Volume 7, Issue 2

Researchers have associated agriculture and food processing with adverse environmental impacts like; falls in the underground freshwater table, energy consumption, and high carbon emission. These factors have the worst effect on developing countries. Therefore, there is a need for on-demand food production techniques that require minimum resource utilization. For these reasons, scientists are now focusing their attention on hydroponics. Hydroponics is the process of growing crops without the use of soil. However, different components of the system need to be closely monitored and controlled. In this paper, we compared the performance of an automated hydroponic system using cluster-based wireless sensor networks against a multihop-based one. We used Simponics for the simulation. It is a simulator based on the OMNET++ framework. Simulation results show that both latency and energy overhead of the multihop network increases with the number of nodes. However, they stay constant on a cluster-based network.

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Various applications have helped make vehicular Ad-hoc network communication a reality. Real-time applications, for example, need broadcasting in high video quality with minimal latency. The new High-Efficiency Video Coding (HEVC) has shown great promise for real-time video transmission through Vehicle Ad-hoc Networks due to its high compression level. These networks, on the other hand, have highly changeable channel quality metrics and limited capacity, making it challenging to maintain good video quality. HEVC real-time video streaming on VANET may now benefit from an end-to-end dynamic adaptive cross-layer method. According to the video coding process’s time prediction structure, frame size, and network density, each video packet should be assigned to a suitable Access Category (AC) queue on the Medium Access Control layer (MAC). The results we’ve gotten demonstrate that the new method suggested delivers considerable improvements in video quality at end-to-end latency and reception in comparison to the Enhanced Distributed Channel Access (EDCA) specified in the 802.11p standard for several targeted situations. Quality of Experience (QoE) and Quality of Service (QoS) assessments have been used to verify our proposed strategy.

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The Nodes equipped with wireless technology cooperate in an autonomous and instantaneous way to form a mobile ad hoc network. It turns out that several factors make this type of network vulnerable to various security threats. Considering the sensitivity of user data routed through nodes, routing security should be a priority in mobile ad hoc networks (MANET). Techniques and schemes have been proposed to secure the basic routing protocols in order to guarantee the availability of information routing services between network nodes. The majority of the solutions presented in the literature belong to two categories, namely those that use cryptographic techniques and those that use trust schemes. Given the characteristics of MANET networks, we need approaches that guarantee a level of honesty of the nodes to prevent possible routing attacks from malicious nodes. This study presents the security extensions of the basic routing protocols AODV, DSR and DSDV.A first part is devoted to extensions based on cryptography and a second part introduces extensions using trusted systems. Then we discussed and analyzed them while drawing up a comparative table to measure the effectiveness of the mechanisms used as well as the limits and strengths of each proposed extensions. In this study, we conclude that a new trust model that combines an access strategy with lightweight techniques must be developed to ensure honest node behavior can be a key to securing the routing protocol in MANET.

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The Nodes equipped with wireless technology cooperate in an autonomous and instantaneous way to form a mobile ad hoc network. It turns out that several factors make this type of network vulnerable to various security threats. Considering the sensitivity of user data routed through nodes, routing security should be a priority in mobile ad hoc networks (MANET). Techniques and schemes have been proposed to secure the basic routing protocols in order to guarantee the availability of information routing services between network nodes. The majority of the solutions presented in the literature belong to two categories, namely those that use cryptographic techniques and those that use trust schemes. Given the characteristics of MANET networks, we need approaches that guarantee a level of honesty of the nodes to prevent possible routing attacks from malicious nodes. This study presents the security extensions of the basic routing protocols AODV, DSR and DSDV.A first part is devoted to extensions based on cryptography and a second part introduces extensions using trusted systems. Then we discussed and analyzed them while drawing up a comparative table to measure the effectiveness of the mechanisms used as well as the limits and strengths of each proposed extensions. In this study, we conclude that a new trust model that combines an access strategy with lightweight techniques must be developed to ensure honest node behavior can be a key to securing the routing protocol in MANET.

