Search results for: capabilities

Authors: E. Farg, M. M. El-Sharkawy, M. S. Mostafa, S. M. Arafat

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Mapping water stress provides important baseline data for sustainable agriculture. Recent developments in the new Sentinel-1 data which allow the acquisition of high resolution images and varied polarization capabilities. This study was conducted to detect and quantify vegetation water content from canopy backscatter for extracting spatial information to encourage drought mapping activities throughout new reclaimed sandy soils in western Nile delta, Egypt. The performance of radar imagery in agriculture strongly depends on the sensor polarization capability. The dual mode capabilities of Sentinel-1 improve the ability to detect water stress and the backscatter from the structure components improves the identification and separation of vegetation types with various canopy structures from other features. The fieldwork data allowed identifying of water stress zones based on land cover structure; those classes were used for producing harmonious water stress map. The used analysis techniques and results show high capability of active sensors data in water stress mapping and monitoring especially when integrated with multi-spectral medium resolution images. Also sub soil drip irrigation systems cropped areas have lower drought and water stress than center pivot sprinkler irrigation systems. That refers to high level of evaporation from soil surface in initial growth stages. Results show that high relationship between vegetation indices such as Normalized Difference Vegetation Index NDVI the observed radar backscattering. In addition to observational evidence showed that the radar backscatter is highly sensitive to vegetation water stress, and essentially potential to monitor and detect vegetative cover drought.

Keywords: canopy backscatter, drought, polarization, NDVI

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Authors: Iruka C. Anugwo, Winston M. Shakantu

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The objective of this study is to uncover the basic business-forces that necessitated the survival and sustainable performance of the medium scale contractors in the South African construction market. This study is essential as it set to contribute towards long-term strategic solutions for combating the incessant failure of start-ups construction organizations within South African. The study used a qualitative research methodology; as the most appropriate approach to elicit and understand, and uncover the phenomena that are basic business-forces for the active contractors in the market. The study also adopted a phenomenological study approach; and in-depth interviews were conducted with 20 medium scale contractors in Port Elizabeth, South Africa, between months of August to October 2015. This allowed for an in-depth understanding of the critical and basic business-forces that influenced their survival and performance beyond the first five years of business operation. Findings of the study showed that for potential contractors (startups), to survival in the competitive business environment such as construction industry, they must possess the basic business-forces. These forces are educational knowledge in construction and business management related disciplines, adequate industrial experiences, competencies and capabilities to delivery excellent services and products as well as embracing the spirit of entrepreneurship. Convincingly, it can be concluded that the strategic approach to minimize the endless failure of startups construction businesses; the potential construction contractors must endeavoring to access and acquire the basic educationally knowledge, training and qualification; need to acquire industrial experiences in collaboration with required competencies, capabilities and entrepreneurship acumen. Without these basic business-forces as been discovered in this study, the majority of the contractors gaining entrance in the market will find it difficult to develop and grow a competitive and sustainable construction organization in South Africa.

Keywords: basic business-forces, medium scale contractors, South Africa, sustainable organisations

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Eric Pla Erra, Mariana Jimenez Martinez

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While aggregated loads at a community level tend to be easier to predict, individual household load forecasting present more challenges with higher volatility and uncertainty. Furthermore, the drastic changes that our behavior patterns have suffered due to the COVID-19 pandemic have modified our daily electrical consumption curves and, therefore, further complicated the forecasting methods used to predict short-term electric load. Load forecasting is vital for the smooth and optimized planning and operation of our electric grids, but it also plays a crucial role for individual domestic consumers that rely on a HEMS (Home Energy Management Systems) to optimize their energy usage through self-generation, storage, or smart appliances management. An accurate forecasting leads to higher energy savings and overall energy efficiency of the household when paired with a proper HEMS. In order to study how COVID-19 has affected the accuracy of forecasting methods, an evaluation of the performance of a state-of-the-art LGBM (Light Gradient Boosting Model) will be conducted during the transition between pre-pandemic and lockdowns periods, considering day-ahead electric load forecasting. LGBM improves the capabilities of standard Decision Tree models in both speed and reduction of memory consumption, but it still offers a high accuracy. Even though LGBM has complex non-linear modelling capabilities, it has proven to be a competitive method under challenging forecasting scenarios such as short series, heterogeneous series, or data patterns with minimal prior knowledge. An adaptation of the LGBM model – called “resilient LGBM” – will be also tested, incorporating a concept drift detection technique for time series analysis, with the purpose to evaluate its capabilities to improve the model’s accuracy during extreme events such as COVID-19 lockdowns. The results for the LGBM and resilient LGBM will be compared using standard RMSE (Root Mean Squared Error) as the main performance metric. The models’ performance will be evaluated over a set of real households’ hourly electricity consumption data measured before and during the COVID-19 pandemic. All households are located in the city of Barcelona, Spain, and present different consumption profiles. This study is carried out under the ComMit-20 project, financed by AGAUR (Agència de Gestiód’AjutsUniversitaris), which aims to determine the short and long-term impacts of the COVID-19 pandemic on building energy consumption, incrementing the resilience of electrical systems through the use of tools such as HEMS and artificial intelligence.

