[Capital FM] Nairobi Kenya -- President William Ruto will preside over the second edition of the Maasai Cultural Festival in Samburu County, an event dedicated to celebrating the traditions, customs, and lifestyle of the Maasai people.

January 19, 2006 – There is a lot of talk in the media about natural disasters. In the past year the United States has faced hurricanes, flooding, tornados and fires. The first thing on the mind of anyone who goes through a disaster is physical survival. But what very few people consider is economic survival. Just because you lose all of your physical possessions doesn’t mean that you have to lose everything that you have worked for all of your life. But in order to survive economically, you need to do some pre-planning.

Cell phones are now very common in the Western world and have become increasingly more important in a crisis. There are a number of different ways that cell phones can be  extremely helpful in an emergency situation, as a result it is important that the cell phone be operational and have power in the event it is needed.

During a crisis the battery life of a cell phone is crucial. A cell phone may be the only source of communication available.

Prolonging the battery life of a cell phone can be very important and should be considered a priority in an emergency situation. Regardless of whether you have an iPhone or an Android phone there are a number of things that can be done to extend the life of a cell phone’s battery.

Cell Phone Use in Natural Disasters and How to Conserve Battery Life

(Telecompaper) Spanish rural broadband providers Adamo and Avatel as well as MasOrange have secured the majority of the funds made available under the government's Unico Broadband 2024 call...

Influences from around the world in luxury home design

Fr. John Whiteford shares about the Good Samaritan and the story of his father-in-law's life in Communist China.

Unnatural Associations (w/ Fr. Seraphim Aldea)

Are there uniform criteria for Orthodox Christian cultural choices? The answer may not be the same for everyone.

In part one of this four-part series, Matthew outlines the problem that exists with pluralism in Christianity.

In part two of this four-part lecture, Matthew examines the "We all worhip the same Jesus" theory and shows why it is a fallacy.

In part three of four, Matthew shows the contradictions between various interpretations of Christ, thereby tearing down the notion of pluralism.

In the final part of this series, Matthew shows how unity is not only possible, but already exists.

For those of us who cannot go, work or provide, Fr. John notes that we can still contribute in the most important way.

One of the challenges of our present spiritual situation is that our society has settled for something less than truth. This affects the quality of our opinions, policies, and judgments and undermines our ability to live and spread the Gospel. An indicator of the seriousness of this is our growing inability to listen to, learn from, and love people who think differently than we do. In this presentation, I frame the situation as a problem of discernment, compare scientific and Orthodox methods of knowing, and describe how polarization keeps us from using either well. I conclude with a discussion of the critical role diversity plays in discerning truth, and how the Gospel can transform the (Babelic) divisions that deafen us to the truth into a (Pentecostal) harmony that proclaims and celebrates it. Emulating the academic forum the paper was written for (the 2020 Institute for Studies in Eastern Theology), Dn. Timothy Kelleher then offers his thoughts on the presentation and subject. Enjoy the show!

In this episode Fr. Anthony talks with Fr. Harry, the Canonist for the UOC-USA, about the scriptural and canonical context and instructions about sex. Framing it within the context of holiness, they address real issues that Christians need to understand and deal with in the materialist and sex-saturated age. Warning: some graphic terms were used (e.g. fornication, masturbation, adultery).

Today, we consider the Old Testament readings appointed for March 17 (Isaiah 13:2-13; Genesis 8:4-21; Proverbs 10:31-11:12) in the light of the life of Holy Bishop Patrick, and especially the prayer of the “Lorica” (the Breastplate) ascribed to him.

Fr. Ted reminds us of the deep connections between the Old and New Testaments and then shares some of the prophecies that were fulfilled by the healing of the blind man.

research and short essays about cultural loss and the critical importance of preservation and access #

Dr. John Mark Reynolds asks Bishop Thomas questions about angels, demons, miracles, house blessings, weeping icons, and other topics.

Archbishop Joseph delivers his inaugural comments at the Parish Life Conference for the Western Diocese of the Antiochian Archdiocese in San Francisco, California, after being named Metropolitan by Patriarch John X and the Holy Synod of Antioch.

Nyarai moved to Carmarthenshire when she was 13 and felt "very different" in a white, rural area.

Alongside a team of volunteers, Rosemary Stevenson has raised £1.5m to fund care for older people in Ballantrae.

Coroner Joseph Turner says the man's medical cause of death could not be ascertained.

The bridge on Squibbers Way in Bridgwater was closed due to a fire that happened underneath it but was reopened following an inspection.

Police say a trailer was among the stolen items seized by officers during the operation.

Brummie painter tells Radio WM how Stephen knight came to commission his artwork

Content may be king, but data sits behind the throne and has the king’s ear. 

