Low Initial Cost Research Articles

An Investigation Of Factors Influencing The Implementation Of Cloud Computing By SMEs

Cloud Computing has emerged as a groundbreaking technology with widespread impact, bringing ad- vantages such low initial costs, cost-effectiveness for intermittent use, ease of management, scalability, device and location independence, and rapid innovation to businesses of various scales. Despite the benefits of implementing Cloud Computing, SMEs are yet to fully embrace it. To increase cloud implementation rate there is the need to investigate the key factors that influence its implementation by SMEs. The study employed the TOE framework to identify factors that have great influence in cloud implementation through a literature review and a survey of selected SMEs. A closed ended questionnaire was developed to ascertain these factors within the context of Bolgatanga by engaging key stakeholders, including ICT managers, CEOs/General Managers, and Admin/Accounts personnel, of selected SMEs to provide insights into the study. The study reveals that relative advantage holds the most significant influence among various factors, such as compatibility, top management support, competitive pressure, and regulatory support, across technological, organizational, and environmental categories in the cloud implementation process. This underscores the importance for SMEs to prioritize effective communication especially the benefits of cloud technology to stakeholders. This would pose a great deal for SMEs to implement cloud thereby enhancing business operations.

Analisis Faktor–faktor yang mempengaruhi minat mahasiswa berinvestasi di aplikasi bibit

Based on observations of students who have invested, many of them use the Bibit App. Apart from the low initial investment cost, they also trust the Bibit App because it is registered with the Financial Services Authority (OJK). The Bibit App was created with the aim that people can immediately start investing easily and get risks that match their financial goals. This study was conducted to examine whether perceived benefits, perceived convenience, investment risk and investment knowledge have an influence on student interest in investing in the Bibit Application. This study uses a sample of undergraduate students at Merdeka University of Malang who have and have used the Bibit Application as a means of investment with a total of 64 respondents. This research method is quantitative research, the data obtained through google form is a type of primary data. The data in this study were processed using the SPSS (Statistical Package for Social Sciens) version 23 application. This study shows the results that perceived benefits and investment risk have an influence on student interest in investing in the Bibit Application. Meanwhile, perceived convenience and investment knowledge have no influence on student interest in investing in the Bibit Application.

A proposed design for 5-G fire detecting and extinguishing system: ultra-large container ship case study

ABSTRACT The containerized cargo volume reaches 168.2 million TEU. There have recently been a staggering number of fire catastrophes onboard container ships. Investigations have identified that a rapidly developing fire is one of the main challenges in container fires. On the other hand, firefighting regulations had disregarded container vessel capacity increase. The resulting financial losses and environmental catastrophes paid astronomical bills. This research elaborates on an innovative solution utilizing a 5 G wireless self-detecting and extinguishing fire-control system. The system was applied in a case study of 19,870 TEU ultra large-container ships; The results demonstrate the number and locations of the system components. The system can reduce human interference with the fires onboard. The feasibility analysis output shows a low initial cost compared to the losses of such incidents. Moreover, the time of radio spectrum signals of the proposed system is high speed; remarkably, the internal container monitoring needs around 30 seconds to detect heat and another few seconds to activate the CO2 and smother the suspicious container in its early intuition with allocation bothered alarm. The firefighting improvement technology could be a promising solution for monitoring and controlling dangerous cargo containers fire.

Ferrocement, Carbon, and Polypropylene Fibers for Strengthening Masonry Shear Walls.

This paper describes an experimental investigation into the feasibility of using ferrocement jacketing, polypropylene fibers, and carbon fiber reinforced polymer sheets (CFRP) to enhance the shear resistance of unreinforced brick masonry. The study involved testing 12 wall panels in diagonal compression, three of which were strengthened using each of the above-mentioned techniques. The results showed that all three strengthening techniques led to a significant improvement in the shear resistance and deformation capacity of the unreinforced walls. Furthermore, the results showed that the strengthened walls exhibited a significant improvement in shear resistance and deformation capacity by a factor of 3.3-4.7 and 3.7-6.8, respectively. These findings suggest that ferrocement jacketing is a viable and highly effective method for strengthening masonry structures. Test results can assist in the decision-making process to identify the most suitable design and retrofitting solution, which could indicate that not only new materials, but also traditional methods and materials (ferrocement) could be interesting and effective, also considering their lower initial cost.