Keywords: concept drift, forecasting, home energy management system (HEMS), light gradient boosting model (LGBM)

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Authors: Negin Mohammadrezaee Larki

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Cloud Computing is a popular solution that has been used in recent years to cooperate and collaborate among distributed applications over networks. Moving successfully into cloud computing requires an architecture that will support the new cloud capabilities. Many business leaders and analysts agree that moving to cloud requires having a solid, service-oriented architecture to provide the infrastructure needed for successful cloud implementation.

Keywords: Service Oriented Architecture (SOA), Service Oriented Cloud Computing Architecture (SOCCA), cloud computing, cloud computing architecture

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Authors: Bolatbek Rysbaiuly, Aliya S. Azhibekova

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Problems concerning the interpretation of the well testing results belong to the class of inverse problems of subsurface hydromechanics. The distinctive feature of such problems is that additional information is depending on the capabilities of oilfield experiments. Another factor that should not be overlooked is the existence of errors in the test data. To determine reservoir properties, some inverse problems for parabolic equations were investigated. An approach to solving the inverse problems based on the method of regularization is proposed.

Keywords: iterative approach, inverse problem, parabolic equation, reservoir properties

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Authors: Shanorfizah Mohd Safar, Shaizatulaqma Kamalul Ariffin

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Internationalization of halal small and medium-sized enterprises (SMEs) is necessary for SMEs to become more involved in regional trade and business cooperation. By internationalization, SMEs' profit can increase, and market expansion of SMEs is basic for rising economies of countries to contend all around in the halal industry globally. There are several modes of internationalization; exporting is one of the first steps for internationalization with less capital needed. The study examines the influential factors of export performance amongst halal SMEs in Malaysia. Specifically, this study examines the positive and significant relationships amongst human capital, managerial capability, Halal Assurance Management System (HAMS), digital transformation, government support, and networking capability on halal SMEs' export performance toward SMEs' competitive advantage. In addition, this study will examine innovation capabilities as a moderator in the relationship between independence variables and competitive advantage. Competitive advantage is the most compelling perspective that drives the export performance of halal SMEs in Malaysia. A quantitative method will be used: an online questionnaire survey distributed through emails and face-to-face toward selected halal-certificated SMEs registered in JAKIM, MATRADE website and SME Corp Malaysia website. Nevertheless, whether the halal SMEs practice global business, they will still be the potential respondents. The data were examined and obtained using the statistical software Smart PLS. The analysis used is reliability, correlation, and regression analysis to meet the research objectives. This study contributes significantly to the theory by integrating Resource Based View (RBV) theory, Technology–Organization–Environment (TOE) framework and Networking theory. In addition, this research extends the RBV by extending a variable, the Halal Assurance Management System. This study also examines a moderating role of innovation capabilities in the framework and competitive advantage as a mediator. This research aims to analyze the factors that will impact the internationalization of halal SMEs.

Keywords: internationalization, halal SMEs, competitive advantage, export performance

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Authors: Ashhar Ahmed Shaikh, Ayush Tandon

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The swift reduction of fossil fuels from nature has crucial need for alternative energy sources to cater vital demand. It is essential to boost alternative energy sources to cover the continuously increasing demand for energy while minimizing the negative environmental impacts. Solar energy is one of the reliable sources that can generate energy. Solar energy is freely available in nature and is completely eco-friendly, and they are considered as the most promising power generating sources due to their easy availability and other advantages for the local power generation. This paper is to review the implementation of power electronic devices through Solar Energy Grid Integration System (SEGIS) to increase the efficiency. This paper will also concentrate on the future grid infrastructure and various other applications in order to make the grid smart. Development and implementation of a power electronic devices such as PV inverters and power controllers play an important role in power supply in the modern energy economy. Solar Energy Grid Integration System (SEGIS) opens pathways for promising solutions for new electronic and electrical components such as advanced innovative inverter/controller topologies and their functions, economical energy management systems, innovative energy storage systems with equipped advanced control algorithms, advanced maximum-power-point tracking (MPPT) suited for all PV technologies, protocols and the associated communications. In addition to advanced grid interconnection capabilities and features, the new hardware design results in small size, less maintenance, and higher reliability. The SEGIS systems will make the 'advanced integrated system' and 'smart grid' evolutionary processes to run in a better way. Since the last few years, there was a major development in the field of power electronics which led to more efficient systems and reduction of the cost per Kilo-watt. The inverters became more efficient and had reached efficiencies in excess of 98%, and commercial solar modules have reached almost 21% efficiency.

