Size Of Items Research Articles

Constant-Ratio Approximation for Robust Bin Packing with Budgeted Uncertainty

We consider robust variants of the bin packing problem with uncertain item sizes. Specifically we consider two uncertainty sets previously studied in the literature. The first is budgeted uncertainty (the $U^\Gamma$ model), in which at most $\Gamma$ items deviate, each reaching its peak value, while other items assume their nominal values. The second uncertainty set, the $U^\Omega$ model, bounds the total amount of deviation in each scenario. We show that a variant of the Next-cover algorithm is a $2$ approximation for the $U^\Omega$ model, and another variant of this algorithm is a $2\Gamma$ approximation for the $U^\Gamma$ model. Unlike the classical bin packing problem, it is shown that (unless $\mathcal{P}=\mathcal{NP}$) no asymptotic approximation scheme exists for the $U^\Gamma$ model, for $\Gamma=1$. This motivates the question of the existence of a constant approximation factor algorithm for the $U^\Gamma$ model. Our main result is to answer this question by proving a (polynomial-time) $4.5$ approximation algorithm, based on a dynamic-programming approach.

Anisotropic representations of visual space modulate visual numerosity estimation

Humans can estimate the number of visually displayed items without counting. This capacity of numerosity perception has often been attributed to a dedicated system to estimate numerosity, or alternatively to the exploitation of various stimulus features, such as density, convex hull, the size of items, and occupancy area. The distribution of the presented items is usually not varied with eccentricity in the visual field. However, our visual fields are highly asymmetric. To date, it is unclear how inhomogeneities of the visual field impact numerosity perception. Besides eccentricity, a pronounced asymmetry is the radial-tangential anisotropy. For example, in crowding, radially placed flankers interfere more strongly with target perception than tangentially placed flankers. Similarly, in redundancy masking, the number of perceived items in repeating patterns is reduced when the items are arranged radially but not when they are arranged tangentially. Here, we investigated whether numerosity perception is subject to the radial-tangential anisotropy of spatial vision to shed light on the underlying topology of numerosity perception. In Experiment 1, observers were presented with varying numbers of discs, predominantly arranged radially or tangentially, and asked to report their perceived number. In Experiment 2, observers were presented with the same displays as in Experiment 1, and were asked to encircle items that were perceived as a group. We found that numerosity estimation depended on the arrangement of discs, suggesting a radial-tangential anisotropy of numerosity perception. Grouping among discs did not seem to explain our results. We suggest that the topology of spatial vision modulates numerosity estimation and that asymmetries of visual space should be taken into account when investigating numerosity estimation.

Comparing the costs of Any Fit algorithms for bin packing

An online bin packing instance is a list of item sizes each of which is a rational number in (0,1], the goal is to partition the items into bins where the total size of items in a bin is at most 1, and the total number of bins is minimized. Here we analyze the ratio of two online algorithms for sequences where the total size of items is large and prove an old open conjecture of Johnson.

Bias in media coverage of antitrust actions

One of the main goals of competition authorities is to deter anticompetitive practices. That is one of the reasons why antitrust decisions are made public: to reinforce the deterrence effect, as the impact of the mass media on public opinion may affect firms’ reputations. Our empirical strategy focuses on identifying how the nature of specific antitrust actions by competition authorities affects the size of news items and their visibility within the newspaper. We study this relationship by using a new database containing all news published in Spain over a 30-month period, regarding all cases analysed by the Spanish competition authority. Our analysis produced two key conclusions about how the media deals with positive and negative news on the reputation of listed and non-listed companies. On average, the difference in size between positive and negative news for listed firms is greater than the difference present in the actions referring to non-listed firms. Secondly, newspapers concede greater visibility to them by positioning more favourably, both on the right-hand side of the paper and on initial pages. These results suggest that the deterrence effect that competition authorities seek by making their decisions public may be weakened by the presence of bias in media.