Energy and Economic Analysis of Renewable Energy-Based Isolated Microgrids with AGM and Lithium Battery Energy Storage: Case Study Bigene, Guinea-Bissau

By the year 2020, 90% of the population with access to electricity worldwide was surpassed. However, the reality is very different for many countries, especially for those on the African continent that had more than 572 million people without electricity service at the end of 2019. This work studies the implementation of an isolated microgrid activated with photovoltaic energy and energy storage in batteries under the case study of the community of Bigene, located in the African country of Guinea-Bissau. This type of project is a potential solution to the problem of access to energy, but as the cost of the energy storage system is typically very high, this work technically and economically addresses the effect of using absorbed glass material (AGM) and lithium batteries. A simulator was developed using TRNSYS software to analyze the operation of the microgrid under a defined annual demand profile for different types of users, and economic analysis was conducted considering a project lifetime of 25 years. The results showed no significant differences in the solar fraction of both types of batteries when the photovoltaic power was less than 600 kW, regardless of the capacity of the storage bank. The analysis of auxiliary power requirements showed that lithium technology leads to a lower consumption from 800 kW of PV capacity, and utilizing less than this capacity did not have a significant difference with AGM batteries. In this microgrid with a photovoltaic capacity of less than 700 kW and an energy storage of less than 2580 kWh, the type of storage technology, AGM or lithium, did not represent a considerable difference in the levelized cost of energy, indicating that AGM technology could be selected considering its low initial investment cost compared to lithium batteries.

Comparison of Oxford Nanopore Technologies and Illumina MiSeq sequencing with mock communities and agricultural soil

Illumina MiSeq is the current standard for characterizing microbial communities in soil. The newer alternative, Oxford Nanopore Technologies MinION sequencer, is quickly gaining popularity because of the low initial cost and longer sequence reads. However, the accuracy of MinION, per base, is much lower than MiSeq (95% versus 99.9%). The effects of this difference in base-calling accuracy on taxonomic and diversity estimates remains unclear. We compared the effects of platform, primers, and bioinformatics on mock community and agricultural soil samples using short MiSeq, and short and full-length MinION 16S rRNA amplicon sequencing. For all three methods, we found that taxonomic assignments of the mock community at both the genus and species level matched expectations with minimal deviation (genus: 80.9–90.5%; species: 70.9–85.2% Bray–Curtis similarity); however, the short MiSeq with error correction (DADA2) resulted in the correct estimate of mock community species richness and much lower alpha diversity for soils. Several filtering strategies were tested to improve these estimates with varying results. The sequencing platform also had a significant influence on the relative abundances of taxa with MiSeq resulting in significantly higher abundances Actinobacteria, Chloroflexi, and Gemmatimonadetes and lower abundances of Acidobacteria, Bacteroides, Firmicutes, Proteobacteria, and Verrucomicrobia compared to the MinION platform. When comparing agricultural soils from two different sites (Fort Collins, CO and Pendleton, OR), methods varied in the taxa identified as significantly different between sites. At all taxonomic levels, the full-length MinION method had the highest similarity to the short MiSeq method with DADA2 correction with 73.2%, 69.3%, 74.1%, 79.3%, 79.4%, and 82.28% of the taxa at the phyla, class, order, family, genus, and species levels, respectively, showing similar patterns in differences between the sites. In summary, although both platforms appear suitable for 16S rRNA microbial community composition, biases for different taxa may make the comparison between studies problematic; and even with a single study (i.e., comparing sites or treatments), the sequencing platform can influence the differentially abundant taxa identified.

