Search results for: Network coverage

Authors: Misha Alexander, S. B. Waykar

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Visual Cryptography is a special unbreakable encryption technique that transforms the secret image into random noisy pixels. These shares are transmitted over the network and because of its noisy texture it attracts the hackers. To address this issue a Natural Visual Secret Sharing Scheme (NVSS) was introduced that uses natural shares either in digital or printed form to generate the noisy secret share. This scheme greatly reduces the transmission risk but causes distortion in the retrieved secret image through variation in settings and properties of digital devices used to capture the natural image during encryption / decryption phase. This paper proposes a new NVSS scheme that extracts the secret key from randomly selected unaltered multiple natural images. To further improve the security of the shares data hiding techniques such as Steganography and Alpha channel watermarking are proposed.

Keywords: decryption, encryption, natural visual secret sharing, natural images, noisy share, pixel swapping

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Authors: Luqman Ali Shah, Murtaza Sayed, Mohammad Siddiq

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Three-dimensional cross-linked polymer microgels with temperature responsive N-isopropyl acrylamide (NIPAM) and pH-sensitive methacrylic acid (MAA) were successfully synthesized by free radical emulsion polymerization with different amount of MAA. Silver and gold nanoparticles with size of 6.5 and 3.5 nm (±0.5 nm) respectively were homogeneously reduced inside these materials by chemical reduction method at pH 2.78 and 8.36 for the preparation of hybrid materials. The samples were characterized by FTIR, DLS and TEM techniques. The catalytic activity of the hybrid materials was investigated for the reduction of 4-nitrophenol (4- NP) using NaBH4 as reducing agent by UV-visible spectroscopy. The hybrid polymer network synthesized at pH 8.36 shows enhanced catalytic efficiency compared to catalysts synthesized at pH 2.78. In this study, it has been explored that catalyst activity strongly depends on amount of MAA, synthesis pH and type of metal nanoparticles entrapped.

Keywords: cross-linked polymer microgels, free radical polymerization, metal nanoparticles, catalytic activity, comparative study

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Authors: Idris Lawal

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Electronic payment system is simply a payment or monetary transaction made over the internet or a network of computers. This study was carried out in order to assess how electronic payment system has impacted on banks service delivery, to examine the efficiency of electronic payment system in Nigeria and to determine the level of customer's satisfaction as a direct result of the deployment of electronic payment systems. It is an empirical study conducted using structured questionnaire distributed to officials and customers of Access Bank plc. Chi-square(x2) was adopted for the purpose of data analysis. The result of the study showed that the development of electronic payment system offer great benefit to bank customers including improved services, reduced turn-around time, ease of banking transaction, significant cost saving etc. The study recommends that customer protection laws should be properly put in place to safeguard the interest of end users of e-payment instruments.

Keywords: bank, electronic payment systems, service delivery, customer's satisfaction

Procedia PDF Downloads 384

Authors: Nan Xu

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In airlines, the crew scheduling problem is usually decomposed into two stages: crew pairing and crew rostering. In the crew pairing stage, pairings are generated such that each flight is covered by exactly one pairing and the overall cost is minimized. In the crew rostering stage, the pairings generated in the crew pairing stage are combined with off days, training and other breaks to create individual work schedules. The paper focuses on cabin crew rostering problem, which is challenging due to the extremely large size and the complex working rules involved. In our approach, the objective of rostering consists of two major components. The first is to minimize the number of unassigned pairings and the second is to ensure the fairness to crew members. There are two measures of fairness to crew members, the number of overnight duties and the total fly-hour over a given period. Pairings should be assigned to each crew member so that their actual overnight duties and fly hours are as close to the expected average as possible. Deviations from the expected average are penalized in the objective function. Since several small deviations are preferred than a large deviation, the penalization is quadratic. Our model of the airline crew rostering problem is based on column generation. The problem is decomposed into a master problem and subproblems. The mater problem is modeled as a set partition problem and exactly one roster for each crew is picked up such that the pairings are covered. The restricted linear master problem (RLMP) is considered. The current subproblem tries to find columns with negative reduced costs and add them to the RLMP for the next iteration. When no column with negative reduced cost can be found or a stop criteria is met, the procedure ends. The subproblem is to generate feasible crew rosters for each crew member. A separate acyclic weighted graph is constructed for each crew member and the subproblem is modeled as resource constrained shortest path problems in the graph. Labeling algorithm is used to solve it. Since the penalization is quadratic, a method to deal with non-additive shortest path problem using labeling algorithm is proposed and corresponding domination condition is defined. The major contribution of our model is: 1) We propose a method to deal with non-additive shortest path problem; 2) Operation to allow relaxing some soft rules is allowed in our algorithm, which can improve the coverage rate; 3) Multi-thread techniques are used to improve the efficiency of the algorithm when generating Line-of-Work for crew members. Here a column generation based algorithm for the airline cabin crew rostering problem is proposed. The objective is to assign a personalized roster to crew member which minimize the number of unassigned pairings and ensure the fairness to crew members. The algorithm we propose in this paper has been put into production in a major airline in China and numerical experiments show that it has a good performance.

