Limited Usage Research Articles

Examining usable security features and user perceptions of Physical Authentication Devices

Despite the enhanced security benefits offered by Physical Authentication Devices (PADs) compared to other forms of Multi-Factor Authentication (MFA), the adoption and retention of PADs remain relatively low in comparison to other MFA methods. Evidence indicates that the limited widespread adoption and usage of PADs are primarily due to negative user perceptions concerning their usability and security features. Moreover, there's a limited understanding of how users from diverse backgrounds perceive PADs with their varying standards and features. To bridge this knowledge gap, we undertook a multiple case study with 23 users spanning varied demographic characteristics (age, gender, education, and experience with MFA) to use and test three distinct PADs. Case study participants were provided with three unique PAD devices featuring different characteristics/features and were prompted to share their experiences of installation, usage, and troubleshooting over a 2-week span via an initial questionnaire, logbook, and a final interview. The gathered data were analysed using NVIVO, a Qualitative Research Software platform, uncovering notable disparities between user groups and their predilections for specific PADs. Further discussions from our research illuminate four primary areas (Compatibility, Support, Quality and Simplicity) where usable security features impede positive user perception of PAD devices and addressing these areas is crucial for enhancing PAD adoption and retention rates.

Answering Binary Causal Questions Using Role-Oriented Concept Embedding

Answering binary causal questions is a challenging task, and it requires rich background knowledge to answer such questions. Extracting useful causal features from the background knowledge base and applying them effectively in a model is a crucial step to answering binary causal questions. The state-of-the-art approaches apply deep learning techniques to answer binary causal questions. In these approaches, candidate concepts are often embedded into vectors to model causal relationships among them. However, a concept may play the role of a cause in one question, but it could be an effect in another question. This aspect has not been extensively explored in existing approaches. Role-oriented causal concept embeddings are proposed in this paper to model causality between concepts. We also propose leveraging semantic concept similarity to extract causal information from concepts. Finally, we develop a deep learning framework to answer binary causal questions. Our approach yields accuracy that is comparable to or better than the benchmark approaches. <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Impact Statement</u> —Understanding causality is crucial for automatic question-answering systems, which are useful in extracting and distributing human knowledge. An automatic question-answering system with causal knowledge can be used to check whether there is causal relationship between two concepts. Existing approaches to answer binary causal questions often answer such questions with close to 55% accuracy due to the limited usage of causal and contextual features. The deep learning framework we propose in this paper uses a role-oriented concept embedding to address such issues. Our approach achieves better accuracy by up to 3.6%, compared to the state-of-the-art benchmark approaches. The proposed approach can be used in a variety of fields, including prescriptive analysis, event prediction, and any other area where entity relationships are essential. It could also be used to improve the retrieval of causality-related inquiries in web search engines.

Assessing the Challenges &amp; Opportunities of Digital Marketing in Ethiopia: The case of Somali Regional State

This study assesses the challenges and opportunities of digital marketing in Somali regional state of Ethiopia. We selected the sample purposively in this study. The collected data were analyzed by using descriptive statistics, regression model was also used to analyse the data. Quantitative data were used. The researcher collected the data with the help of questionnaire. The collected data shows that growing online markets, growing human capacity, growing telecommunication sectors and favourable government policies were digital marketing opportunities, the study also found that risk of privacy and security, e-payment accessibility, limited usage of computer technology, high cost of internet, frequent power disruption and lack of awareness are the challenging factors of digital marketing in Somali region. The findings also show the existence of positive attitude toward digital marketing in the study area. The study also witnesses that the current condition of digital marketing activities in Somali region is poor. The study shows that security and privacy, infrastructure, e-payment accessibility, and awareness have direct impact on digital marketing performance in Somali regional state. The study recommends improvement of government infrastructures, developing of e-payment systems and creation of awareness toward digital marketing

Genoprettende ret i det danske ungdomskriminalitetsnævn?

