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With the rapid growth in the requirements of the Internet of Things (IoT), the scarcity of spectrum resources is becoming serious. Non-orthogonal multiple access (NOMA) and spectrum sensing offer the opportunity of addressing spectrum shortage to some extent. In particular, NOMA stably enables multiple users to share the same frequency band, while spectrum sensing dynamically detects the target spectrum utilization. However, due to the characteristics of NOMA, the application of spectrum sensing to the uplink IoT systems makes the process more complex, also brings the challenge of obtaining the target users’ states accurately from interfered multi-user signals. Meanwhile, the combination of NOMA and spectrum sensing does not reach the upper bound of spectrum utilization. Under the context, we are motivated to propose an adaptive NOMA-based spectrum sensing method for uplink IoT networks, which aims to flexibly and precisely identify the target frequency usage. The relationship among the threshold, the false-alarm probability, and the transmission willingness are derived in closed form. We also customize a sensing algorithm of the complete adaptive working mechanism. Numerical results clarify that the proposed method achieves stability under different SNRs and transmission willingness, while improves the system throughput which outperforms the existing technologies by 38.20%.

Even though digital technologies such as cloud technologies are prevalent in transforming businesses, the role of employees and their digital skills in the process is, to a large extent, neglected. This article brings forward the novel concept of digital literacy to explore the role of employees in understanding the wide variety of opportunities of digital technologies and their actualization. By treating digital literacy as the antecedent of cognitive behavior of employees in utilizing cloud technology at companies, we apply the Theory of Planned Behavior (TPB) for analyzing preliminary empirical data collected from 124 Australian employees’ technology use intentionality and behavior. The quantitative analysis shows that the TPB holds for the utilization of cloud technology and there is a positive relationship between employees' digital literacy and the utilization of cloud technology at companies. Overall, the study contributes to the technology management literature by offering a workable construct to measure the digital skills of employees in the form of digital literacy. Further, it expands the TPB framework by introducing digital literacy as a perceived behavior control variable that helps to examine the role of employees in digital transformation. The paper ends with implications and limitations of our preliminary study, followed with suggestions for future studies.

Abstract The crop-livestock farming system in paddy fields is integrated between rice crops and beef cattle (rice-beef cattle CLFS). Rice plants will produce straw and rice bran that can be used for animal feed, and livestock will produce compost/manure that can be used for rice nutrition. Some other benefits of implementing CLFS are increasing crop productivity, increasing the value of farmers' income, farming cost efficiency, and preserving the environment. The probability of the sustainability of CLFS application in paddy fields can be measured by calculating the system proximity index ratio using the SPIR formula. This research aims to demonstrate the accuracy of the SPIR formula in predicting the probability of CLFS sustainability in paddy fields. This study compares CLFS programs in several regions in Indonesia. It uses an independent sample t-test analysis tool with one-way rejection criteria to see the difference in SPIR scores on sustainable and unsustainable CLFS. The results showed that the SPIR formula could predict the sustainability of the CLFS program in Indonesia. However, further studies are needed to prove its ability to predict CLFS sustainability in other parts of the world.

Smart home environments, which consist of various Internet of Things (IoT) devices to support and improve our daily lives, are expected to be widely adopted in the near future. Owing to a lack of awareness regarding the risks associated with IoT devices and challenges in replacing or the updating their firmware, adequate security measures have not been implemented. Instead, IoT device identification methods based on traffic analysis have been proposed. Since conventional methods process and analyze traffic data simultaneously, bias in the occurrence rate of traffic patterns has a negative impact on the analysis results. Therefore, this paper proposes an IoT traffic analysis and device identification method based on two-stage clustering in smart home environments. In the first step, traffic patterns are extracted by clustering IoT traffic at a local gateway located in each smart home and subsequently sent to a cloud server. In the second step, the cloud server extracts common traffic units to represent IoT traffic by clustering the patterns obtained in the first step. Two-stage clustering can reduce the impact of data bias, because each cluster extracted in the first clustering is summarized as one value and used as a single data point in the second clustering, regardless of the occurrence rate of traffic patterns. Through the proposed two-stage clustering method, IoT traffic is transformed into time series vector data that consist of common unit patterns and can be identified based on time series representations. Experiments using public IoT traffic datasets indicated that the proposed method could identify 21 IoTs devices with an accuracy of 86.9%. Therefore, we can conclude that traffic analysis using two-stage clustering is effective for improving the clustering quality, device identification, and implementation in distributed environments.

This study aimed to clarify the vegetation history of planted forests that are still in use today by comparing the types of land afforested in 1960 with the post-war afforestation period in Japan’s Hokkaido, Kyushu, and Kinki regions. It was during that time that the majority of the planted forest in these regions was established. We calculated the afforestation ratios (afforested area of each type of land/total afforested area) for the smallest survey unit, the 1950 administrative sections, using data from the 1960 World Agriculture and Forestry Census on the afforested areas of various types of land (i.e., deforested areas resulting from natural forests, deforested areas resulting from planted forests, and areas other than forests). The afforestation ratios were then sorted into ten categories for each municipality in the three regions and mapped using GIS. The analysis results showed that the vegetation history in Kyushu, even within the same municipality, was frequently mixed in 1960; in Hokkaido, the afforestation ratio for deforested areas resulting from natural forests was extremely high, while the afforestation ratio for deforested areas resulting from planted forests was low. In contrast, the Kinki region has a low afforestation ratio for non-forest regions. This study provides useful information for ecosystem management.

