Miracle-dz/UniFAR-FTUs huggingface dataset:
Device Indentification In Network Traffic Using Artificial Intelligence Based Capsule Networks

: In recent decade, the security threats poses a high risk in an organization, which is associated with the proliferation of IoT devicesand increasing organizational assets. This ensures that the organization is unaware of the IoT devices connection with their own network. In such cases, security and integrity of network might pose a serious security threat to the network communications. In this paper, capsule network, which is an improved version of Convolutional Neural Network (CNN) is used to monitor the network traffic to identify accurately the trusted devices connected to the home network. Inadequacy of CNN in identifying the IoT devices during its communication in the network has made the present research to choose Capsule Networks (CapsNet) for device identification. Capsule network carries out the operation in an iterative manner in order to attain improved classification of IoT devices. The activation function used in the capsule network is a squash function that normalizes the magnitude of vector rather than the conventional usage of scalar elements. The outputs of activation function helps to find the trusted IoT devices through different capsules, which are formally trained using various concepts. The capsule network performs the identification of IoT devices and classifies the trusted and non-trusted devices based on the labeled network traffic data. The simulation is performed by the computation of collected labeled network data from IoT associated network.
Ultrasonic sensor for detecting the internal discharge of vacuum quenching pot

A sensor detected ultrasonic wave during the discharge in vacuum quenching pot has been developed . The demands for the sensor and its realization scheme are shown.In addition,the insulation and the anti-interference of the sensor are discussed too. The real characteristics and the example of taking over the sound wave have validated the practicability of the sensor.
Exploring the Potential of Adapting Conversational Systems to Different Age Groups: A Pilot Study

A bstract. This pilot study is part of an interdisciplinary project –rooted in communication science as well as AI research on dialogue systems– that aims to explore the potential of adapting conversational systems to different age groups. The main objective of the pilot is to gain insights in users’ perceptions of their interactions with a non-adapted state-of-the-art system (i.e., GPT-2 not conditioned towards a specific age group). This provides necessary input for the next steps in the project, particularly for the set-up of the final experiment and the dialogue scripts that we will develop. The pilot consists of in-depth interviews (N=6) with members of two distinctive age groups (19-29 years versus 50+ years), and the results focus on participants’ perceptions of the system’s language style, their appreciation, perceived comprehensibility, social presence, anthropomor-phism, and trust. Implications for the adapted system and the dialogue scripts are discussed.
IT process conformance measurement : a sarbanes-oxley requirement

In 2006, the most important Canadian distributor and retailer of hardware products was faced with formalizing its internal processes in response to the requirements of the Sarbanes-Oxley Act. This publication is a follow-up information to our first paper on process conformance and audits (7). The software testing process and how conformance to the documented process was achieved within 3 months is described. This research paper presents an introduction, the testing process itself, the process conformance measurement and the results obtained during the first three months of measurement.
Utilization of Global System for Mobile (Gsm) For Communication Byfarmers’ In the Fertilizer Voucher Programmme (FVP) In Taraba State, Nigeria

The main objectives of the study was to assess the utilization of Global System for Mobile (GSM) for communication by farmers’ in the Fertilizer Voucher Programmme (FVP) in Taraba State, Nigeria Specifically, the study sought to: determine extent of needs for information by farmers participating in the Fertilizer Voucher Programme; identify major sources of information used farmers participating in the Fertilizer Voucher Programme; ascertain farmers’ level of productivity as a result of Fertilizer Voucher Programme; and determine major constraints in the implementation of the Fertilizer Voucher Programme in Taraba State. The population for the study comprised all farmers that participated/benefited in FVP in the Taraba State, numbering 51,098 smallholder farmers. Multistage sampling technique was used to draw the sample size. In stage one (1), two senatorial zones (Central & Northern) was purposively selected for their relative peace and security. In stage two, 6 LGAs (Bali, Gashaka, Gassol and Ardokola, Jalingo, Zing) respectively were randomly selected, 3 LGAs in each of selected zones. From each of the selected LGA, 2 percent of the beneficiaries totaling 336 were proportionally selected for primary data collection. Results on the extent of information needs by beneficiaries on programme activities showed that they need information on prices of fertilizer (93.5%), time of arrival of fertilizers (90.2%), quality of fertilizers by the suppliers in FVP (84.2 %), role of cooperative associations (77.4%), pattern in fertilizer purchase in FVP (67.6%), involvement of private suppliers (66.7%), leadership development among participants (64.0%) and redeeming vouchers (60.4%). The findings revealed that all (100%) the respondents owned GSM phones. Majority (91.6%) of respondents utilized the Mobile Phone (GSM) in communication and dissemination of information in the FVP. Variables were grouped under factor 2 (point of purchase related factors) which included: transport to distribution points (0.834), Purchase from wholesalers (0.850) and purchase from importers (0.833). The sales related factors has only sales to wholesalers, dealers and large farmers (0.902) and the last class of challenges comprised: limited access to credit (0.839) and diversion and late arrival of fertilizers (0.785) which were categorized under credit and corruption related factors. The study recommended the use of GSM technology in all agricultural extension programmes for its popularity among farmers in Nigeria as a whole and Taraba state in particular.
PUTTING THE RBV BACK INTO NRBV: A META-ANALYSIS OF MODERATING EFFECTS BETWEEN ENVIRONMENTAL STRATEGY AND FINANCIAL PERFORMANCE