Diet of juveniles and adults of the Cuban Giant Frog, Eleutherodactylus zeus (Anura: Eleutherodactylidae)

Anurans are gape-limited predators and therefore larger individuals are capable of consuming larger prey. Stomach contents of the Cuban Giant Frog, Eleutherodactylus zeus, from caves in the northeastern-most part of the Sierra de Quemados in Viñales National Park, Pinar del Río Province, Cuba, were indicative of ontogenetic changes in diet. Although niche overlap among size classes was relatively high, larger frogs consumed larger but fewer prey items. Predator and prey sizes were positively correlated in both adults and juveniles, whereas predator size and number of prey items per stomach was negatively correlated.

A FINGERPRINT REMOVAL METHOD BASED ON FRACTAL–CRIMINISI TECHNOLOGY

Against the circumstance of redundant fingerprint information remaining in photographed images due to lens contamination, a fingerprint removal method is proposed by combining fractal technology and the Criminisi method. Fingerprints on an image are usually distributed in a dispersive pattern, and show statistical fractal characteristic. Therefore, based on the Criminisi method, the textural complexity of image pixel blocks expressed by box-counting fractal dimension is introduced into this method as a parameter of pixel block size and subitem of the data item with priority. On the one hand, this way of operation can select the size of the pixel blocks to be removed adaptive to the box fractal dimension; on the other hand, the box fractal dimension, as the subitem of the data item with priority, can avoid the effect of particular value and improve the reliability and stability of priority. The experimental results show that the proposed method can satisfactorily perform the fingerprint removal task and fill the information.

Analysis of Computer Network Technology on New Media Problem-Based Learning (PBL) Teaching Method

Today’s skill development can support modern technologies to understand in a simple manner. The teaching methods with problem-based learning (PBL) have improved exploration of collaborative inquiry. The deep understanding of concepts is possible with computer network technology through critical analysis. The reasoning, decision, and defending concepts are solving unfamiliar directions of teaching methods. The computer network technologies are making PBL efficient with teaching method. The 3 factors like learning goals, projecting elements, and teaching practices are maintained by computer network technology. This study solely uses students from one major as the experimental subjects, ignoring the fact that students from other majors have diverse logical thinking styles. As a result, the author will raise the sample size and kind of study items in the next research project. Structuralism is a scientifically educational paradigm that, with its particular vision of information, learning, and students, has become the theoretical foundation of teaching and has offered theoretical direction for many instructors’ instruction. MBPBL learning paradigm outperforms standard PBL and its N-Gain score is obtained as N- Gain > 70 , 30 ≤ g ≤ 70 , and N- Gain < 30 . Training and teaching methods must also be updated on a regular basis. As an emerging technology in the realm of education, virtual reality (VR) technology may assist instructors in implementing immersion instruction. The virtual environment provided by virtual reality technology transcends time and place, allowing students to master new skills in a new “real” setting.

New application of game theory in supply chain management

Game theory has become an essential tool in the analysis of supply chains with multiple players who often have different interests. In this study, we use the game theory to examine the possibility of decision optimization and achieving equilibrium in the operation of the supply chain. Our goal is to determine the optimal agreement between the wholesaler and the retailer(s) to minimize the total cost in the supply chain in the given situation. The research method used in the study enriches the literature on the topic by linking the minimization of costs not to abstract evaluation metrics but to the stock order item size often calculated in real business as well. This facilitates the interpretation of the strategies and decision motivations used by the members of the supply chain.

Functional impact and trophic morphology of small, sand‐sifting fishes on coral reefs

