Kinds Of Items Research Articles

Dual-View Preference Learning for Adaptive Recommendation

While recommendation systems have been widely deployed, most existing approaches only capture user preferences in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">macro-view</i> , i.e., the user's general interest across all kinds of items. However, in real-world scenarios, user preferences could vary with items of different natures, which we call the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">micro-view</i> . Both views are crucial for fully personalized recommendation, where an underpinning macro-view governs a multitude of finer-grained preferences in the micro-view. To model the dual views, in this paper, we propose a novel model called Dual-View Adaptive Recommendation (DVAR). In DVAR, we formulate the micro-view based on item categories, and further integrate it with the macro-view. Moreover, DVAR is designed to be adaptive, which is capable of automatically adapting to the dual-view preferences in response to different input users and item categories. To the best of our knowledge, this is the first attempt to integrate user preferences in macro- and micro- views in an adaptive way, without relying on additional side information such as text reviews. Finally, we conducted extensive quantitative and qualitative evaluations on several real-world datasets. Empirical results not only show that DVAR can significantly outperform other state-of-the-art recommendation systems, but also demonstrate the benefit and interpretability of the dual views.

Сравнительно-сопоставительный анализ дискурсивных единиц

The article deals with discourse markers — idiomatic utterances made in response to the interlocutor’s statement in the course of a conversation. The paper introduces and inter-prets discourse formulae formed with propositional verbs with the meaning of agreement and confirmation, disagreement and denial, surprise, indignation. The interest to discourse mark-ers is due to their obviously notable contribution to spoken communication. Also, this kind of items are in most cases language-specific. A variety of discourse markers in several languages is under review, with the focus on their language-specific features. The innovative and rele-vant character of the paper arises from its bearing on the area of semantic typology.

Measuring Morality: An Examination of the Moral Foundation Questionnaire's Factor Structure.

Moral foundations theory proposes five domains of morality-harm, fairness, loyalty, purity, and authority. Endorsement of these moral domains is assessed by the Moral Foundations Questionnaire (MFQ), a 30-item scale that has undergone intense measurement scrutiny. Across five samples (N = 464,229), we show greatly improved model fit using a Bifactor model that accounts for two kinds of items in the MFQ: judgment and relevance. We add to this space by demonstrating how using this improved measurement structure changes the strength of correlations of the moral foundations with numerous attitudes, cognitive styles, and moral decision-making. Future research should continue to identify what, if anything, the relevance and judgment factors might substantively capture over and above the substantive domains of moral foundations. In the meantime, we recommend that researchers use the Bifactor model for its improved model structure, rather than dropping the relevant items as some have proposed.

Akibat Hukum Terhadap Penarikan Kembali Harta Yang Di Hibahkan Menurut KUH Perdata

A grant is the gift of an item to someone where the giver is still alive. Materially, the existence of a grant has something to do with inheritance. In contrast to a will, a grant is a lifetime expenditure of assets based on affection for the benefit of a person or for the benefit of a social, religious, scientific body, also to someone who has the right to be his heir. The purpose of this study is to find out the law on the withdrawal of donated assets according to the Civil Code, to find out the legal consequences of withdrawing donated assets according to the Civil Code, and to find out the settlement of the withdrawal of donated assets according to the Civil Code. The research conducted is legal research which is descriptive analysis in nature and uses normative juridical research. Through descriptive research, researchers try to describe events and events that are the center of attention without giving special treatment to these events. This study uses secondary data by processing data from primary legal materials, secondary legal materials and tertiary legal materials. Based on the results of the research it is understood that the withdrawal of gift items according to the Civil Code is regulated in article 1688 which reads that a grant cannot be revoked and therefore cannot be revoked, except in 3 cases, namely if the grantee's conditions are not met, if the person who was given the gift is guilty of committing or participating in an attempt to kill or some other crime against the donor himself, and if the grantor falls into poverty while the one who was given the gift refuses to provide for him. If the recipient of the grant refuses to provide a living or allowance to the grantor, after that the grantor falls into poverty. With the withdrawal or elimination of this gift, all kinds of items that have been donated must be returned to the grantor in a clean condition of the burdens attached to the item. The legal consequence of the decision to cancel a grant that has permanent legal force is that the object of the dispute, namely land, will return to the grantor and their rights. If the object of the dispute has been certified on behalf of the recipient of the grant, then with this decision the certificate becomes null and void.