Keywords: solar energy grid integration systems, smart grid, advanced integrated system, power electronics

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Authors: Savvas Rogotis, Nikolaos Kalatzis, Stergios Dimou-Sakellariou, Nikolaos Marianos

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As precision holds the key for the introduction of distinct benefits in agriculture (e.g., energy savings, reduced labor costs, optimal application of inputs, improved products, and yields), it steadily becomes evident that new initiatives should focus on rendering Precision Agriculture (PA) more accessible to the average farmer. PA leverages on technologies such as the Internet of Things (IoT), earth observation, robotics and positioning systems (e.g., the Global Navigation Satellite System – GNSS - as well as individual positioning systems like GPS, Glonass, Galileo) that allow: from simple data georeferencing to optimal navigation of agricultural machinery to even more complex tasks like Variable Rate Applications. An identified customer pain point is that, from one hand, typical triangulation-based positioning systems are not accurate enough (with errors up to several meters), while on the other hand, high precision positioning systems reaching centimeter-level accuracy, are very costly (up to thousands of euros). Within this paper, a Ground-Based Augmentation System (GBAS) is introduced, that can be adapted to any existing IoT field-sensing station infrastructure. The latter should cover a minimum set of requirements, and in particular, each station should operate as a fixed, obstruction-free towards the sky, energy supplying unit. Station augmentation will allow them to function in pairs with GNSS rovers following the differential GNSS base-rover paradigm. This constitutes a key innovation element for the proposed solution that encompasses differential GNSS capabilities into an IoT field-sensing infrastructure. Integrating this kind of information supports the provision of several additional PA beneficial services such as spatial mapping, route planning, and automatic field navigation of unmanned vehicles (UVs). Right at the heart of the designed system, there is a high-end GNSS toolkit with base-rover variants and Real-Time Kinematic (RTK) capabilities. The GNSS toolkit had to tackle all availability, performance, interfacing, and energy-related challenges that are faced for a real-time, low-power, and reliable in the field operation. Specifically, in terms of performance, preliminary findings exhibit a high rover positioning precision that can even reach less than 10-centimeters. As this precision is propagated to the full dataset collection, it enables tractors, UVs, Android-powered devices, and measuring units to deal with challenging real-world scenarios. The system is validated with the help of Gaiatrons, a mature network of agro-climatic telemetry stations with presence all over Greece and beyond ( > 60.000ha of agricultural land covered) that constitutes part of “gaiasense” (www.gaiasense.gr) smart farming (SF) solution. Gaiatrons constantly monitor atmospheric and soil parameters, thus, providing exact fit to operational requirements asked from modern SF infrastructures. Gaiatrons are ultra-low-cost, compact, and energy-autonomous stations with a modular design that enables the integration of advanced GNSS base station capabilities on top of them. A set of demanding pilot demonstrations has been initiated in Stimagka, Greece, an area with a diverse geomorphological landscape where grape cultivation is particularly popular. Pilot demonstrations are in the course of validating the preliminary system findings in its intended environment, tackle all technical challenges, and effectively highlight the added-value offered by the system in action.

Keywords: GNSS, GBAS, precision agriculture, RTK, smart farming

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Authors: Narissa Lewis, Susan Geertshuis

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The global and national employability agenda is changing the higher education landscape as academic staff are faced with the responsibility of developing employability capabilities and attributes in addition to delivering discipline specific content and skills. They realise that the shift towards teaching sustainable capabilities means a shift in the way they teach. But what that shift should be or how they should bring it about is unclear. As part of a national funded project, representatives from several New Zealand (NZ) higher education institutions and the NZ Association of Graduate Employers partnered to discover, trial and disseminate means of embedding employability in the curriculum. Findings from four focus groups (n=~75) and individual interviews (n=20) with staff from several NZ higher education institutions identified factors that enable or hinder embedded employability development within their respective institutions. Participants believed that higher education institutions have a key role in developing graduates for successful lives and careers however this requires a significant shift in culture within their respective institutions. Participants cited three main barriers: lack of strategic direction, support and guidance; lack of understanding and awareness of employability; and lack of resourcing and staff capability. Without adequate understanding and awareness of employability, participants believed it is difficult to understand what employability is let alone how it can be embedded in the curriculum. This presentation will describe some of the impacts that the employability agenda has on staff as they try to move from traditional to contemporary forms of teaching to develop employability attributes of students. Changes at the institutional level are required to support contemporary forms of teaching, however this is often beyond the sphere of influence at the teaching staff level. The study identified that small changes to teaching practices were necessary and a simple model to facilitate change from traditional to contemporary forms of teaching was developed. The model provides a framework to identify small but impactful teaching practices and exemplar teaching practices were identified. These practices were evaluated for transferability into other contexts to encourage small but impactful changes to embed employability in the curriculum.

Keywords: curriculum design, change management, employability, teaching exemplars

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Authors: Si-Jie Ji, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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With the rapid development of industrialization and urbanization, air pollution poses significant global environmental challenges, contributing to acid rain, global warming, and adverse health effects. Therefore, it is necessary to monitor the concentration of toxic gases in the atmospheric environment in real-time and to deploy cost-effective gas sensors capable of detecting their emissions. In this study, we systematically investigated the sensing capabilities of the two-dimensional MoSe₂ for seven key environmental gases (NO, NO₂, CO, CO₂, SO₂, SO₃, and O₂) using density functional theory (DFT) and non-equilibrium Green’s function (NEGF) calculations. We also investigated the impact of H₂O as an interfering gas. Our results indicate that the MoSe₂ monolayer is thermodynamically stable and exhibits strong gas-sensing capabilities. The calculated adsorption energies indicate that these gases can stably adsorb on MoSe₂, with SO₃ exhibiting the strongest adsorption energy (-0.63 eV). Electronic structure analysis, including projected density of states (PDOS) and Bader charge analysis, demonstrates significant changes in the electronic properties of MoSe₂ upon gas adsorption, affecting its conductivity and sensing performance. We find that oxygen (O₂) adsorption notably influenced the deformation of MoSe₂. To comprehensively understand the potential of MoSe₂ as a gas sensor, we used the NEGF method to assess the electronic transport properties of MoSe₂ under gas adsorption, evaluating current-voltage (I-V), resistance-voltage (R-V) characteristics, and transmission spectra to determine sensitivity, selectivity, and recovery time compared to pristine MoSe₂. Sensitivity, selectivity, and recovery time are analyzed at a bias voltage of 1.7V, showing excellent performance of MoSe₂ in detecting SO₃, among other gases. The pronounced changes in electronic transport behavior induced by SO₃ adsorption confirm MoSe₂’s strong potential as a high-performance gas-sensing material. Overall, this theoretical study provides new insights into the development of high-performance gas sensors, demonstrating the potential of MoSe₂ as a gas-sensing material, particularly for gases like SO₃.