Digital tools in chemical engineering education: The needs and the desires

Educators in chemical engineering have a long and rich history of employing digital tools to solve fundamental engineering problems. Today, with the megatrend of digitalisation, there is a growing set of tools that can be used for chemical engineering education. However, identifying which tool is ideally suited to support teaching a given chemical engineering concept can be challenging. To answer this question a survey was distributed to Heads of Departments at IChemE institutions and members of the IChemE committees focused on digitalisation. The survey respondents rated Microsoft Excel (VBA), commercial simulators, and scripting tools as ideal for teaching core subjects such as mass and energy balances, mass transfer and reaction engineering while respondents found 3D Models, and Virtual/Augmented Reality models as being most suited for teaching subjects such as process design, safety and sustainability. Mathematical/programming simplicity, ease of maintenance, and low initial investment costs were identified as key non-technical aspects that will hinder the adoption of a given digital tool. Weighing the benefits of education and non-technical hurdles, the respondents preferred the use of simpler digitalisation platforms such as Excel and scripting languages over the more advanced platforms such as Virtual/Augmented Reality where possible. It was identified that the widespread adoption of more advanced digitalisation tools will require removal of the above mentioned non-technical barriers as well as other barriers such as tool shareability.

Insights into biohydrogen production from algal biomass: Challenges, recent advancements and future directions

Detrimental greenhouse gases (GHGs) emissions producing conventional sources of energy are needed to be replaced with eco-friendly and renewable energy sources. Researchers have strongly highlighted biohydrogen is an alternate source of high-energy for alleviating the energy crisis due to its having energy content 2.75 times higher than that of fossil fuels. In addition, the fuel known for leaving no trails of harmful emissions by combustion and emits only water as a by-product. Algal biomass has emerged as a potential feedstock for biohydrogen production. The objectives of the present article is to illustrate the various ways of algal biohydrogen production along with mechanisms and challenges of biohydrogen production in which factors controlling the hydrogen production process and challenges in the economic aspect, technical aspect and storage are considered. Future road map of biohydrogen from algae is also delineated in view of decarbonization pathway and respective SWOT analysis pointing strength, weakness, opportunities and threats. Key strength of algal biohydrogen is identified as excellent carbon capture and waste valorization capability of algae to promote zero-waste circular bioeconomy. Along with these, some weaknesses of this biological approach include technological hinderances leading low biohydrogen yield and high initial cost investment. Implementing genetic/metabolic or environmental manipulations has shown promising opportunity to improve algal biohydrogen to ensure long-term sustainability. Cascading effects of technological immaturity followed by lack of credibility even after suggested alterations are few of threats that need to be superintended by optimizing operational parameters, metabolic engineering, etc.

Socio-Economic Factors Contributing to Crashes Involving Motor Tricycles in Greater Kumasi Metropolitan Area, Ghana

Commercial passenger motor tricycles are a recent addition to the vehicle mix in urban areas of Ghana having been introduced in about 2015. While they serve a good purpose and fill a niche in the transport market in Ghanaian cities, this mode of transport is characterized by several road crashes that sometimes result in fatalities. Consequently, the objective of this study was to understand social and economic factors as well as motor tricycles’ operational characteristics and related crashes. A detailed study of this mode of transport in the study area revealed that the socio-economic factors that contribute to crashes involving commercial motor tricycles include the revenue per day, amount spent on fuel per day, and operating days, but with a negative relationship between daily revenue and amount spent on fuel and crash severity. Operational characteristics studied revealed a general improvement in operators’ level of education, a situation where owner-operators are more careful with their vehicles, patrons’ preference for new tricycles, and relatively good returns from operations of these vehicles. Operators also work for long hours and on all days of the week. Further analysis of the data revealed that there are major safety concerns. While the Building and Road Research Institute (BRRI) reports a fatality share of 28% with an annual increase of 3.9% for motorcycle-related crashes in Ghana, the National Road Safety Authority, in the year 2010, indicated a crash rate of more than 50% which is yet to be updated. Recent data for 2019 published by the BRRI estimate a rate of 8.15 fatalities per 10,000 vehicles with a total of 829 total crashes in 2019 for motorcycles, tricycles, and rickshaws and 2.7 motorcycle fatalities per 10,000 vehicles. Similar data are yet to be estimated for motorcycles and commercial tricycles in the Greater Kumasi Metropolitan Area. However, our study revealed a crash rate of 67% for motor tricycle operators in the study area on account of an increase in population, low initial capital cost, and the ability to maneuver in inaccessible areas. It is recommended that, in view of the preponderance of passenger tricycles in the study area, massive educational campaigns involving all stakeholders be pursued.

Finite Difference Modeling and Experimental Investigation of Cyclic Thermal Heating in the Fused Filament Fabrication Process.