Theory and empirical evidence for the relationship between a firm’s environmental strategy and financial performance, as well as contingencies in that relationship, remains inconsistent. The Natural Resource Based View of the firm offers an overarching framework that can help resolve this inconsistency. Leveraging its genesis in the Resource Based View, we examine environmental strategies identified by the NRBV, recasting them and previously proposed contingencies in common terms: their impact on the value and rarity of the underlying capabilities. Testing resulting hypotheses via meta-analysis of 56 studies published over a 10-year period reveals the importance of considering the type, rather than just the intensity, of environmental strategies. Additionally, conflicts in prior studies likely reflect important, but previously unrecognized, differences in the timeframes, countries, and industries examined.
Reconstruction of high fidelity turbulent flow at various Reynolds number based on generative adversarial deep learning networks

This study presents a deep learning-based framework to reconstruct high-resolution turbu lent velocity fields from extremely low-resolution data at various Reynolds numbers using the concept of generative adversarial networks (GANs). A multiscale enhanced super resolution generative adversarial network (MS-ESRGAN) is applied as a model to recon struct the high-resolution velocity fields, and direct numerical simulation (DNS) data of turbulent channel flow with large longitudinal ribs at various Reynolds numbers are used to evaluate the performance of the model. The model is found to have the capacity to ac curately reproduce high-resolution velocity fields from data at two different low-resolution levels in terms of the quantities of velocity fields and turbulent statistics. The results fur ther reveal that the model is able to reconstruct velocity fields at Reynolds numbers that are not used in the training process.
CONTROL OF THERMOPHILIC SPORES BY SPORICIDAL AGENTS AND THERMAL INACTIVATION

In this study, the adhesion patterns of thermophilic spores of Geobacillus thermodenitrificans DSM 465T, Geobacillus thermoglucosidans B84a, Anoxybacillus kamchatkensis subp. asaccharedens F81 and Anoxybacillus flavithermus DSM 2641T, all of which are biofilm producers in dairy products, were investigated by epifluorescence microscopy on 6 different abiotic surfaces commonly used in the dairy industry. The spores of G. thermodenitrificans DSM 465T and A. kamchatkensis subp. asaccharedens F81 were found to adhere mainly to rubber, polycarbonate, PTFE and stainless steel surfaces. In addition, the efficacy of sporicidal agents on the spores of these bacteria was investigated and only peracetic acid, cetylpyridinium chloride and formaldehyde were found to be the most effective of the sporicidal agents tested. Among the sporicidal agents that showed high efficacy against spores, peracetic acid and nitric acid were selected because they had the shortest contact time, low toxicity and cost. Binary combination effects were tested by determining the LD50 values of the selected agents and it was found that there was a synergistic effectbetween these two effective chemicals. In addition, the thermal resistance profiles of planktonic and sessile spores of A. flavithermus DSM 2641T and G. thermodenitrificans DSM 465T were evaluated.
LIBRO DE ACTAS | 13 A METHODOLOGICAL APPROACH FOR PRIORITIZING WATER REUSE PROJECTS IN AGRICULTURAL IRRIGATION: A CASE STUDY IN SPAIN

Water reuse is a strategic priority for Water Authorities in Europe to reduce the pressure on water resources. However, its implementation is lagging behind expectations largely due to financial concerns. In this context, there is a special interest to identify in which specific Wastewater Treatment Plants it would be interesting to add a Water Regeneration Plant, taking account of potential existing clients in the vicinity and the implied costs and benefits. This paper proposes a methodology to quantify the infrastructure and operation costs of project implementation, and the benefits generated by the additional water offer. An algorithm designs the distribution network, allowing for a quick infrastructure cost analysis. The methodology is applied to the Upper Guadiana in Central Spain, where irrigation led to the overexploitation of the local aquifers and the subsequent restrictions on water use. Taking account of the existing Wastewater Treatment Plants, candidate reuse projects are classified according to their benefit/cost ratio, showing large differences according to the location and potential use of the regenerated water. The methodology allows for a quick assessment of the costs and benefits implied in different reuse projects and scenarios, providing science-based evidence to support water policy decisions.
From Enterprise Architecture To It Governance Elements Of Effective It Management