Keywords: density functional theory, gas sensing, MoSe₂, non-equilibrium Green’s function, SO

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Authors: Mona Isazad Mashinchi, Davood Roshan Sangachin, Francis J. Sullivan, Dietrich Rebholz-Schuhmann

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Background: Decision-making processes are nowadays driven by data, data analytics and Business Intelligence (BI). BI as a software platform can provide a wide variety of capabilities such as organization memory, information integration, insight creation and presentation capabilities. Visualizing data through dashboards is one of the BI solutions (for a variety of areas) which helps managers in the decision making processes to expose the most informative information at a glance. In the healthcare domain to date, dashboard presentations are more frequently used to track performance related metrics and less frequently used to monitor those quality parameters which relate directly to patient outcomes. Providing effective and timely care for patients and improving the health outcome are highly dependent on presenting and visualizing data and information. Objective: In this research, the focus is on the presentation capabilities of BI to design a dashboard for prostate cancer (PC) data that allows better decision making for the patients, the hospital and the healthcare system related to a cancer dataset. The aim of this research is to customize a retrospective PC dataset in a dashboard interface to give a better understanding of data in the categories (risk factors, treatment approaches, disease control and side effects) which matter most to patients as well as other stakeholders. By presenting the outcome in the dashboard we address one of the major targets of a value-based health care (VBHC) delivery model which is measuring the value and presenting the outcome to different actors in HC industry (such as patients and doctors) for a better decision making. Method: For visualizing the stored data to users, three interactive dashboards based on the PC dataset have been developed (using the Tableau Software) to provide better views to the risk factors, treatment approaches, and side effects. Results: Many benefits derived from interactive graphs and tables in dashboards which helped to easily visualize and see the patients at risk, better understanding the relationship between patient's status after treatment and their initial status before treatment, or to choose better decision about treatments with fewer side effects regarding patient status and etc. Conclusions: Building a well-designed and informative dashboard is related to three important factors including; the users, goals and the data types. Dashboard's hierarchies, drilling, and graphical features can guide doctors to better navigate through information. The features of the interactive PC dashboard not only let doctors ask specific questions and filter the results based on the key performance indicators (KPI) such as: Gleason Grade, Patient's Age and Status, but may also help patients to better understand different treatment outcomes, such as side effects during the time, and have an active role in their treatment decisions. Currently, we are extending the results to the real-time interactive dashboard that users (either patients and doctors) can easily explore the data by choosing preferred attribute and data to make better near real-time decisions.

Keywords: business intelligence, dashboard, decision making, healthcare, prostate cancer, value-based healthcare

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Authors: Gürkan Şakar, Akgün Alsaran, Emrah E. Özbaldan

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In this study, lateral buckling analysis of composite beams with particle additive was carried out experimentally and numerically. The effects of particle type, particle addition ratio on buckling loads of composite beams were determined. The numerical studies were performed with ANSYS package. In the analyses, clamped-free boundary condition was assumed. The load carrying capabilities of composite beams were influenced by different particle types and particle addition ratios.

Keywords: lateral buckling, nanoparticle, composite beam, numeric analysis

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Authors: Jong-Hyo Park, Eunyoung Choi, Jae-Yeon Lim, Seon-Suk Lee, Yeong-Rong Koo, Ji-Ung Kwon, Kyung-Sung Kim, Jong-Ik Lee, Juhan Park, Hyun-Kyu Lee, Won-Kyoung Oh, Jisang Lee, Jiwon Choe

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Due to COVID-19, cyber violence among youths has soared as they spend more time online than before. In contrast to the deepening concerns, measurement tools that can assess the vulnerability of cyber violence in individual youths still need to be supplemented. The measurement tools lack consideration of various factors related to cyber violence among youths. Most of the tools are self-report questionnaires, and these adolescents' self-report questionnaire forms can underestimate the harmful behavior and overestimate the damage experience. Therefore, this study aims to develop a multi-report measurement tool for youths that can reliably measure individuals' ecological factors related to cyber violence. The literature review explored factors related to cyber violence, and the questions were constructed. The face validity of the questions was confirmed by conducting focus group interviews. Exploratory and confirmatory factor analyses (N=671) were also conducted for statistical validation. This study developed a multi-report measurement tool for cyber violence with 161 questions, consisting of six domains: online behavior, cyber violence awareness, victimization-perpetration-witness experience, coping efficacy (individuals, peers, teachers, and parents), psychological characteristics, and pro-social capabilities. In addition to self-report from a youth respondent, this measurement tool includes peers, teachers, and parents reporting for the respondent. It is possible to reliably measure the ecological factors of individual youths who are vulnerable or highly resistant to cyber violence. In schools, teachers could refer to the measurement results for guiding students, better understanding their cyber violence conditions, and assessing their pro-social capabilities. With the measurement results, teachers and police officers could detect perpetrators or victims and intervene immediately. In addition, this measurement tool could analyze the effects of the prevention and intervention programs for cyber violence and draw appropriate suggestions.

