International Journal of Innovation in Engineering
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Business Location and Customer Patronage in the Hotel Industry in Benue State, Nigeria
Get PDFThis study examined the effect of business location on customer patronage of hotels in Benue State, Nigeria: The study specifically examined the effect of parking space, road network and accessibility and security and safety on customer patronage in the hotel industry in Benue State, Nigeria. The survey design was adopted for the study. The population for this study was 474. This figure consists of 159 tenured staff of 9 hotels selected across the 3 geopolitical zones of the state and 315 customers purposively sampled (35 from each hotel). The study adopted census sampling and 474 questionnaires were administered on entire population. However, only 402 were retrieved and analyzed. Pearson correlation was used to test the hypotheses while multiple regression analysis was employed to test the extent of the effect of independent variables on the dependent variable. Findings of the study revealed that parking space, road network and accessibility and security and safety all have significant effect on customer patronage in the hotel industry in Benue State, Nigeria The study concluded that repeat patronage, customer retention and customer referrals can be achieved through provision of innovative parking space, accessible road network and assured security and safety of guest. The study recommended among others that hotels managers in Benue State should be innovative and aggressive in providing parking space for their customers
DHVSU Electrical Engineering Department Goes Green: Feasibility of Solar-Powered Building Using an Off-Grid Hybrid Solar Inverter
Get PDFThis research project unfolds the practicability of utilizing an Off-Grid Hybrid Solar Inverter to power up the Electrical Engineering Building in Don Honorio Ventura State University. To satisfy the aims of this research, a Solar PV System design was used to make use of the solar energy converting it to electrical energy to supply the whole building. This study was guided by doing a load schedule of all the appliances in the whole building to acquire the total power and total energy consumption, using it as a basis for the selection of the required electrical components and computation of the roof area to select a suitable solar panel in order to ensure the functionality of the whole Solar PV System. The raw data gathered was analyzed using formulas to acquire the needed electrical values. The findings resulted in the development and completion of the Solar PV System Design. The last part of the research is the results, discussions, conclusions, and recommendations. These provided the finalization and endorsement of the whole study
Optimizing The Transportation of Petroleum Products in A Possible Multi-Level Supply Chain
Get PDFThe goal of many supply chain optimization problems is to minimize the costs of the entire supply chain network. However, since environmental protection is one of the main concerns, the green supply chain network has been seriously considered as a solution to this concern in order to minimize its effects on nature. This article refers to the modeling and solution of a green supply chain network for the transportation of petroleum products in order to reduce the annual costs, considering the environmental effects. In this article, the cost elements of the supply chain such as the transportation costs of each petroleum product, operating costs, the cost of purchasing crude oil products and the fixed costs of building oil centers as well as the components of the environmental effects of the supply chain such as the amount of gas emissions and volatile organic particles produced by transportation options in the supply chain. considered green. Considering these two components (cost and environmental impact), we have proposed a multi-objective supply chain model. In this facility model, oil centers have limited capacity and at each level of the chain, there are several types of transportation options with different costs. To solve the problem, we have used two multi-objective particle swarm optimization algorithms and genetic multi-objective optimization algorithm with non-dominant sorting II with a priority-based decoding to encode the chromosome. Finally, we have used TOPSIS method to compare these two algorithms
Using Support Vector Machine For Classification And Feature Extraction Of Spam In Email
Get PDFWe provide an overview of recent and successful content-based e-mail spam filtering algorithms in this article. Our main focus is on spam filters based on machine learning and variants influenced by them. We report on significant ideas, methodologies, key endeavors, and the field's current state-of-the-art. The initial interpretation of previous work demonstrates the fundamentals of spam filtering and feature engineering in e-mail. We finish by looking at approaches, procedures, and evaluation standards, as well as exploring intriguing offshoots of recent breakthroughs and proposing directions of future research
Organoleptic Evaluation and Physiochemical Characteristics of Powdered Plant Organs of the Traditional Medicinal Plant Caloncoba Echinata
Get PDFThe organoleptic evaluation and physiochemical characteristics of dried powdered plant organs (leaves, stem bark and root bark) of the traditional medicinal plant Caloncoba echinata have been investigated. Organoleptic character refers to evaluation each of the powdered traditional medicinal plant by colour, odour, taste, texture and particle size. Physico‐chemical studies such total ash, water soluble ash, acid insoluble ash, water and alcohol soluble extract, loss on drying at 105°C of dried powdered plant organs and then heated in a laboratory furnace to 1000oC were carried out. The spicy and bitter taste each of the powdered plant materials during organoleptic evaluation indicated that the plant organs investigated contained alkaloids thus supporting the use of the plant as a traditional pharmaceutical. The colour of the powdered plant organs ranges from light green for the leaves to brown for both the stem and root barks. The colour of the powdered plant material will also help who so ever wish to buy and use the plant material for medicinal purpose. It helps prevent adulteration. The moisture content in the various plant organs investigated is greater in the root bark (33.0%) than in the stem bark (16.463%) and the root bark (13.62%). The ash content in the plant organs investigated was also greater in the root bark (12.509%) than the stem bark (8.7%) and leaves bark (6.4%), thus indicating that the root bark of the plant contained more inorganic compounds. The leaves of the plant contained more water soluble (50.2%) substances than the stem bark (19.6%) and the root bark (6.4%). The root bark contained more water insoluble (93.6%) and acid soluble (84.9%) substances than the leaves and stem bark of the plant organs investigated. The pH of water soluble ash was found to be greater than 7 indicating the basicity of the extracts, with the root bark (pH = 10.70) more basic than the stem bark (pH = 9.10) and leaves (pH = 8.71) respectively. Organoleptic evaluation and physiochemical characteristics carried out on the dried powdered plant organs of the traditional medicinal plant Caloncoba echinata indicated that the plant is suitable for use in Traditional Medicine