Architecture and Integration: Methods, Implementation and TechnologiesHandbook on Enterprise ArchitectureIntersectionEnterprise Architecture at WorkThe Open Group Architecture Framework TOGAF™ Version 9Force.com Enterprise ArchitectureAdaptive Cloud Enterprise ArchitectureSun Certified Enterprise Architect for J2EE Technology Study GuideIT Architecture For DummiesEnterprise Architecture PatternsEnterprise ArchitectureEvaluating the Realization of Benefits from Enterprise Architecture Management - Construction and Validation of a Theoretical ModelRequirements AnalysisAgile Business Architecture for Digital TransformationThe Practice of Enterprise ArchitectureHow to Become an It ArchitectArchiMate® 2.0 SpecificationThe Art of Enterprise Architecture for Business ArchitectsI/T Architecture in ActionEnterprise Architecture - The Eight Fundamental FactorsLightweight Enterprise ArchitecturesPrinciple Based Enterprise ArchitectureReaching the PinnacleFEAC Certified Enterprise Architect
Improved Deep Residual Network forApple Leaf Disease Identification

Plant disease is one of the most irritating problems for agriculture growers. Thus, timely detection of plant diseases is of high importance to practical value, and corresponding measures can be taken at the early stage of plant diseases. Therefore, numerous researchers have made unremitting efforts in plant disease identification. However, this problem was not solved effectively until the development of artificial intelligence and big data technologies, especially the wide application of deep learning models in different fields. Since the symptoms of plant diseases mainly appear visually on leaves, computer vision and machine learning technologies are effective and rapid methods for identifying various kinds of plant diseases. As one of the fruits with the highest nutritional value, apple production directly affects the quality of life, and it is important to prevent disease intrusion in advance for yield and taste. In this study, an improved deep residual network is proposed for apple leaf disease identification in a novel way, a global residual connection is added to the original residual network, and the local residual connection architecture is optimized. Including that 1,977 apple leaf disease images with three categories that are collected in this study, experimental results show that the proposed method has achieved 98.74% top-1 accuracy on the test set, outperforming the existing state-of-the-art models in apple leaf disease identification tasks, and proving the effectiveness of the proposed method.
Semantic Space-Based Self-Training for Semi-Supervised Multi-label Text Classification

Finetuning a pre-trained language model is recognized as an effective method for text classification. Since the learning rate in the finetuning stage is often small, we think that classification accuracy depends largely on the quality of the pre-trained model. Based on such an assumption, we design a self-training method that better adapt to the popular two stage training pattern for multi-label text classification under a semi-supervised scenario. We enhance the quality of the pre-trained model by continuously finetuning the semantic space toward increasing high-confidence predictions, intending to further promote the performance on target tasks. We also introduce a comprehensive confidence score and dynamic confidence threshold in selecting high-confidence predictions. Finally, stop criteria are newly designed to prevent the classifier from being poisoned by noise. Our experimental results confirm the effectiveness of our method and show a significant improvement over the baseline methods.
YoloTalk: An Object Detection Platform with IoT

With the advancement of science and the development of computer technology, artificial intelligence (AI) has been used in many aspects. Object detection combining artificial intelligence and computer vision is also one of the very popular issues. However, when users who are not experts at AI methods try to implement object detection, they are likely to encounter difficulties in programming, environment setting, etc., which greatly delays the development time and process. To resolve the problem above, we propose YoloTalk, a webbased object detection platform. Users can conveniently execute object detection by creating a cyber IoT device (called Yolo device) and manage the Yolo device through a browser without any programming effort. Through simple and intuitive website design, users just follow YoloTalk’s step-by-step guidance to create their Yolo device for object detection. In addition, YoloTalk also provides a labeling interface. When the basic Yolo model (trained by MS-COCO dataset) detects wrong object as a person, for example, users can use the labeling interface to add extra labels or correct the wrong results to generate a custom dataset, then train the custom Yolo model using the custom dataset. By retraining the new custom model repeatedly and using Non-maximum suppression (NMS) to ensemble the results of the basic Yolo model and the custom Yolo model, YoloTalk consecutively improves the accuracy. This thesis elaborates on the design concept, implementation, and related application (smart electronic fence) of YoloTalk.
Review on Block Chain based Privacy-Preserving Authentication Scheme for VANETS

:- Recent advances in machine learning and the desire to expand the "smart city", various technology companies and car manufacturers have begun to pour billions of dollars into research and development of private cars. While many companies are working hard to build their own cars, it is important to start planning how these vehicles will interact with other infrastructure. Because passenger and pedestrian safety is highly dependent on this communication, careful design and use of these networks is essential. Blockchain is one of the important key parameters in terms of security. It has garnered a lot of attention in recent years. There are three categories of BC Public, private and consortium which is discussed in the paper.
WebAssembly-based Delta Sync for Cloud Storage Services

