Search results for: deep Q networks

Authors: A. Anitha, M. Aishwariya

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The realization of truly ubiquitous wireless sensor networks (WSN) demands Ultra-low power wireless communication capability. Because the radio transceiver in a wireless sensor node consumes more power when compared to the computation part it is necessary to reduce the power consumption. Hence, a low power transceiver is designed and implemented in a 120 nm CMOS technology for wireless sensor nodes. The power consumption of the transceiver is reduced still by maintaining the sensitivity. The transceiver designed combines the blocks including differential oscillator, mixer, envelope detector, power amplifiers, and LNA. RF signal modulation and demodulation is carried by On-Off keying method at 2.4 GHz which is said as ISM band. The transmitter demonstrates an output power of 2.075 mW while consuming a supply voltage of range 1.2 V-5.0 V. Here the comparison of LNA and power amplifier is done to obtain an amplifier which produces a high gain of 1.608 dB at receiver which is suitable to produce a desired sensitivity. The multistage RF amplifier is used to improve the gain at the receiver side. The power dissipation of the circuit is in the range of 0.183-0.323 mW. The receiver achieves a sensitivity of about -95 dBm with data rate of 1 Mbps.

Keywords: CMOS, envelope detector, ISM band, LNA, low power electronics, PA, wireless transceiver

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Authors: Aulia Dwi Nastiti

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A number of studies and reports on terrorism have continuously addressed the role of internet and online activism to support terrorist and extremist groups. In particular, they stress on social media’s usage that generally serves for the terrorist’s propaganda as well as justification of their causes. While those analyses are important to understand how social media is a vital tool for global network terrorism, they are inadequate to explain the online communication patterns that enable terrorism acts. Beyond apparent online narratives, there is a deep cyber sphere where the very vein of terrorism movement lies. That is a hidden space in the internet called ‘darknet’. Recent investigations, particularly in Middle Eastern context, have shed some lights that this invisible space in the internet is fundamental to maintain the terrorist activities. Despite that, limited number of research examines darknet within the issue of terrorist movements in Indonesian context—where the country is considered quite a hotbed for extremist groups. Therefore, this paper attempts to provide an insight of darknet operation in Indonesian cases. By exploring how the darknet is used by the Indonesian-based extremist groups, this paper maps out communication patterns of terrorist groups on the internet which appear as an intermingled network. It shows the usage of internet is differentiated in different level of anonymity for distinctive purposes. This paper further argues that the emerging terrorist communication network calls for a more comprehensive counterterrorism strategy on the Internet.

Keywords: communication pattern, counterterrorism, darknet, extremist groups, terrorism

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Authors: El Oualid Mokhnache, Noureddine Ramdani

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The choice of gun barrel materials is crucial to ensure the maximum high rate of fire. The high rate of fire causes wear-out damage and shuts off mechanical properties (hardness, strength, wear resistance, etc.) and ballistic properties (bullet speed, dispersion and precision, longevity of barrel, etc). To overcome these kinds of problems, a deep understanding of the effect of the firing cycle on the mechanical and ballistic properties of the barrel is regarded as crucial to improving its characteristics. In the present work, a real experimental test of firing by using a high steel barrel with 7.62x39 ammunition was carried. Microstructural observations by using SEM were investigated. Hardness evolution through the barrel of both barrels labeled as reference barrels and as fired barrels were compared and discussed. Ballistic properties during the firing test, including speed of projectile and precision dispersion, are revealed and discussed as well. The aim of the present communication is about to discuss the relationship between pressure distribution versus mechanical properties through the wall barrel. Ballistic properties, including speed of the projectile, dispersion, and precision results during the shooting process, were investigated. Microstructure observations of the as-rifled barrel in comparison with the as-reference barrel were performed as well.

Keywords: barrel, ballistic, pressure, microstructure evolution, hardness

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Authors: Robyn Moloney, HuiLing Xu

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Many countries wish to produce Asia-literate citizens, through language education. International contexts of Chinese language education are seeking pedagogical innovation to meet local contextual factors frequently holding back learner success. In multicultural Australia, innovative pedagogy is urgently needed to support motivation in sustained study, with greater strategic integration of technology. This research took a qualitative approach to identify need and solutions. The paper analyses strategies that three secondary school teachers are adopting to meet specific challenges in the Australian context. The data include teacher interviews, classroom observations and student interviews. We highlight the use of task-based learning and differentiated teaching for multilevel classes, and the role which digital technologies play in facilitating both areas. The strategy examples are analysed in reference both to a research-based framework for describing quality teaching, and to current understandings of motivation in language learning. The analysis of data identifies learning featuring deep knowledge, higher-order thinking, engagement, social support, utilisation of background knowledge, and connectedness, all of which work towards the learners having a sense of autonomy and an imagination of becoming an adult Chinese language user.