Keywords: adolescents, cyber violence, cyber violence measurement tool, measurement tool, multi-report measurement tool, youths

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Authors: Sujit Kumar, Anita Surroch

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Indian culture, religions, literature and philosophy has attracted attention of the scholars across the globe since time immemorial. They endeavoured to interpret these dimensions as per their comprehension of Indian Society. The present paper is an attempt to portray a critical analysis of traditional bases of Indian Society as articulated by the great Indians who immensely contributed by shaping, practicing and passing these sub-systems on to the successive generations. India was endowed with a class of intellectuals par excellence during ancient times that traversed lengths and breaths of the country, interacted with the people, understood their capabilities & limitations and needs and churned such knowledge with their fellow beings. It witnessed an era of emergence of Varnashrama, Purushartha, Dharma and Sanskara system. Mention of Varna system in the Purush hymn of Rigveda, Vrihadyaranyak Upnishda. Shantiparva of Mahabharata, the Gita and the interpretations offered by Lord Krishna, Bhrigua Rishi, Yudhishtra and philosophers of modern times give a glimpse of macro level division of labour in ancient Indian Society. The Ashrama system, the four stages of life as referred to in Upnishdas (Chandogaya, Jawali) Sutras (Vashisht Dharma Sutra, Gautma Dharma Sutra), Smritis (Manusmiriti) and four step ladder described by Ved Vyasa is a comprehensive scheme of harmonious development of physical, mental and spiritual capabilities of human beings during different stages of life. The Purushartha, the four broad duties (Dharama, Artha, Kama & Moksha) of human being, lays emphasis on discharging duties as per ones Varna, Ashrama and also keeping in view the time, space and circumstances. Sanskaras are methods and a process to purify mind, body and soul. Today, one gets refraction (not reflection as shades of beliefs, customs practices and interpretations of Varnashrama, Purushartha, Dharma and Sanskara in letter and spirit has undergone changes) of such traditional bases from the writings of Indologists and other scholars.

Keywords: intellectuals, Rigveda, Sanskaras, traditional

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Authors: Vincenzo Capalbo, Gianpaolo Ghiani, Emanuele Manni

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Global e-commerce sales have reached unprecedented levels in the past few years. As this trend is only predicted to go up as we continue into the ’20s, new challenges will be faced by companies when planning and controlling e-commerce logistics. In this paper, we survey the related literature on Optimization and Machine Learning as well as on combined methodologies. We also identify the distinctive features of next-generation planning algorithms - namely scalability, model-and-run features and learning capabilities - that will be fundamental to cope with the scale and complexity of logistics in the next decade.

Keywords: e-commerce, hardware acceleration, logistics, machine learning, mixed integer programming, optimization

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Authors: Silvia Santano Guillén, Luigi Lo Iacono, Christian Meder

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One of the main aims of current social robotic research is to improve the robots’ abilities to interact with humans. In order to achieve an interaction similar to that among humans, robots should be able to communicate in an intuitive and natural way and appropriately interpret human affects during social interactions. Similarly to how humans are able to recognize emotions in other humans, machines are capable of extracting information from the various ways humans convey emotions—including facial expression, speech, gesture or text—and using this information for improved human computer interaction. This can be described as Affective Computing, an interdisciplinary field that expands into otherwise unrelated fields like psychology and cognitive science and involves the research and development of systems that can recognize and interpret human affects. To leverage these emotional capabilities by embedding them in humanoid robots is the foundation of the concept Affective Robots, which has the objective of making robots capable of sensing the user’s current mood and personality traits and adapt their behavior in the most appropriate manner based on that. In this paper, the emotion recognition capabilities of the humanoid robot Pepper are experimentally explored, based on the facial expressions for the so-called basic emotions, as well as how it performs in contrast to other state-of-the-art approaches with both expression databases compiled in academic environments and real subjects showing posed expressions as well as spontaneous emotional reactions. The experiments’ results show that the detection accuracy amongst the evaluated approaches differs substantially. The introduced experiments offer a general structure and approach for conducting such experimental evaluations. The paper further suggests that the most meaningful results are obtained by conducting experiments with real subjects expressing the emotions as spontaneous reactions.

Keywords: affective computing, emotion recognition, humanoid robot, human-robot-interaction (HRI), social robots

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Authors: M. Saba, A. Iaaly, E. Carlier, N. Georges

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This research focuses on assessing the ground water quality of Northern Lebanon affected by saline water intrusion. The chemical, physical and microbiological parameters were collected in various seasons spanning over the period of two years. Results were assessed using Geographic Information System (GIS) due to its visual capabilities in presenting the pollution extent in the studied region. Future projections of the excessive pumping were also simulated using GIS in order to assess the extent of the problem of saline intrusion in the near future.

