This document presents a proposed end-to-end tour system that uses machine learning and recommendation algorithms. The system would allow users to take a quiz to receive personalized tour destination recommendations. It would also provide pre-packaged tour options and allow users to customize their own tours by selecting different components. The system is divided into three modules: a prediction quiz, a recommendation system using singular value decomposition, and a customization module. The goal is to make the tour planning process easy and hassle-free for users.
A survey on a cocktail approach for travel package recommendationeSAT Journals
Abstract Providing better travel services for tourists is one of the important applications in urban computing. The worlds is of commerce, travel, entertainment, and Internet technology are linked, different types of business data is accessible for innovative use and regular analysis. Here it provides a study of utilizing online travel information for the personalized travel package recommendation. Though many recommender systems have been developed for enhancing the quality of travel service, most of them lack a systematic and open framework to dynamically incorporate multiple types of additional context information existing in the tourism domain, such as the travel area, season, and price of the travel packages. First analyze the properties of the old travel packages and develop a tourist-area-season topic (TAST) model. This TAST model represents different travel packages and different topic distributions of tourist, the topic extraction is stated on both the tourists and the natural characteristics of the landscapes. According to the topic model representation, a cocktail approach is generated so that to form lists for personalized travel package recommendation. The TAST model is extended to the tourist-relation-area-season topic (TRAST) model for collecting the relationships among the tourists for all travel groups. Then analyze TAST model, TRAST model, and cocktail recommendation approach on the current travel package data. The TAST model can effectively grabs the individual characteristics of travel data and cocktail approach, so it is more efficient than old recommendation techniques for travel package recommendation by including tourist relationships, TRAST model is used as an effective evaluation for travel group formation. Keywords: Travel package, recommender systems, cocktail, topic modeling, collaborative filtering
Maede Kiani Sarkaleh, Mehregan Mahdavi and Mahsa BaniardalanIJMIT JOURNAL
Today, mobile devices are widely used by many tourists. They can use mobile for accessing information
about all sightseeing around the world. On the other hand, it seems essential to personalize the content due
to diversity of learners and variation of the tools they use. On the whole, the goal for personalization is to
suggest a collection of comprehensive activities, taking into consideration factors such as location, user
preferences and interests and so on. One of the applications of recommender systems is in tourism industry.
A survey on a cocktail approach for travel package recommendationeSAT Journals
Abstract Providing better travel services for tourists is one of the important applications in urban computing. The worlds is of commerce, travel, entertainment, and Internet technology are linked, different types of business data is accessible for innovative use and regular analysis. Here it provides a study of utilizing online travel information for the personalized travel package recommendation. Though many recommender systems have been developed for enhancing the quality of travel service, most of them lack a systematic and open framework to dynamically incorporate multiple types of additional context information existing in the tourism domain, such as the travel area, season, and price of the travel packages. First analyze the properties of the old travel packages and develop a tourist-area-season topic (TAST) model. This TAST model represents different travel packages and different topic distributions of tourist, the topic extraction is stated on both the tourists and the natural characteristics of the landscapes. According to the topic model representation, a cocktail approach is generated so that to form lists for personalized travel package recommendation. The TAST model is extended to the tourist-relation-area-season topic (TRAST) model for collecting the relationships among the tourists for all travel groups. Then analyze TAST model, TRAST model, and cocktail recommendation approach on the current travel package data. The TAST model can effectively grabs the individual characteristics of travel data and cocktail approach, so it is more efficient than old recommendation techniques for travel package recommendation by including tourist relationships, TRAST model is used as an effective evaluation for travel group formation. Keywords: Travel package, recommender systems, cocktail, topic modeling, collaborative filtering
Maede Kiani Sarkaleh, Mehregan Mahdavi and Mahsa BaniardalanIJMIT JOURNAL
Today, mobile devices are widely used by many tourists. They can use mobile for accessing information
about all sightseeing around the world. On the other hand, it seems essential to personalize the content due
to diversity of learners and variation of the tools they use. On the whole, the goal for personalization is to
suggest a collection of comprehensive activities, taking into consideration factors such as location, user
preferences and interests and so on. One of the applications of recommender systems is in tourism industry.