Abstract Oligotrophic tropical coral reefs are built on efficient internal energy and nutrient cycling, facilitated by tight trophic interactions. In the competition for available prey, some small fishes have evolved to feed on apparently barren sand patches that connect hard‐substratum patches in many reef habitats. One strategy for obtaining prey from a particulate matrix is to sift out small prey items from the sediment (often called ‘winnowing’). Yet, the trophic link between small winnowing consumers and their prey are poorly resolved, let alone the morphological specialisations that enable this foraging behaviour. We used aquarium‐based feeding experiments to quantify the impact of winnowing by two sand‐dwelling goby species (Valenciennea sexguttata and Valenciennea strigata) on meiobenthos abundance and diversity and examined their actual ingestion of meiobenthos using gut content analysis. To identify potential morphological structures involved in winnowing, we investigated the gobies' feeding apparatus with electron microscopy (SEM) and micro‐computed tomography (micro‐CT). After 4 days of sifting through the sand matrix, the two species significantly reduced meiobenthic prey abundance by 30.7% ± 9.2 SE (V. sexguttata) and 46.1% ± 5.1 SE (V. strigata), but had little impact on the meiobenthic diversity. The most abundant prey groups (copepods and annelids) experienced the greatest reduction in number, suggesting selection by size, shape and density of prey items. Furthermore, gut content analysis confirmed that winnowing gobies can efficiently separate meiobenthic prey from heavier inorganic particles (sand), likely facilitated by a specialised epibranchial lobe, pharyngeal jaws and highly abundant papillose taste buds in the oropharyngeal cavity. Our results provide important background on the trophic link between the meiobenthos and winnowing gobies on coral reefs. The revealed specialisations of the goby feeding apparatus facilitate sand‐sifting foraging behaviour and access to an otherwise inaccessible trophic niche of microscopic prey. By having evolved a specialised strategy to obtain nutritious and highly abundant prey from seemingly barren sand, we suggest that winnowing gobies act as an important conduit for sand‐derived energy to higher trophic levels. Read the free Plain Language Summary for this article on the Journal blog.

Interpolation of non-random missing values in financial statements’ big data using CatBoost

Financial statements’ big data have the characteristics of “Incompleteness” and “Nonrepresentative”. In this paper, employing the world’s largest commercial database on finance, ORBIS, we first find that the rate of missing data varies depending on the country, the type and size of financial items, and the year. Using information on missing data, we interpolate non-random missing financial variables from the previous- and/or next-year values of the same financial item, the values of other financial items, and the conditions of missing values determined by CatBoost. Because the distribution of financial values obeys Zipf’s law in the large-scale range and mean and variance diverge, we employ an inverse hyperbolic function to convert the value of a financial item as a target variable. We introduce two types of missing interpolation models according to the two types of situations involving missing objective variables. After verifying the accuracies and stabilities of these models, we describe the properties of firm-scale variables in which non-random missing values are interpolated. In the final stage of this work, we combine these two models. From our observations, we confirm that the range in which Zipf’s law is established becomes wider than before interpolation.

Adaptation of Validity and Reliability of Indonesian Instruments of Attitudes towards Suicide (ATTS) with The Rasch Model Approach

Background: Indonesia has a suicide rate that continues to increase so suicide attempts need to be made. One of the early prevention steps is to find suicidal ideation. ATTS is a multi-dimensional measuring tool by measuring Cognitive, Affective and Behavioral aspects that is easy to fill, fast and precise in measuring attitudes towards suicide in the general population through large surveys than other instruments and ATTS is also not yet developed in Indonesia. Therefore, with the Rasch Model that can perform analysis at the item and respondent level, it is expected to produce a psychometric tool in preventing suicide in Indonesia.Purpose: The purpose of this study is to test the validity and reliability of the adaptation of the Attitudes Toward Suicide (ATTS) instrument into Indonesian using the RASCH model approach. Method: The method used is non-experimental with an analytical observational approach which is carried out cross-sectionally using the RASCH model with winstep software. The number of samples used was 243 residents with inclusion criteria of being adults (20-40 years) and knowing about suicide cases in Plered District, one of the sub-districts in Purwakarta Regency which had several suicide cases in 2020. This instrument consists of 73 questions.Result: The results showed a value of scale-level (S-CVI) = 0.89 and content validity ratio (S-CVR/UA) = 0.72. This value indicates a good quality of content validity. Analysis based on RASCH shows very good item reliability with a value of 0.98 but the result of person reliability is 0.27 which is caused by the lack of variation in respondents' answers in filling out the questionnaire. This also has an impact on Cronbach's alpha value = 0.32. The analysis is elaborated into four factors consisting of summary statistics, unidimensionality, item size, and Differential Item Functioning (DIF). The results show ideal results, but the pattern of person responses that are not diverse from the respondents causes a logit distribution that is not too far away and the variance is not large.Conclusion: it can be concluded that the consistency of respondents' answers is weak but the quality of the instrument questions in terms of reliability is good and can still be used to measure ATTS.