Fused filament fabrication (FFF) is one of the most popular additive manufacturing (AM) processes due to its simplicity and low initial and maintenance costs. However, good printing results such as high dimensionality, avoidance of cooling cracks, and warping are directly related to heat control in the process and require precise settings of printing parameters. Therefore, accurate prediction and understanding of temperature peaks and cooling behavior in a local area and in a larger part are important in FFF, as in other AM processes. To analyze the temperature peaks and cooling behavior, we simulated the heat distribution, including convective heat transfer, in a cuboid sample. The model uses the finite difference method (FDM), which is advantageous for parallel computing on graphics processing units and makes temperature simulations also of larger parts feasible. After the verification process, we validate the simulation with an in situ measurement during FFF printing. We conclude the process simulation with a parameter study in which we vary the function of the heat transfer coefficient and part size. For smaller parts, we found that the print bed temperature is crucial for the temperature gradient. The approximations of the heat transfer process play only a secondary role. For larger components, the opposite effect can be observed. The description of heat transfer plays a decisive role for the heat distribution in the component, whereas the bed temperature determines the temperature distribution only in the immediate vicinity of the bed. The developed FFF process model thus provides a good basis for further investigations and can be easily extended by additional effects or transferred to other AM processes.

Experimental and numerical investigation of moisture variations in unbound pavements with sprayed seals during drying and wetting

Unbound pavements with sprayed seals are one of the major types of flexible pavements used worldwide. Sprayed sealing can be considered as an economical surfacing method in particularly Australia and New Zealand due to the low initial cost. However, moisture can enter the underlying pavement layers through sprayed seals as they are variably permeable, resulting in significant performance losses in underlying pavement structural layers. Hence, an in-depth understanding of how moisture varies in the base layer under different sprayed seals is essential for designing and maintaining pavement to meet the required long-term performance.This paper investigates moisture variations in unbound base layers under typical sprayed seals using experimental and numerical techniques. Pavement layers were replicated in the laboratory in columns with three different sealing conditions such as unsealed, 10 mm single-single sealed and 14 mm single-single sealed. The moisture variations in the base layers were monitored under drying and wetting conditions using moisture sensors over several months with targeted experiments. Moreover, this study characterises two typical types of sprayed seal samples collected from operating road surfaces using X-ray tomography and laboratory experiments. The experimental results show that typical single-single sprayed seals exhibit porosity in the range of 5% to 8%, leading to saturated permeability from 10−6 to 10−7 m/s. The numerical simulations show that significant drying and wetting of the base layer occurs when the pavement operates under actual climatic conditions. In addition, this study reveals that for a given seal condition, it is easier for moisture to enter the unbound base than drying out of the base layer once the moisture has entered. However, the drying rate depends on the saturation condition of the base layer before drying begins.

A Performance-Based Decision Support Workflow for Retrofitting Residential Buildings

The trend towards high-performance residential buildings with new building regulations necessitates fundamental changes in the residential market, which is currently driven by low initial investment costs and dominated by weak innovative cycles. This change involves a difficult decision-making process that must consider the multiple and generally conflicting objectives regarding optimal retrofitting for residential buildings. This study aimed to develop an approach that would provide feedback about a building’s energy and economic performance in relation to the decision-making process to ensure that the complex residence retrofitting process is more efficient. For this purpose, a performance-oriented decision support workflow is recommended for a typical multifamily apartment block within a hypothetical settlement context in Istanbul Province, which includes (i) an automated parametric energy simulation through the coupling of EnergyPlus and MATLAB® to determine differences between retrofit alternatives in relation to the building envelope, energy systems and renewable energy systems, and (ii) a multiple-criteria decision analysis to determine the retrofit alternatives by which the optimal performance can be achieved, taking into account the conflicting nature of key performance indicators (primary energy saving and life-cycle cost saving). Architects and residence owners—who are the main decision makers—can use this proposed workflow to explore effective retrofit alternatives and to make informed decisions about performance-based retrofitting by comparing the energy and economic performance of these alternatives.