Keywords: GIS, saline water, quality control, drinkable water quality standards, pumping

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Authors: Khairy M. A. Zoheir, Nehma A. Ali, Ahmed M. Darwish, Mohamed S. Kishta, Ahmed A. Abd-Rabou, Mohamed A. Abdelhafez, Karima F. Mahrous

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The study comprehensively investigated the multifaceted therapeutic properties of the IQGAP1shRNA plasmid, encompassing its hepatoprotective, immunomodulatory, and anticancer activities. The study employed a Prednisolone-induced immunosuppressed rat model to assess the hepatoprotective and immunomodulatory effects of IQGAP1shRNA plasmid. Using this model, IQGAP1shRNA plasmid was found to modulate haematopoiesis, improving RBC, platelet, and WBC counts, underscoring its potential in hematopoietic homeostasis. Organ atrophy, a hallmark of immunosuppression in spleen, heart, liver, ovaries, and kidneys, was reversed with IQGAP1shRNA plasmid treatment, reinforcing its hepatotrophic and organotropic capabilities. Elevated hepatic biomarkers (ALT, AST, ALP, LPO) indicative of hepatocellular injury and oxidative stress were reduced with GST, highlighting its hepatoprotective and antioxidative effects. IQGAP1shRNA plasmid also restored depleted antioxidants (GSH and SOD), emphasizing its potent antioxidative and free radical scavenging capabilities. Molecular insights into immune dysregulation revealed downregulation of IQGAP1, IQGAP3 interleukin-2 (IL-2), and interleukin-4 (IL-4) mRNA expression in the liver of immunosuppressed rats. IL-2 and IL-4 play pivotal roles in immune regulation, T-cell activation, and B-cell differentiation. Notably, treatment with IQGAP1shRNA plasmid exhibited a significant upregulation of IL-2 and IL-4 mRNA expression, thereby accentuating its immunomodulatory potential in orchestrating immune homeostasis. Additionally, immune dysregulation was associated with increased levels of TNF-α. However, treatment with IQGAP1shRNA plasmid effectively decreased the levels of TNF-α, further underscoring its role in modulating inflammatory responses and restoring immune balance in immunosuppressed rats. Additionally, pharmacokinetics, bioavailability, drug-likeness, and toxicity risk assessment prediction suggest its potential as a pharmacologically favourable agent with no serious adverse effects. In conclusion, this study confirms the therapeutic potential of the IQGAP1shRNA plasmid, showcasing its effectiveness against hepatotoxicity, oxidative stress, immunosuppression, and its notable anticancer activity.

Keywords: IQGAP1, shRNA, cancer, liver, rat

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Authors: Ananya Gangavarapu

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Convolutional Neural Networks (CNN) based models are providing diagnostic capabilities on par with the medical specialists in many specialty areas. However, collecting the medical data for training purposes is very challenging because of the increased regulations around data collections and privacy concerns around personal health data. The gathering of the data becomes even more difficult if the capture devices are edge-based mobile devices (like smartphones) with feeble wireless connectivity in rural/remote areas. In this paper, I would like to highlight Federated Learning approach to mitigate data privacy and security issues.

Keywords: deep learning in healthcare, data privacy, federated learning, training in distributed environment

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Authors: Nilanthi Ratnayake, Wen-Ling Liu

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Prior research indicates an increasing gap between the skills and capabilities of graduates in the contemporary workplace across the globe. The challenge of addressing this issue primarily lies on the hands of higher education institutes/universities. In particular, surveys of UK employers and retailers found that soft skills including communication, numeracy, teamwork, confidence, analytical ability, digital/IT skills, business sense, language, and social skills are highly valued by graduate employers, and in achieving this, there are various assessed and non-assessed learning exercises have already been embedded into the university curriculum. To this end, this research study aims to explore the reflections of postgraduate student participation in a live commercial project (i.e. designing an advertising campaign for open days, summer school etc.) implemented with the intention of offering a transformative experience by deploying this project. Qualitative research methodology has been followed in this study, collecting data from three types of target audiences; students, academics and employers via a series of personal interviews and focus group discussions. Recorded data were transcribed, entered into NVIVO, and analysed using meaning condensation and content analysis. Students reported that they had a very positive impact towards improving self-efficacy, especially in relation to soft skills and confidence in seeking employment opportunities. In addition, this project has reduced cultural barriers for international students in general communications. Academic staff and potential employers who attended on the presentation day expressed their gratitude for offering a lifelong experience for students, and indeed believed that these type of projects contribute significantly to enhance skills and capabilities of students to cater the demands of employers. In essence, key findings demonstrate that an integration of knowledge-based skills into a live commercial project facilitate individuals to make the transition from education to employment in terms of skills, abilities and work behaviours more effectively in comparison to some other activities/assuagements that are currently in place in higher education institutions/universities.

