Bobby Maddex interviews Bill Marianes, host of the live call-in show Stewardship Calling, about his role in the Ancient Faith Ministries Conference "Facing Forward: An Ancient Faith Conference for the Second Half of Life."

Bobby Maddex interviews Donna Haddad and Monica Youssef about the upcoming Orthodox Christian Attorney Network Conference on Saturday, October 17th. Donna and Monica share how past years' conferences have benefited them both personally and professionally. This year the free virtual conference features Archbishop Michael Dahulich, Hon. Stephanos Bibas, and Steven Christoforou. Find out more and register for this amazing conference here!

Bobby Maddex interviews Matthew Namee about the upcoming OCAN Conference, which takes place on November 6th. Listeners can learn more and register for the conference here!

Bobby Maddex interviews Joan Berg and Jesse Roberts about the upcoming Orthodox Christian Attorney Network National Conference in Newport Beach, CA. This year's conference will be held from October 7-8 and will feature keynote speaker, The Honorable Gregory Katsas. To learn more about this conference, to register, and to find details on financial assistance, please visit the OCAN website.

Bobby Maddex interviews Kenneth Liu, the Executive Director of the Orthodox Christian Attorney Network, about some new developments at the organization that listeners will want to learn more about and even perhaps support.

Bobby Maddex interviews Kendra Hunter, Kristina Tartara, and Stephanie Petrides, the authors of the new companion guide to Dr. Philip Mamalakis's book Parenting Toward the Kingdom: Orthodox Christian Principles of Child Rearing, publishing by Ancient Faith Publishing.

Most of us know about the so-called Great Schism, which tragically divided the Christian Church between East and West in 1054. But there was an earlier division in the 5th century, following the Fourth Ecumenical Council in Chalcedon in 451, which clarified how Jesus is both God and Man. Charges of heresy were brought, anathemas were proclaimed, and communion was broken. Which Churches did not accept the decision of the Council and the subsequent three Councils that followed? Today they are known as the Oriental Orthodox Churches, including the Coptic, Armenian, Syrian, Malankara, Eritrean, and Ethiopian Orthodox Churches. What specifically separates us theologically? Are there reasons to hope that we are closer to these believers than we thought? What efforts have been made to better understand each other in recent decades? On this special edition of Ancient Faith Today Live, Fr. Tom Soroka and John Maddex examine the causes of our division and consider what any path to unity might involve. Panelists include: Bishop (Dr.) Daniel (Findikyan) Dr. Peter Bouteneff Christine Chaillot Dr. David Ford Dr. Emmanuel Gergis Dr. Chad Hatfield Dr. Michael Ibrahim Rev. Dr. Joseph Lucas Dr. Sam Noble Rev Dr. Timothy Thomas

Part of our communion with God is our connection to the saints; chief among them after the Theotokos are Peter and Paul.

It seems that our society is trying to walk on water without the power of God, and is consequently in the process of drowning in its many confusions. Fr. Patrick Henry Reardon reflects on our adhering to God’s revealed will vs. trying to make history.

Israel recognized no possibility of conflict between God’s will fixed in the Torah and the more fluid guidance He provided in the cloud and the pillar. Fr. Pat offers reflections from Numbers Chapter 9.

Fr. Pat offers pre-Lenten reflections on Hanna, the mother of Samuel and Anna the Prophetess.

Fr. Pat preaches from Isaiah 2:1-9, in which Isaiah delivers two oracles: the first about the ideal Jerusalem which is to come and the second about the actual Jerusalem which exists in Isaiah’s time.

Fr. Pat preaches from 1 Kings 18:42-19:18, about Elijah, who, after his fearless encounter with the priests of Baal, is now isolated and filled with self-pity.

The Parable of the Talents is often used as a reminder to be the best you can be. It's really about the structure of history and the Lordship of Jesus.

Fr. Pat's homily from Forgiveness Vespers 2012.

Both Galatians 1 and Luke 8 contain stories of men converting to Christ. Fr. Pat examines these two accounts.

Fr. Pat compares the story of Peter walking on the water with that of the man who brings his son to Jesus.

Fr. Pat discusses three words from the first chapter of 2 Corinthians.

On the Feast of the Entrance of the Theotokos into the Temple, Fr. Pat compares our Lord's Mother with the rich man in Luke 12, today's Gospel reading.

What the heros and forefathers of the Old Testament could only dream about is yours for the having. So Come and See!