Delta synchronization (sync) is crucial to the network-level efficiency of cloud storage services, especially when handling large files with small increments. Practical delta sync techniques are, however, only available for PC clients and mobile apps, but not web browsers—the most pervasive and OS-independent access method. To bridge this gap, prior work concentrates on either reversing the delta sync protocol or utilizing the native client, all striving around the tradeoffs among efficiency, applicability, and usability and thus forming an “impossible triangle. ” Recently, we note the advent of WebAssembly (WASM), a portable binary instruction format that is efficient in both encoding size and load time. In principle, the unique advantages of WASM can make web-based applications enjoy near-native runtime speed without significant cloud-side or client-side changes. Thus, we implement a straightforward WASM-based delta sync solution, WASMrsync, finding its quasi-asynchronous working manner and conventional In-situ Separate Memory Allocation greatly increase sync time and memory usage. To address them, we strategically devise sync-async code decoupling and streaming compilation, together with Informed In-place File Construction. The resulting solution, WASMrsync+, achieves comparable sync time as the state-of-the-art (most efficient) solution with nearly only half of memory usage, letting the “impossible triangle” reach a reconciliation.
Study on Trip Caused by Windage Yaw of 500kV Transmission Line

In order to reduce the trip caused by windage yaw, the windage yaw trips in Huazhong area in June and July, 2004 are analyzed. In thsee cases there is strong wind and heavy rain. There arc trace on tower, hardware and conductors, the reclosing were not successful. Closing were successful after strong wind. The main reason of windage yaw discharge are: 1)The windage yaw is too big due to strong wind; 2) The discharge voltage reduce due to heavy rain; 3) Estimation of scurviness of meteorological condition is not efficient. Adding the heavy punch or jumper line insulator string on dead end tower jumper line, adding heavy punch on insulator string on tangent tower, checking the windage yaw gap combining with meteorological condition and checking the windage yaw foe tree, mountain slope are necessary measure to prevent discharge.
Exploration of high potential in Mobile Learning Technologies-Situations for Higher Education

Meta­reviews have provided an interesting overview over current trends and developments of mobile learning ­ a field that is increasingly attracting academic and public interest. To add to the extant literature, this qualitative literature review focuses on higher education, the most popular domain for mobile learning research. This critical analysis examines which pedagogical approaches based on digital mobile technologies such as cell phones, PDAs, Smartphones, tablets etc., are effective, specifically when contrasted with other forms of digital and non­digital designs. Accordingly, the analysis specifically concentrates on mobile learning projects (and processes), underlying pedagogical strategies and educational outcomes. The findings indicate that despite the rich and vast body of literature, convincing evidence that recommends the use of mobile learning in higher education is still limited. The most convincing studies are those that combine approaches of situated, constructionist and/or collaborative learning. These results do not only provide a synthesis of the current state of mobile learning research in HE, but they can also support teachers and higher education management in their decisions of whether and how to use mobile technologies in and beyond the classroom.
Typology and Development of Local Administrative Units: Spatial Discriminant Analysis

Purpose: The aim is the evaluation of the consistency of typology of local administrative units (LAU) with their level of socio-economic development. The authors identified also the impact of the incorporation of spatial relations on the stability of such consistency. Design/Methodology/Approach: The spatial linear discriminant analysis with various weights matrices has been applied. Introducing the spatial relationship between observations in different locations to the classical classification method allows to identify non-measurable spatial factors differentiating different locations as well as the directions of their development. Findings: The results confirmed a high discrepancy between the administrative type and the level of development of Polish communes in 2006-2018. The higher compliance of official typology of examined units with their actual level of development was found when spatial relations were incorporated. The obtained results indicated the marginalisation of mediumsized cities, and underdevelopment of urban-rural communes. The following predictors, new dwellings, employment rate, population density, and registered entities, had the highest power of discrimination in the classification process. Practical Implications: Proposed models could have the practical application for determining the actual type of local administrative unit and designing regional policy. Especially in the case when some intervention is needed in the area of financial external support. Such policy may reduce disparities between the levels of development of the various regions, especially addressing the problems of less developed areas. Originality/Value: This research presents a concept of spatial linear discriminant analysis with a spatial component of regional structure integrated in form of spatial weights matrices. The proposed method was applied to identify the meaning of neighbouring regions characteristics in classification of territorial units, as well as to indicate the group of Polish voivodeships characterized by a high and low degree of correspondence between the actual and expected type of the territorial unit.