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Appl. Syst. Innov., Volume 4, Issue 4 (December 2021) – 11 articles

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Article
Decision Support System in Dynamic Pricing of Horticultural Products Based on the Quality Decline Due to Bacterial Growth
Appl. Syst. Innov. 2021, 4(4), 80; https://doi.org/10.3390/asi4040080 - 14 Oct 2021
Viewed by 153
Abstract
A decision support system (DSS) was developed to help reduce food waste at traditional food retailers while selling fresh horticultural products, but also to promote food safety and quality. This computational tool includes two major functions: (1) the prediction of the remaining shelf [...] Read more.
A decision support system (DSS) was developed to help reduce food waste at traditional food retailers while selling fresh horticultural products, but also to promote food safety and quality. This computational tool includes two major functions: (1) the prediction of the remaining shelf life of fresh horticultural product, namely lettuce, onion, carrot, and cabbage based on its microbial growth status, governed by extrinsic and intrinsic parameters (temperature, water activity and pH, respectively). The remaining shelf life of the studied horticultural products is determined by using the online predictive food microbiology tool— the Combined Database for Predictive Microbiology (Combase). The time to reach the infectious doses of bacteria considered in the study for each of the four horticultural products are predicted; (2) the calculation of the dynamic price of the produce that should be set each day, depending on the predicted end of the marketing period to increase the demand and potential for sale to the final consumer. The proposed dynamic pricing model assumes a linear relation with the remaining shelf life of the analyzed vegetable to set the selling price. The shelf life determined by the DSS for optimal storage conditions is, in general, conservative, ensuring food safety. The automatic dynamic pricing gives new opportunities to small retailers to manage their business, fostering profit and simultaneously contributing to reduce food waste. Thus, this decision support system can contribute to the sustainable value of reducing food waste by providing information to small grocers and retailers on the safety of their perishable status depending on storage conditions and allowing them to suggest a fair price depending on that quality. Full article
Article
Epidemic Location Intelligence System as Response to the COVID-19 Outbreak in Bosnia and Herzegovina
Appl. Syst. Innov. 2021, 4(4), 79; https://doi.org/10.3390/asi4040079 - 14 Oct 2021
Viewed by 146
Abstract
The outbreak of COVID-19 is a public health emergency that caused disastrous results in many countries. The global aim is to stop transmission and prevent the spread of the disease. To achieve it, every country needs to scale up emergency response mechanisms, educate [...] Read more.
The outbreak of COVID-19 is a public health emergency that caused disastrous results in many countries. The global aim is to stop transmission and prevent the spread of the disease. To achieve it, every country needs to scale up emergency response mechanisms, educate and actively communicate with the public, intensify infected case finding, contact tracing, monitoring, quarantine of contacts, and isolation of cases. Responding to an emergency requires efficient collaboration and a multi-skilled approach (medical, information, statistical, political, social, and other expertise), which makes it hard to define one interface for all. As actors from different perspectives and domain backgrounds need to address diverse functions, the possibility to exchange available information quickly would be desirable. In Bosnia and Herzegovina, a joint state-level public health institution has not been established, but is covered by entity competencies. In this sense, a geoportal has been developed as an epidemiological location-intelligence system (ELIS) that supports the exchange of such information between the entities and the cantons. For its development, open source software components in the cloud were used as a working platform with all the necessary functionalities. The geoportal provides an entry point for access to geospatial, epidemiological, environmental and statistical data used for analysis, geocoding of confirmed COVID-19 cases, identification of disease dynamics, identification of vulnerable groups, mapping of health capacities, and general modeling of infection spread with application support for communication and collaboration between all institutions and the public. The paper describes the challenges and ways to overcome them in the development and use of ELIS. Full article
(This article belongs to the Special Issue Systems and Industries in Response to COVID-19 Crisis)
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Article
Soft Sensors for State of Charge, State of Energy and Power Loss in Formula Student Electric Vehicle
Appl. Syst. Innov. 2021, 4(4), 78; https://doi.org/10.3390/asi4040078 - 13 Oct 2021
Viewed by 184
Abstract
The proliferation of electric vehicle (EV) technology is an important step towards a more sustainable future. In the current work, two-layer feed-forward artificial neural-network-based machine learning is applied to design soft sensors to estimate the state of charge (SOC), state of energy (SOE), [...] Read more.