You want to be informed by data before you make changes to your marketing strategies. This is never truer than in the case of your website, which is a rich source of behavioural analytics and, therefore, a valuable insight into your audience’s interests.

Neural network learning approach for color image restoration has been discussed in this paper and one of the possible solutions for restoring images has been presented. Here neural network weights are considered as regularization parameter values instead of explicitly specifying them. The weights are modified during the training through the supply of training set data. The desired response of the network is in the form of estimated value of the current pixel. This estimated value is used to modify the network weights such that the restored value produced by the network for a pixel is as close as to this desired response. One of the advantages of the proposed approach is that, once the neural network is trained, images can be restored without having prior information about the model of noise/blurring with which the image is corrupted.

E-speranto is a formal language for generating multilingual texts on the World Wide Web. It is currently still under development. The vocabulary and grammar rules of E-speranto are based on Esperanto; the syntax of E-speranto, however, is based on XML (eXtensible Markup Language). The latter enables the integration of documents generated in E-speranto into web pages. When a user accesses a web page generated in E-speranto, the interpreter interprets the document into a chosen natural language, which enables the user to read the document in any arbitrary language supported by the interpreter.

The basic parts of the E-speranto interpreting system are the interpreters and information resources, which complies with the principle of separating the interpretation process from the data itself. The architecture of the E-speranto interpreter takes advantage of the resemblance between the languages belonging to the same linguistic group, which consequently results in a lower production cost of the interpreters for the same linguistic group.

We designed a proof-of-concept implementation for interpreting E-speranto in three Slavic languages: Slovenian, Serbian and Russian. These languages share many common features in addition to having a similar syntax and vocabulary. The content of the information resources (vocabulary, lexicon) was limited to the extent that was needed to interpret the test documents. The testing confirmed the applicability of our concept and also indicated the guidelines for future development of both the interpreters and E-speranto itself.

The quality attributes of a software system are, to a large extent, determined by the decisions taken early in the development process. Best practices in software engineering recommend the identification of important quality attributes during the requirements elicitation process, and the specification of software architectures to satisfy these requirements. Over the years the software engineering community has studied the relationship between quality attributes and the use of particular architectural styles and patterns. In this paper we study the relationship between quality attributes and Aspect-Oriented Software Architectures - which apply the principles of Aspect-Oriented Software Development (AOSD) at the architectural level. AOSD focuses on identifying, modeling and composing crosscutting concerns - i.e. concerns that are tangled and/or scattered with other concerns of the application. In this paper we propose to use AO-ADL, an aspect-oriented architectural description language, to specify quality attributes by means of parameterizable, and thus reusable, architectural patterns. We particularly focus on quality attributes that: (1) have major implications on software functionality, requiring the incorporation of explicit functionality at the architectural level; (2) are complex enough as to be modeled by a set of related concerns and the compositions among them, and (3) crosscut domain specific functionality and are related to more than one component in the architecture. We illustrate our approach for usability, a critical quality attribute that satisfies the previous constraints and that requires special attention at the requirements and the architecture design stages.

This research explores vehicular ad hoc networks (VANETs) and their extensive applications, such as enhancing traffic efficiency, infotainment, and passenger safety. Despite significant study, widespread deployment of VANETs has been hindered by security and privacy concerns. Challenges in implementation, including scalability, flexibility, poor connection, and insufficient intelligence, have further complicated VANETs. This study proposes leveraging cloud computing to address these challenges, marking a paradigm shift. Cloud computing, recognised for its cost-efficiency and virtualisation, is integrated with VANETs. The paper details the nomenclature, architecture, models, services, applications, and challenges of VANET-based cloud computing. Three architectures for VANET clouds - vehicular clouds (VCs), vehicles utilising clouds (VuCs), and hybrid vehicular clouds (HVCs) - are discussed in detail. The research provides an overview, delves into related work, and explores VANET cloud computing's architectural frameworks, models, and cloud services. It concludes with insights into future work and a comprehensive conclusion.

The prevalence of social media transforms e-business into social commerce and facilitates consumers' engagement in cross-cultural social commerce. However, social commerce operations encounter unpredictable challenges in cross-cultural business environment. It is vital to further investigate how contextual elements affect consumers' trust and their engagement when they are exposed to the complexity of cross-cultural business environment. The stimuli-organism-response paradigm is employed to examine how the two dimensions of social media usage influence consumers' engagement in cross-cultural social commerce. The current study surveyed 2,058 samples from 135 countries, and the regression analysis results illustrate the mechanism whereby informational and socialising usage of social media positively influences consumers' engagement in social commerce through consumers' trust toward social commerce websites. Additionally, the associations between two aspects of social media usage and consumers' trust towards social commerce are negatively moderated by cultural distance. Both theoretical and practical implications are also discussed.