Long-term option pricing with a lower reflecting barrier

AbstractThis paper considers the pricing of long-term options on assets such as housing, where either government intervention or the economic nature of the asset limits large falls in prices. The observed asset price is modelled by a geometric Brownian motion (“the notional price”) reflected at a lower barrier. The resulting observed price has standard dynamics but with localised intervention at the barrier, which allows arbitrage with interim losses; this is funded by the government’s unlimited powers of intervention, and its exploitation is subject to credit constraints. Despite the lack of an equivalent martingale measure for the observed price, options on this price can be expressed as compound options on the arbitrage-free notional price, to which standard risk-neutral arguments can be applied. Because option deltas tend to zero when the observed price approaches the barrier, hedging with the observed price gives the same results as hedging with the notional price and so exactly replicates option payoffs. Hedging schemes are not unique, with the cheapest scheme for any derivative being the one which best exploits the interventions at the barrier. The price of a put is clear: direct replication has a lower initial cost than synthetic replication, and the replication portfolio always has positive value. The price of a call is ambiguous: synthetic replication has a lower initial cost than direct replication, but the replication portfolio may give interim losses. So the preferred replication strategy (and hence price) of a call depends on what margin payments need to be made on these losses.

BaseLess: lightweight detection of sequences in raw MinION data.

With its candybar form factor and low initial investment cost, the MinION brought affordable portable nucleic acid analysis within reach. However, translating the electrical signal it outputs into a sequence of bases still requires mid-tier computer hardware, which remains a caveat when aiming for deployment of many devices at once or usage in remote areas. For applications focusing on detection of a target sequence, such as infectious disease monitoring or species identification, the computational cost of analysis may be reduced by directly detecting the target sequence in the electrical signal instead. Here, we present baseLess, a computational tool that enables such target-detection-only analysis. BaseLess makes use of an array of small neural networks, each of which efficiently detects a fixed-size subsequence of the target sequence directly from the electrical signal. We show that baseLess can accurately determine the identity of reads between three closely related fish species and can classify sequences in mixtures of 20 bacterial species, on an inexpensive single-board computer. baseLess and all code used in data preparation and validation are available on Github at https://github.com/cvdelannoy/baseLess, under an MIT license. Used validation data and scripts can be found at https://doi.org/10.4121/20261392, under an MIT license. Supplementary data are available at Bioinformatics Advances online.

Development and evaluation of a low-cost evaporative cooling system for agricultural product storage

Agricultural products are highly perishable and, hence, we need to preserve these products after harvest. India is an agricultural country and, thus, the post-harvest storage of perishable agricultural products is important to reduce the gap between the demand and supply. Cold storage technologies have been developed and are used in India; however, these technologies are not popular in rural and remote areas due to the higher initial cost and the electrical energy requirement. Therefore, a number of low-cost technologies have been developed and, among these technologies, the evaporative cooling technology is gaining in popularity due to its simple design and lower initial cost. In this work, we have developed and tested a solar photovoltaic (PV) powered evaporative cooling system and used coconut coir as the cooling medium and compared the results with celdex pad. From this work, we observed that this system is an economical and efficient in reducing the temperature and increasing the relative humidity for the storage of agricultural products.

Investigating the Laboratory Performance of Crumb-Rubber-Modified and High-Float Polymer-Modified Asphalt Emulsions in Chip Sealing

Chip sealing is a widely popular pavement maintenance treatment because of its low initial cost and convenient construction process. Bleeding, loss of aggregate, reduced skid resistance, and aging have been identified as the most common type of distress that lead to the failure of chip sealing. The objective of this study was to evaluate the laboratory performance of a crumb-rubber-modified asphalt emulsion and a high-float polymer-modified asphalt emulsion in chip sealing and to evaluate the effects of crumb rubber as a modifier as well as its utilization as part of the aggregate stone. To achieve this objective, four types of emulsion were evaluated, namely a crumb-rubber-modified asphalt emulsion (CRS-2TR), a high-float polymer-modified emulsion (CHFRS-2P), a polymer-modified emulsion (CRS-2P), and a conventional unmodified emulsion (CRS-2). Based on the results of the experimental program, it was concluded that the aggregate retention properties of polymer-modified and crumb-rubber emulsions were superior to the unmodified emulsion. In addition, the granite aggregate performed better than the granite–crumb-rubber blends regardless of the type of emulsion used. However, a small percentage of crumb rubber may be used in chip sealing without significantly affecting its performance. According to the rheological and physical test results, CHFRS-2P showed the highest useful temperature interval (92.7), followed by CRS-2P (87.8), CRS-2TR (82.6), and CRS-2 (76.7). Based on Fourier transform infrared spectroscopy and saturate, aromatic, resin, and asphaltene test results, both CRS-2TR and CHFRS-2P showed lower carbonyl indices growth as compared to the other emulsions, indicating superior resistance to aging.