The proliferation of electric vehicle (EV) technology is an important step towards a more sustainable future. In the current work, two-layer feed-forward artificial neural-network-based machine learning is applied to design soft sensors to estimate the state of charge (SOC), state of energy (SOE), and power loss (PL) of a formula student electric vehicle (FSEV) battery-pack system. The proposed soft sensors were designed to predict the SOC, SOE, and PL of the EV battery pack on the basis of the input current profile. The input current profile was derived on the basis of the designed vehicle parameters, and formula Bharat track features and guidelines. All developed soft sensors were tested for mean squared error (MSE) and R-squared metrics of the dataset partitions; equations relating the derived and predicted outputs; error histograms of the training, validation, and testing datasets; training state indicators such as gradient, mu, and validation fails; validation performance over successive epochs; and predicted versus derived plots over one lap time. Moreover, the prediction accuracy of the proposed soft sensors was compared against linear or nonlinear regression models and parametric structure models used for system identification such as autoregressive with exogenous variables (ARX), autoregressive moving average with exogenous variables (ARMAX), output error (OE) and Box Jenkins (BJ). The testing dataset accuracy of the proposed FSEV SOC, SOE, PL soft sensors was 99.96%, 99.96%, and 99.99%, respectively. The proposed soft sensors attained higher prediction accuracy than that of the modelling structures mentioned above. FSEV results also indicated that the SOC and SOE dropped from 97% to 93.5% and 93.8%, respectively, during the running time of 118 s (one lap time). Thus, two-layer feed-forward neural-network-based soft sensors can be applied for the effective monitoring and prediction of SOC, SOE, and PL during the operation of EVs. Full article
Article
Prediction on Domestic Violence in Bangladesh during the COVID-19 Outbreak Using Machine Learning Methods
Appl. Syst. Innov. 2021, 4(4), 77; https://doi.org/10.3390/asi4040077 - 13 Oct 2021
Viewed by 291
Abstract
The COVID-19 outbreak resulted in preventative measures and restrictions for Bangladesh during the summer of 2020—these unstable and stressful times led to multiple social problems (e.g., domestic violence and divorce). Globally, researchers, policymakers, governments, and civil societies have been concerned about the increase [...] Read more.
The COVID-19 outbreak resulted in preventative measures and restrictions for Bangladesh during the summer of 2020—these unstable and stressful times led to multiple social problems (e.g., domestic violence and divorce). Globally, researchers, policymakers, governments, and civil societies have been concerned about the increase in domestic violence against women and children during the ongoing COVID-19 pandemic. In Bangladesh, domestic violence against women and children has increased during the COVID-19 pandemic. In this article, we investigated family violence among 511 families during the COVID-19 outbreak. Participants were given questionnaires to answer, for a period of over ten days; we predicted family violence using a machine learning-based model. To predict domestic violence from our data set, we applied random forest, logistic regression, and Naive Bayes machine learning algorithms to our model. We employed an oversampling strategy named the Synthetic Minority Oversampling Technique (SMOTE) and the chi-squared statistical test to, respectively, solve the imbalance problem and discover the feature importance of our data set. The performances of the machine learning algorithms were evaluated based on accuracy, precision, recall, and F-score criteria. Finally, the receiver operating characteristic (ROC) and confusion matrices were developed and analyzed for three algorithms. On average, our model, with the random forest, logistic regression, and Naive Bayes algorithms, predicted family violence with 77%, 69%, and 62% accuracy for our data set. The findings of this study indicate that domestic violence has increased and is highly related to two features: family income level during the COVID-19 pandemic and education level of the family members. Full article
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Article
Towards Design and Development of a Data Security and Privacy Risk Management Framework for WBAN Based Healthcare Applications
Appl. Syst. Innov. 2021, 4(4), 76; https://doi.org/10.3390/asi4040076 - 12 Oct 2021
Viewed by 211
Abstract
Assuring security and privacy of data is a key challenge for organizations when developing WBAN applications. The reasons for this challenge include (i) developers have limited knowledge of market-specific regulatory requirements and security standards, and (ii) there are a vast number of security [...] Read more.