Keywords: aircrew rostering, aircrew scheduling, column generation, SPPRC

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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A method and system for neuropsychological performance test, comprising a mobile terminal, used to interact with a cloud server which stores user information and is logged into by the user through the terminal device; the user information is directly accessed through the terminal device and is processed by artificial neural network, and the user information comprises user facial emotions information, performance test answers information and user chronometrics. This assessment is used to evaluate the cognitive performance and emotional response of the subject to a series of dichotomous questions describing various situations of daily life and challenging the users' knowledge, values, ethics, and principles. In industrial applications, the timing of this assessment will depend on the users' need to obtain a service from a provider, such as opening a bank account, getting a mortgage or an insurance policy, authenticating clearance at work, or securing online payments.

Keywords: artificial intelligence, neurofinance, neuropsychology, risk management

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Authors: Anas H. Aljemely, Jianping Xuan

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Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

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Authors: Rodrigo S. Fonseca, Antônio C. P. Veiga

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Aiming at helping people with some movement limitation that makes typing and communication difficult, there is a need to customize an assistive tool with a learning environment that helps the user in order to optimize text input, identifying the error and providing the correction and possibilities of choice in the Portuguese language. The work presents an Orthographic and Grammatical System that can be incorporated into writing environments, improving and facilitating the use of an alphanumeric keyboard, using a prototype built using a genetic algorithm in addition to carrying out the prediction, which can occur based on the quantity and position of the inserted letters and even placement in the sentence, ensuring the sequence of ideas using a Long Short Term Memory (LSTM) neural network. The prototype optimizes data entry, being a component of assistive technology for the textual formulation, detecting errors, seeking solutions and informing the user of accurate predictions quickly and effectively through machine learning.

Keywords: genetic algorithm, neural networks, word prediction, machine learning

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Authors: Gaurav Sancheti

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This study presents an impacting approach of Artificial Neural Networks (ANNs) in determining the quantity of High Tensile Steel (HTS) strands required in post-tensioned (PT) slabs. Various PT slab configurations were generated by varying the span and depth of the slab. For each of these slab configurations, quantity of required HTS strands were recorded. ANNs with backpropagation algorithm and varying architectures were developed and their performance was evaluated in terms of Mean Square Error (MSE). The recorded data for the quantity of HTS strands was used as a feeder database for training the developed ANNs. The networks were validated using various validation techniques. The results show that the proposed ANNs have a great potential with good prediction and generalization capability.

Keywords: artificial neural networks, back propagation, conceptual design, high tensile steel strands, post tensioned slabs, validation techniques

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Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova

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We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.

Keywords: cybersecurity, epidemiology, cyber epidemiology, malware

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Authors: Lan Nguyen, Kien Le Tan, Bao Nguyen Pham Gia

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Due to the high cost, specialized dynamic measurement devices for industrial lands are difficult for many colleges to equip for hands-on teaching. This study connects a dynamic measurement sensor and receiver utilizing an inexpensive Raspberry Pi 4 board, some 24-bit ADC circuits, a geophone vibration sensor, and embedded Python open-source programming. Gather and analyze signals for dynamic measuring, ground vibration monitoring, and structure vibration monitoring. The system may wirelessly communicate data to the computer and is set up as a communication node network, enabling real-time monitoring of background vibrations at various locations. The device can be utilized for a variety of dynamic measurement and monitoring tasks, including monitoring earthquake vibrations, ground vibrations from construction operations, traffic, and vibrations of building structures.