Philosophy and the real reasons for action: G. H. von Wright's understanding explanations

According to the received view, philosophy of action took a justified turn towards causalism because anti-causalists failed the causalist challenge about efficacious reasons. This paper contests that view by examining the ways in which Georg Henrik von Wright responded to causalism in his later philosophy. First, von Wright attacked the subjectivism of causalism by arguing for an objectivist view that construes reasons not as subjective mental states but as external facts of the agent's situation. Second, von Wright fundamentally disagreed with the view of philosophical inquiry that underpinned causalism. For von Wright, the task of philosophy was conceptual: to explicate what one is looking for when one is looking for the real reasons for action. In contrast, for causalists the task was ontological: to determine what kind of item in the world the real reason for action is. Examining von Wright's account contributes to contemporary assessments of the metaphilosophical dimension of the reasons/causes debate.

Read between the interactions: Understanding non-interacted items for accurate multimedia recommendation

This paper addresses the problem of multimedia recommendation that additionally utilizes multimedia data, such as visual and textual modalities of items along with the user-item interaction information. Existing multimedia recommender systems assume that all the non-interacted items of a user have the same degree of negativity, thus regarding them as candidates for negative samples when training the model. However, this paper claims that a user?s non-interacted items do not have the same degree of negativity. We classify these non-interacted items of a user into two kinds of items with different characteristics: unknown and uninteresting items. Then, we propose a novel negative sampling technique that only considers the uninteresting items (i.e., rather than the unknown items) as candidates for negative samples. In addition, we show that using the multiple Bayesian personalized ranking (BPR) losses with both unknown and uninteresting items (i.e., all the noninteracted items) in existing multimedia recommendation methods is very effective in improving recommendation accuracy. By conducting extensive experiments with three real-world datasets, we show the superiority of our ideas. Our ideas can be easily and orthogonally applied to any multimedia recommender systems.

Exploratory study of skills and knowledge in Algebra and Arithmetic in new students of the UPSLP

Exploratory Study of Skills and Knowledges in Algebra and Aritmethic of Freshman Students from the Universidad Politécnica de San Luis Potosí. Every program degree of the Universidad Politécnica de San Luis Potosí includes the regularization course called “Math Introduction”. It is mainly addressed for topics in the areas of algebra and arithmetic and it is taught to freshman students in our University. In order to know if the course topics are appropriate and efficient for the graduates who take this study plan, we made an exploratory test for first semester students from every degree program offered by the University. In this work, it is described the way the exploratory test was realized, the kind of items and questions that it contains. The obtained results are statistically shown for each program degree, by gender and by age.

Development of an Android Grocery Checklist Application

Purpose – Grocery shopping is a regular affair in most people’s lives. With a variety of necessities such as food, toiletries, and the like being purchased whenever people go grocery shopping, shopping lists are usually made to help buyers remember and organize what they need to purchase. This research introduces a mobile application that allows users to create and manage shopping lists for grocery shopping, as well as allowing them to mark what they’ve purchased by scanning the barcode of the purchased product. It also allows users to track their stocks of purchased items as well as view their expenditures and what kinds of products take up most of their expenses. 4 Method – The barcode data used is a selection of 100 unique products taken by the researchers, and the application uses SQLite to store both checklist data and the barcodes. Result – Based on the results, all the test cases were able to pass the expected result which means that the main features of the application were able to run smoothly. There are times that the barcode scanner was not able to read the barcode properly. This scenario is seen especially when the camera is at the right angle when scanning the product’s barcode. The front angle the scanner's success rate was 99%, but from the right, left, top, and bottom, the success rate was 84%, 93%, 97%, and 94%, respectively. Although the success rate is still high, it is still preferable to scan barcodes from the front. Overall, it has an average success rate of 93.8% on all the angles. The stocks screen was able to change the number of stocks it recorded when adding and removing items from each category of item. The system was also able to display if an item was running out of stock and if it already is out of stock. It was found that the stock system's functions were working properly. The maps function was tested via changing the current area and testing if it can pin locations based on the set condition. All in all, 5 locations were tested, with each location successfully having pins on multiple locations. The charts were able to display different expenditures for different weeks and months. Conclusion – The research has resulted in the creation of an app that can help users in managing their grocery shopping. It can create and edit checklists, access, and manage checklists from the local storage, as well as add and remove items from the created checklists. The system can scan barcodes of items that are in the internal database and automatically record them in both item stocks and expenditure statistics. These can help the user in managing their shopping, as well as showing them what they need to buy and how much they are spending on certain kinds of items. The app was built at a minimum Android SDK of 16. This left the researchers with difficulties in implementing some functions due to much simpler ways of implementation added in later SDKs being unavailable, but this also meant that the app was compatible with a lot more devices. Recommendation – Organize the list of products into categories to make searching for items faster. Add an option for statistics to break down expenditures even further to individual items instead of just categories. It is also recommended to integrate the product database with different grocery stores to be more accurate in terms of getting the total price of a checklist. Practical Implication – Developing of an Android grocery checklist application for the beneficiaries is useful because it can be use and can able to track the grocery or stock the user has. Also, the application as the capability to pin the location of the available grocery store with in the area.

