Search results for: graph operations

Authors: Mujahid Muhammad, Paul Kearney, Adel Aneiba

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The ability for vehicles to communicate with other vehicles (V2V), the physical (V2I) and network (V2N) infrastructures, pedestrians (V2P), etc. – collectively known as V2X (Vehicle to Everything) – will enable a broad and growing set of applications and services within the intelligent transport domain for improving road safety, alleviate traffic congestion and support autonomous driving. The telecommunication research and industry communities and standardization bodies (notably 3GPP) has finally approved in Release 14, cellular communications connectivity to support V2X communication (known as LTE – V2X). LTE – V2X system will combine simultaneous connectivity across existing LTE network infrastructures via LTE-Uu interface and direct device-to-device (D2D) communications. In order for V2X services to function effectively, a robust security mechanism is needed to ensure legal and safe interaction among authenticated V2X entities in the LTE-based V2X architecture. The characteristics of vehicular networks, and the nature of most V2X applications, which involve human safety makes it significant to protect V2X messages from attacks that can result in catastrophically wrong decisions/actions include ones affecting road safety. Attack vectors include impersonation attacks, modification, masquerading, replay, MiM attacks, and Sybil attacks. In this paper, we focus our attention on LTE-based V2X security and access control mechanisms. The current LTE-A security framework provides its own access authentication scheme, the AKA protocol for mutual authentication and other essential cryptographic operations between UEs and the network. V2N systems can leverage this protocol to achieve mutual authentication between vehicles and the mobile core network. However, this protocol experiences technical challenges, such as high signaling overhead, lack of synchronization, handover delay and potential control plane signaling overloads, as well as privacy preservation issues, which cannot satisfy the adequate security requirements for majority of LTE-based V2X services. This paper examines these challenges and points to possible ways by which they can be addressed. One possible solution, is the implementation of the distributed peer-to-peer LTE security mechanism based on the Bitcoin/Namecoin framework, to allow for security operations with minimal overhead cost, which is desirable for V2X services. The proposed architecture can ensure fast, secure and robust V2X services under LTE network while meeting V2X security requirements.

Keywords: authentication, long term evolution, security, vehicle-to-everything

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Authors: Bashiru Abdullahi, Isah Bala Yabo, Ibrahim Yakubu Seini

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In this paper, the steady/transient MHD heat transfer within radiative porous channel due to convective boundary conditions is considered. The solution of the steady-state and that of the transient version were conveyed by Perturbation and Finite difference methods respectively. The heat transfer mechanism of the present work ascertains the influence of Biot number〖(B〗_i1), magnetizing parameter (M), radiation parameter(R), temperature difference, suction/injection(S) Grashof number (Gr) and time (t) on velocity (u), temperature(θ), skin friction(τ), and Nusselt number (Nu). The results established were discussed with the help of a line graph. It was found that the velocity, temperature, and skin friction decay with increasing suction/injection and magnetizing parameters while the Nusselt number upsurges with suction/injection at y = 0 and falls at y =1. The steady-state solution was in perfect agreement with the transient version for a significant value of time t. It is interesting to report that the Biot number has a cogent influence consequently, as its values upsurge the result of the present work slant the extended literature.

Keywords: heat transfer, thermal radiation, porous channel, MHD, transient, convective boundary condition

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Authors: Lamia Bouzgarrou, Amira Omrane, Haithem Kalel, Salma Kammoun