AbstractThe Danish Youth Crime Boards were launched January 1, 2019. They were part of a new legislation to fight and prevent youth offending. The target group consists of offenders aged 10 to 17, of which those 10 to 14 are legally considered below the age of criminal responsibility. In the legislative framework it is recommended that the verdicts of the boards should have a ‘restorative character to the extent possible’. A new category of verdicts – instant reactions – is introduced in this context. It is noted in several places that these verdicts should be in line with the principles of restorative justice.&#x0D; In the current article, I examine this restorative aspect of the legislative framework of the boards, as well as how it is put into practice by the boards and perceived by board members. Not only does the legislative framework appear unclear on this aspect, it also does not seem to align with recognized international definitions of restorative justice, the principles of which the verdicts of the boards should be in line with.&#x0D; As of October 31, 2021, instant reactions had only been applied in 1.5% of the cases handled by the boards. A key reason for thisis that the municipal recommendations – on the basis of which the boards issue their verdicts – do not include instant reactions in the vast majority of cases. Furthermore, the author’s survey among board members displays a notable uncertainty regarding appropriate instant reactions as well as rather varied connotations of how restorative character should be understood in this context.&#x0D; The Danish political level displays dissatisfaction with the limited usage of instant reactions to date. Initiatives are on the way to address this point, including a catalogue of ideas for possible instant reactions. The author questions whether this approach will actually take the practice of the boards in a more restorative direction. Instead, the author suggests looking towards Norway for inspiration on this matter.

Formation processes, fire use, and patterns of human occupation across the Middle Palaeolithic (MIS 5a-5b) of Gruta da Oliveira (Almonda karst system, Torres Novas, Portugal).

Gruta da Oliveira features a c. 13 m-thick infilling that includes a c. 6.5 m-thick archaeological deposit (the "Middle Palaeolithic sequence" complex), which Bayesian modelling of available dating results places in MIS 5a (layers 7-14) and MIS 5b (layers 15-25), c. 71,000-93,000 years ago. The accumulation primarily consists of sediment washed in from the slope through gravitational processes and surface dynamics. The coarse fraction derives from weathering of the cave's limestone bedrock. Tectonic activity and structural instability caused the erosional retreat of the scarp face, explaining the large, roof-collapsed rock masses found through the stratification. The changes in deposition and diagenesis observed across the archaeological sequence are minor and primarily controlled by local factors and the impact of humans and other biological agents. Pulses of stadial accumulation-reflected in the composition of the assemblages of hunted ungulates, mostly open-country and rocky terrain taxa (rhino, horse, ibex)-alternate with interstadial hiatuses-during which carbonate crusts and flowstone formed. Humans were active at the cave throughout, but occupation was intermittent, which allowed for limited usage by carnivores when people visited less frequently. During the accumulation of layers 15-25 (c. 85,000-93,000 years ago), the carnivore guild was dominated by wolf and lion, while brown bear and lynx predominate in layers 7-14 (c. 71,000-78,000 years ago). In the excavated areas, conditions for residential use were optimal during the accumulation of layers 20-22 (c. 90,000-92,000 years ago) and 14 (c. 76,000-78,000 years ago), which yielded dense, hearth-focused scatters of stone tools and burnt bones. The latter are ubiquitous, adding to the growing body of evidence that Middle Palaeolithic Neandertals used fire in regular, consistent manner. The patterns of site usage revealed at Gruta da Oliveira are no different from those observed 50,000 years later in comparable early Upper Palaeolithic and Solutrean cave sites of central Portugal.