Comparative Analysis of FMCG Products with Special Reference to HUL and ITC

India's fourth major industry, Fast-Moving Consumer Goods (FMCG), has an influence on everyone's everyday lives. When selling quickly changing consumer goods, it can be challenging to forecast consumer behaviour. There are several reasons why this behaviour is lacking. In today's globalised environment, consumer wants change over time. For India's economy, fast-moving consumer goods (FMCG) are crucial. As a result, when it comes to FMCG products, it's vigorous to keep track of changes in customer buying behaviour. The study focused on these two companies brand categories, as well as both firms' product portfolios. The research focuses on comparing the brand awareness between HUL &amp; ITC products. The kind of items that consumers utilise, and their consumption patterns are also factors in determining their gratification levels. Keywords: Comparative analysis, FMCG, Personal care, Consumer Behaviour. Consumer Product, Brand, Product Category.

An Uncertain Programming Model for Fixed Charge Transportation Problem with After‐Sale Service

This paper constructs an uncertain mathematical model for the fixed charge transportation problem in which several kinds of items are transported from different sources to various destinations via different methods. In addition, after‐sale service such as product return and exchange that help to raise the customer’s satisfaction is considered during the trade to meet the reality. Meanwhile, some indeterministic factors may occur during the transportation process; probability theory is not the best option due to the lack of adequate historical data. In the light of this statement, some parameters like supplies, demands, return rate, and exchange rate are all defined as uncertain variables to formulate the uncertain programming model. After that, the equivalent deterministic models are derived with the help of uncertainty theory. Finally, some numerical experiments are implemented via three algorithms; the optimal values are displayed and compared to show the application of this problem. The study of this paper provides an applicable method for the decision maker.

Hazy Borders: Legality and Illegality across the US-Mexico Border

This paper analyzes the different trading networks, the flux of merchandise, and the actors involved in the act of crossing goods through the United States-Mexico border, particularly in the Tijuana-San Diego region. It argues that the line dividing both countries works differently depending on who travels through it, what kind of items are brought across, and which direction a person is going. These different patterns can be further analyzed when comparing northbound and southbound traffic; roughly speaking, products crossed into the US are usually prescription drugs, herbs, food, and cigarettes, among others; whereas, items crossed into Mexico are usually construction materials, electronics and electrodomestics, toys, marijuana, guns, and so forth. This paper proposes that the border is not a well-defined barrier when it comes to different types of merchandise, instead becoming hazy and allowing for the small-scale smuggling of products without incurring legal and/or problematic situations.

Distributed Recommendation Considering Aggregation Diversity

Recommender systems (RSs) are popular in e-commerce as they suggest different kinds of items for different users. Most existing research works focus on how to improve the accuracy of recommender systems. Recently, some recommendation ranking techniques have been proposed to obtain more diverse recommendations for all the users. In this paper, the authors propose design a distributed mechanism for improving the aggregated recommendation diversity and define three new metrics to evaluate the diversity of RSs. To avoid the disclosure of information to a central agency, a distributed mechanism is designed to collect user ratings. To increase the diversity of set recommendations, user-based and item-based weighted methods are proposed. The tasks of them are to deal with non-ratings by weighting the common ratings and calculating the weighted cosine similarities to predict the unknown ratings.