Keywords: Chinese pedagogy, digital technologies, motivation, secondary school

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%- 40% compared to a traditional RL model.

Keywords: control system, hydroponics, machine learning, reinforcement learning

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Authors: Ruth Mandujano Lopez

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

Keywords: mexico, steamships, transpacific, maritime companies

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Esperanza C. Santos

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Japanese Language was traditionally considered as a means of imparting culture and training aesthetic experience in students and therefore as something beyond the practical aims of language teaching and learning. Due to the complexity of foreign languages, lots of language learners and teachers shared deep reservations about the potentials of foreign language in enhancing the communication skills of the students. In spite of the arguments against the use of Foreign Language (Nihon-go) in the classroom, the researcher strongly support the use of Nihon-go in teaching communication skills as the researcher believes that Nihon-go is a valuable resource to be exploited in the classroom in order to help the students explore the language in an interesting and challenging way. The focus of this research is to find out the relationship between the preferences, opinions, and perceptions with the communication skills. This study also identifies the significance of the relationship between preferences, opinions and perceptions and communications skills in the activities employed in Foreign language (Nihon-go) among the junior and senior students in Foreign Language 2 at the Imus Institute, Imus Cavite during the academic year 2013-2014. The results of the study are expected to encourage further studies that particularly focused on the communication skills as brought about by the identified factors namely: preferences, opinions, and perceptions on the benefits factor namely the language acquisition; access to Japanese culture and students' interpretative ability. Therefore, this research is in its quest for the issues and concerns on how to effectively teach different learning activities in a Nihon-go class.

Keywords: preferences, opinions, perceptions, language acquisition

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Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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Authors: Yonatan Sverdlov, Shimon Ullman

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Artificial neural networks encounter a notable challenge known as continual learning, which involves acquiring knowledge of multiple tasks over an extended period. This challenge arises due to the tendency of previously learned weights to be adjusted to suit the objectives of new tasks, resulting in a phenomenon called catastrophic forgetting. Most approaches to this problem seek a balance between maximizing performance on the new tasks and minimizing the forgetting of previous tasks. In contrast, our approach attempts to maximize the performance of the new task, while ensuring zero forgetting. This is accomplished through the introduction of task-specific modulation parameters for each task, and only these parameters are learned for the new task, after a set of initial tasks have been learned. Through comprehensive experimental evaluations, our model demonstrates superior performance in acquiring and retaining novel tasks that pose difficulties for other multi-task models. This emphasizes the efficacy of our approach in preventing catastrophic forgetting while accommodating the acquisition of new tasks.

Keywords: continual learning, life-long learning, neural analogies, adaptive modulation

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Authors: Ghazi Al Sukkar, Yazid Khattabi, Shifen Zhong

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Most of the recent wireless LANs, broadband access networks, and digital broadcasting use Orthogonal Frequency Division Multiplexing techniques. In addition, the increasing demand of Data and Internet makes fiber optics an important technology, as fiber optics has many characteristics that make it the best solution for transferring huge frames of Data from a point to another. Radio over fiber is the place where high quality RF is converted to optical signals over single mode fiber. Optimum values for the bias level and the switching voltage for Mach-Zehnder modulator are important for the performance of radio over fiber links. In this paper, we propose a method to optimize the two parameters simultaneously; the bias and the switching voltage point of the external modulator of a radio over fiber system considering RF gain. Simulation results show the optimum gain value under these two parameters.

