Enhancing Promotional Strategy Mapping Using the K-Means Clustering Algorithm to Raise Sales

To enhance sales, organizations must improve the alignment of their promotional tactics. Enterprises have the ability to promote their goods in locations where there is demand for them. Facilitating the delivery of the goods would enhance the ease with which clients can carry out their purchases and sales transactions. A corporation's ability to strategically allocate its goods enables it to expand its operations. Prospective clients have a greater array of choices at their disposal than the total number of enterprises operating within the same sector. This is accomplished by using a diverse range of promotional media to enhance the sales of products and services. Optimizing promotional strategies is the first and critical stage in presenting items to clients, as it directly impacts the benefits that the firm will get. So far, the sales process has not been affected by the promotional method. The objective of this research was to use the K-Means Clustering algorithm in a data mining procedure to optimize the categorization of customer data, CRISP-DM is used for the purpose of comprehending and preparing data, constructing models, evaluating them, and deploying them. The CRISP-DM method is employed specifically for the construction of clusters. A non-hierarchical clustering technique called K-Means divides data into many groups according on how similar they are. The program facilitates the determination of appropriate location mapping for promotional purposes. The study results may serve as a foundation for decision-making in order to maximize promotional techniques, using the generated clusters

Climate change and Spatial Conservation Planning

Peer Reviewe

High-Level Object Oriented Genetic Programming in Logistic Warehouse Optimization

Disertační práce je zaměřena na optimalizaci průběhu pracovních operací v logistických skladech a distribučních centrech. Hlavním cílem je optimalizovat procesy plánování, rozvrhování a odbavování. Jelikož jde o problém patřící do třídy složitosti NP-težký, je výpočetně velmi náročné nalézt optimální řešení. Motivací pro řešení této práce je vyplnění pomyslné mezery mezi metodami zkoumanými na vědecké a akademické půdě a metodami používanými v produkčních komerčních prostředích. Jádro optimalizačního algoritmu je založeno na základě genetického programování řízeného bezkontextovou gramatikou. Hlavním přínosem této práce je a) navrhnout nový optimalizační algoritmus, který respektuje následující optimalizační podmínky: celkový čas zpracování, využití zdrojů, a zahlcení skladových uliček, které může nastat během zpracování úkolů, b) analyzovat historická data z provozu skladu a vyvinout sadu testovacích příkladů, které mohou sloužit jako referenční výsledky pro další výzkum, a dále c) pokusit se předčit stanovené referenční výsledky dosažené kvalifikovaným a trénovaným operačním manažerem jednoho z největších skladů ve střední Evropě.This work is focused on the work-flow optimization in logistic warehouses and distribution centers. The main aim is to optimize process planning, scheduling, and dispatching. The problem is quite accented in recent years. The problem is of NP hard class of problems and where is very computationally demanding to find an optimal solution. The main motivation for solving this problem is to fill the gap between the new optimization methods developed by researchers in academic world and the methods used in business world. The core of the optimization algorithm is built on the genetic programming driven by the context-free grammar. The main contribution of the thesis is a) to propose a new optimization algorithm which respects the makespan, the utilization, and the congestions of aisles which may occur, b) to analyze historical operational data from warehouse and to develop the set of benchmarks which could serve as the reference baseline results for further research, and c) to try outperform the baseline results set by the skilled and trained operational manager of the one of the biggest warehouses in the middle Europe.