Attribute-aware multi-task recommendation

User-item rating interactions in the recommender system have a deep potential connection with the friend relationships in the social network. In short, users who like the same kind of items may be potential friends in social network, and vice versa, friends in social networks tend to like similar items. Although the above-mentioned two kinds of interactive information can complement and inspire each other, either of them is sparse, which is still not enough to make accurate recommendations. In order to make up for this defect, we then mine useful information from attribute information, learning more informative node representation. In this paper, we explore attribute learning and mutual utilization, complementation and inspiration between social data and rating data. We propose a generic Attribute-Aware Multi-task Recommendation framework (AAMR) for rating prediction and social prediction, which learns representations for users and items by preserving both rating data and social data and attribute information, so as to conduct both rating prediction and trust relationship prediction tasks. Because many users are both in the rating matrix and in social networks, in the common learning, the two tasks will share the embedding of users, which makes the social data and rating data enrich each other’s semantics and alleviate each other’s sparsity. To justify our proposal, we conduct extensive experiments on a real-world dataset. Compared to the state-of-the-art rating and trust prediction approaches, AAMR can learn more informative representations, achieving substantial gains on both tasks.

Silver and silvery alloys in Early Minoan IB Crete

ABSTRACT This paper presents the results of X-ray fluorescence analysis carried out in the last years on silver objects from three different Cretan Early Minoan cemeteries, Hagia Photia Siteias, Kephala Petras, and Livari Skiadi, dated to ca. 3000 to 2800 BC. The classes of objects discussed in this paper comprise mainly daggers and jewelry pieces; other kinds of items, however, can also be included as comparisons. For this project various groups of copper-alloy and silver-alloy artifacts from Hagia Photia, from the Petras rock shelter, and from Livari have been analyzed. The silver-based objects of this period can be distributed into two groups according to their composition: unalloyed silver and alloys of silver and copper or silver and arsenical copper. The analyses of the metal finds, both of silver and of arsenical copper, from the three sites indicate their appurtenance to the same metallurgical tradition, common to the areas around the Black Sea, Anatolia, and the Near East, with similar metallurgical practice, esthetic choices, and styles.

Supply Chain Model for Expiring Items Following Ramp-Type Demand With Stochastic Lead Time Under Crisp and Fuzzy Environment

Supply chain models with deteriorating items, season pattern demand, expiration and uncertain lead time, though common in practice; had received little attention from researchers. In this article, the authors proposed a collaborative system with ramp type seasonal pattern demand rate for expiring items with supplier's random lead time under crisp and fuzzy environment considering the effect of inflation and time value of money. For the seasonal kind of items, demand rate follows the combination of increasing-steady-decreasing demand patterns. A supplier's lead time is a stochastic function of his managing cost; thus, the extra costs incurred on the retailer due to the uncertainty in lead time in terms of shortages costs and lost sales costs are owed by the supplier. Numerical examples are cited to illustrate the results and its significant features. Finally, to study the effect of change of parameters sensitivity analysis is presented and necessary observations are made.

Formulation and Examination of Organic Oil and Shampoo from Fish Scales

Cosmetics are utilized to upgrade the appearance or scent of the human body. Beautifying agents incorporate skin creams, lotions, powders, aromas, lipsticks, fingernail and toe nail polish, eye and facial cosmetics, permanent waves, and numerous different kinds of items. To make the hair sound and gleaming, there are several manufactured oils and hair shampoos. But when in contrast to the artificial one, natural cosmetics have growing demand in the world market and are an priceless gift of nature, as it is secure and free from facet results like hair fall and damage. As it is safe and free from symptoms like hair fall and harm. As the age increases, people suffer from hair loss and damage due to the less secretion of keratin. As we age, our body’s natural levels of collagen decrease, leading to thinning and shedding of hair. Research shows that collagen may support and increase hair-building proteins (keratin) in the body. This can help strengthen hair strands, promote hair growth and prevent hair loss. Collagen may even help to prevent the appearance of grey hairs by supporting the healthy structure of the hair follicle, where the pigment of hair is produced. Collagen supplements also have been shown to be effective in treating dry, brittle hair, helping to maintain healthy moisture levels in the hair. The present work was aimed to formulate organic oil and shampoo using fish scales and various herbs. The formulated organic oil and shampoo were evaluated for homogeneity, appearance, odour, saponification value, pH etc.