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In 1998 we were talking about an NTIC era, and since the years 2010, we are tracing the beginning of a new era of technological development, called the era of digital transformation. During this new era companies have started to run towards the digitalization of their processes, which represent a large part of the market, the implementation of IT projects for the simplification and automation of their business. This new technological mode has generated new constraints related to the digital transformation in the management of IT projects. Beyond the constraints related to this era, old constraints already exist in the literature in the two modes of development that can be found, waterfall or agile. The main purpose of this study is to review the literature for a theoretical understanding of the issue, and an analysis through practice, through a case study and observations in the field, to better identify and understand the practical concerns. The results of this study led us to identify the constraints of digital transformation, the strong and weak points of each management model. The matrix linking these elements allowed us to propose a new hybrid development mode that exploits the potential of both waterfall and agile models, while considering and highlighting the constraints of this new era.

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DC Microgrids (DCMGs) aggregate and integrate various distribution generation (DG) units through the use of power electronic converters (PECs) that are present on both the source side and the load side of the DCMGs. Tightly regulated PECs at the load side behave as constant power loads (CPLs) and may promote instability in the entire DCMG. Previous research has mostly focused on devising stabilization techniques with ideals CPLs that may not be feasible to realize; few publications that emulate DCMG stability with practical CPLs are restricted in application because they add components that considerably increase the cost of the DCMGs. This study aims at stabilizing the DCMG in the presence of practical CPL in a way that is economically feasible, i.e., without the addition of complex compensators. This paper presents a Simulink model of the smallest DCMG, i.e., a cascaded DC-DC power converter network with a practical CPL assumed at the load side of the network. Using theoretical calculations and computer simulations, we have determined the suitable CPL power level and the bandwidth of the current controller at which the smallest DCMG is stable. We have performed the stability analysis of the source side buck converter and the CPL with the derived power level and bandwidth, and found that individual converter systems are stable, thereby proving that the entire DCMG is stable despite the presence of a CPL.

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Our world is characterised by uncertainty and complex, relational structures that carry temporal information, yielding large dynamic probabilistic relational models at the centre of many applications. We consider an example from logistics in which the transportation of cargoes using vessels (objects) driven by the amount of supply and the potential to generate revenue (relational) changes over time (temporal or dynamic). If a model includes only a few objects, the model is still considerably small, but once including more objects, i.e., with increasing domain size, the complexity of the model increases. However, with an increase in the domain size, the likelihood of keeping redundant information in the model also increases. In the research field of lifted probabilistic inference, redundant information is referred to as symmetries, which, informally speaking, are exploited in query answering by using one object from a group of symmetrical objects as a representative in order to reduce computational complexity. In existing research, lifted graphical models are assumed to already contain symmetries, which do not need to be constructed in the first place. To the best of our knowledge, we are the first to propose symmetry construction a priori through a symbolisation scheme to approximate temporal symmetries, i.e., objects that tend to behave the same over time. Even if groups of objects show symmetrical behaviour in the long term, temporal deviations in the behaviour of objects that are actually considered symmetrical can lead to splitting a symmetry group, which is called grounding. A split requires to treat objects individually from that point on, which affects the efficiency in answering queries. According to the open-world assumption, we use symmetry groups to prevent groundings whenever objects deviate in behaviour, either due to missing or contrary observations.