Keywords: sensors, FFT, signal processing, real-time data monitoring, ground propagation wave, python, raspberry Pi 4

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Authors: Ruth Mandujano Lopez

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During the second half of the 19th century, in the transition from sail to steam navigation, the transpacific space underwent major transformation. This paper examines the role that the steamship companies between Mexico, the rest of North America and Asia played in that process. Based on primary sources found in Mexico, California, London and Hong Kong, it argues that these companies actively participated in the redefining of the Pacific space as they opened new routes, transported thousands of people and had an impact on regional geopolitics. In order to prove this, the text will present the cases of a handful of companies that emerged between 1867 and 1910 and of some of their passengers. By looking at the way the Mexican ports incorporated to the transpacific steam maritime network, this work contributes to have a better understanding of the role that Latin American ports have played in the formation of a global order. From a theoretical point of view, it proposes the conceptualization of space in the form of transnational networks as a point of departure to conceive a history that is truly global.

Keywords: mexico, steamships, transpacific, maritime companies

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Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

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Several meteorological parameters were used for the prediction of monthly average daily global solar radiation on horizontal using recurrent neural networks (RNNs). Climatological data and measures, mainly air temperature, humidity, sunshine duration, and wind speed between 1995 and 2007 were used to design and validate a feed forward and recurrent neural network based prediction systems. In this paper we present our reference system based on a feed-forward multilayer perceptron (MLP) as well as the proposed approach based on an RNN model. The obtained results were promising and comparable to those obtained by other existing empirical and neural models. The experimental results showed the advantage of RNNs over simple MLPs when we deal with time series solar radiation predictions based on daily climatological data.

Keywords: recurrent neural networks, global solar radiation, multi-layer perceptron, gradient, root mean square error

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Authors: Ahmidah Elgali

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SCADA is the abbreviation for "Administrative Control And Data Acquisition." SCADA frameworks are generally utilized in industry for administrative control and information securing of modern cycles. Regular SCADA frameworks use PC, journal, slim client, and PDA as a client. In this paper, a Java-empowered cell phone has been utilized as a client in an example SCADA application to show and regulate the place of an example model crane. The paper presents a genuine execution of the online controlling of the model crane through a cell phone. The remote correspondence between the cell phone and the SCADA server is performed through a base station by means of general parcel radio assistance GPRS and remote application convention WAP. This application can be used in industrial sites in areas that are likely to be exposed to a security emergency (like terrorist attacks) which causes the sudden exit of the operators; however, no time to perform the shutdown procedures for the plant. Hence this application allows shutting down units and equipment remotely by mobile and so avoids damage and losses.

Keywords: control, industrial, mobile, network, remote, SCADA

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Authors: Nebojsa Stefanovic, Sasa Milijic, Natasa Danilovic Hristic

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Spatial plan of the special purpose area constitutes a basic tool in the planning of infrastructure corridor of a highway. The aim of the plan is to define the planning basis and provision of spatial conditions for the construction and operation of the highway, as well as for developing other infrastructure systems in the corridor. This paper presents a methodology and approach to the preparation of the Spatial Plan for the special purpose area for the infrastructure corridor of the highway E-80, Section Niš-Merdare in Serbia. The applied methodological approach is based on the combined application of the integrative and participatory method in the decision-making process on the sustainable development of the highway corridor. It was found that, for the planning and management of the infrastructure corridor, a key problem is coordination of spatial and urban planning, strategic environmental assessment and sectoral traffic planning and designing. Through the development of the plan, special attention is focused on increasing the accessibility of the local and regional surrounding, reducing the adverse impacts on the development of settlements and the economy, protection of natural resources, natural and cultural heritage, and the development of other infrastructure systems in the corridor of the highway. As a result of the applied methodology, this paper analyzes the basic features such as coverage, the concept, protected zones, service facilities and objects, the rules of development and construction, etc. Special emphasis is placed to methodology and results of the Strategic Environmental Assessment of the Spatial Plan, and to the importance of protection measures, with the special significance of air and noise protection measures. For evaluation in the Strategic Environmental Assessment, a multicriteria expert evaluation (semi-quantitative method) of planned solutions was used in relation to the set of goals and relevant indicators, based on the basic set of indicators of sustainable development. Evaluation of planned solutions encompassed the significance and size, spatial conditions and probability of the impact of planned solutions on the environment, and the defined goals of strategic assessment. The framework of the implementation of the Spatial Plan is presented, which is determined for the simultaneous elaboration of planning solutions at two levels: the strategic level of the spatial plan and detailed urban plan level. It is also analyzed the relationship of the Spatial Plan to other applicable planning documents for the planning area. The effects of this methodological approach relate to enabling integrated planning of the sustainable development of the infrastructure corridor of the highway and its surrounding area, through coordination of spatial, urban and sectoral traffic planning and design, as well as the participation of all key actors in the adoption and implementation of planned decisions. By the conclusions of the paper, it is pointed to the direction for further research, particularly in terms of harmonizing methodology of planning documentation and preparation of technical-design documentation.