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Background: During recent decades, mechanical and electrical industrial sector has greatly expanded with a significant employability potential. However, this sector faces the increasing prevalence of musculoskeletal disorders with heavy consequences associated with direct and indirect costs. Objective: The current intervention was motivated by large musculoskeletal upper limbs and back disorders frequency among the operators of an assembly workshop in a leader company specialized in sanitary equipment and water and gas connections. We aimed to identify biomechanical constraints among these operators through activity and biomechanical exposures semi-quantitative analysis based on video recordings and MUSKA-TMS software. Methods: We conducted, open observations and exploratory interviews at first, in order to overall understand work situation. Then, we analyzed operator’s activity through systematic observations and interviews. Finally, we conducted a semi-quantitative biomechanical constraints analysis with MUSKA-TMS software after representative activity period video recording. The assessment of biomechanical constrains was based on different criteria; biomechanical characteristics (work positions), aggravating factor (cold, vibration, stress, etc.) and exposure time (duration and frequency of solicitations, recovery phase); with a synthetic score of risk level variable from 1 to 4 (1: low risk of developing MSD and 4: high risk). Results: Semi-quantitative analysis objective many elementary operations with higher biomechanical constrains like high repetitiveness, insufficient recovery time and constraining angulation of shoulders, wrists and cervical spine. Among these risky elementary operations we sited the assembly of sleeve with the body, the assembly of axis, and the control on testing table of gas valves. Transformation of work situations were recommended, covering both the redevelopment of industrial areas and the integration of new tools and equipment of mechanical handling that reduces operator exposure to vibration. Conclusion: Musculoskeletal disorders are complex and costly disorders. Moreover, an approach centered on the observation of the work can promote the interdisciplinary dialogue and exchange between actors with the objective to maximize the performance of a company and improve the quality of life of operators.

Keywords: musculoskeletal disorders, biomechanical constrains, semi-quantitative analysis, ergonomics

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Authors: T. Rajamäki

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In clean room environment molecular contamination in very small concentrations can cause significant harm for the components and processes. This is commonly referred as airborne molecular contamination (AMC). There is a shortage of high sensitivity continuous measurement data for existence and behavior of several of these contaminants. Accordingly, in most cases correlation between concentration of harmful molecules and their effect on processes is not known. In addition, the formation and distribution of contaminating molecules are unclear. In this work sensitive optical techniques are applied in clean room facilities for investigation of concentrations, forming mechanisms and effects of contaminating molecules. Special emphasis is on reactive acid and base gases ammonia (NH3) and hydrogen fluoride (HF). They are the key chemicals in several operations taking place in clean room processes.

Keywords: AMC, clean room, concentration, reactive gas

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Authors: I. McAndrew, K. L. Witcher, E. Navarro

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This paper presents the theory and application of low speed flight for unmanned aerial vehicles when subjected to surface environmental conditions such as ice on the leading edge and upper surface. A model was developed and tested in a wind tunnel to see how theory compares with practice at various speed including take-off, landing and operational applications where head winds substantially alter parameters. Furthermore, a comparison is drawn with maned operations and how that this subject is currently under supported with accurate theory or knowledge for designers or operators to make informed decision or accommodate individual applications. The effects of ice formation for lift and drag are determined for a range of different angles of attacks.

Keywords: aerodynamics, low speed flight, unmanned vehicles, environmental influences

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Authors: Zeinab. Shahrokhifar, Abolfazl Meshkini, Seyed Ali. Alavi

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Considering the different dimensions of deprivation, housing supply is noted as a basic requirement in Iran after 1979 (coming to work of the new government). The government had built the constitution and obliged to meet this need in the form of five-year development programs in Iran’s provinces. This study focused on the adaptive analysis of housing policies in these five development programs in Kermanshah province located in western Iran. Our research is divided into two different analytical sections. In the first section, we collected the documentary information using approved plans and field studies. In the second section, a questionnaire was prepared and designed for the elite community (30) to support the documentary analysis. The results showed that various projects adopted in the form of strategic plans and implemented the policies included both quantitative and qualitative housing in Kermanshah province after 1979. The quality of housing, from the first to the fifth development plans has improved the situation in the housing indicators. The quantity of housing units for households has also been implemented through various policies that has desired results. The sequences of housing policies and plans do not overlap in the five development programs. According to the radar graph, the development programs overlapped in some policies, which shows the continuation of the previous policies, but this overlap is not perfect.