State of health estimation of lithium-ion batteries using EIS measurement and transfer learning

Accurately estimating the state of health (SOH) of lithium-ion batteries in real-world scenarios, especially for electric vehicles (EVs) is challenging due to dynamic operating conditions and limited battery usage data. To address these challenges, transfer learning, as an effective approach that uses the knowledge gained from a source task to improve efficiency and accuracy on a similar target task, has been combined with deep neural networks (DNN) to determine the SOH of Li-ion batteries at various temperatures with a limited amount of target data. In this study, the SOH of Li-ion batteries has been estimated using one of the largest Electrochemical Impedance Spectroscopy (EIS) datasets collected at three different temperatures, 25, 35, and 45 degrees Celsius. The source task is to estimate the SOH using DNN models at one or two operating temperatures (25, 35, and 45 degrees Celsius), while the target task is to estimate the SOH at the other temperature. The results demonstrate that the average mean squared error (MSE) and mean absolute percentage error (MAPE) for estimating the SOH using transfer learning-based DNN (DNN-TL) at 35 degrees Celsius have been reduced up to 72.63% and 48.43%, respectively, compared with the DNN model without transfer learning. Similarly, the average MSE and MAPE for estimating the SOH at 45 degrees Celsius using DNN-TL have been reduced up to 79.51% and 55.11%, respectively. Also, our findings demonstrate the robustness of DNN-TL models, requiring target data with only 6% of the size of source data for retraining, leveraging previously learned knowledge from the source data. Furthermore, the exclusion of fixed layers in the retraining process enhances the performance of the DNN-TL model.

Redefining entrepreneurship education in the age of artificial intelligence: An explorative analysis

AI-powered chatbots, such as ChatGPT, have gained significant attention in the education field due to recent advancements and growing popularity. This article investigates the potential uses of ChatGPT in higher education, specifically within entrepreneurship courses, and explores the benefits and challenges associated with its implementation. To address the need for further research on the use of AI in business education, a survey was conducted among undergraduate students enrolled in entrepreneurship courses. The survey focused on students' awareness and usage of ChatGPT, perceived benefits and limitations, and integration strategies for this tool into entrepreneurship courses. As entrepreneurship education evolves alongside AI advancements, AI technologies like ChatGPT can play a transformative role in various activities, from idea generation, to crafting a business model, writing a business plan, or conducting customer interviews. The study's results indicate that ChatGPT has the potential to streamline processes, increase students' efficiency, and support certain types of creativity. The article also addresses concerns regarding ChatGPT accuracy and reliability, emphasizing the importance of using it critically. This research contributes to the understanding of how AI can enable entrepreneurship education and provides valuable insights for educators, students, and institutions seeking to leverage AI in the classroom.

A comparative study of the 2D- and 3D-based skeleton avatar technology for assessing physical activity and functioning among healthy older adults.

Background: Maintaining physical activity (PA) and functioning (mobility, balance) is essential for older adults' well-being and quality of life. However, current methods (functional tests, self-reports) and available techniques (accelerometers, sensors, advanced movement analysis systems) for assessing physical activity and functioning have shown to be less reliable, time- and resource-consuming with limited routine usage in clinical practice. There is a need to simplify the assessment of physical activity and functioning among older adults both in health care and clinical studies. This work presents a study on using Skeleton Avatar Technology (SAT) for this assessment. SAT analyzes human movement videos using artificial intelligence (AI). The study compares handy SAT based on 2D camera technology (2D SAT) with previously studied 3D SAT for assessing physical activity and functioning in older adults. Objective: To explore whether 2D SAT yields accurate results in physical activity and functioning assessment in healthy older adults, statistically compared to the accuracy of 3D SAT. Method: The mobile pose estimation model provided by Tensorflow was used to extract 2D skeletons from the video recordings of functional test movements. Deep neural networks were used to predict the outcomes of functional tests (FT), expert-based movement quality assessment (EA), accelerometer-based assessments (AC), and self-assessments of PA (SA). To compare the accuracy with 3D SAT models, statistical analysis was used to test whether the difference in the predictions between 2D and 3D models is significant or not. Results: Overall, the accuracy of 2D SAT is lower than 3D SAT in predicting FTs and EA. 2D SAT was able to predict AC with 7% Mean Absolute Error (MAE), and self-assessed PA (SA) with 16% MAE. On average MAE was 4% higher for 2D than for 3D SAT. There was no significant difference found between the 2D and the 3D model for AC and for two FTs (30 seconds chair stand test, 30sCST and Timed up and go, TUG). A significant difference was found for the 2D- and 3D-model of another FT (4-stage balance test, 4SBT). Conclusion: Altogether, the results show that handy 2D SAT might be used for assessing physical activity in older adults without a significant loss of accuracy compared to time-consuming standard tests and to bulky 3D SAT-based assessments. However, the accuracy of 2D SAT in assessing physical functioning should be improved. Taken together, this study shows promising results to use 2D SAT for assessing physical activity in healthy older adults in future clinical studies and clinical practice.