Keywords: OFDM, Mach Zehnder bias voltage, switching voltage, radio-over-fiber, RF gain

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Authors: Ki-seok Kwon, Dong-woo Ryu, Heung-Youl Kim

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Although high-strength concrete has many advantages over generic concrete at normal temperatures (around 20℃), it undergoes spalling at high temperatures, which constitutes its structurally fatal drawback. In this study, fire resistance tests were conducted for 3 hours in accordance with ASTM E119 on bearing wall specimens which were 3,000mm x 3,000mm x 300mm in dimensions to investigate the influence the type of admixtures would exert on the fire resistance performance of high-strength concrete. Portland cement, blast furnace slag, fly ash and silica fume were used as admixtures, among which 2 or 3 components were combined to make 7 types of mixtures. In 56MPa specimens, the severity of spalling was in order of SF5 > F25 > S65SF5 > S50. Specimen S50 where an admixture consisting of 2 components was added did not undergo spalling. In 70MPa specimens, the severity of spalling was in order of SF5 > F25SF5 > S45SF5 and the result was similar to that observed in 56MPa specimens. Acknowledgements— This study was conducted by the support of the project, “Development of performance-based fire safety design of the building and improvement of fire safety” (18AUDP-B100356-04) which is under the management of Korea Agency for Infrastructure Technology Advancement as part of the urban architecture research project for the Ministry of Land, Infrastructure and Transport, for which we extend our deep thanks.

Keywords: high strength concrete, mineral admixture, fire resistance, social disaster

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Authors: Supriadi Hardianto, Aditya Daniswara

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Today's workplace, flooded by millennial Generation or known also as Generation Y. A common problem that faced by the company towards Gen Y is a high turnover rate, attitudes problem, communication style, and different work style than the older generation. This is common in private sector. The objective of this study is to get a better understanding of the Gen Y Career Attitude at the workplace. The subject of this study is focusing on 430 respondent of Gen Y which age between 20 – 35 years old who works for a private company. The Questionnaire as primary data source captured 9 aspects of career attitude based on Career Attitudes Strategy Inventory (CASI). This Survey distributes randomly among Gen Y in the IT Industry (125 Respondent) and Manufacture Company (305 Respondent). A Random deep interview was conducted to get the better understanding of the etiology of their primary obstacles. The study showed that most of Indonesia Gen Y have a moderate score on Job satisfaction but in the other aspects, Gen Y has the lowest score on Skill Development, Career Worries, Risk-Taking Style, Dominant Style, Work Involvement, Geographical Barrier, Interpersonal Abuse, and Family Commitment. The top 5 obstacles outside that 9 aspects that faced by Gen Y are 1. Lower communication & networking support; 2. Self-confidence issues; 3. Financial Problem; 4. Emotional issues; 5. Age. We also found that parent perspective toward the way they are nurturing their child are not aligned with their child’s real life. This research fundamentally helps the organization and other Gen Y’s Stakeholders to have a better understanding of Gen Y Career Attitude at the workplace.

Keywords: career attitudes, CASI, Gen Y, career attitude at workplace

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Authors: Abhishek Dixit, Sandip S. Sathe, Chandan Mahanta

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The Siang river originates in Angsi glacier in southern Tibet (there known as the Yarlung Tsangpo). After traveling through Indus-Tsangpo suture zone and deep gorges near Namcha Barwa peak, it takes a south-ward turn and enters India, where it is known as Siang river and becomes a major tributary of the Brahmaputra in Assam plains. In this study, we have analyzed the bed sediment of the Siang river at two locations (one at extreme upstream near the India-China border and one downstream before Siang Brahmaputra confluence). We have also sampled bed sediment at the remote location of Yammeng river, an eastern tributary of Siang. The magnetic hysteresis properties show the combination of paramagnetic and weak ferromagnetic behavior with a multidomain state. Moreover, curie temperature analysis shows titanomagnetite solid solution series, which is causing the weak ferromagnetic signature. Given that the magnetic mineral was in a multidomain state, the presence of Ti, Fe carrying heave mineral, may be inferred. The Chemical index of alteration shows less weathered sediment. However, the Yammeng river sample being close to source shows fresh grains subjected to physical weathering and least chemically alteration. Enriched Ca and K and depleted Na and Mg with respect to upper continental crust concentration also points toward the less intense chemical weathering along with the dominance of calcite weathering.

Keywords: bed sediment, magnetic properties, Siang, weathering

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Authors: S. Benessam, T. H. Debieche, A. Drouiche, S. Mahdid, F. Zahi