Keywords: law enforcement policy, housing policy, development programs, housing indicators, the city of Kermanshah

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Authors: Safiyya A. Abba, Shehu U. R. Aliyu

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This paper deals with Islamic social security: a discourse explores the meaning and nature of Islamic social security system. The paper reviews the social security framework and operations during the early period. The paper further identifies the instruments of Islamic social security discusses its principles and objectives. The paper discovers that Islamic social security is a personification of a comprehensive welfare approach in view of its varied instruments that are deeply rooted in the Islamic law, unique principles and realistic and achievable objectives. Furthermore, the Islamic social security system has far reaching socioeconomic implications; social justice, cohesion, equity, a catalyst for poverty eradication, income redistribution, economic growth and development.

Keywords: Islamic social security, basic needs, zakat, socioeconomic justice, equity

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Authors: Khan Md. Abdus Subhan, Rabeya Bushra

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The management of Intellectual Property (IP) in museums can be complex and challenging, as it requires balancing access and control. On the one hand, museums must ensure that they have balanced permissions to display works in their collections and make them accessible to the public. On the other hand, they must also protect the rights of creators and owners of works and ensure that they are not infringing on IP rights. Intellectual property has become an increasingly important aspect of museum operations in the digital age. Museums hold a vast array of cultural assets in their collections, many of which have significant value as IP assets. The balanced management of IP in museums can help generate additional revenue and promote cultural heritage while also protecting the rights of the museum and its collections. Digital technologies have greatly impacted the way museums manage IP, providing new opportunities for revenue generation through e-commerce and licensing while also presenting new challenges related to IP protection and management. Museums must take a comprehensive approach to IP management, leveraging digital technologies, protecting IP rights, and engaging in licensing and e-commerce activities to maximize income and the economy of countries through the strong management of cultural institutions. Overall, the balanced management of IP in museums is crucial for ensuring the sustainability of museum operations and for preserving cultural heritage for future generations. By taking a balanced approach to identifying museum IP assets, museums can generate revenues and secure their financial sustainability to ensure the long-term preservation of their cultural heritage. We can divide IP assets in museums into two kinds: collection IP and museum-generated IP. Certain museums become confused and lose sight of their mission when trying to leverage collections-based IP. This was the case at the German State Museum in Berlin when the museum made 100 replicas from the Nefertiti bust and wrote under the replicas all rights reserved to the Berlin Museum and issued a certificate to prevent any person or Institution from reproducing any replica from this bust. The implications of IP in museums are far-reaching and can have significant impacts on the preservation of cultural heritage, the dissemination of information, and the development of educational programs. As such, it is important for museums to have a comprehensive understanding of IP laws and regulations and to properly manage IP to avoid legal liability, damage to reputation, and loss of revenue. The research aims to highlight the importance and role of intellectual property in museums and provide some illustrative examples of this.

Keywords: zakat, economic development, Muslim world, poverty alleviation.

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Authors: Antti Lanki, Justiina Halonen, Juuso Punnonen, Emmi Rantavuo

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Marine oil spill response operation requires extensive vessel maneuvering and navigation skills. At-sea oil containment and recovery include both single vessel and multi-vessel operations. Towing long oil containment booms that are several hundreds of meters in length, is a challenge in itself. Boom deployment and towing in multi-vessel configurations is an added challenge that requires precise coordination and control of the vessels. Efficient communication, as a prerequisite for shared situational awareness, is needed in order to execute the response task effectively. To gain and maintain adequate maritime skills, practical training is needed. Field exercises are the most effective way of learning, but especially the related vessel operations are resource-intensive and costly. Field exercises may also be affected by environmental limitations such as high sea-state or other adverse weather conditions. In Finland, the seasonal ice-coverage also limits the training period to summer seasons only. In addition, environmental sensitiveness of the sea area restricts the use of real oil or other target substances. This paper examines, whether maritime simulator training can offer a complementary method to overcome the training challenges related to field exercises. The objective is to assess the efficiency and the learning impact of simulator training, and the specific skills that can be trained most effectively in simulators. This paper provides an overview of learning results from two oil spill response pilot courses, in which maritime navigational bridge simulators were used to train the oil spill response authorities. The simulators were equipped with an oil spill functionality module. The courses were targeted at coastal Fire and Rescue Services responsible for near shore oil spill response in Finland. The competence levels of the participants were surveyed before and after the course in order to measure potential shifts in competencies due to the simulator training. In addition to the quantitative analysis, the efficiency of the simulator training is evaluated qualitatively through feedback from the participants. The results indicate that simulator training is a valid and effective method for developing marine oil spill response competencies that complement traditional field exercises. Simulator training provides a safe environment for assessing various oil containment and recovery tactics. One of the main benefits of the simulator training was found to be the immediate feedback the spill modelling software provides on the oil spill behaviour as a reaction to response measures.