In order to further improve the teaching quality of multimedia teaching in school daily teaching, a classroom facial expression emotion recognition model is proposed based on convolutional neural network. VGGNet and CliqueNet are used as the basic expression emotion recognition methods, and the two recognition models are fused while the attention module CBAM is added. Simulation results show that the designed classroom face expression emotion recognition model based on V-CNet has high recognition accuracy, and the recognition accuracy on the test set reaches 93.11%, which can be applied to actual teaching scenarios and improve the quality of classroom teaching.

We introduce a unique inductive bias to improve the reconstruction quality of Neural Radiance Fields (NeRF), NeRF employs the Fourier transform to map 3D coordinates to a high-dimensional space, enhancing the representation of high-frequency information in scenes. However, this transformation often introduces significant noise, affecting NeRF's robustness. Our approach allocates attention effectively by segregating channels within NeRF using attention-based gating units. We conducted experiments on an open-source data set to demonstrate the effectiveness of our method, which leads to significant improvements in the quality of synthesised new-view images compared to state-of-the-art methods. Notably, we achieve an average PSNR increase of 0.17 compared to the original NeRF. Furthermore, our method is implemented through a carefully designed special Multi-Layer Perceptron (MLP) architecture, ensuring compatibility with most existing NeRF-based methods.

Food quality is defined as a collection of properties that differentiate each unit and influences acceptability degree of food by users or consumers. Owing to the nature of food, food quality prediction is highly significant after specific periods of storage or before use by consumers. However, the accuracy is the major problem in the existing methods. Hence, this paper presents a BEFA_DRNN approach for accurate food quality prediction using dairy products. Firstly, input data is fed to data normalisation phase, which is performed by min-max normalisation. Thereafter, normalised data is given to feature fusion phase that is conducted employing DNN with Canberra distance. Then, fused data is subjected to data augmentation stage, which is carried out utilising oversampling technique. Finally, food quality prediction is done wherein milk is graded employing DRNN. The training of DRNN is executed by proposed BEFA that is a combination of BES and FA. Additionally, BEFA_DRNN obtained maximum accuracy, TPR and TNR values of 93.6%, 92.5% and 90.7%.

The proliferation of technology and communication has resulted in increased digitalisation that includes digital payments. This study is aimed at unravelling the relationship between awareness of individuals about the digital payment system and customer satisfaction with digital payments. Two models were developed in this study. First model considers awareness → usage pattern → customer satisfaction. Second model considers usage pattern → customer satisfaction → perception of digital payments. These two alternative models were tested by collecting data from 507 respondents in southern India was analysed using the structural equation modelling. The results indicate that usage pattern acted as a mediator between awareness and satisfaction, and satisfaction acted as a mediator between usage pattern and consumers' perception of digital payments. The implications for theory and practice are discussed.

To achieve psychological and emotional analysis of massive internet chats, researchers have used statistical methods, machine learning, and neural networks to analyse the dynamic tendencies of texts dynamically. For long readers, the author first compares and explores the differences between the two psychoanalysis algorithms based on the emotion dictionary and machine learning for simple sentences, then studies the expansion algorithm of the emotion dictionary, and finally proposes an extended text psychoanalysis algorithm based on conditional random field. According to the experimental results, the mental dictionary's accuracy, recall, and F-score based on the cognitive understanding of each additional ten words were calculated. The optimisation decreased, and the memory and F-score improved. An <i>F</i>-value greater than 1, which is the most effective indicator for evaluating the effectiveness of a mental analysis problem, can better demonstrate that the algorithm is adaptive in the literature dictionary. It has been proven that this scheme can achieve good results in analysing emotional tendencies and has higher efficiency than ordinary weight-based psychological sentiment analysis algorithms.

This article studies the application of artificial intelligence technology in natural resource planning and management. This article first introduces the background of NR and AI intelligent technology, then conducts academic research and summary on NR planning management and AI intelligent technology. Then, an algorithm model based on multi-objective intelligent planning algorithm is established. Finally, simulation experiments are conducted, and experiments summary and discussion are provided. The experimental results show that the average efficiency value of the four stages of NR planning and management before use is 5.25, and the average efficiency value of the four stages of NR planning and management after use is 7. The difference in the average efficiency value before and after use is 1.75. It can be seen that the use of AI intelligent technology can effectively improve the efficiency of natural resource planning and management.