High-efficient sunlight-driven hydrogen production from methanol steam reforming on a novel photo-thermo-catalysis and thermo-catalysis dual-bed reactor

Sunlight-driven methanol-steam-reforming (MSR) reaction using solar energy promises efficient production and safe transportation of hydrogen energy while storing solar energy. However, the low efficiency of photo-reforming and the high cost of thermo-reforming, intrinsically due to limited usage of full-spectrum solar energy, pose a significant challenge to practical application. Here, we propose a sunlight-driven dual-bed photo-thermo-catalytic reactor (DBPTR) for high-efficient hydrogen production from MSR with the cascaded utilization of photo-thermo-catalysis (PTC) over Pt-CuO catalyst bed and thermo-catalysis (TC) over CuO/ZnO/Al2O3 catalyst bed, respectively. The experimental data verify that the overall solar-to-hydrogen (STH) efficiencies of DBPTR remarkably achieve 22.5% in the laboratory and 20.3% outdoors, respectively. These excellent performances are evidently attributed to the fact that our DBPTR could harvest the short-wave radiation (high-energy photons) in the PTC bed for photo-thermo-driven hydrogen production and confine the long-wave radiation (low-energy photons) in the TC bed for thermo-driven hydrogen production. Meanwhile, the proposed DBPTR has been proved to be scaled-up and operate under a reasonably concentrated irradiance of 16 kW m−2 with the above high STH efficiency, harmonizing the high-performance reactor, low-cost concentrator and moderate-accuracy sun-tracker. This work opens up a novel practical pathway towards high-efficient solar-to-chemical conversion.

Rotavirus and bacterial diarrhoea among children in Ile-Ife, Nigeria: Burden, risk factors and seasonality.

Diarrhoea is a leading cause of death among under-five children globally, with sub-Saharan Africa alone accounting for 1/3 episodes yearly. Viruses, bacteria and parasites may cause diarrhoea. Rotavirus is the most common viral aetiology of diarrhoea in children less than five years globally. In Nigeria, there is scarce data on the prevalence/importance, burden, clinical/risk factors and seasonality of rotavirus and bacteria and this study aims to determine the role of rotavirus and bacteria on diarrhoea cases in children less than five years in Ile-Ife, Nigeria. Socio-demographic data, environmental/risk factors and diarrhoiec stool samples were collected from children less than five years presenting with acute diarrhoea. Rotavirus was identified using ELISA. Bacteria pathogens were detected using cultural technique and typed using PCR. Diarrhoeagenic E. coli (DEC) isolates were subjected to antimicrobial susceptibility testing. Pathogen positive and negative samples were compared in terms of gender, age-group, seasonal distribution, and clinical/risk factors using chi-square with two-tailed significance. SPSS version 20.0.1 for Windows was used for statistical analysis. At least one pathogen was detected from 63 (60.6%) children having gastroenteritis while 28 (44.4%) had multiple infections. Rotavirus was the most detected pathogen. Prevalence of rotavirus mono-infection was 22%, multiple infection with bacteria was 45%. Mono-infection prevalence of DEC, Shigella spp., and Salmonella spp. were 5.8% (6/104), 5.8% (6/104), and 2.9% (3/104) and co-infection with RVA were 23.1% (24/104), 21.2% (22/104) and 10.6% (11/104) respectively. All rotaviral infections were observed in the dry season. The pathotypes of DEC detected were STEC and EAEC. Parent earnings and mid-upper arm circumference measurement have statistical correlation with diarrhoea (p = 0.034; 0.035 respectively). In this study, rotavirus was more prevalent than bacteria and occurred only in the dry season. Among bacteria aetiologies, DEC was the most common detected. Differences in seasonal peaks of rotavirus and DEC could be employed in diarrhoea management in Nigeria and other tropical countries to ensure optimal limited resources usage in preventing diarrhoea transmission and reducing indiscriminate use of antibiotics.