Assuring security and privacy of data is a key challenge for organizations when developing WBAN applications. The reasons for this challenge include (i) developers have limited knowledge of market-specific regulatory requirements and security standards, and (ii) there are a vast number of security controls with insufficient implementation detail. To address these challenges, we have developed a WBAN data security and privacy risk management framework. The goal of this paper is trifold. First, we present the methodology used to develop the framework. The framework was developed by considering recommendations from legislation and standards. Second, we present the findings from an initial validation of the framework’s usability and effectiveness of the security and privacy controls. Finally, we present an updated version of the framework and explain how it addresses the aforementioned challenges. Full article
(This article belongs to the Special Issue Recent Developments in Risk Management)
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Commentary
Systematic Nomination of COVID-19 Quarantine Facilities
Appl. Syst. Innov. 2021, 4(4), 75; https://doi.org/10.3390/asi4040075 - 11 Oct 2021
Viewed by 204
Abstract
This short communication explains the need for a clear method for the selection of COVID-19 quarantine hotels. It also lists available systematic methods that are usable for this aim. Full article
(This article belongs to the Special Issue Systems and Industries in Response to COVID-19 Crisis)
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Article
Design and Optimization of Vertical Axis Wind Turbines Using QBlade
Appl. Syst. Innov. 2021, 4(4), 74; https://doi.org/10.3390/asi4040074 - 09 Oct 2021
Viewed by 234
Abstract
Wind energy is considered one of the most important sources of renewable energy in the world, because it contributes to reducing the negative effects on the environment. The most important types of wind turbines are horizontal and vertical axis wind turbines. This work [...] Read more.
Wind energy is considered one of the most important sources of renewable energy in the world, because it contributes to reducing the negative effects on the environment. The most important types of wind turbines are horizontal and vertical axis wind turbines. This work presents the full details of design for vertical axis wind turbine (VAWT) and how to find the optimal values of necessary factors. Additionally, the results shed light on the efficiency and performance of the VAWT under different working conditions. It was taken into consideration the variety of surrounding environmental conditions (such as density and viscosity of fluid, number of elements of the blade, etc.) to simulate the working of vertical wind turbines under different working conditions. Furthermore, the effect of the design factors was investigated such as the number and size of the blades on the behavior and performance of VAWT. It was assumed that the vertical wind blade works in different sites of Iraq. QBlade software (Version 8) was used to achieve the calculations and optimization processes to obtain the optimal design of vertical axis wind turbines that is suitable for the promising sites. The results proved that accurate results can be obtained by using QBlade software. Full article
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Article
Case-Based Reasoning with an Artificial Neural Network for Decision Support in Situations at Complex Technological Objects of Urban Infrastructure
Appl. Syst. Innov. 2021, 4(4), 73; https://doi.org/10.3390/asi4040073 - 27 Sep 2021
Viewed by 308
Abstract
The article considers the tasks of intellectual support for decision support in relation to a complex technological object. The relevance is determined by a high level of responsibility, together with a variety of possible situations at a complex technological facility. The authors consider [...] Read more.
The article considers the tasks of intellectual support for decision support in relation to a complex technological object. The relevance is determined by a high level of responsibility, together with a variety of possible situations at a complex technological facility. The authors consider case-based reasoning (CBR) as a method for decision support. For a complex technological object, the problem defined is the uniqueness of the situations, which is determined by a variety of elements and the possible environmental influence. This problem complicates the implementation of CBR, especially the stages of comparing situations and a further selection of the most similar situation from the database. As a solution to this problem, the authors consider the use of neural networks. The work examines two neural network architectures. The first part of the research presents a neural network model that builds upon the multilayer perceptron. The second part considers the “Comparator-Adder” architecture. Experiments have shown that the proposed neural network architecture “Comparator-Adder” showed higher accuracy than the multilayer perceptron for the considered tasks of comparing situations. The results have a high level of generalization and can be used for decision support in various subject areas and systems where complex technological objects arise. Full article
(This article belongs to the Collection Feature Paper Collection on Civil Engineering and Architecture)
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Article
Zeroize: A New Method to Improve the Utilization of 5G Networks When Running VoIP over IPv6
Appl. Syst. Innov. 2021, 4(4), 72; https://doi.org/10.3390/asi4040072 - 26 Sep 2021
Viewed by 435
Abstract
5G technology is spreading extremely quickly. Many services, including Voice Over Internet Protocol (VoIP), have utilized the features of 5G technology to improve their performance. VoIP service is gradually ruling the telecommunication sector due to its various advantages (e.g., free calls). However, VoIP [...] Read more.