Basically the project is having two parts namely the recommender system and the planner system. The tour
recommender system firstly asks the user for logging in then he asks for the various details about his tour in order
to recommend a perfect tour. The recommender system collects the information regarding the type of place, the
travelling method the user would like to prefer and more importantly the cost which the user can afford. The
collected data is sent to the recommender algorithm which processes the data and finds a perfect place with
required specification from the system database. Three best results are displayed. Then the user selects one tour as
per his choice. Next the planner system displays all the possible travelling and accommodation methods with their
costs and offers. Then the user selects the services according to his convenience and enjoys the trip.
A location based movie recommender systemijfcstjournal
Available recommender systems mostly provide recommendations based on the users’ preferences by
utilizing traditional methods such as collaborative filtering which only relies on the similarities between users and items. However, collaborative filtering might lead to provide poor recommendation because it does not rely on other useful available data such as users’ locations and hence the accuracy of the recommendations could be very low and inefficient. This could be very obvious in the systems that locations would affect users’ preferences highly such as movie recommender systems. In this paper a new locationbased movie recommender system based on the collaborative filtering is introduced for enhancing the
accuracy and the quality of recommendations. In this approach, users’ locations have been utilized and
take in consideration in the entire processing of the recommendations and peer selections. The potential of
the proposed approach in providing novel and better quality recommendations have been discussed through experiments in real datasets.
A LOCATION-BASED MOVIE RECOMMENDER SYSTEM USING COLLABORATIVE FILTERINGijfcstjournal
Available recommender systems mostly provide recommendations based on the users’ preferences by
utilizing traditional methods such as collaborative filtering which only relies on the similarities between
users and items. However, collaborative filtering might lead to provide poor recommendation because it
does not rely on other useful available data such as users’ locations and hence the accuracy of the
recommendations could be very low and inefficient. This could be very obvious in the systems that locations
would affect users’ preferences highly such as movie recommender systems. In this paper a new locationbased movie recommender system based on the collaborative filtering is introduced for enhancing the
accuracy and the quality of recommendations. In this approach, users’ locations have been utilized and
take in consideration in the entire processing of the recommendations and peer selections. The potential of
the proposed approach in providing novel and better quality recommendations have been discussed
through experiments in real datasets.
In artificial intelligence, an expert system is the computer system that emulates the decision making ability of a human expert. Expert systems are designed to solve the complex problems by reasoning about the knowledge represented primarily as If-then rules rather than through conventional procedural code Intelligent Travelling System is the system that will run on most of the phones and palms which enable the user to visit the places at user criteria . In the current situations, systems have the information about the places they want to visit and they don’t have usable or valuable information about points of interest except the phone numbers and addresses. In order to overcome this problem the Intelligent Travelling System has been proposed. The users who want to travel around can answer the set of questions and the system will provide tourist spot, path to the spot, some picture of the spot and rough estimated cost based on the answers given by the user. The primary advantage of this system is to fulfill user criteria by approximate estimation of cost and time.
Design of recommender system based on customer reviewseSAT Journals
Abstract Recommendations play a significant role in every human life. People choose their ideas based on other’s recommendations since they trust the recommendations more. For giving recommendations there emerged a system called Recommender system. Recommender systems play a important role in E-Marketing. Many companies adopt recommender systems to increase in their sales in the market. They can establish their products such that they can attract more customers by giving offers. Many ranking approaches have emerged to rank the top product recommendation to give to user. Ratings calculated can be an explicit or impliocit rating. Popular sites are Amazon.com, Netflix.com, and Movielens.com etc. These sites help the customers to find relevant product to their interest. They play as a place where customers can find all kinds of items. They do so because recommendations given by other customers have been published after they have used the product. Those customers will have experience about the product. From the customers their view of how is the product usage has been collected. This is used in recommendations. In the Proposed system, customer’s views are used for recommendations. While new customer search products, old users views are published for the particular product. On getting the customer views, one user can trust it since common people have more confidence on words-of other people. Based on product, users are given form to fill their views.On getting views, Ratings are calculated from it. These kind of recommender system give useful recommendations since we collect views of people who are familiar with the item or product. Index Terms: Recommender system, E-Commerce, collaborative filtering, Customer reviews
Basically the project is having two parts namely the recommender system and the planner system. The tour
recommender system firstly asks the user for logging in then he asks for the various details about his tour in order
to recommend a perfect tour. The recommender system collects the information regarding the type of place, the
travelling method the user would like to prefer and more importantly the cost which the user can afford. The
collected data is sent to the recommender algorithm which processes the data and finds a perfect place with
required specification from the system database. Three best results are displayed. Then the user selects one tour as
per his choice. Next the planner system displays all the possible travelling and accommodation methods with their
costs and offers. Then the user selects the services according to his convenience and enjoys the trip.