Structure, and Mechanical and Thermal Properties of Vinyl-Polydimethylsiloxane/Zinc Dimethacrylate/Isobutylene-Isoprene Rubber Composites

The vinyl-polydimethylsiloxane (v-PDMS) composite reinforced by micron size ZDMA particles previously showed high modulus, thermal stability, solvent-proofness, and good processing ability. However, its poor damping properties limited usages. Thus, incorporation of new polymers into the composite was imperative to improve its loss factors. With a similar solubility parameter and good damping properties, isobutylene-isoprene rubber (IIR) was melt-blended in, then heat-pressed and cross-linked. The v-PDMS/ZDMA/IIR composites gotten were characterized by scanning electric microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), mechanical tests, dynamic mechanical analysis (DMA) and thermal gravimetric analysis (TGA) methods. The IR spectra of the composites illustrated that the incorporation of IIR was successful. The SEM observation showed good dispersion of the IIR, and the increasing deformation on the surface with growing dosage of IIR. The incorporation of IIR rubber decreased the composite’s modulus sharply and also the tensile strength, but improved the elongation and damping properties of the v-PDMS/ZDMA composites at low temperature. The TGA test results in N2 gas showed the composites had good thermal stability below 350 °C, then deteriorated at higher temperature owing to the decomposition of the IIR at 400 °C. The decomposition activation energy at 400 °C was determined by the Kissinger method.

Popularization of Books from the Scientific and Technical Library Collections: Holding Intellectual Games and Book Illustrative Exhibitions

The Central Scientific and Technical Library for Construction and Architecture (CSTL C&amp;A) in Moscow is the leading library of the Russian Federation in these areas. The library stock contains more than 1 million items of specialized literature, including foreign books and periodicals, and its readers are scholars and researchers from construction and architectural organizations, professors from the higher education institutions, as well as students of specialized colleges and institutes. Starting from 2022, the library has been actively engaged in cultural and educational activities, introducing new formats of events and developing interaction with audiences of different age groups, attracting more and more students from specialized colleges and universities.The purpose of the article is to present the experience of CSTL C&amp;A in popularizing books from its collections by means of holding intellectual games and book illustrative exhibitions. The prerequisites for the introduction of a new format of educational activities into the cultural activities of the institution are considered, the course of the game is described and nuances of its preparation are analyzed.The e xperience presented by the author at the XXVII Annual Conference of the Russian Library Association “Library – the cultural code of Russia” can be useful for libraries with collections of limited usage, since it provides visitors with the opportunity to familiarize themselves with literature during the event.

An assessment of Qatari school students’ perspective towards using sustainable modes of transport to school

Being a car dependent country traditionally, private cars are widely used for various trip purposes in State of Qatar including school trips. This paper assesses the factors affecting sustainable mode choices, walking or using school bus to/from school from school students’ perspective. A data of 2639 students from public schools was used to conduct the quantitative analysis. The results suggested that gender, age, and nationality were important demographic factors in determining mode choice to/from school. Further, the selection of school bus was dependent on general safety factors, policy of loading or unloading, service cost, dropoff/pickup points, and availability of driver assistant. Additionally, three obstacles limited school bus usage by students, which were long trip timing, unavailability of service, unsafe service, inconvenient time, and private or personal reasons. These results can be used to address students’ concerns/issues while planning and policy making which can help to increase school bus usage among school students and reduce reliance on private cars.