Keywords: corridor, environment, highway, impact, methodology, spatial plan, urban

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Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam

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Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.

Keywords: autonomous strategies, distributed database systems, high priority, query optimization

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Authors: Zahra Afshordi

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Instagram, as an everyday life social network, hosts from the ultrasound image of an unborn fetus to the pictures of newly placed gravestones and funerals. It is a platform that allows its users to create a second identity independently from and at the same time in relation to the real space identity. The motives behind this identification are what this article is about. This article studies the motivations of Instagram users mourning for celebrities with a focus on the death of MohammadReza Shajarian. The Shajarian’s death had a wide reflection on Instagram Persian-speaking users. The purpose of this qualitative survey is to comprehend and study the user’s motivations in posting mourning and memorializing content. The methodology of the essay is a hybrid methodology consisting of content analysis and open-ended interviews. The results highlight that users' motives are more than just simple sympathy and include political protest, gaining cultural capital, reaching social status, and escaping from solitude.

Keywords: case study, celebrity, identity, Instagram, mourning, qualitative survey

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Authors: Ashish James, Anusha James

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The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.

Keywords: uncertainty estimation, neural networks, transfer learning, regression

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Authors: Victor Chomel, Maziyar Panahi, David Chavalarias

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Misinformation has taken an increasingly worrying place in social media. Propagation patterns are closely linked to the structure of communities. This study proposes a method of community analysis based on a combination of centrality indicators for the network and its main communities. The objective is to establish a link between the stability of the communities over time, the social ascension of its members internally, and the propagation of information in the community. To this end, data from the debates about global warming and political communities on Twitter have been collected, and several tens of millions of tweets and retweets have helped us better understand the structure of these communities. The quantification of this stability allows for the study of the propagation of information of any kind, including disinformation. Our results indicate that the most stable communities over time are the ones that enable the establishment of nodes capturing a large part of the information and broadcasting its opinions. Conversely, communities with a high turnover and social ascendancy only stabilize themselves strongly in the face of adversity and external events but seem to offer a greater diversity of opinions most of the time.

Keywords: community analysis, disinformation, misinformation, Twitter

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Authors: Monica Sanchez

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What responsibility does urban planning have on climate changes? How does the territory give us answers of resilience? Historically, urban plans have civilized territories: waters are channeled, grounds are sealed, foreign species are incorporated, native ones are extinguished, and/or enclosed spaces are heated or cooled. Socially this facilitates coexistence, but in turn brings negative environmental consequences. The past fifty years, mankind has tried to redirect these consequences through different strategies. Research studies produced strategies designed to alleviate climate change. Exploring the nature of territories has been incorporated in urban planning to discover natures response. The case to be studied is Santiago, Chile: for its combined impacts of climate change and the significant response by this city on climate governance in the last decades. Warmer areas in Santiago are seen in the areas of high-density buildings such as the commune of Recoleta, while the coldest are characterized by the predominance of low residential densities as the commune of Providencia. These two communes are separated and complemented by an undulating body that comes from the Andes mountains called San Cristobal Hill. What if the hill were taken into account when making roads, zoning and buildings? Was it difficult to prolong in the urban plans the hill characteristics to the city solving the intersection with other natural areas? Apparently it was, because the projected-profile informs us that the planned strategies used correspond to the same operations used in the flat areas of Santiago. This research focuses on: explaining the geographic relationships between city-hill; explaining the planning process around the hill with a morphological analysis; evaluating how the hill has been considered the in the city in the plans that intended to cushion the environmental impacts and studying what is missing on the hill and city to strengthen their integration. Therefore, the research will have different scales of understanding: addressing territorial scale -understanding the vegetation, topography and hydrology; a city scale -analyzing urban plans that Santiago has dealt with the environment and city; and a local scale -studying the integration and public spaces and coverage- norms of the adjacent communes. The expected outcome is to decipher possible deficits and capabilities of the current urban plans for climate change. It is anticipated that the hill and valley is now trying to reconcile after such a long separation. Yet it seems that never will prevail all the Rules of Nature, but the Urban Rules. The plans will require pruning, irrigation, control of invasive alien species and public safety standards, but will be rejoining a dose of nature with the building environment -this will protect us better from it from the time that we feared from it and knew little about it. Today we know a little more, enough to adapt to the process. Although nature is not perceived and we ignore it, it has a remarkable ability to respond.