GIS based Infestation Biogeography of Palm Weevils, Pachymerus cardo in the Niger Delta, Nigeria

Data on Oil Palm Kernel Borer Pachymerus cardo were compiled from several sites in the Niger Delta at different Euclidean distances ranging from 11-127 kilometers. The monthly infestation rates and location similarity in infestation were examined with univariate non-spatial statistics and geographic information geostatistical tools. The results of the within month abundance of the weevils showed an average and peak infestation rate of (452:800)  in May with a slow increase through the months of June(497:921) to peak values in August (616:1272). This dropped to 578:1206 and 525:924 in September and October respectively. No significant differences within-month mean scores for all the months (p < 0.05) by both the student t and Hsu pair comparisons were observed. Significant differences from univariate non-spatial statistics were however observed in site infestation distribution (p < 0.05) between  Obiozimini, Omerelu,  Ebubu, Omoku, Egbeda and the following sites namely Abuloma, Obowo, Mbieri, Isiala Ngwa, Kaiama, Old  Bakana and between Egbeda and Obiozomini. A scaling of the sites using geostatistics techniques of kriging and inverse distance weighting indicated that geographic association among sites was independent of nearness or distance decay. A spatial autocorrelation analysis at a z-score of 2.98 and 95% confidence rejected the null hypothesis of the cause for the observed distribution to be random. The clustered nature of the weevil pest is attributed to the stable habitat and wide spread of the oil palm which is thriving within the same environmental variables of rainfall and humidity among the sites from where the weevils were collected. Key words. Oil Palm, Weevil, Pachymerus cardo, GIS, Autocorrelatio

A Survey on Natural Inspired Computing (NIC): Algorithms and Challenges

Nature employs interactive images to incorporate end users2019; awareness and implication aptitude form inspirations into statistical/algorithmic information investigation procedures. Nature-inspired Computing (NIC) is an energetic research exploration field that has appliances in various areas, like as optimization, computational intelligence, evolutionary computation, multi-objective optimization, data mining, resource management, robotics, transportation and vehicle routing. The promising playing field of NIC focal point on managing substantial, assorted and self-motivated dimensions of information all the way through the incorporation of individual opinion by means of inspiration as well as communication methods in the study practices. In addition, it is the permutation of correlated study parts together with Bio-inspired computing, Artificial Intelligence and Machine learning that revolves efficient diagnostics interested in a competent pasture of study. This article intend at given that a summary of Nature-inspired Computing, its capacity and concepts and particulars the most significant scientific study algorithms in the field

Global loss of avian evolutionary uniqueness in urban areas

Urbanization, one of the most important anthropogenic impacts on Earth, is rapidly expanding worldwide. This expansion of urban land-covered areas is known to significantly reduce different components of biodiversity. However, the global evidence for this effect is mainly focused on a single diversity measure (species richness) with a few local or regional studies also supporting reductions in functional diversity. We have used birds, an important ecological group that has been used as surrogate for other animals, to investigate the hypothesis that urbanization reduces the global taxonomical and/or evolutionary diversity. We have also explored whether there is evidence supporting that urban bird communities are evolutionarily homogenized worldwide in comparison with nonurban ones by means of using evolutionary distinctiveness (how unique are the species) of bird communities. To our knowledge, this is the first attempt to quantify the effect of urbanization in more than one single diversity measure as well as the first time to look for associations between urbanization and phylogenetic diversity at a large spatial scale. Our findings show a strong and globally consistent reduction in taxonomic diversity in urban areas, which is also synchronized with the evolutionary homogenization of urban bird communities. Despite our general patterns, we found some regional differences in the intensity of the effect of cities on bird species richness or evolutionary distinctiveness, suggesting that conservation efforts should be adapted locally. Our findings might be useful for conservationists and policymakers to minimize the impact of urban development on Earth's biodiversity and help design more realistic conservation strategies.Peer Reviewe