Highly fluorinated non-aqueous solid-liquid hybrid interface realizes water impermeability for anti-calendar aging zinc metal batteries

The thermodynamic instability of zinc metal in aqueous electrolytes is attributed to severe interfacial problems at the zinc anode. In this study, we designed and synthesized a porous-fluorinated covalent organic framework (FCOF) to encapsulate liquid perfluoropolyether (PFPE) and Zn(OTf)2 using a host-guest strategy to effectively solve the static corrosion problem of the anode. The highly fluorinate solid-liquid interface restricted free water from contacting zinc, thus greatly improving the anti-calendar aging of aqueous zinc-metal batteries. The highly fluorinated solid-liquid hybrid was constructed as a water impermeability and defect-free protection layer on the Zn surface (denoted as P-PFL@Zn). The P-PFL@Zn had integrated advantages: the liquid PFPE filled structural voids to eliminate interfacial defects, improve contact with Zn, and effectively adapt to the dynamic interface fluctuations. The solid FCOF promoted fast ion transport, provided confined space, and exhibited strong adsorption with the liquid phase, restricting the mobility of PFPE and facilitating the tight adherence of FCOF to the Zn surface. Due to the synergistic effect between the FCOF and PFPE, P-PFL@Zn exhibited a 40-day anti-calendar aging cycle, high Zn2+ transference number, ultrafast charging, and dendrite-free features. The assembled high mass-loading (20 mg cm−2) MnO2 cathode-based full cells exhibited good practical level performance under intermittent cycle mode (1000-cycle life with 90% capacity retention) and continuous cycle mode (1000-cycle life with limited Zn usage and high current density).

Promotions, Information Asymmetry and Usage of Traditional Medicine in Central Uganda: A Qualitative Perspective

Background: While extant literature highlights several motivations for Traditional Medicine (TM) usage; few studies have examined how promotions and information asymmetries influence traditional medicine usage behaviors. This study aimed to map out information biases underlying the marketing and promotion of Traditional Medicines in Central Uganda and explored the dimensions of attitudes and usage behaviors of TM users.&#x0D; Methods: The study utilized a qualitative approach by conducting in-depth face-to-face semistructured interviews with TM users in the metropolitan parts of Central Uganda. The study participants were recruited from the Traditional Health Practitioners (THPs) clinics with the help of community development officers under the guidance of the National Council for Traditional Healers and Herbalists' Association (NACOTHA). Study participants gave their written consent, and their identities have since been kept confidential. Saturation point was reached at 34 respondents. Data was recorded and transcribed verbatim and analyzed using content analysis.&#x0D; Results: The study indicates that incomplete, inadequate and inconsistent information especially from TM promotions leads users to overly buy and use TM. Identified themes related to information asymmetry include unverifiable information, usage side effects, and absence of expiry dates on the labels, naturalness of TM, unclear dosage rates, limited diagnosis, limited usage guidelines, and lack of authentic approvals by regulatory bodies among others.&#x0D; Conclusions: The findings raise the need for policy guidelines in the alternative health segment and multi-agency regulation of THPs in Uganda. Further, massive community sensitization and customer education are recommended since the potential for information asymmetries in TM promotions is quite large.

Secure identity key and blockchain‐based authentication approach for secure data communication in multi‐WSN

SummaryBlockchain technology is an effective way to protect data that is handled by wireless sensor network (WSN). The traditional authentication protocol relies on trusted third parties, and most of the WSN paradigm does not allow these conditions, which results in single‐point failure. Sometimes the authentication process is slower, eventually hampers user experience, and thus users are inclined towards other alternatives that can offer multi‐factor authentication. To solve such issues, a secure identity key and blockchain‐based authentication framework is designed using a hybrid blockchain system in multi‐WSN to enhance the system's security. The nodes cooperate in the network to perform specific tasks such that interaction between nodes ensures the legitimacy of node's identity. With hybrid blockchain technology, nodes' identity information is authenticated and stored in the network after verification to establish communication among ordinary nodes and between the ordinary nodes and end user. The proposed method obtains higher security by achieving less computation time, higher detection rate, and limited memory usage of 0.072 s, 92.48%, and 3.925 MB, respectively. The developed authentication method is proved capable of proving resistance in case of different attacks in the network.