Keywords: resilience, climate change, urban plans, land use, hills and cities, heat islands, morphology

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Authors: Mahmoud M. Othman, Almoataz Y. Abdelaziz, Yasser G. Hegazy

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This paper presents a load control strategy based on modification of the Big Bang Big Crunch optimization method. The proposed strategy aims to determine the optimal load to be controlled and the corresponding time of control in order to minimize the energy purchased from substation. The presented strategy helps the distribution network operator to rely on the renewable energy sources in supplying the system demand. The renewable energy sources used in the presented study are modeled using the diagonal band Copula method and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithm.

Keywords: big bang big crunch, distributed generation, load control, optimization, planning

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Authors: Anocha Rojanapanich

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The purpose of this research is to develop and design an accounting management information system for convenient shop in Bangkok Thailand. The study applied the System Development Life Cycle (SDLC) for development which began with study and analysis of current data, including the existing system. Then, the system was designed and developed to meet users’ requirements via the internet network by use of application software such as My SQL for database management, Product diversity, Apache HTTP Server for Web Server and PHP Hypertext Preprocessor for an interface between web server, database and users. The system was designed into two subsystems as the main system, or system for head office, and the branch system for branch shops. These consisted of three parts which are classified by user management as shop management, inventory management and Point of Sale (POS) management and importance of cost information for decision making also as well as.

Keywords: accounting management information system, convenient shop, cost information for decision making system, development life cycle

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Authors: Yiqi Wu, Simon Tait, Andrew Nichols

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Management of UK railway drainage assets is challenging due to the large amounts of historical assets with long asset life cycles. A major concern for asset managers is to maintain the required performance economically and efficiently while complying with the relevant regulation and legislation. As the majority of the drainage assets are buried underground and are often difficult or costly to examine, it is important for asset managers to understand and model the degradation process in order to foresee the upcoming reduction in asset performance and conduct proactive maintenance accordingly. In this research, a Markov chain approach is used to model the deterioration process of rail drainage assets. The study is based on historical condition scores and characteristics of drainage assets across the whole railway network in England, Scotland, and Wales. The model is used to examine the effect of various characteristics on the probabilities of degradation, for example, the regional difference in probabilities of degradation, and how material and shape can influence the deterioration process for chambers, channels, and pipes.

Keywords: deterioration, degradation, markov models, probability, railway drainage

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Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

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Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

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Authors: Toufik Karech, Abderahmen Benseghir, Tayeb Bouzid

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This work presents a 2D numerical simulation of an earth dam to assess the behavior of its foundation after a treatment by stone columns. This treatment aims to improve the bearing capacity, to increase the mechanical properties of the soil, to accelerate the consolidation, to reduce the settlements and to eliminate the liquefaction phenomenon in case of seismic excitation. For the evaluation of the pore pressures, the position of the phreatic line and the flow network was defined, and a seepage analysis was performed with the software MIDAS Soil Works. The consolidation calculation is performed through a simulation of the actual construction stages of the dam. These analyzes were performed using the Mohr-Coulomb soil model and the results are compared with the actual measurements of settlement gauges implanted in the dam. An analysis of the bearing capacity was conducted to show the role of stone columns in improving the bearing capacity of the foundation.

