model in which consumer satisfaction with the store brand mediates the effects of attitude towards sales personnel and the convenience of the store’s payment conditions or options on PI, WPAY, and RECM. The relationships hypothesized in the model were tested using two apparel store brands familiar to consumers in the city of Istanbul, Turkey. All findings were in favour of the model proposed for both apparel store brands studied, which were either a sample of men or women.

Keywords: satisfaction, willingness to pay more, purchase intention, recommendation, payment conditions, attitude towards sales personnel."

Uncertain times require prompt reflexes to survive and this study is a collaborative reflex to better understand uncertainty and navigate through it. The Coronavirus (Covid-19) pandemic hit hard and interrupted many dimensions of our lives, particularly education. As a response to interruption of education due to the Covid-19 pandemic, this study is a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population. In addition to the value of each case by country, the synthesis of this research suggests that the current practices can be defined as emergency remote education and this practice is different from planned practices such as distance education, online learning or other derivations. Above all, this study points out how social injustice, inequity and the digital divide have been exacerbat...

— Social media are progressively being utilized as a part of mainstream researchers as a key wellspring of information to help comprehend differing common and social term, and this has prompted the advancement of an extensive variety of computational information mining apparatuses that can remove learning from web-based social networking for both ad-hoc and ongoing examination. The expansion of enthusiasm for utilizing web-based social networking as a hotspot for look into has roused handling the test of consequently geolocating tweets, given the absence of express area data in the lion's share of tweets. As opposed to much past work that has concentrated on area grouping of tweets limited to a particular nation, here we attempt the assignment in a more extensive setting by ordering worldwide tweets at the country level, which is so far unexplored in an ongoing situation. We break down the degree to which a tweet's nation of starting point can be dictated by making utilization of eight tweet-inherent highlights for classification.

A controlled field study of wine promotions in a mid-price chain restaurant generated three key findings: 1) effective wine recommendations increased sales by 12%, 2) effective food-wine pairing recommendations increased sales by 7.6%, and 3) effective wine tastings increased sales by 48%. In general, 21% of the increase in sales of promoted wines come from possible risk-averse diners who would ordinarily not purchase wine. Specific implications for responsible restaurateurs are outlined, including the caveat to not cannibalize sales by promoting a lower margin, lower profit wine.

Uncertain times require prompt reflexes to survive and this study is a collaborative reflex to better understand uncertainty and navigate through it. The Coronavirus (Covid-19) pandemic hit hard and interrupted many dimensions of our lives, particularly education. As a response to interruption of education due to the Covid-19 pandemic, this study is a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population. In addition to the value of each case by country, the synthesis of this research suggests that the current practices can be defined as emergency remote education and this practice is different from planned practices such as distance education, online learning or other derivations. Above all, this study points out how social injustice, inequity and the digital divide have been exacerbat...

This research examines how customers' perceptions about controversial labor practices of food delivery platforms may affect their intentions to use and recommend these services. Three studies reveal that customers' behavioral intentions depend on their perceptions of the working conditions for the delivery workers, as well as service quality. This influence is higher among customers with a high level of social conscious consumption. Our research also explores the costs that customers would be willing to assume to be served by a food delivery service that offers better working conditions. These insights reveal several relevant managerial implications for gig economy firms.

Purpose – Our study analyzes the non-linear effect of customer lifetime
value (CLV), which accounts for the revenue accumulated over the
lifetime of a customer relationship, calculated using a discount rate,
on customer referral value (CRV), which accounts for the value created
by customers converted to the firm.
Design/methodology/approach – We collected data from customers
of a financial institution that provides retirement plan products. A
random sample of 768 customers provided the full names of individuals
to whom they made a recommendation. After these names were elicited,
respondents and referrals were identified in the firm’s records, and we
calculated the CLV and CRV values.
Findings – The results show the existence of a U-shaped effect of
CLV on CRV, and a negative linear effect of CLV on recommendation
intention.
Originality/value – Our study contributes to the body of literature on
word of mouth by focusing on a product and business segment with
low perceived brand differentiation and low customer involvement.
We contribute to the marketing literature by showing a U-shape
relationship between CLV and word of mouth activity, represented
by CRV

This research examines how customers' perceptions about controversial labor practices of food delivery platforms may affect their intentions to use and recommend these services. Three studies reveal that customers' behavioral intentions depend on their perceptions of the working conditions for the delivery workers, as well as service quality. This influence is higher among customers with a high level of social conscious consumption. Our research also explores the costs that customers would be willing to assume to be served by a food delivery service that offers better working conditions. These insights reveal several relevant managerial implications for gig economy firms.