Model Transmission-Based Online Updating Approach for Massive MIMO CSI Feedback

Deep learning has been widely applied in frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems to achieve the accurate and effective channel state information (CSI) feedback. The challenges of the network models applied in real-world systems has also obtained more attention, especially the problem of generalization. In this letter, a model transmission-based online updating approach is proposed to achieve the real-time adaptation of the model and solve the problem of model mismatch when unseen data occurs. The feedback model will be updated using the real-time data with limited overhead, and the updating procedure is designed considering the feedback accuracy, requirement on training data, and storage usage. Experimental results indicate that the proposed approach can achieve quick model adjustment in changing scenarios and achieve comprehensive accuracy with limited training cost and storage usage, contributing to the feasibility of AI-based schemes.

A Review on Solid Dispersion

The majority of patients prefer to take their medications orally. However, many drugs' limited usage in oral administration is a result of their poor solubility. One important element that influences the rate of dissolution and bioavailability is solubility. Increasing the pace at which weakly water-soluble substances dissolve through solid dispersion is useful. medicines, hence affecting its bioavailability. This study focuses on different approaches to solid dispersion preparation, their benefits and significant difficulties.

Mung Bean (Vigna radiata L.) Production Status and Challenges in Ethiopia

Mung bean is one of the most important pulse crops, grown from the tropical to sub-tropical areas around the world. Mung bean has good potential for crop rotation system, for crops under drier farmland cultivation areas and ability of growing on dry and irrigated conditions. Mung bean has considerable importance in economical, food, fodder and agricultural (green manure crop to improve soil fertility) aspects. Sowing of mung bean mainly occurs during summer when sufficient rain is available for growth but it is sensitive to waterlogging. It is grown in several types of cultivation systems, including sole cropping, intercropping, multiple cropping and relay cropping, where it is planted after cereals using residual moisture. Mung bean accounts insufficient amount of cultivation practice for food and fodder. Mung bean has considerable importance in economical, food, fodder and agricultural (green manure crop to improve soil fertility) aspects. The huge constraints of pulse crop value-chain production, aggregation and trading, and demand sinks/export. Productivity is below potential due to low input usage, especially chemical fertilizers inability to increase yields, limited availability of seed, limited familiarity with the variety of existing seed types, and limited usage of modern agronomic practices. The link between the producers and the export markets is weak, due to the large number of ineffective intermediaries operating in the value chain. The fragmentation of intermediaries between the producer and consumer markets creates a lack of transparency in markets. We have to support the farmers with recommended agronomic packages, we have to protect disease and insect pest, improved varieties, recommended fertilizer should be applied for better grain yield production of mung bean.

ALSketch: An adaptive learning-based sketch for accurate network measurement under dynamic traffic distribution

Learning-based sketch improves accuracy and reduces the space overhead of traditional sketches by using machine learning to recognize input data patterns. However, most learning-based sketches adopts offline learning to train a learning model, which shows poor accuracy in measuring dynamic network traffic. To accommodate unpredictable changes in network traffic, it is urgent to study a learning-based sketch that not only supports timely updating recognition rules but also keeps accurate and efficient network traffic measurement. We propose a novel adaptive learning-based sketch (ALSketch) to accurately and efficiently measure dynamic network traffic with online machine learning. ALSketch incrementally constructs a learner to identify hot and cold flows and store them separately. Such a strategy reduces hash conflicts and improves estimated accuracy under limited memory usage. We perform extensive comparative experiments to verify the performance of ALSketch. Experimental results reveal that the average relative error of ALSketch is approximately 1.86∼5.25 times lower than that of traditional sketches under the same memory conditions.