Keywords: earth dam, dam foundation, numerical simulation, stone columns, seepage analysis, consolidation, bearing capacity

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Authors: Muhammad Rana, Quazi Mamun, Rafiqul Islam

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In the Internet of Things (IoT), many devices are connected and accumulate a sheer amount of data. These Internet-driven raw data need to be transferred securely to the end-users via dependable networks. Consequently, the challenges of IoT security in various IoT domains are paramount. Cryptography is being applied to secure the networks for authentication, confidentiality, data integrity and access control. However, due to the resource constraint properties of IoT devices, the conventional cipher may not be suitable in all IoT networks. This paper designs a robust and effective lightweight cipher to secure the IoT environment and meet the resource-constrained nature of IoT devices. We also propose a symmetric and block-cipher based lightweight cryptographic algorithm. The proposed algorithm increases the complexity of the block cipher, maintaining the lowest computational requirements possible. The proposed algorithm efficiently constructs the key register updating technique, reduces the number of encryption rounds, and adds a new layer between the encryption and decryption processes.

Keywords: internet of things, cryptography block cipher, S-box, key management, security, network

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Authors: Khaled Ben Oualid Medani, Samir Sayah

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The Optimal Reactive Power Dispatch (ORPD) problem has been solved and analysed usually in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, power system analysis, real power loss minimization, contingency condition, metaheuristic technique, whale optimization algorithm

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Authors: Regan Harper, Song Yang, Douglas Adams

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During the historically unprecedent time of Covid-19 pandemic, we survey college students with social issue generators to measure their core discussion groups. For the total 191 students, we elicit 847 conversation partners (alters) with our five social issue generators such as school closing, facemasks, collegiate sports, race and policing, and social inequality, producing an average of 4.43 alters per respondent. The core discussion groups of our sample are very gender balanced, with female alters slightly outnumbering male alters. However, the core discussion groups are racially homogenous, consisting of mostly white students (around or above 80 percent). Explanatory analyses reveal that gender and race of respondents significantly impact the size, gender composition, and racial composition of their core discussion networks. We discuss those major findings and implications of future studies in our conclusion section.

Keywords: core discussion groups, social issue generators, ego-centric network, Covid-19 pandemic

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Authors: Jarek Krajewski, Andre Wittenborn, Martin Sauerland

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This abstract describes a promising approach for estimating post-traumatic stress disorder (PTSD) based on prosodic speech characteristics. It illustrates the validity of this method by briefly discussing results from an Arabic refugee sample (N= 47, 32 m, 15 f). A well-established standardized self-report scale “Reaction of Adolescents to Traumatic Stress” (RATS) was used to determine the ground truth level of PTSD. The speech material was prompted by telling about autobiographical related sadness inducing experiences (sampling rate 16 kHz, 8 bit resolution). In order to investigate PTSD-induced speech changes, a self-developed set of 136 prosodic speech features was extracted from the .wav files. This set was adapted to capture traumatization related speech phenomena. An artificial neural network (ANN) machine learning model was applied to determine the PTSD level and reached a correlation of r = .37. These results indicate that our classifiers can achieve similar results to those seen in speech-based stress research.

Keywords: speech prosody, PTSD, machine learning, feature extraction

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Authors: Yu Cheng-Yu

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‘Heterotopia’, ‘Visual Cultural Art Education’ and ‘New Media’ of these three subjects seemingly are irrelevant. In fact, there are synchronicity and intertextuality inside. In addition to visual culture, art education inspires students the ability to reflect on popular culture image through visual culture teaching strategies in school. We should get involved in the community to construct the learning environment that conveys visual culture art. This thesis attempts to probe the heterogeneity of space and value from Michel Foucault and to research sustainable development strategy in ‘New Media Art Village’ heterogeneity from Jean Baudrillard, Marshall McLuhan's media culture theory and social construction ideology. It is possible to find a new media group that can convey ‘Visual Culture Art Education’ around the National Taipei University of Technology in this commercial district that combines intelligent technology, fashion, media, entertainment, art education, and marketing network. Let the imagination and innovation of ‘New Media Art Village’ become ‘implementable’ and new media Heterotopia of inter-subjectivity with the engagement of big data and digital media. Visual culture art education will also bring aesthetics into the community by New Media Art Village.

Keywords: social construction, heterogeneity, new media, big data, visual culture art education

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Authors: Mhaned Oubounyt, Jan Baumbach

Abstract:

Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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