Keywords: maritime training, oil spill response, simulation, vessel manoeuvring

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Authors: Min Kyung An

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In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

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Authors: Ahmed Al-Adaileh

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Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

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Authors: Steffen Schieweck, Johannes Dregger, Sascha Kaczmarek, Michael ten Hompel

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Logistics distributors face the issue of having to provide increasing service levels while being forced to reduce costs at the same time. Same-day delivery, quick order processing and rapidly growing ranges of articles are only some of the prevailing challenges. One key aspect of the performance of an intra-logistics system is how often and in which amplitude congestions and dysfunctions affect the processing operations. By gaining knowledge of the so called ‘performance availability’ of such a system during the planning stage, oversizing and wasting can be reduced whereas planning transparency is increased. State of the art for the determination of this KPI are simulation studies. However, their structure and therefore their results may vary unforeseeably. This article proposes a concept for the establishment of ‘certified’ and hence reliable and comparable simulation models.

Keywords: intra-logistics, performance availability, simulation, warehousing

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Authors: Henok Mezemr Besfat, Haftom Gebreslassie Gebregwergs

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wireless network is one of the most important mediums of transmission of information from one device to another devices. Wireless communication has a broad range of applications, including mobile communications through cell phones and satellites, Internet of Things (IoT) connecting several devices, wireless sensor networks for traffic management and environmental monitoring, satellite communication for weather forecasting and TV without requiring any cable or wire or other electronic conductors, by using electromagnetic waves like IR, RF, satellite, etc. This paper summarizes different wireless network technologies, applications of different wireless technologies and different types of wireless networks. Generally, wireless technology will further enhance operations and experiences across sectors with continued innovation. This paper suggests different strategies that can improve wireless networks and technologies.

Keywords: wireless senser, wireless technology, wireless network, internet of things

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Authors: Pradyumna Mohanty

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The paper aims to explore whether accounting information of Indian companies in the Steel sector are value relevant or not. Ohlson’s model which usually takes into consideration book value per share (BV) and earnings per share (EARN) has been used and the same has been expanded to include two more variables such as cash flow from operations (CFO) and return on equity (ROE). The data were collected from CMIE-Prowess data base in respect of BSE-listed steel companies and the time frame spans from 2010 to 2014. OLS regression has been used to test the value relevance of these accounting numbers. Results indicate that both CFO and BV are having significant influence on the stock price in two out of five years of study. But, BV is emerging as the most significant and highly value relevant of all the four variables during the entire period of study.

Keywords: value relevance, accounting information, book value per share, earnings per share

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Authors: Mehmet Savsar

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This paper presents a practical case application of simulation modeling and analysis in a specific industrial setting. Various maintenance related parameters of the equipment in the system under consideration are determined and a simulation model is developed to study system behavior. System performance is determined based on established parameters and operational policies, which included system operation with and without preventive maintenance implementation. The results show that preventive maintenance practice has significant effects on improving system productivity. The simulation procedures outlined in this paper can be used by operation managers to perform production line analysis under different maintenance policies in various industrial settings.

Keywords: simulation, production line, machine failures, maintenance, industrial bakery

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Authors: Zhao Xueran, Yang Dong

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In order to improve the problem that old wells in oilfields are shut down due to low oil recovery, sidetracking has become one of the main technical means to restore the vitality of old wells. A variety of sidetracking technologies have been researched and formed internationally. Among them, coiled tubing sidetracking horizontal wells have significant advantages over conventional sidetracking methods: underbalanced pressure operations; reducing the number of trips of tubing, while drilling and production, saving construction costs, less ground equipment and less floor space, orienter guidance to reduce drilling friction, etc. This paper mainly introduces the steering technology in coiled tubing intelligent sidetracking at home and abroad, including the orienter and the rotary steerable system.