Keywords: soft skills, commercially live project, higher education, student participation

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Authors: M. Moyzykh, I. Klichuk, L. Sabirov, D. Kolomentseva, E. Magommedov

Abstract:

Modern city electrical grids are forced to increase their density due to the increasing number of customers and requirements for reliability and resiliency. However, progress in this direction is often limited by the capabilities of existing network equipment. New energy sources or grid connections increase the level of short-circuit currents in the adjacent network, which can exceed the maximum rating of equipment–breaking capacity of circuit breakers, thermal and dynamic current withstand qualities of disconnectors, cables, and transformers. Superconducting fault current limiter (SFCL) is a modern solution designed to deal with the increasing fault current levels in power grids. The key feature of this device is its instant (less than 2 ms) limitation of the current level due to the nature of the superconductor. In 2019 Moscow utilities installed SuperOx SFCL in the city power grid to test the capabilities of this novel technology. The SFCL became the first SFCL in the Russian energy system and is currently the most powerful SFCL in the world. Modern SFCL uses second-generation high-temperature superconductor (2G HTS). Despite its name, HTS still requires low temperatures of liquid nitrogen for operation. As a result, Moscow SFCL is built with a cryogenic system to provide cooling to the superconductor. The cryogenic system consists of three cryostats that contain a superconductor part and are filled with liquid nitrogen (three phases), three cryocoolers, one water chiller, three cryopumps, and pressure builders. All these components are controlled by an automatic control system. SFCL has been continuously operating on the city grid for over three years. During that period of operation, numerous faults occurred, including cryocooler failure, chiller failure, pump failure, and others (like a cryogenic system power outage). All these faults were eliminated without an SFCL shut down due to the specially designed cryogenic system backups and quick responses of grid operator utilities and the SuperOx crew. The paper will describe in detail the results of SFCL operation and cryogenic system maintenance and what measures were taken to solve and prevent similar faults in the future.

Keywords: superconductivity, current limiter, SFCL, HTS, utilities, cryogenics

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Authors: Nasar Aldian Ambark Shashoa

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Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

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Authors: Annika Schmidt, Ausama Hadi Ahmed, Carlo Menon

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End effectors for robotic systems are becoming more and more advanced, resulting in a growing variety of gripping tasks. However, most grippers are application specific. This paper presents a gripper that interacts with an object’s surface rather than being dependent on a defined shape or size. For this purpose, ingressive and astrictive features are combined to achieve the desired gripping capabilities. The developed prototype is tested on a variety of surfaces with different hardness and roughness properties. The results show that the gripping mechanism works on all of the tested surfaces. The influence of the material properties on the amount of the supported load is also studied and the efficiency is discussed.

Keywords: claw, dry adhesion, insects, material properties

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Authors: Wei-Kuo Soong

Abstract:

The forecasting of typhoon tracks remains a formidable challenge, primarily attributable to the paucity of observational data in the open sea and the intricate influence of weather systems at varying scales. This study investigates the case of Typhoon Hinnamnor in 2022, examining its trajectory and intensity fluctuations in relation to the interaction with a concurrent tropical cyclone and sea surface temperatures (SST). Utilizing the Weather Research and Forecasting Model (WRF), to simulate and analyze the interaction between Typhoon Hinnamnor and its environmental factors, shedding light on the mechanisms driving typhoon development and enhancing forecasting capabilities.

Keywords: typhoon, sea surface temperature, forecasting, WRF

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Authors: Si-Gwan Kim

Abstract:

Small-size and low-power sensors with sensing, signal processing and wireless communication capabilities is suitable for the wireless sensor networks. Due to the limited resources and battery constraints, complex routing algorithms used for the ad-hoc networks cannot be employed in sensor networks. In this paper, we propose node-disjoint multi-path hexagon-based routing algorithms in wireless sensor networks. We suggest the details of the algorithm and compare it with other works. Simulation results show that the proposed scheme achieves better performance in terms of efficiency and message delivery ratio.

Keywords: clustering, multi-path, routing protocol, sensor network

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Authors: Razul Ikmal Ramli

Abstract:

Successful implementation of innovation is a key success formula of a great organization. Innovation will ensure competitive advantages as well as sustainability of organization in the long run. In public sector context, the role of innovation is crucial to resolve dynamic challenges of public services such as operating in economic uncertainty with limited resources, increasing operating expenditure and growing expectation among citizens towards high quality, swift and reliable public services. Acknowledging the prospect of innovation as a tool for achieving high-performance public sector, the Malaysian New Economic Model launched in the year 2011 intensified government commitment to foster innovation in the public sector. Since 2011 various initiatives have been implemented, however little is known about the performance of public sector innovation in Malaysia. Hence, by applying the national innovation system theory as a pillar, the formulated research objectives were focused on measuring the level of innovation capabilities, wider public sector condition for innovation, innovation activity, and innovation performance as well as to examine the relationship between the four constructs with innovation performance as a dependent variable. For that purpose, 1,000 sets of self-administrated survey questionnaires were distributed to heads of units and divisions of 22 Federal Ministry and Central Agencies in the administrative, security, social and economic sector. Based on 456 returned questionnaires, the descriptive analysis found that innovation capabilities, wider sector condition, innovation activities and innovation performance were rated by respondents at moderately high level. Based on Structural Equation Modelling, innovation performance was found to be influenced by innovation capability, wider sector condition for innovation and innovation activity. In addition, the analysis also found innovation activity to be the most important construct that influences innovation performance. The implication of the study concluded that the innovation policy implemented in the public sector of Malaysia sparked motivation to innovate and resulted in various forms of innovation. However, the overall achievements were not as well as they were expected to be. Thus, the study suggested for the formulation of a dedicated policy to strengthen innovation capability, wider public sector condition for innovation and innovation activity of the Malaysian public sector. Furthermore, strategic intervention needs to be focused on innovation activity as the construct plays an important role in determining the innovation performance. The success of public sector innovation implementation will not only benefit the citizens, but will also spearhead the competitiveness and sustainability of the country.