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The context for the study was a naturally occurring quasi-experiment in the core mathematics program in a large Australian university. Delivery of teaching was changed in a sequence of two initial core mathematics subjects taken by engineering and science students. The change replaced one of two face-to-face tutorial classes per week by an online tutorial. Tasks in the online tutorial were designed to lead the students through the week’s topics, using initially simpler tasks as scaffolding for more complex tasks. This was the only change: syllabus and written materials were the same, as was students’ access to help from staff and discussion with peers. The study compared learning outcomes among students in two adjacent years: Cohort 1, the last before the change, and Cohort 2, in the first implementation of the change to a blended learning environment. Learning outcomes were assessed by a method derived from the SOLO taxonomy, which used a common scale for scoring written answers to examination questions in the two cohorts. In the first mathematics subject students doing online tutorials had significantly higher scores than those studying before the change. In the second mathematics subject there were no significant differences. The conclusion was that the online tutorials gave an advantage to students beginning university study and gave adequate support to those in the subject taken a little later. It can be concluded that the use of an online teaching component in the delivery of university mathematics programs is not only justifiable but desirable, subject to careful design of the teaching material offered.

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On Renewable Energy (RE), this field covers the most significant share of the world energy demand and challenges on the expensive measurement and maintenance equipment to be used. In all studies and designs, global solar radiation (GSR) measurements require assessment, estimation, and models to be applied together with the environment and meteorological data on installing stations at the specific location. These meteorology stations provide measured data throughout the year/ annually or at specified periods, depending on the site of interest. This study includes assessment and estimations of the solar radiation at the Vhembe District using the geographical data measured daily, monthly, and throughout a year in the area. It provides variables such as the geographical maps of the solar availability at a minimum and maximum temperatures obtained during the annual analyses. Determining the solar radiation at a specific location for energy generation involves several procedures, estimations, and calculations using the climatological weather data measurements through MATLAB simulations. In addition, the Geographical Remote Sensing (RS) and Mappings, and Spreadsheet Graph Analytics, were applied to the measured data from the nine installed Weather Stations (WS) in the Vhembe District area was used. The analysis determines the minimum and maximum solar radiation equations associated with the local climate patterns in accommodating the theoretical bases and period changes. The paper contributes to the main project objectives on renewable energy assessment for potentials and generation at a micro/small scale in the district. These parameters are fundamental in estimating and determining the potential solar energy radiation using its extraterrestrial solar radiation per day/ weekly/ monthly. Annual periods towards methods to develop micro/small energy projects for rural and urban communities for domestic and commercial use. As a result, the meteorology analysis is being presented in this study.

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The novel coronavirus infection (COVID-19), which appeared at the end of 2019 has developed into a global pandemic with numerous deaths, and has also become a serious social concern. The most important and basic measure for preventing infection is hand hygiene. In this study, by photographing palm images of nursing students after hand-washing, using fluorescent lotion to conduct hand-washing training and as a black light, we developed a hand hygiene evaluation system using pix2pix, which is a type of the generative adversarial network (GAN). In pix2pix, the input image adopted was a black light image obtained after hand-washing, and the ground truth image was a binarized image obtained by extracting the residue left on the input image by a trained staff member. We adopted 443 paired-images after hand-washing as training models, and employed 20 images as verification images, which included 10 input images with 65% or more of the residue left, and 10 input images with 35% or less of the residue left in the ground truth images. To evaluate the training models, we calculated the percentage of residue left in the estimated images generated from the verification images, and conducted two-class discriminant analysis using the Mahalanobis distance. Consequently, misjudgment only occurred in one image for each image group, and the proposed system with pix2pix exhibited high discrimination accuracy.

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An enduring vision of Artificial Intelligence is to build robots that can recognize and learn the visual world and who can speak about it in natural language. Automatic image description generation is a demanding problem in Computer Vision and Natural Language Processing. The applications of image description generation systems are in biomedicine, military, commerce, digital libraries, education, and web searching. A description is needed to understand the semantics of the image. The main motive of the work is to generate description of the image using visually salient features. The encoder-decoder architecture with a visual attention mechanism for image description generation is implemented. The system uses a Densely connected convolutional neural network as an encoder and Bidirectional LSTM as a decoder. The visual attention mechanism is also incorporated in this work. The optimization of the caption is also done using a Cooperative game-theoretic search. Finally, an integrated framework for an automatic image description generation system is implemented. The performance of the system is measured using accuracy, loss, BLEU score and ROUGE. The grammatical correctness of the description is checked using a new evaluation measure called GCorrect. The system gives a the-state-of-art performance on the Flickr8k and ImageCLEF2019 challenge dataset.