Keywords: sidetracking, coiled tubing, orienter, rotary steering system

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Authors: Susana Marques

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Research on how store environment cues influence consumers’ store choice decision criteria, such as store operations, product quality, monetary price, store image and sales promotion, is sparse. Especially absent research on the simultaneous impact of multiple store environment cues. The authors propose a comprehensive store choice model that includes: three types of store environment cues as exogenous constructs; various store choice criteria as possible mediating constructs, and store patronage intentions as an endogenous construct. On the basis of testing with a sample of 561 customers of hypermarkets, the model is partially supported. This study used structural equation modelling to test the proposed model.

Keywords: store choice, store patronage, structural equation modelling, retailing

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Authors: Shih-Chieh Liao, Cheng-Yan Shuai

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The feature of a side-scrolling shooting game is facing the surrounding enemy and barraging in entire screen. The player will be in trouble when they are trying to do complicated operations because of the physical and system limitations of the joystick in the games. This study designed the prototype of a new type of arcade stick by focus group and assessed by the expert. By filtering the most representative, and build up the control system for the arcade stick, and testing time and bullets consumed in two experiments, try to prove it works in the game. Finally, the prototype of L-1 solves the dilemma of scroll shooting games when the player uses the arcade stick and improves the function of the arcade stick.

Keywords: arcade stick, joystick, user interface, 2D STG

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Authors: Elisa Pautasso, Matteo Castagno, Michele Osella

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In the last decade, the emergence of new social needs as an effect of the economic crisis has stimulated the flourishing of business endeavours characterised by explicit social goals. Social start-ups, social enterprises or Corporate Social Responsibility operations carried out by traditional companies are quintessential examples in this regard. This paper analyses these kinds of initiatives in order to discover the main characteristics of social business models and to provide insights to social entrepreneurs for developing or improving their strategies. The research is conducted through the integration of literature review and case study analysis and, thanks to the recognition of the importance of both profits and social impacts as the key success factors for a social business model, proposes a framework for identifying indicators suitable for measuring the social impacts generated.

Keywords: business model, case study, impacts, social business

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Authors: M. Hemnath, S. Kannan, R. Kiran, K. Thanigaivelu

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This paper is based on exploring the possible opportunities and applications using Power Line Communication (PLC) for security and surveillance operations. Various research works are done for introducing PLC into onboard vehicle communication and networking (CAN, LIN etc.) and various international standards have been developed. Wireless power transfer (WPT) is also an emerging technology which is studied and tested for recharging purposes. In this work we present a system which embeds the detection and the response into one which eliminates the need for dedicated network for data transmission. Also we check the feasibility for integrating wireless power transfer system into this proposed security system for transmission of power to detection unit wirelessly from the response unit.

Keywords: power line communication, wireless power transfer, surveillance

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Authors: Mohammed Kafaji

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This paper aims to investigate the influence of quality of education and quality of research, provided by local educational institutions, on the adoption of Information and Communication Technology (ICT) in managing business operations for companies in Saudi market. A model was developed and tested using data collected from 138 CEO’s of foreign companies in diverse business sectors. The data is analysed and managed using multivariate approaches through standard statistical packages. The results showed that educational quality has little contribution to the ICT adoption while research quality seems to play a more prominent role. These results are analysed in terms of business environment and market constraints and further extended to the perceived effectiveness of applied pedagogical approaches in schools and universities.

Keywords: quality of education, quality of research, mediation, domestic competition, ICT adoption

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Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

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Authors: Athena Nguyen, Rojin Belganeh

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Detecting and identifying differences in like polymer materials are key factors in deformulation, comparative analysis as well as reverse engineering. Pyrolysis-GC/MS is an easy solid sample introduction technique which expands the application areas of gas chromatography and mass spectrometry. The Micro-furnace pyrolyzer is directly interfaced with the GC injector preventing any potential of cold spot, carryover, and cross contamination. This presentation demonstrates the study of two similar polymers by performing different mode of operations in the same system: Evolve gas analysis (EGA), Flash pyrolysis, Thermal desorption analysis, and Heart-cutting analysis. Unknown polymer materials and their chemical compositions are identified.