Deep Variational Embedding Representation on Neural Collaborative Filtering Recommender Systems

Visual representation of user and item relations is an important issue in recommender systems. This is a big data task that helps to understand the underlying structure of the information, and it can be used by company managers and technical staff. Current collaborative filtering machine learning models are designed to improve prediction accuracy, not to provide suitable visual representations of data. This paper proposes a deep learning model specifically designed to display the existing relations among users, items, and both users and items. Making use of representative datasets, we show that by setting small embedding sizes of users and items, the recommender system accuracy remains nearly unchanged; it opens the door to the use of bidimensional and three-dimensional representations of users and items. The proposed neural model incorporates variational embedding stages to “unpack” (extend) embedding representations, which facilitates identifying individual samples. It also replaces the join layers in current models with a Lambda Euclidean layer that better catches the space representation of samples. The results show numerical and visual improvements when the proposed model is used compared to the baselines. The proposed model can be used to explain recommendations and to represent demographic features (gender, age, etc.) of samples.

3D Campus Map Towards Sustainable Development and Infrastructure Management In UPNM

Abstract 3D technology is used in GIS maps to create descriptive graphics that accurately depict the size of real-world items. In a wide variety of various areas, 3D models aid in appearance and survey. For example, 3D maps may depict the height of a building or a mountain in addition to its location. 3D tools must be utilized in conjunction with 2D GIS and then visualized in a 3D environment. The current UPNM campus map accessible to students and staff is not sufficiently helpful and hardly identified its whereabouts. This project was undertaken to develop a web-based 3D campus map and analyze specifically the campus’s area zoning. This study uses a personal computer with Esri CityEngine software to develop the 3D campus map and ArcGIS Online to publish the web-based 3D campus map. The data was acquired by downloading the base map of UPNM from OpenStreetMap (OSM). Completion of data processing results in a web-based 3D UPNM campus map with area zoning. The finding shows that the 3D map, using the Geographical Information System (GIS) platform, is more informative and attractive than the 2D map due to the attribute and spatial data. In addition, the capabilities of the 3D map to visualize and show the campus area and area zoning in the map can be managed according to the structural information. All in all, it can be concluded that this web-based 3D map contributes towards the sustainability of the UPNM infrastructure and campus while facilitating campus maintenance and rehabilitation.

Vision-Based Self-Adaptive Gripping in a Trimodal Robotic Sorting End-Effector

Recyclable waste management, which includes sorting as a key process, is a crucial component of maintaining a sustainable ecosystem. The use of robots in sorting could significantly facilitate the production of secondary raw materials from waste in the sense of a recycling economy. However, due to the complex and heterogeneous types of the recyclable items, the conventional robotic gripping end-effectors, which typically come with a fixed structure, are unlikely to hold onto the full range of items to enable separation and recycling. To this end, a trimodal adaptive end-effector is proposed that can be integrated with robotic manipulators to improve their gripping versatility. The end-effector can deploy effective modes of gripping to different objects in response to their size and porosity via gripping mechanisms based on Nano Polyurethane (PU) adhesive gels, pumpless vacuum suction, and radially deployable claws. While the end-effector's mechanical design allows the three gripping modes to be deployed independently or in conjunction with one another, this work aims at deploying modes that are effective for gripping onto the recyclable item. In order to decide on the suitable modes of gripping a real-time vision system is designed to measure the size and porosity of the recyclable items and advise on a suitable combination of gripping modes to be deployed. Integrated current sensors provide an indication of successful gripping and releasing of the recyclable items. The results of the experiments confirmed the ability of our vision-based approach in identifying suitable gripping modes in real-time, the deployment of the relevant mechanisms and successful gripping onto a maximum of 84.8% (single-mode), 90.9% (dual-mode) and 96.9% (triple-mode) of a specified set of recyclable items.