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WhatsApp application is considered the largest messaging application around the world and an important source of information, they just incorporated a new technique that operates on end-to-end encryption, which presents a significant problem for forensic investigators and analysts. This study describes how to recover the encryption key from WhatsApp to decrypt WhatsApp databases and retrieve important artifacts displayed and saved in the Android system without rooting the device. As a means of presenting and analyzing artifacts taken from the most recent version of WhatsApp to signs of fresh and important evidence and artifacts to assist investigators and forensic analysts in the investigation. As a result, various techniques, devices, and software may now be utilized for WhatsApp digital forensics. The findings of this study showed a variety of artifacts in the internal memory unit utilized by the Android system for the WhatsApp application, which might aid digital forensic examiners in their examination of WhatsApp on the Android system without the need to root the device.

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Instead of approaches of solid mechanics or a formal description of experimental data an interdisciplinary approach is proposed to consider failure and deformation as thermodynamic processes. Mathematical modeling of the processes is carried out using rheological models of the material. One fracture criterion is used, that formally corresponds to the achievement of a threshold concentration of micro-damage in any volume of the material. The prediction of the durability of materials under constant or variable temperature and force conditions is performed by time steps, including situations with changes in the material structure. Calculations of durability of structural components are based on the relationship of plastic flow and failure processes distributed over the volume of the material.

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With the development of Internet of Things technology and the widespread use of smart devices, artificial intelligence is now being applied as a decision-making tool in a variety of fields. To make machine learning models, including deep neural network models, more interpretable, various techniques have been proposed. In this paper, a method for explaining the outputs of machine learning models using inductive logic programming is described. For an evaluation of this method, diagnostic models of bovine mastitis were trained using a dataset of dairy cows, and interpretable rules were obtained to explain the trained models. As a result, the rules obtained indicate that the trained classifiers detected mastitis cases depending on certain variations in the electrical conductivity (EC) values, and in some of these cases, the EC and lactate dehydrogenase fluctuated in different ways. The interpretable rules help people understand the outputs of machine learning models and encourage a practical introduction of the models as decision-making tools.

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The use of Covid-19 contact tracing applications has become almost irrelevant now that several flavors of Covid-19 vaccine have been developed and are constantly being distributed to people during the pandemic to help alleviate the need for lockdowns. Also, the availability of at-home testing kits and testing sites means that people do not need to contact trace as much since individuals can get tested and follow the health guidelines in ensuring their health and the safety of others around them. Nevertheless, governments around the world are still faced with the Covid-19 pandemic challenge because the virus is not yet controlled due to the different variants and the rapid contamination rate that outpaced the logistic supply chain processes in the distribution of the vaccines and the time it takes in convincing individuals to take the vaccine swiftly to reach herd immunity. Therefore, the current pressing need is that of addressing the infection rate by finding ways and solutions to minimize or slow down contamination among people especially with the increased number of variants. This paper is an extension of the “COVIDFREE App: The User-Enabling Contact Prevention Application” work originally presented in 2020 IEEE International Symposium on Technology and Society (ISTAS) conference that provided a smartphone application architecture with the goal of proactively enabling users to avoid encountering infected Covid-19 patients. This paper elucidates and discusses additional concerns not thoroughly addressed previously regarding the Covid-19 variants, vaccines, booster, and infection rates, and demonstrates the feasibility of the proposed architecture with a web application prototype. This paper also discusses the benefits of funding and developing contact tracing and prevention applications, such as the COVIDFREE App, to provide the needed ingredient in reducing the infection rate and provide citizens the needed preparedness and relief in actively fighting the virus.