Efficient Dye Removal from Real Textile Wastewater Using Orange Seed Powder as Suitable Bio-Adsorbent and Membrane Technology

Textile wastewater is widely produced and its discharge without treatment contributes to environmental pollution. The adsorption process is a suitable and eco-friendly process due to its low initial cost, no formation of degradation products, operation simplicity, insensitivity to toxic compounds, and the possibility of removal from greatly diluted solutions. Orange seed (OS) powder, from which lipids were removed by hexane extraction, was evaluated as a bio-adsorbent to remove dyes from real textile wastewater. In the screening step, pH was a more significant variable (p-value < 0.05) than bio-adsorbent dosage, temperature, stirring speed, and process time. Moreover, under optimized conditions (pH = 2.6, 0.58 g/L from OS powder and 26 °C), more than 95% of the dye was removed from real textile wastewater. Additionally, the dye removal percentage was reduced by only 4% when the volume of textile wastewater was increased from 0.05 L to 10 L. Then, 96% turbidity was removed using a 3 µm tubular ceramic membrane at a pH of 11. Furthermore, the permeate flux through the membrane was kept constant for longer than was observed at low pH (<11). Therefore, the proposed process is an interesting option, due to the fact that orange seeds are currently not valorized and, combined with the membrane process, this could prove a suitable option for the treatment of real textile wastewater.

The Development and Validation of an Autonomous UVC (Ultraviolet - C) Disinfection Robot System

In this research, we developed an Autonomous UVC robot disinfection system suitable for a healthcare setting. The effectiveness of cleaning with UVC light inspired the design of the robot. The experiment was designed to determine how long, how far, and how much energy would be required to prevent the germs from replicating and kill them as rapidly as possible. The UVC robot is lightweight and simple to move about. The ultraviolet-candelabra (UVC) lamp was used in its construction. UVC light kills bacteria and viruses by interfering with the way their DNA bases couple together. Our experiment involved shutting the UVC robot in a room and observing its behavior. The UVC robot is equipped with four 30W lights that can illuminate an entire room. Within 30 seconds after commencement, samples were placed 60 centimeters from the lights and left there for a time from 0 to 6 minutes. Killing 92% of the germs in 6 minutes is a strong indicator that the suggested approach works effectively. The low initial cost and relatively straightforward nature of the design suggest that it might eventually achieve its full potential.

Data Quality Evaluation of Photovoltaic Power Station based on Entropy Weight Method and Grey Comprehensive Evaluation Method

The increasing necessity of renewable energy utilization has fueled the successful development of photovoltaic power generation technology. Distributed photovoltaic power stations have been rapidly promoted because of their small installed capacity and low initial investment costs. Scientific and comprehensive data evaluation of distributed PV is conducive to improving the operational efficiency of the power station. An index evaluation system is constructed for distributed power station data in each province. The entropy weighting method is used to determine the weights of different dimensions. Then, the data quality evaluation level is contrasted with the help of the gray evaluation method. Simulations of the proposed method were conducted. Finally, the results showed that the data of the tested distributed PV were at an excellent level, which verified the applicability of the method. In addition, the causes of data quality deficiencies are preliminarily explored.

A Technical Review of Grid Connected Solar Photovoltaic System with MPPT Techniques

Abstract: The Maximum Power Point Tracking (MPPT) is a technique used in power electronic circuits to extract maximum energy from the Photovoltaic (PV) Systems. In the recent decades, photovoltaic power generation has become more important due to its many benefits such as it needs a few maintenance with environmental advantage of being fossil fuel free. However, there are two major barriers for the use of PV systems, low energy conversion efficiency and high initial cost. To improve the energy efficiency, it is important to work PV system always at its maximum power point. So far, many researches has conducted and many papers were published and suggested different methods for extracting maximum power point.