Keywords: public sector, innovation, performance, innovation policy

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Authors: Varun Dongre, Stefan Pirker, Stefan Heinrich

Abstract:

Over the last decades, the numerical modelling of fluidized bed processes has become feasible even for industrial processes. Commonly, continuous two-fluid models are applied to describe large-scale fluidization. In order to allow for coarse grids novel two-fluid models account for unresolved sub-grid heterogeneities. However, computational efforts remain high – in the order of several hours of compute-time for a few seconds of real-time – thus preventing the representation of long-term phenomena such as heating or particle conversion processes. In order to overcome this limitation, data-based recurrence computational fluid dynamics (rCFD) has been put forward in recent years. rCFD can be regarded as a data-based method that relies on the numerical predictions of a conventional short-term simulation. This data is stored in a database and then used by rCFD to efficiently time-extrapolate the flow behavior in high spatial resolution. This study will compare the numerical predictions of rCFD simulations with those of corresponding full CFD reference simulations for lab-scale and pilot-scale fluidized beds. In assessing the predictive capabilities of rCFD simulations, we focus on solid mixing and secondary gas holdup. We observed that predictions made by rCFD simulations are highly sensitive to numerical parameters such as diffusivity associated with face swaps. We achieved a computational speed-up of four orders of magnitude (10,000 time faster than classical TFM simulation) eventually allowing for real-time simulations of fluidized beds. In the next step, we apply the checkerboarding technique by introducing gas tracers subjected to convection and diffusion. We then analyze the concentration profiles by observing mixing, transport of gas tracers, insights about the convective and diffusive pattern of the gas tracers, and further towards heat and mass transfer methods. Finally, we run rCFD simulations and calibrate them with numerical and physical parameters compared with convectional Two-fluid model (full CFD) simulation. As a result, this study gives a clear indication of the applicability, predictive capabilities, and existing limitations of rCFD in the realm of fluidization modelling.

Keywords: multiphase flow, recurrence CFD, two-fluid model, industrial processes

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Authors: Francisco J. García-de-Quirós, Gianmarco Radice

Abstract:

When considering small robots working in a cooperative community for Moon surface exploration, navigation and inter-nodes communication aspects become a critical issue for the mission success. For this approach to succeed, it is necessary however to deploy the required infrastructure for the robotic community to achieve efficient self-localization as well as relative positioning and communications between nodes. In this paper, an exploration mission concept in which two cooperative robotic systems co-exist is presented. This paradigm hinges on a community of reference agents that provide support in terms of communication and navigation to a second agent community tasked with exploration goals. The work focuses on the role of the agent community in charge of the overall support and, more specifically, will focus on the positioning and navigation methods implemented in RF microwave bands, which are combined with the communication services. An analysis of the different methods for range and position calculation are presented, as well as the main limiting factors for precision and resolution, such as phase and frequency noise in RF reference carriers and drift mechanisms such as thermal drift and random walk. The effects of carrier frequency instability due to phase noise are categorized in different contributing bands, and the impact of these spectrum regions are considered both in terms of the absolute position and the relative speed. A mission scenario is finally proposed, and key metrics in terms of mass and power consumption for the required payload hardware are also assessed. For this purpose, an application case involving an RF communication network in UHF Band is described, in coexistence with a communications network used for the single agents to communicate within the both the exploring agents as well as the community and with the mission support agents. The proposed approach implements a substantial improvement in planetary navigation since it provides self-localization capabilities for robotic agents characterized by very low mass, volume and power budgets, thus enabling precise navigation capabilities to agents of reduced dimensions. Furthermore, a common and shared localization radiofrequency infrastructure enables new interaction mechanisms such as spatial arrangement of agents over the area of interest for distributed sensing.

Keywords: cooperative robotics, localization, robot navigation, surface exploration

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Authors: M. Kebisek, L. Spendla, M. Kopcek, T. Skulavik

Abstract:

In our paper we describe the security capabilities of data collection. Data are collected with probes located in the near and distant surroundings of the company. Considering the numerous obstacles e.g. forests, hills, urban areas, the data collection is realized in several ways. The collection of data uses connection via wireless communication, LAN network, GSM network and in certain areas data are collected by using vehicles. In order to ensure the connection to the server most of the probes have ability to communicate in several ways. Collected data are archived and subsequently used in supervisory applications. To ensure the collection of the required data, it is necessary to propose algorithms that will allow the probes to select suitable communication channel.

Keywords: communication, computer network, data collection, probe

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