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Dynamic Searchable Symmetric Encryption (DSSE) methods address the problem of securely outsourcing updating private data into a semi-trusted cloud server. Furthermore, Forward Privacy (FP) notion was introduced to limit data leakage and thwart the related attacks on DSSE approaches. FP schemes ensure previous search queries cannot be linked to future updates and newly added files. Since FP schemes use ephemeral search tokens and one-time use index entries, many scholars conclude that privacy attacks on traditional SSE schemes do not apply to SSE approaches that support forward privacy. However, to obtain efficiency, all FP approaches accept a certain level of data leakage, including access pattern leakage. Here, we introduce two new attacks on forward-private schemes. We demonstrate that it is still plausible to accurately unveil the search pattern by reversing the access pattern. Afterward, the attackers can exploit this information to uncover the search queries and consequently the documents. We also show that the traditional privacy attacks on SSE schemes are still applicable to schemes that support forward privacy. We then construct a new DSSE approach that supports parallelism and obfuscates the search and access pattern to thwart the introduced attacks. Our scheme is cost-efficient and provides secure search and update. Our performance analysis and security proof demonstrate our approach’s practicality, efficiency, and security.

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This paper presents findings and proposes recommendations from an evaluation of the level of digital competencies among Saudi university graduates to ascertain their readiness for becoming digital citizens, with high confidence in using digital technologies to successfully engage in digital transformation efforts to achieve Saudi Vision 2030. The sample comprised 352 University of Tabuk students from ten different colleges (faculties) who answered an online five-point Likert-type structured questionnaire pertaining to their awareness and readiness concerning aspects of digital competence, based on previous research. The questionnaire dimensions comprised information and data literacy, digital content creation, communication and collaboration, safety, and problem-solving. The data was analyzed using SPSS statistical software package to perform, reliability test, descriptive statistics, and comparative tests. The study revealed a fair degree of digital competencies in general, with notable differences between graduates from different colleges, when comparing the five levels dimensions of digital competencies.

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Blockchain technology is seeing a trend of popularity and adoption in many different application areas. One such area is healthcare, as there is a need to develop a system that can reliably store and share electronic health records (EHRs) among hospital-based health facilities. In this paper, we present a cloud-based hierarchical consortium blockchain framework for storing and sharing EHRs in a scalable, secure, and reliable manner. The framework enables data sharing between local hospital blockchain networks (HBNs) through high-level blockchain networks, namely, city blockchain networks (CBNs) and a state blockchain network (SBN). To support the timely publication of EHRs in HBNs, we adopt a temporary and permanent block scheme in hospital blockchains. In addition, we develop role-based access control (RBAC) policies for data authorization and procedures for concurrent search and retrieval of EHRs across cities and states. The experimental results show that our proposed approach is feasible and supports timely publication and efficient retrieval of EHRs in cloud-based hierarchical blockchain networks.

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The aim of the research is to contribute to the emergent field of strategic design as an approach to creating transformational impacts in organizations. This is driven by international strategies to promote sustainable business environments which are innovative and adaptive to change. The literature identifies a gap in the knowledge in relation to how knowledge flows within an organization from knowledge producing activities and back. This flow between management and operational activity is identified as the ongoing innovation capability and ultimately the area of transformational impact within the organization. However, the structures which support this flow and how it is measured are ambiguous and ill defined. Strategic design is a holistic approach to developing business strategies which may provide methods which support the flow of knowledge and provide the transformational impacts. A ‘research through design’ approach was taken to collect data from small to medium enterprises engaging in a series of strategic design workshops. Analysis was carried out through visual mapping of how strategic design is applied in an organization at management and operational level. This identifies the nuanced differences in application and design tools used to develop management strategy versus operational strategy. It also identifies the points of knowledge creation and transfer which builds business intelligence to inform both business and operational strategies. This is presented as a contextual framework which provides the basis for understanding the complexity of the flow between the two. This contributes to informing organizations of where the links between these strategies may be built, resulting in a more dynamic organization which is nimble, innovative, and adaptive to change.

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