Keywords: gas chromatography/mass spectrometry, pyrolysis, pyrolyzer, thermal desorption-GC/MS

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Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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Authors: Gyula Fülöp, Bettina Hernádi

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This paper deals with the current strategic challenges related to the reshaping of the basic conditions of corporate operations. With the help of the experimental analysis of some domestic corporations, it presents the form and extent the Hungarian corporations are prepared for the current strategic challenges. The study examines how strategic directions and answer opportunities changed in the following interrelated areas in the past five years: economic globalization, corporate sustainability, IT applications, labour force diversity and ethical competences. The conclusions of the empirical survey give a reliable basis for economic organizations and enterprises to formulate their strategy.

Keywords: economic globalization, corporate sustainability, IT applications, labour force diversity, ethical competences

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Authors: P. O. Ughachukwu, P. O. Okonkwo, P. C. Unekwe, J. O. Ogamba

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Background: The prevalence of hepatitis B viral infection is high worldwide with liver cirrhosis and hepatocellular carcinoma as important complications. Cases of poor antibody response to hepatitis B vaccination abound. Immunosuppression, especially from glucocorticoids, is often cited as a cause of poor antibody response and there are documented evidences of irrational administration of glucocorticoids to children and adults. The study was, therefore, designed to find out if administration of glucocorticoids affects immune response to vaccination against hepatitis B in mice. Methods: Mice of both sexes were randomly divided into 2 groups. Daily intramuscular methylprednisolone injections, (15 mg kg-1), were given to the test group while sterile deionized water (0.1ml) was given to control mice for 30 days. On day 6 all mice were given 2 μg (0.1ml) hepatitis B vaccine and a booster dose on day 27. On day 34, blood samples were collected and analyzed for anti-HBs titres using enzyme-linked immunosorbent assay (ELISA). Statistical analysis was done using Graph Pad Prism 5.0 and the results taken as statistically significant at p value < 0.05. Results: There were positive serum anti-HBs responses in all mice groups but the differences in titres were not statistically significant. Conclusions: At the dosages and length of exposure used in this study, methylprednisolone injection did not significantly inhibit anti-HBs response in mice following immunization against hepatitis B virus. By extrapolation, methylprednisolone, when used in the usual clinical doses and duration of therapy, is not likely to inhibit immune response to hepatitis B vaccinations in man.

Keywords: anti-HBs, hepatitis B vaccine, immune response, methylprednisolone, mice

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Authors: Kartik Mahajan

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DevOps methodologies streamline software development and operations, promoting collaboration and automation. Traditional server management often relies on manual, repetitive tasks, leading to inefficiencies, potential errors, and increased operational costs. Ansible, as a configuration management tool, presents a compelling solution for automating infrastructure management processes. This review paper explores the implementation and testing of Ansible for server management, specifically focusing on automated user account configuration. By replacing manual procedures with Ansible playbooks, we aim to optimize server management, reduce human error, and potentially mitigate operational expenses. This study offers insights into Ansible’s efficacy within a DevOps context, highlighting its potential to transform server administration practices.

Keywords: cloud, Devops, automation, ansible

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Authors: Ashis Pradhan, Mohan P. Pradhan

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Pattern Matching is useful for recognizing character in a digital image. OCR is one such technique which reads character from a digital image and recognizes them. Line segmentation is initially used for identifying character in an image and later refined by morphological operations like binarization, erosion, thinning, etc. The work discusses a recognition technique that defines a set of morphological operators based on its orientation in a character. These operators are further categorized into groups having similar shape but different orientation for efficient utilization of memory. Finally the characters are recognized in accordance with the occurrence of frequency in hierarchy of significant pattern of those morphological operators and by comparing them with the existing database of each character.

Keywords: binary image, morphological patterns, frequency count, priority, reduction data set and recognition

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