Various Deep Learning Techniques Involved In Breast Cancer Mammogram Classification – A Survey
Get PDFThe most common and rapidly spreading disease in the world is breast cancer. Most cases of breast cancer are observed in females. Breast cancer can be controlled with early detection. Early discovery helps to manage a lot of cases and lower the death rate. On breast cancer, numerous studies have been conducted. Machine learning is the method that is utilized in research the most frequently. There have been a lot of earlier machine learning-based studies. Decision trees, KNN, SVM, naive bays, and other machine learning algorithms perform better in their respective fields. However, a newly created method is now being utilized to categorize breast cancer. Deep learning is a recently developed method. The limitations of machine learning are solved through deep learning. Convolution neural networks, recurrent neural networks, deep belief networks, and other deep learning techniques are frequently utilized in data science. Deep learning algorithms perform better than machine learning algorithms. The best aspects of the images are extracted. CNN is employed in our study to categorize the photos. Basically, CNN is the most widely used technique to categorize images, on which our research is based
Dynamic DEA based on DMAIC model to evaluate passengers’ transportation in road transportation organization
Get PDFIn Iran, more than 94% of transportation is road transportation. The goal of this article is to assess and to rate road transportation companies of 31 country provinces and to determine the effect of integrating six sigma DMAIC cycle and dynamic data envelopment analysis (DDEA) on effective inputs and outputs. In this article the BCC output-oriented has been changed to dynamic model. According to the conducted sensitivity analysis in improvement phase, it is determined what changes should be made in the values of inputs and outputs for inefficient units to become efficient. DMAIC cycle control system is monitored through statistical control charts to be able to control and monitor the values of inputs and outputs. Integrating these methods help us with a more effective evaluation of dynamic environment and through sensitivity analysis in improvement phase, effectiveness and efficiency of units will increase and help to achieve the goals set
Innovative Drying Tool (Oven) with the Hot Air Flow Method to Improve Productivity and Quality of Sugar for Small Medium Enterprise in Indonesia
Get PDFSugar production from palm trees, has become a livelihood for some Indonesian people. The aim of this research is to help Small Medium Enterprises increase the production of ant sugars by modifying conventional ovens with ovens using the hot air flow method. the result was that it could add capacity (kg) in shorter time period (minutes) also reduce the use of liquid petroleum gas (kg), so that it became more cost-effective and did not require work to rotate containers, and most importantly the produced ant sugar also had better quality
Investigation of the Effects of Nano Silica Particles and Zeolite on the Mechanical Strengths of Metakaolin-Based Geopolymer Concrete
Get PDFDue to its unique qualities, concrete is the most extensively utilized substance in the construction sector after water. However, because one ton of Portland cement produces about one ton of CO2, the Portland cement manufacturing process has considerable disadvantages. As a result, an alternative to Portland cement appears to be required. Geopolymer is a new and environmentally friendly cementitious material that can be used in place of Portland cement. Chemically and mechanically, geopolymer concrete outperforms traditional concrete. The weight ratio of water to dry matter used in polymerization, as well as the weight ratio of sodium silicate to NaOH solution, have an impact on the compressive strength of geopolymer concrete. As a result, additional research into these variables appeared to be necessary. This paper specifically looked at how nanosilica and zeolite affected the mechanical strength of metakaolin-based geopolymer concrete. Nanosilica was added to metakaolin-based geopolymer concrete to improve mechanical characteristics. Furthermore, using zeolite in a metakaolin-based aluminosilicate source lowers the mechanical strength of geopolymer concrete while also lowering the cost. The optimal weight ratios for polymerization water to dry matter and sodium silicate solution to NaOH solution were 0.4741 and 1.5, respectively, resulting in maximum compressive pressures of 3, 7, and 28 days
Providing a model for the issue of multi-period ambulance location
Get PDFIn this study, two mathematical models have been developed for assigning emergency vehicles, namely ambulances, to geographical areas. The first model, which is based on the assignment problem, the ambulance transfer (moving ambulances) between locations has not been considered. As ambulance transfer can improve system efficiency by decreasing the response time as well as operational cost, we consider this in the second model, which is based on the transportation problem. Both models assume that the demand of all geographical locations must be met. The major contributions of this study are: ambulance transfer between locations, day split into several time slots, and demand distribution of the geographical zone. To the best of our knowledge the first two have not been studied before. These extensions allow us to have a more realistic model of the real-world operation. Although, in previous studies, maximizing coverage has been the main objective of the goal, here, minimizing operating costs is a function of the main objective, because we have assumed that the demand of all geographical areas must be met