Effects of Urbanization on the Avian Community of Oak Woodlands

Continued human population growth leads to further expansion of high-density population centers and agricultural land necessary to sustain them. With this urban expansion comes a myriad of effects on both native habitat and wildlife. In birds, these effects can have a variety of negative impacts on behavior and physical health. Habitat degradation, largely through various forms of pollution, leads to impaired immune responses, increased stress levels, altered behavior, and much more. The wide range of effects impacting wild birds and their habitat can also alter the structure of local communities. Only species that can survive on or adapt to the resources and conditions of the urban landscape fare well, leading to a reduction in avian diversity, and the homogenization of urban avian communities. The city of Chicago, together with the range of land use types around it, makes up an urban-rural gradient, providing an opportunity to study the effects of urbanization. Across this gradient, during the summers of 2018 and 2019, point-count surveys of breeding birds in 28 oak woodland patches were performed to measure the effect of urbanization on the local bird community. Contrary to similar studies, no significant effect of urban development was found on either density or overall species richness of breeding birds. When grouped by guilds, significant impacts on species richness were found. While some results matched expected patterns (omnivore species richness peaks at high levels of development), many did not. Granivores and ground-foragers tend to respond positively to urbanization but showed no significant difference here. The focus of this study on oak woodlands may be responsible, as a single habitat type is far more consistent than the whole of an urban-rural matrix. Additionally, the urban birds typically found in cities across the world do not typically inhabit woodlands, freeing up resources for local natives

Linking Environmental Variability to the Biogeography of Placopecten magellanicus in the Gulf of Maine

The Atlantic sea scallop (Placopecten magellanicus) supports a highly valuable fishery in the United States over its range on the Northwest Atlantic Shelf. Scallop distribution has been shown to be highly affected by changes in climactic variables. Therefore, long-term changes in the thermal regime of the Gulf of Maine are expected to greatly impact scallop ecology; however, these projected changes have rarely been quantified. The modeling framework developed for my dissertation research will improve our understanding of the distribution of scallop habitat as well as the biogeography for this species. Additionally, this modeling capacity will provide several tangible tools to visualize species distribution over space and time as well as to evaluate potential impacts of a changing Gulf of Maine ecosystem. The framework for my dissertation research is comprised of 1) a bioclimate envelope covering the Gulf of Maine to quantify spatiotemporal variability in scallop habitat; 2) a statistical species distribution model to predict spatiotemporal changes in scallop distribution in the Gulf of Maine; 3) the design of a dredge survey in the Northern Gulf of Maine to obtain scallop biomass estimates; and 4) a two-stage modeling and computer simulation framework to refine fisheries surveys. Due to changing oceanographic conditions within the Gulf of Maine ecosystem it is becoming increasingly important to view resource management from within the context of climate change. Effective management of marine resources requires knowledge of population distribution and dynamics, however; fisheries managers must frequently base decisions on limited information. The modeling framework developed in my dissertation establishes the ability to better visualize sea scallop distribution as well as to evaluate the potential impacts of a changing ecosystem on this species. The results provided by this research increase the extent of knowledge about sea scallop ecology and have the potential to contribute to the conservation of this species. Additionally, the modeling approaches developed throughout my dissertation are highly generalizable to a variety of commercially important species and may be useful in advising conservation efforts for other fisheries in the Northwest Atlantic to help ensure the implementation of adaptive management strategies under uncertain climate conditions

Barriers to chimpanzee gene flow at the south-east edge of their distribution

Populations on the edge of a species' distribution may represent an important source of adaptive diversity, yet these populations tend to be more fragmented and are more likely to be geographically isolated. Lack of genetic exchanges between such populations, due to barriers to animal movement, can not only compromise adaptive potential but also lead to the fixation of deleterious alleles. The south-eastern edge of chimpanzee distribution is particularly fragmented, and conflicting hypotheses have been proposed about population connectivity and viability. To address this uncertainty, we generated both mitochondrial and MiSeq-based microsatellite genotypes for 290 individuals ranging across western Tanzania. While shared mitochondrial haplotypes confirmed historical gene flow, our microsatellite analyses revealed two distinct clusters, suggesting two populations currently isolated from one another. However, we found evidence of high levels of gene flow maintained within each of these clusters, one of which covers an 18,000 km2 ecosystem. Landscape genetic analyses confirmed the presence of barriers to gene flow with rivers and bare habitats highly restricting chimpanzee movement. Our study demonstrates how advances in sequencing technologies, combined with the development of landscape genetics approaches, can resolve ambiguities in the genetic history of critical populations and better inform conservation efforts of endangered species