—Information filtering and recommender systems exploit various techniques to deal with the information overload problem. One popular technique for making recommendations is based on trust statements between users in a social network. Yet explicit trust statements are usually very sparse leading to the need for expanding the trust networks by inferring new trust relationships. This study proposes a novel model to infer new trusted neighbors and combines it with existing methods to achieve a fully expanded trust network. Experimental results demonstrate that the proposed method outperforms the existing methods.

Smoke inhalation causes systemic and mucosal toxicity due to the asphyxiant and irritant properties of toxic gases. It represents the first cause of death at the fire scene and after hospital admission. Carbon monoxide and cyanide are the main gases produced during combustion in fires: they are responsible for a syndrome of oxygen deprivation. In smoke inhalation victims, loss of consciousness may result from either CO or CN inhalation, although differentiating the exact role of each of them remains quite impossible. The occurrence of hypotension, abnormal respiratory pattern and/or significant lactic acidosis (with plasma lactate concentration ≥10 mmol/l) is consistent with smoke inhalation induced-cyanide poisoning. Irritant gases contained in smoke are responsible for the ocular and respiratory mucosal injuries. Dysphonia and bronchial ronchi are predictive of delayed lung injury possibly resulting in acute respiratory failure. In smoke inhalation victims, supportive treatment is the cornerstone, based on oxygen administration and aiming at treating respiratory failure. If consciousness impairment persists despite oxygen (100% FiO2), cyanide intoxication should be suspected. According to the recommendations of the European Society of Emergency Medicine, hysdroxocobalamin should be early administered as first-line antidote on the scene. Its efficiency has been well-recognized and its safety well-assessed. After hospital transfer, hyperbaric oxygen should be discussed according to the severity of features attributed to carbon monoxide poisoning. In the presence of irritant gas-related lung injuries, treatment of acute respiratory distress syndrome is based on the usual critical cares. However, final outcome of fire smoke-poisoned survivors remains critical, with possible significant cognitive sequellae

Customer behavior analytics have implemented in many systems, though still it's a developing and unexplored market has greater potential for better advancements. One of the major challenges for knowledge discovery and data mining systems stands in developing their data analysis capability to discover out of the ordinary models in the data. Now-a-days data mining became more important due to the arrival of powerful data collection and storage tools. In this paper, a Map Reduce implementation of statistical classifier, C4.5 algorithm has to be proposed. The problem addressed in this paper is Big data processing is complex using traditional database management tools. The objective of this paper is To reduce the average time spend by the customer in supermarket. To analysis customer behavior which helps to turn big data into big value by allowing to predict the buyer behavior to improve their sales. The proposed system is to implementation of C4.5 algorithm using Mapreduce framework.

In this research, we are creating an android tablet based interactive hotel menu system. We are integrating data mining algorithms in the system to extract all the orders' data, and subsequently observe trends in the orders. We use these analytics to help improve the menu with recommendations and combo-offers. Also, we are using clustering analysis to make customer groups, so as to reach out to them in a more personalized way with customer loyalty offers and extra discounts. Additionally, we are creating a dynamic JSP website on which the customers can view all the items remotely, and call for a home delivery. All these things will essentially help the hotel business gain even more happy customers and henceforth, more profits.

Cet article fait le point sur un état de l'art de la prise de décision stratégique. Il est question d'étudier et de comprendre les variables affectant le processus de prise de décision. Notre étude empirique s'est basée sur une étude qualitative avec une analyse sémantique par le logiciel TROPES. Les résultats obtenus expliquent les différentes variables qui ont un impact