5G technology is spreading extremely quickly. Many services, including Voice Over Internet Protocol (VoIP), have utilized the features of 5G technology to improve their performance. VoIP service is gradually ruling the telecommunication sector due to its various advantages (e.g., free calls). However, VoIP service wastes a substantial share of the VoIP 5G network’s bandwidth due to its lengthy packet header. For instance, the share of the packet header from bandwidth and channel time reaches 85.7% of VoIP 5G networks when using the IPv6 protocol. VoIP designers are exerting considerable efforts to solve this issue. This paper contributes to these efforts by designing a new technique named Zeroize (zero sizes). The core of the Zeroize technique is based on utilizing the unnecessary fields of the IPv6 protocol header to keep the packet payload (voice data), thereby reducing or “zeroizing” the payload of the VoIP packet. The Zeroize technique substantially reduces the expanded bandwidth of VoIP 5G networks, which is reflected in the wasted channel time. The results show that the Zeroize technique reduces the wasted bandwidth by 20% with the G.723.1 codec. Therefore, this technique successfully reduces the bandwidth and channel time of VoIP 5G networks when using the IPv6 protocol. Full article
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Article
Treatment of Infectious Waste through the Application Rotary Kiln Incinerators and Ozone Technology
Appl. Syst. Innov. 2021, 4(4), 71; https://doi.org/10.3390/asi4040071 - 26 Sep 2021
Viewed by 510
Abstract
The alarming rate at which infectious waste is growing was an unsolved problem worldwide before the pandemic, and it has only gotten worse. It is especially prominent in the medical services, owing to the improper use or the lack of high-efficiency waste management [...] Read more.
The alarming rate at which infectious waste is growing was an unsolved problem worldwide before the pandemic, and it has only gotten worse. It is especially prominent in the medical services, owing to the improper use or the lack of high-efficiency waste management systems. To address this issue, this paper presents a modification to the conventional rotary kiln incineration method using add-on ozone (O3) at a concentration of 100–160 g/h in order to enhance its efficiency when treating emitted air pollutants. These pollutants of Hg, HF, TSP, SO2, NO2, CO, and HCl were measured, and their percent opacity concentrations were 0.006 mg/m3, 0.680 mg/m3, 21.900 mg/m3, 5.600 mg/m3, 16.300 mg/m3, 13.700 mg/m3, 0.022 mg/m3, and 6%, respectively. The amounts of these air pollutants were considerably lower than those released from a rotary kiln incinerator without the add-on ozone. Additionally, all the measurements were lower than the emission thresholds established in the US Environmental Protection Agency Emission Standards Reference Guide. Therefore, using the proposed rotary kiln incineration method modified with add-on ozone is suitable for use in the elimination of infectious waste in that it drastically reduces air pollution and improves air quality, resulting in environmental improvements aimed at mitigating the devastating impacts pollution has on human health. Full article
(This article belongs to the Section Control and Systems Engineering)
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Review
Creating Smart Cities: A Review for Holistic Approach
Appl. Syst. Innov. 2021, 4(4), 70; https://doi.org/10.3390/asi4040070 - 22 Sep 2021
Viewed by 451
Abstract
With the rapid proliferation of Internet of Things (IoT) into urban people’s everyday walk of life, the functions of smart cities are fast approaching to be embedded in every step of people’s life. Despite the concept of smart cities founded in the late [...] Read more.
With the rapid proliferation of Internet of Things (IoT) into urban people’s everyday walk of life, the functions of smart cities are fast approaching to be embedded in every step of people’s life. Despite the concept of smart cities founded in the late 1990s, there has been limited growth until recent popularity due to the advancements of IoTs. However, there are many challenges, predominantly people-centric, that require attention for the realisation of smart cities and expected real-life success. In this paper, we intend to investigate the state-of-the-art focus of smart cities from three angles: infrastructure engineering, information technology and people-centric management. We adopt a mixed-methods analysis of currently published literature on the topic of smart cities. Our study attempts to draw attention to the need for developing smart cities with a holistic approach involving multiple perspectives rather than a siloed emphasis on technology alone. We highlight that the fields of specialisations such as information technology and infrastructure engineering in contributing to smart cities need a cross-domain holistic approach of managing people-centric service requirements for improving consumer satisfaction and sustainability. Full article
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