The problem was thousands of hungry people. The disciples brought them to the Lord in prayer and had their own solution which was: "Send them away!" However, the Lord had other ideas. Matthew 14: 14-22

Matthew discusses the careers of Nicholas Bjerring (1870) and James Chrystal (1868), the first two convert priests in American Orthodox history. Learn more HERE.

Matthew continues his discussion with Fr. John Erickson about one of the past attempts at Orthodox administrative unity. Learn more HERE.

When you’re feeling overwhelmed, ask yourself why. (It’s usually one of two reasons.) Are you: (1) on the verge of something new? Or (2) is life showing you that something needs to be cut out? If you’re on the edge of breakthrough with a big project, then sometimes the answer is to keep working and […]

The situation at one primary highlights the issues raised in a report on the state of school buildings.

A car, a van and a lorry were involved in the accident on the A7 north of Langholm.

Locals say a crossroads in Cheadle by The Huntsman pub is becoming notorious for crashes.

A judge tells Jack Bradley the failed raid was "a spectacularly stupid thing to do".

The speed restriction zone is backed by most residents taking part in a consultation, says council.

Witnesses report overhearing the driver say: "I'm more concerned about the living than the dead."

Personalisation in marketing works because personal connections matter. That extends beyond your customers, too. Personal connections include the relationships you have with your suppliers, your stakeholders, your employees, industry peers… the list goes on.

I have been working with Across for several years, but I never got rid of impression that this CAT tools is very user-unfriendly and bugged. A great limitation is a lack of means for an easy transfer of projects between … Continue reading →

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.

This paper reports on the Joaquim Nabuco Project, a pioneering work in Latin America on document digitalization, enhancement, compression, indexing, retrieval and network transmission of historical document images.

Small and Medium Enterprises (SMEs) face new challenges in the global market as customers require more complete and flexible solutions and continue to drastically reduce the number of suppliers. SMEs are trying to address these challenges through cooperation within collaborative enterprise networks (CENs). Human aspects constitute a fundamental issue in these networks as people, as opposed to organizations or Information Technology (IT) systems, cooperate. Since there is a lack of empirical studies on the role of human factors in IT-supported collaborative enterprise networks, this paper addresses the major human aspects encountered in this type of organization. These human aspects include trust issues, knowledge and know-how sharing, coordination and planning activities, and communication and mutual understanding, as well as their influence on the business processes of CENs supported by IT tools. This paper empirically proves that these aspects constitute key factors for the success or the failure of CENs. Two case studies performed on two different CENs in Switzerland are presented and the roles of human factors are identified with respect to the IT support systems. Results show that specific human factors, namely trust and communication and mutual understanding have to be well addressed in order to design and develop adequate software solutions for CENs.

Collaborative Filtering(CF) is a well-known technique in recommender systems. CF exploits relationships between users and recommends items to the active user according to the ratings of his/her neighbors. CF suffers from the data sparsity problem, where users only rate a small set of items. That makes the computation of similarity between users imprecise and consequently reduces the accuracy of CF algorithms. In this article, we propose a clustering approach based on the social information of users to derive the recommendations. We study the application of this approach in two application scenarios: academic venue recommendation based on collaboration information and trust-based recommendation. Using the data from DBLP digital library and Epinion, the evaluation shows that our clustering technique based CF performs better than traditional CF algorithms.

This paper presents a sequential edge swap (SQES) mechanism to design a robust network for a healthcare system utilising energy and communication range of nodes. Two operations: sequential degree difference operation (SQDDO) and sequential angle sum operation (SQASO) are performed to enhance the robustness of network. With equivalent degrees of nodes from the network's centre to its periphery, these operations build a robust network structure. Disaster attacks that have a substantial impact on the network are carried out using the network information. To identify a link between the malicious and disaster attacks, the Pearson coefficient is employed. SQES creates a robust network structure as a single objective optimisation solution by changing the connections of nodes based on the positive correlation of these attacks. SQES beats the current methods, according to simulation results. When compared to hill-climbing algorithm, simulated annealing, and ROSE, respectively, the robustness of SQES is improved by roughly 26%, 19% and 12%.