The application of computer image digitisation has realised the transformation of people's production and lifestyle, and also promoted the development of the construction industry. This article aims to realise the research on architectural decoration design and production under computer network environment and promote the ecological development of indoor and outdoor design in the construction industry. This article proposes to use virtual reality technology in image digitisation to guide architectural decoration design research. In the comparative analysis of the weight of architectural decoration elements, among the calculated weights of secondary elements, the spatial function has the largest weight, which is 0.2155, and the landscape has the smallest weight, which is 0.0113. Among the three-level unit weights, the service area has the largest weight, which is 0.0976, and the fence frame has the smallest weight, which is 0.0119.

Physical and social aspects each make up a separate part of servicescape. Together, these make up the servicescape. Although previous research has frequently investigated these aspects separately, the purpose of this study is to simultaneously find out the impact of both aspects within the casual dining restaurants' context. In total, 462 customers in Delhi were polled for this study, and structural equation modelling was used to analyse the data. According to the results, both the social and physical parts of the servicescape have the ability to affect how satisfied customers are, which in turn can affect how they behave in the future.

The supply chains of the Canadian forest products industry are largely dependent on accurate demand forecasts. The USA is the major export market for the Canadian forest products industry, although some Canadian provinces are also exporting forest products to other global markets. However, it is very difficult for each province to develop accurate demand forecasts, given the number of factors determining the demand of the forest products in the global markets. We develop multi-layer feed-forward artificial neural network (ANN) models for demand forecasting of the Canadian forest products industry. We find that the ANN models have lower prediction errors and higher threshold statistics as compared to that of the traditional models for predicting the demand of the Canadian forest products. Accurate future demand forecasts will not only help in improving the short-term profitability of the Canadian forest products industry, but also their long-term competitiveness in the global markets.

The purpose of this study is to explore the effect of electronic service quality subdimensions upon the behavioural and praising intentions of users engaged in internet banking. Using the survey method, 203 responses were collected from users of online banking in Turkey. A partial least square structural equation model was constructed to test both the reliability and validity of the measurement, as well as the structural model. The results indicated that emotional benefits, ease of use, and control subdimensions, which are influenced through graphical quality and layout clarity, have a significant and positive impact upon the behavioural and praising intentions of users of online banking. The study did not find support for the direct effect of layout clarity upon behavioural and praising intentions.

To better explore the application of unsupervised learning neural networks in psychological interventions for college students, this study investigates the relationships among latent psychological variables from the perspective of neural networks. Firstly, college students' psychological crisis and intervention systems are analysed, identifying several shortcomings in traditional psychological interventions, such as a lack of knowledge dissemination and imperfect management systems. Secondly, employing the Human-Computer Interaction (HCI) approach, a structural equation model is constructed for unsupervised learning neural networks. Finally, this study further confirms the effectiveness of unsupervised learning neural networks in psychological interventions for college students. The results indicate that in psychological intervention for college students. Additionally, the weightings of the indicators at the criterion level are calculated to be 0.35, 0.27, 0.19, 0.11 and 0.1. Based on the results of HCI, an emergency response system for college students' psychological crises is established, and several intervention measures are proposed.

In order to shorten the integration and sharing time of English teaching resources, a MOOC English online and offline mixed teaching resource integration model based on convolutional neural networks is proposed. The intelligent integration model of MOOC English online and offline hybrid teaching resources based on convolutional neural network is constructed. The intelligent integration unit of teaching resources uses the Arduino device recognition program based on convolutional neural network to complete the classification of hybrid teaching resources. Based on the classification results, an English online and offline mixed teaching resource library for Arduino device MOOC is constructed, to achieve intelligent integration of teaching resources. The experimental results show that when the regularisation coefficient is 0.00002, the convolutional neural network model has the best training effect and the fastest convergence speed. And the resource integration time of the method in this article should not exceed 2 s at most.

International universities are changing with their style of operation, mode of teaching and learning operations. This change is noticeable rapidly in India and also in international contexts due to healthy and innovative methods, educational strategies, and nomenclature throughout the world. Technologies are changing rapidly, including ICT. Different subjects are developed in the fields of IT and computing with the interaction or applications to other fields, viz. health informatics, bio informatics, agriculture informatics, and so on. Agricultural informatics is an interdisciplinary subject dedicated to combining information technology and information science utilisation in agricultural sciences. The digital agriculture is powered by agriculture informatics practice. For teaching, research and development of any subject educational methods is considered as important and various educational programs are there in this regard viz. Bachelor of Education, Master of Education, PhD in Education, etc. Degrees are also available to deal with the subjects and agricultural informatics should not be an exception of this. In this context, Doctor of Education (EdD or DEd) is an emerging degree having features of skill sets, courses and research work. This paper proposed on EdD program with agricultural informatics specialisation for improving healthy agriculture system. Here, a proposed model core curriculum is also presented.