Сільськогосподарський сектор зіткнувся з серйозними проблемами, пов’язаними зі зміною клімату. Ці зміни потенційно можуть призвести до зниження врожайності сільськогосподарських культур і продовольчої безпеки, підкреслюючи важливість розуміння динаміки температури і управління нею. Ця робота є результатом розробки термодинамічної моделі, яка досліджує динаміку температурного балансу шляхом передачі теплової енергії. Запропоновано схему реологічного теплообміну об’єкта з ізольованою поверхнею та графіки незворотних реологічних перетворень. Наведено основне рівняння теплообміну з хімічною реакцією і виведено рівняння швидкості передачі теплової енергії по довжині об’єкта. Запропоновано подальший розвиток фізико-математичних моделей перетворення теплової енергії в сукупність станів об’єкта. Було проведено експеримент, результати якого корелюється з рівнянням теплообміну. Зразки з насінням томатів опромінювались фотонним опромінювачем з довжиною хвиль – синій 450 нм, зелений 550 нм, червоний 650 нм з експозицією 12/24 год. В результаті 90 % при опроміненні червоним спектром фотонного опромінювача тривалістю 24 години, що на 24 % більше контрольного зразка. Це дозволить оцінити загальний температурний режим сільськогосподарських об’єктів і оптимізувати процес обігріву. Це дослідження розкриває суть регулювання температури на сільськогосподарських об’єктах, використовуючи термодинамічну модель, яка не тільки враховує теплообмін, але і включає вплив хімічних реакцій. Запропонована термодинамічна модель та пов’язані з нею рівняння створюють основу для майбутніх досліджень та практичних застосувань, що в кінцевому підсумку принесе користь сільськогосподарській промисловості та світовому виробництву продуктів харчування The agricultural sector faces serious challenges related to climate change. These changes have the potential to reduce yields and food security, highlighting the importance of understanding and managing temperature dynamics. This work is the result of development a thermodynamic model that investigates the dynamics of temperature balance through heat energy transfer. A scheme of rheological heat exchange of an object with an insulated surface and graphs of irreversible rheological transformations are proposed. The main equation of heat exchange with a chemical reaction is given and the equation of the speed of heat energy transfer along the length of the object is derived. Further development of physical-mathematical models of the transformation of thermal energy into a set of states of the object is proposed. The experimental results fully correlate with the heat transfer equation. Samples with tomato seeds were irradiated with a photon irradiator with wavelengths of blue 450 nm, green 550 nm, red 650 nm with an exposure of 12/24 h. As a result, 90 % under the influence of the red spectrum of the photon irradiator for 24 h, which is 24 % more than the control sample. This will make it possible to assess the general temperature regime of agricultural objects and optimize the heating process. This study reveals the essence of temperature regulation at agricultural facilities using a thermodynamic model, which not only takes into account heat exchange, but also includes the influence of chemical reactions. The proposed thermodynamic model and associated equations provide a foundation for future research and practical applications that will ultimately benefit the agricultural industry, global food production

Dendrobium officinale Kimura et Migo is a kind of herb with high medicinal, ornamental, and commercial value, and is rich in polysaccharides. Polyploid breeding is an important breeding method for the genome doubling of medicinal species to increase biomass and polysaccharide production. Previous studies have revealed comparative transcriptome analysis and polysaccharide biosynthesis across the growth stages and plant parts, but there have been no studies dissecting such genes and pathways in tetraploid D. officinale. Therefore, this study aimed to unravel the molecular mechanisms of the increase in polysaccharide content in tetraploid D. officinale via the generation of four transcriptomic libraries for protocorm-like bodies and six-month-old seedlings of both diploid and tetraploid D. officinale plants. In this study, a total of 230,786,618 clean reads remained with a total of 34.62 Gb nucleotides generated; 274,403 unigenes were assembled, of which 73.99% were annotated to at least one of the protein databases; and of 17,451 unigenes, 6.35% were annotated to all seven protein databases (NR, NT, KO, Swiss-Prot, FAM, GO, and KOG). Putative genes encoding enzymes related to polysaccharide biosynthetic pathways were determined. RT-qPCR for 11 randomly selected genes involved in polysaccharides indicated consistency with RNA-Seq data and polysaccharide content. The expressions of nine genes were higher in tetraploid than in diploid plants, while the expressions of the other two genes encoding bifunctional enzymes were the opposite. This study has provided a foundation for subsequent works regarding the biosynthetic pathways of metabolites involved in the autoploidy of Dendrobium species in general, and D. officinale in particular.