The current advertising push methods have low accuracy and poor advertising conversion effects. Therefore, a Weibo marketing advertising push method based on social network data mining is studied. Firstly, establish a social network graph and use graph clustering algorithm to mine the association relationships of users in the network. Secondly, through sparsisation processing, the association between nodes in the social network graph is excavated. Then, evaluate the tightness between user preferences and other nodes in the social network, and use the TF-IDF algorithm to extract user interest features. Finally, an attention mechanism is introduced to improve the deep learning model, which matches user interests with advertising domain features and outputs push results. The experimental results show that the push accuracy of this method is higher than 95%, with a maximum advertising click through rate of 82.7% and a maximum advertising conversion rate of 60.7%.

This systematic literature study employed bibliometric analysis to identify workplace mindfulness-related methods and practices in literature published from 2000 to 2020 by leading nations, institutions, journals, authors, and keywords. We also assessed the impact of workplace mindfulness research papers. Scopus analysis tools provided a literature report for 638 Scopus articles used in the study. Using VOSviewer, leading nations, institutions, articles, authors, journals, and keyword co-occurrence network maps were constructed. PRISMA was used to identify 56 publications to recognise workplace mindfulness literature's significant achievements. The research's main contribution is a deep review of neurological mindfulness and psychological measuring tools as workplace mindfulness tool categories. The study is the first to use the PRISMA technique to capture the essential contributions of workplace mindfulness papers from 2000 to 2020.

TCP BBR is one of the most powerful congestion control algorithms. In this article, we provide a comprehensive review of BBR analysis, expanding on existing knowledge across various fronts. Utilising ns3 simulations, we evaluate BBR's performance under diverse conditions, generating graphical representations. Our findings reveal flaws in the probe's RTT phase duration estimation and unequal bandwidth sharing between BBR and CUBIC protocols. Specifically, we demonstrated that the probe's RTT phase duration estimation algorithm is flawed and that BBR and CUBIC generally do not share bandwidth equally. Towards the end of the article, we propose a new improved version of TCP BBR which minimises these problems of inequity in bandwidth sharing and corrects the inaccuracies of the two key parameters RTprop and cwnd. Consequently, the BBR' protocol maintains very good fairness with the Cubic protocol, with an index that is almost equal to 0.98, and an equity index over 0.95.

This paper presents a Scalable Video Coding (SVC) system over multicast Software-Defined Networking (SDN), which focuses on, transmission management for the sender-receiver model. Our approach reduces bandwidth usage by allowing the receiver to select various video resolutions in a multicast group, which helps avoid a video freezing issue during bandwidth congestion. Moreover, the SVC Multiple Sessions Transmission Bandwidth thresholds Quantised Level Balance (SVC-MST BWQLB) routes different layers of the SVC stream using distinct paths and reduces storage space and bandwidth congestion problems in different video resolutions. The experimental results show that the proposed model provides better display quality than the traditional Open Shortest Path First (OSPF) routing technique. Furthermore, it reduced transmission delays by up to 66.64% for grouped resolutions compared to SVC-Single Session Transmission (SVC-SST). Additionally, the modified Real-time Transport Protocol (RTP) header and the sorting buffer for SVC-MST are proposed to deal with the defragmentation problem.

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.

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%.

In the context of smart city development, the managed pressure drilling (MPD) drilling process faces many uncertainties, but the characteristics of the process are complex and require accurate wellbore pressure control. However, this process runs the risk of introducing un-modelled dynamics into the system. To this problem, this paper employs neural network control techniques to construct a dual-network system for throttle pressure control, the design encompasses both the controller and identifier components. The radial basis function (RBF) network and proportional features are connected in parallel in the controller structure, and the RBF network learning algorithm is used to train the identifier structure. The simulation results show that the actual wellbore pressure can quickly track the reference pressure value when the pressure setpoint changes. In addition, the controller based on neural network realises effective control, which enables the system to track the input target quickly and achieve stable convergence.

A number of studies have applied social network analysis (SNA) to show that the patterns of social interaction between software developers explain important organisational outcomes. However, these insights are based on a single network relation (i.e., uniplex social ties) between software developers and do not consider the multiple network relations (i.e., multiplex social ties) that truly exist among project members. This study reassesses the understanding of software developer networks and what it means for performance in software development settings. A systematic review of SNA studies between 1990 and 2020 across six digital libraries within the IS and management science domain was conducted. The central contributions of this paper are an in-depth overview of SNA studies to date and the establishment of a research agenda to advance our knowledge of the concept of multiplexity on how a multiplex perspective can contribute to a software developer's coordination of tasks and performance advantages.

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.