Personalization of Multi-day Round Trip Itineraries According to Travelers’ Preferences

Travel planning is a long and tedious process for tourists since it requires processing a vast amount of information. Recommender systems can be used to facilitate the process of scoring points-of-interests (POIs) according to the travelers’ interests and creating feasible itineraries. However, itinerary planning is personal and each itinerary created must reflect the interest of the traveler as well as his/her travel style. In this paper, we extend the creation of multi-day round trip itineraries by adding different personalization options such as the pace of the traveler and diversity level of the route. The information about the travel style of the user is used to personalize the visiting duration of each POI and to create routes for each day that follow the constraints defined by users. We conducted a user study through a mobile application and the results show that the added personalization options improved the recommended multi-day round trip walking tours from a user’s perspective.

Rubber tapping machine performance and procedure

Rubber tapping is a rubber latex extraction process which has to be done early morning in order to satisfy cool climate for latex flow. It is a tedious process which takes great work force and man-hour it has to be done with great accuracy. It is a great necessity for an automated or mechanized tapping to cope with the market requirement. So it is required to design a Rubber tapping machine which should be affordable to small planters.

IoT based Smart Billing Trolley

The smart purchasing trolley machine helps clients while buying. The trolley has an automated billing gadget and it follows the movement instructions supplied by the consumer by using using hand gesture. An android utility is established in customers mobile. The goods bought via the consumer and their value will be robotically updated to the android application via internet and that invoice will routinely ship to the billing counter gadget in the store. This helps client by way of changing tedious process of pulling and pushing the trolley and saves time spent inside the billing counter. The automated buying trolley is a clever trolley which integrates with ultrasonic sensor, arduino, wifi module,weigh sensor in it. The scanned items by the purchaser using cellular app in order to automatically log into the shopping cart and thereby can generate bill for items decided on. These modules are included into an iot gadget and are tested to meet the functionality.

Education and Resentment

That the world is awash with resentment poses a genuine question for educators. Here, we will suggest that resentment can be better harnessed for good if we stop focusing on people and tribes and, instead, focus on systems: those invisible norms that often produce locked-in structures of social interaction. A “systems lens” is vast, so fixes will have to be an iterative process of reflection, and revision toward a more just system. Nonetheless, resentment toward the status quo may be an important element in keeping that otherwise tedious process going, with the caveat that resentment is only productive when it is combined with reason, and that, therefore, educators, rather than privileging participant reactive attitudes, ought, instead, to promote participant reactive reasoning, as the latter can be a genuine force for both personal and interpersonal growth, while the former might very well do the reverse.

Segmentation of Spine Tumour Using K-Means and Active Contour and Feature Extraction Using GLCM

MRI imaging technique is used to detect spine tumours. After getting the spine image through MRI scans calculation of area, size, and position of the spine tumour are important to give treatment for the patient. The earlier the tumour portion of the spine is detected using manual labeling. This is a challenging task for the radiologist, and also it is a time-consuming process. Manual labeling of the tumour is a tiring, tedious process for the radiologist. Accurate detection of tumour is important for the doctor because by knowing the position and the stage of the tumour, the doctor can decide the type of treatment for the patient. Next, important consideration in the detection of a tumour is earlier diagnosis of a tumour; this will improve the lifetime of the patient. Hence, a method which helps to segment the tumour region automatically is proposed. Most of the research work uses clustering techniques for segmentation. The research work used k-means clustering and active contour segmentation to find the tumour portion.

Bulk SMS Communication Portal

Sending SMS to large amount of people in an organization is a tedious process and it requires more human effort tocomplete the task. The best solution in this aspect could be developing a portal which facilitate sending bulk SMS to multiple users. But the problem here is the portal should be more user-friendly. Otherwise, the portal also requires more human effort in entering data like mobile number for large amount of people. This project provide a solution for organization to send bulk SMS and with various features like log generation, notification of failure ofSMS and/or delivery, scheduling of SMS,alert/notification system,read and unread status, provision of importing contact details from excel worksheets, customizing with name of the receiver and so on. The application can be easily used and maintained by an administrator in the organization in a more effective manner.

The Theoretical Value of the Local Hubble Constant

Determining the local Hubble constant Ho from cosmological observations is a long and tedious process requiring accurate datasets obtained by fully calibrated astronomical instruments. To circumvent this need, a simple theoretical approach is introduced in this study which uses the concept of gravitational weakening that could fuel cosmic expansion. There appears to be a fundamental relation of Ho and the rate of orbital expansion that gives a theoretical value for Ho = 69.921 Km/s/Mpc. It is possible that various astrophysical methods using different celestial markers would converge to this theoretical value when cosmological distances and time delay measurements are corrected using the newly discovered seismic-induced phenomenon.

Introduction and Synopsis

This introductory chapter provides an overview of the two texts of the Muziris papyrus. The publication of the Muziris papyrus texts—and the slow, tedious process of their interpretation and explanation—marks a turning point for studies on Indo-Roman trade specifically, and on the Roman economy more broadly. On the Roman side, apart from showing the impressive organizational and financial potential of ancient mercantile communities, the Muziris papyrus clarifies some of the routine practices associated with Greco-Roman maritime loan agreements, and demonstrates how such practices were adapted to the peculiarities of the South Indian trade. It also details how customs duties on imported Indian items were assessed and collected, and hints at the intriguing interplay among the state, the financial elites, and the merchants. On the Indian side, the cargo of the Hermapollon—the Roman Indiaman whose imports are itemized and evaluated on the verso of the Muziris papyrus—highlights the commercial importance of a region and of an emporion strategically poised between the Arabian Sea and the Bay of Bengal.

Domain Independent Automatic Labeling system for Large-scale Social Data using Lexicon and Web-based Augmentation

Recently, with the large-scale adoption of social media, people have begun to express their opinion on these sites in the form of reviews. Potential consumers often forced to wade through huge amount of reviews to make informed decision. Sentiment analysis has become rapid and effective way to automatically gauge consumers’ opinion. However, such analysis often requires tedious process of manual tagging of large training examples or manually building a lexicon for the purpose of classifying reviews as positive or negative. In this paper, we present a method to automate the tedious process of labeling large textual data in an unsupervised, domain independent and scalable manner. The proposed method combines the lexicon-based and Web-based Point Wise Mutual Information (PMI) statistics to find the Semantic Orientation (SO) of opinion expressed in a review. Based on proposed methods a system called Domain Independent Automatic Labeling System (DIALS) has been implemented, which takes collection of text from any domain as input and generates fully labeled dataset in an unsupervised and scalable manner. The result generated can be used to track and summarize online discussion and/or use to train any classifier in the next stage of development. The effectiveness of system is tested by comparing it with baseline machine learning and lexicon-based methods. Experiments on multi-domains dataset has shown that proposed method consistently shown improved recall and accuracy as compared to baseline machine learning and lexicon-based methods.

AN ENCOURAGING STRATEGY IN PEER CORRECTION

The purpose of the article is to introduce a strategy in the peer correction. Any correction of the mistake being reluctantly welcomed is usually accepted with a sense of disfavor. Peer correction in speaking activity is no exception. To turn this tedious process into an attractive one we have developed a relatively new strategy. Peer correction in writing activity has long been practiced. Learners enjoy discovering each other’s mistakes in essays, spelling or grammar tests, etc. But correcting speaker’s errors being rarely carried out has gradually almost been forgotten. The paper introduces a new concept in peer correction involving a point system. The students actively participating in a correction process are praised with a surplus point for a corrected mistake, which is further taken into account. The strategy has proved to be a motivating one in teaching English as a foreign language.