Home Loans in DHFL Corporation Ltd Company in Chennai

The reportcontains the hierarchical investigation done at DHFL. Thereport title is"A STUDY ON HOME LOANS". The report gives an outline of the Home credit Sector.Awareness ofcustomers about various kinds of items and administrations offered by dhfl. This examination was led to discover the consumer loyalty with respect to dhfl.The philosophy embraced for the investigation was through an organized survey. The information gathered from the contrastingly broke down altogether and introduced as diagrams and tables. DHFL must promote consistently and make brand an incentive for its items and administrations. The greater part of its rivals like ICICI, HDFC and LIC use TV commercials to advance their items. [1],[ 3],[5]

Effect of online Shopping in Local Market of India

Marketing and shopping is hobby of most of individuals. Everyone likes to go for shopping. Now-a-days, there are many method of shopping’s. The malls are available in cities. At one place, individuals’ can get all kinds of items from buying vegetables to clothes, footwear, accessories, to furniture, electronic gadgets etc. It needs to go outside the home to purchase the things. It requires time as well as physical efforts. Therefore, online shopping in new terms of shopping. Online shopping has made easy way of shopping. In India, it has made shopping easy for each person. The best things online shopping is that it has done is to realise everyone’s vision about shopping at enormously cheap rates. It is very convenient to all, from doorstep delivery to great exchange return policies. The current paper is an attempt to focus on the effect of online shopping to Local Market of India.

Periodicity analysis using weighted sequential pattern in recommending service

Nowadays, due to escalating the demands of the direct purchase of e-commerce with many kinds of item, the demand for e-commerce is exploding. The recommender system finds items for customer easily and targets in customers for the e-commerce firms easily by an automated recommending process. And also, association rules are often used to facilitate product sales in marketing pattern analysis through recommender systems in e-commerce. This paper takes aim at a new recommending service in e-commerce using periodicity analysis of weighted sequential pattern. In e-commerce, we need the FRAT segmentation method based on the various items purchased by the customer, to reflect the weights and perform the pre-processing tasks using sequential patterns for period analysis. We apply an effective incremental sequential data mining method that adds incremental purchasing data as a change of the four season changes. As a result, we suggest a recommendation service for micro-marketing of e-commerce based on big data analysis for promoting e-commerce purchasing, which satisfies customer’s taste with various products of e-commerce. To check the performance of the proposal, we tested the data set with the same conditions as before. As a result, the proposed system is more efficient than the other systems in the results of system evaluation.

UISTD: A Trust-Aware Model for Diverse Item Personalization in Social Sensing with Lower Privacy Intrusion.

Privacy intrusion has become a major bottleneck for current trust-aware social sensing, since online social media allows anybody to largely disclose their personal information due to the proliferation of the Internet of Things (IoT). State-of-the-art social sensing still suffers from severe privacy threats since it collects users’ personal data and disclosure behaviors, which could raise user privacy concerns due to data integration for personalization. In this paper, we propose a trust-aware model, called the User and Item Similarity Model with Trust in Diverse Kinds (UISTD), to enhance the personalization of social sensing while reducing users’ privacy concerns. UISTD utilizes user-to-user similarities and item-to-item similarities to generate multiple kinds of personalized items with common tags. UISTD also applies a modified k-means clustering algorithm to select the core users among trust relationships, and the core users’ preferences and disclosure behaviors will be regarded as the predicted disclosure pattern. The experimental results on three real-world data sets demonstrate that target users are more likely to: (1) follow the core users’ interests on diverse kinds of items and disclosure behaviors, thereby outperforming the compared methods; and (2) disclose more information with lower intrusion awareness and privacy concern.