A location based movie recommender systemijfcstjournal
Available recommender systems mostly provide recommendations based on the users’ preferences by
utilizing traditional methods such as collaborative filtering which only relies on the similarities between users and items. However, collaborative filtering might lead to provide poor recommendation because it does not rely on other useful available data such as users’ locations and hence the accuracy of the recommendations could be very low and inefficient. This could be very obvious in the systems that locations would affect users’ preferences highly such as movie recommender systems. In this paper a new locationbased movie recommender system based on the collaborative filtering is introduced for enhancing the
accuracy and the quality of recommendations. In this approach, users’ locations have been utilized and
take in consideration in the entire processing of the recommendations and peer selections. The potential of
the proposed approach in providing novel and better quality recommendations have been discussed through experiments in real datasets.
A LOCATION-BASED MOVIE RECOMMENDER SYSTEM USING COLLABORATIVE FILTERINGijfcstjournal
Available recommender systems mostly provide recommendations based on the users’ preferences by
utilizing traditional methods such as collaborative filtering which only relies on the similarities between
users and items. However, collaborative filtering might lead to provide poor recommendation because it
does not rely on other useful available data such as users’ locations and hence the accuracy of the
recommendations could be very low and inefficient. This could be very obvious in the systems that locations
would affect users’ preferences highly such as movie recommender systems. In this paper a new locationbased movie recommender system based on the collaborative filtering is introduced for enhancing the
accuracy and the quality of recommendations. In this approach, users’ locations have been utilized and
take in consideration in the entire processing of the recommendations and peer selections. The potential of
the proposed approach in providing novel and better quality recommendations have been discussed
through experiments in real datasets.
In artificial intelligence, an expert system is the computer system that emulates the decision making ability of a human expert. Expert systems are designed to solve the complex problems by reasoning about the knowledge represented primarily as If-then rules rather than through conventional procedural code Intelligent Travelling System is the system that will run on most of the phones and palms which enable the user to visit the places at user criteria . In the current situations, systems have the information about the places they want to visit and they don’t have usable or valuable information about points of interest except the phone numbers and addresses. In order to overcome this problem the Intelligent Travelling System has been proposed. The users who want to travel around can answer the set of questions and the system will provide tourist spot, path to the spot, some picture of the spot and rough estimated cost based on the answers given by the user. The primary advantage of this system is to fulfill user criteria by approximate estimation of cost and time.
Design of recommender system based on customer reviewseSAT Journals
Abstract Recommendations play a significant role in every human life. People choose their ideas based on other’s recommendations since they trust the recommendations more. For giving recommendations there emerged a system called Recommender system. Recommender systems play a important role in E-Marketing. Many companies adopt recommender systems to increase in their sales in the market. They can establish their products such that they can attract more customers by giving offers. Many ranking approaches have emerged to rank the top product recommendation to give to user. Ratings calculated can be an explicit or impliocit rating. Popular sites are Amazon.com, Netflix.com, and Movielens.com etc. These sites help the customers to find relevant product to their interest. They play as a place where customers can find all kinds of items. They do so because recommendations given by other customers have been published after they have used the product. Those customers will have experience about the product. From the customers their view of how is the product usage has been collected. This is used in recommendations. In the Proposed system, customer’s views are used for recommendations. While new customer search products, old users views are published for the particular product. On getting the customer views, one user can trust it since common people have more confidence on words-of other people. Based on product, users are given form to fill their views.On getting views, Ratings are calculated from it. These kind of recommender system give useful recommendations since we collect views of people who are familiar with the item or product. Index Terms: Recommender system, E-Commerce, collaborative filtering, Customer reviews
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.