The relationship between distal trunk morphology and object grasping in the African savannah elephant (Loxodonta africana).

BackgroundDuring reach-to-grasp movements, the human hand is preshaped depending on the properties of the object. Preshaping may result from learning, morphology, or motor control variability and can confer a selective advantage on that individual or species. This preshaping ability is known in several mammals (i.e., primates, carnivores and rodents). However, apart from the tongue preshaping of lizards and chameleons, little is known about preshaping of other grasping appendages. In particular, the elephant trunk, a muscular hydrostat, has impressive grasping skills and thus is commonly called a hand. Data on elephant trunk grasping strategies are scarce, and nothing is known about whether elephants preshape their trunk tip according to the properties of their food.MethodsTo determine the influence of food sizes and shapes on the form of the trunk tip, we investigated the morphology of the distal part of the trunk during grasping movements. The influence of food item form on trunk tip shape was quantified in six female African savannah elephants (Loxodonta africana). Three food item types were presented to the elephants (elongated, flat, and cubic), as well as three different sizes of cubic items. A total of 107 ± 10 grips per individual were video recorded, and the related trunk tip shapes were recorded with a 2D geometric morphometric approach.ResultsHalf of the individuals adjusted the shape of the distal part of their trunk according to the object type. Of the three elephants that did not preshape their trunk tip, one was blind and another was subadult.Discussion and perspectivesWe found that elephants preshaped their trunk tip, similar to the preshaping of other species’ hands or paws during reach-to-grasp movements. This preshaping may be influenced by visual feedback and individual learning. To confirm these results, this study could be replicated with a larger sample of elephants.

Adaptive Bin Packing with Overflow

Motivated by bursty bandwidth allocation and by the allocation of virtual machines to servers in the cloud, we consider the online problem of packing items with random sizes into unit-capacity bins. Items arrive sequentially, but on arrival, an item’s actual size is unknown; only its probabilistic information is available to the decision maker. Without knowing this size, the decision maker must irrevocably pack the item into an available bin or place it in a new bin. Once packed in a bin, the decision maker observes the item’s actual size, and overflowing the bin is a possibility. An overflow incurs a large penalty cost, and the corresponding bin is unusable for the rest of the process. In practical terms, this overflow models delayed services, failure of servers, and/or loss of end-user goodwill. The objective is to minimize the total expected cost given by the sum of the number of opened bins and the overflow penalty cost. We present an online algorithm with expected cost at most a constant factor times the cost incurred by the optimal packing policy when item sizes are drawn from an independent and identically distributed (i.i.d.) sequence of unknown length. We give a similar result when item size distributions are exponential with arbitrary rates. We also study the offline model, where distributions are known in advance but must be packed sequentially. We construct a soft-capacity polynomial-time approximation scheme for this problem and show that the complexity of computing the optimal offline cost is [Formula: see text]-hard. Finally, we provide an empirical study of our online algorithm’s performance.

Differentials in dietary intake of macro and micronutrients in patients with type 2 diabetes and foot ulcers: Observations from a pilot study.

The dietary profiles of patients with type 2 diabetes mellitus (T2DM) from Southern India have been infrequently studied. We aimed to study the differences in dietary intake of macro and micronutrients in elderly patients of Type 2 diabetes mellitus (T2DM), with and without foot ulcers. Elderly patients with T2DM and foot ulcers (n=79; mean age: 60.6 years) and those without foot ulcers (n=59; mean age: 55.0 years) were studied. Biochemical evaluation for measures of glycemia, lipids and albumin were done and staging of foot ulcers was done using Wagner's scale. A 24-hour dietary recall was administered to quantify the mean daily intake (MDI) of macro, micronutrients and trace elements from portion sizes of food items consumed and compared to the recommended dietary allowance (RDA) for Indians aged 55 years and above. In patients with T2DM and foot ulcers, the MDI of carbohydrates, fats and phosphorus were significantly higher whereas the MDI of proteins and micronutrients namely zinc, folic acid, iron and carotene were lower than the RDA. Elderly patients with nephropathy and longer duration of T2DM have higher odds of developing foot ulcers, when compared to patients without foot ulcers. Elderly patients with T2DM and foot ulcers were deficient in dietary intake of proteins and micronutrients inclusive of carotene, folic acid, zinc, and Iron. Clinical care, regular monitoring of dietary intake and appropriate correction of nutritional deficiencies will aid in the management of diabetic foot ulcers.

Bracketing of purchases to manage size uncertainty: Should online retailers be worried?

AbstractFor online apparel retailers, sizing has proven to be a particularly thorny challenge—no matter how much information is provided online, it is often impossible for an online shopper to determine exactly which size of an apparel item will fit her best. Given the increasing ubiquity of free returns (full refund, no return shipping charge), consumers often manage this size uncertainty by bracketing their online apparel purchases, that is, ordering two additional sizes (one smaller, one larger) with the intention of keeping the one that fits best and returning the others. Since bracketing is a relatively new phenomenon in retailing, its net effect on retailer profits is not well‐understood. From a retailer's perspective, bracketing is detrimental since it leads to an increase in consumer returns and the associated costs, which can be quite substantial. On the other hand, bracketing can also be beneficial to the retailer by alleviating consumers' concerns about size, and driving higher net sales. In this paper, we establish how price can be used as a lever to influence consumer bracketing behavior, and examine the impact of bracketing on the profits of a monopolist retailer who offers free returns. We provide prescriptions for when retailers should encourage or discourage bracketing based on three key parameters: the retailer's reverse logistics cost, consumers' return hassle cost, and the product's match probability. As expected, in many cases it is optimal for the retailer to price such that consumers are discouraged from bracketing, and thus the related returns processing costs are avoided. However, we also find that when the product's match probability is moderate, consumers' hassle cost is low and retailer's reverse logistics cost is low, a price that encourages bracketing is the optimal strategy for the retailer, challenging the conventional wisdom that bracketing by consumers is always bad for retailers.

Small Wideband Antenna for On-Metal UHF RFID Tag Design

A double-layer antenna with a small footprint of 47 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times21$ </tex-math></inline-formula> mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times2.36$ </tex-math></inline-formula> mm is proposed for broadband on-metal applications. Here, a rectangular loop is deployed to excite the underneath patch. A vertical slit is integrated into the patch to effectively improve the impedance matching between the antenna and the microchip as well as the tag bandwidth. The bandwidth tuning mechanism is simple and convenient. It can be easily done by adjusting the slit width or the slit position for different tuning sensitivities. Measurements have been conducted with the use of a 4W EIRP transmitting power, and the tag can be read from at least 4 m within a broad frequency range of 865 MHz – 960 MHz when it is mounted on different sizes of metallic plates (12 cm - 24 cm) and metallic items. The wide operating frequency range of the tag can cover both the European and U.S. RFID bands and it has a stable detectable range.

Meta-Heuristic Algorithms for the Generalized Extensible Bin Packing Problem With Overload Cost

In this paper, we consider a generalized the extensible bin packing problem with overload cost, first proposed by Denton et al. [1] in 2010, in which the total size of items packed into a bin is allowed to exceed its capacity, and the cost incurred each bin is equal to the fixed cost plus the overload cost, the objective is to minimize the total cost of all bins. According to the characteristics of the problem, we first propose an improved ant colony optimization algorithm (IACO), which enhances the positive feedback effect of ACO by improving the update method of pheromone and the adaptive adjustment parameters. We also introduce a variable neighborhood search method in ACO to improve the convergence of the algorithm and get rid of the phenomenon of local extrema. Then, we present a discrete particle swarm optimization algorithm (DPSO) to solve the problem. In order to ensure the uniform distribution and high quality of the initial particle swarm, we use some heuristic methods in the initialization process of the swarm, so that the initial particle can cover the entire search space with a large probability, which effectively improves the performance of DPSO algorithm. Finally, we compare and analyze the performance of these proposed algorithms through two sets of computational experimental frameworks. Compared with some algorithms in the literature, computational results signify that the improved ACO algorithm and MDPSO algorithm are more competitive than some other metaheuristic algorithms..