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The marsh is the impermeable depression. It is not very deep and presents the stagnant water. Their water level varies according to the contributions of water (rain, groundwater, stream etc.), when this last reaches the maximum level of the marsh, it flows towards the downstream through the discharge system. The marsh accumulates all the liquid and solid contributions of upstream part. In the North-East Algerian, the Redjla marsh is located on the course of the Tassift river. Its contributions of water come from the upstream part of the river, often characterized by the presence of several pollutants in water related to the urban effluents, and its discharge system supply the downstream part of the river. In order to determine the effect of the marsh on the water quality of the river this study was conducted. A two-monthly monitoring of the physicochemical parameters and water chemistry of the river were carried out, before and after the marsh, during the period from November 2013 to January 2015. The results show that the marsh plays the role of a natural purifier of water of Tassift river, present by drops of conductivity and concentration of the pollutants (ammonium, phosphate, iron, chlorides and bicarbonates) between the upstream part and downstream of the marsh. That indicates that these pollutants are transformed with other chemical forms (case of ammonium towards nitrate), precipitated in complex forms or/and adsorbed by the sediments of the marsh. This storage of the pollutants in the ground of the marsh will be later on a source of pollution for the plants and river water.

Keywords: marsh, natural purification, urban pollution, nitrogen

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Authors: Julio Kauss, Miguel Cadillo, David Mauricio

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E-commerce is a business model that allows companies to optimize the processes of buying, selling, transferring goods and exchanging services through computer networks or the Internet. In Peru, the electronic commerce is used infrequently. This situation is due, in part to the fact that there is no model that allows companies to implement an e-commerce solution, which means that most SMEs do not have adequate knowledge to adapt to electronic commerce. In this work, a reference model is proposed for the implementation of an e-commerce solution in Peruvian SMEs in the retail sector. It consists of five phases: Business Analysis, Business Modeling, Implementation, Post Implementation and Results. The present model was validated in a SME of the Peruvian retail sector through the implementation of an electronic commerce platform, through which the company increased its sales through the delivery channel by 10% in the first month of deployment. This result showed that the model is easy to implement, is economical and agile. In addition, it allowed the company to increase its business offer, adapt to e-commerce and improve customer loyalty.

Keywords: e-commerce, retail, SMEs, reference model

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Authors: Farid Eltom A. E., Mustafa Abdul-Halim, Abdalla Markaz, Sami Atta, Mohamed Azhari, Ahmed Rashed

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Smart environment sensors integrated with ‘Internet of Things’ (IoT) technology can provide a new concept in tracking, sensing, and monitoring objects in the environment. The aim of the study is to evaluate the farm environmental monitoring system based on (IoT) and to realize the automated management of agriculture and the implementation of precision production. Until now, irrigation monitoring operations in Sudan have been carried out using traditional methods, which is a very costly and unreliable mechanism. However, by utilizing soil moisture sensors, irrigation can be conducted only when needed without fear of plant water stress. The result showed that software application allows farmers to display current and historical data on soil moisture and nutrients in the form of line charts. Design measurements of the soil factors: moisture, electrical, humidity, conductivity, temperature, pH, phosphorus, and potassium; these factors, together with a timestamp, are sent to the data server using the Lora WAN interface. It is considered scientifically agreed upon in the modern era that artificial intelligence works to arrange the necessary procedures to take care of the terrain, predict the quality and quantity of production through deep analysis of the various operations in agricultural fields, and also support monitoring of weather conditions.

Keywords: smart environment, monitoring systems, IoT, LoRa Gateway, center pivot

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Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura

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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.

Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU

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Authors: Mujtaba Roshan, John A. Schormans

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Quality of Experience (QoE) drives churn in the broadband networks industry, and good QoE plays a large part in the retention of customers. QoE is known to be affected by the Quality of Service (QoS) factors packet loss probability (PLP), delay and delay jitter caused by the network. Earlier results have shown that the relationship between these QoS factors and QoE is non-linear, and may vary from application to application. We use the network emulator Netem as the basis for experimentation, and evaluate how QoE varies as we change the emulated QoS metrics. Focusing on Video-on-Demand, we discovered that the reported QoE may differ widely for users of different age groups, and that the most demanding age group (the youngest) can require an order of magnitude lower PLP to achieve the same QoE than is required by the most widely studied age group of users. We then used a bottleneck TCP model to evaluate the capacity cost of achieving an order of magnitude decrease in PLP, and found it be (almost always) a 3-fold increase in link capacity that was required.

Keywords: network capacity, packet loss probability, quality of experience, quality of service

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Authors: Hemalatha Rallapalli, K. Lal Kishore

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In comparison to systems that are typically designed to provide capabilities over a narrow frequency range through hardware elements, the next generation cognitive radios are intended to implement a broader range of capabilities through efficient spectrum exploitation. This offers the user the promise of greater flexibility, seamless roaming possible on different networks, countries, frequencies, etc. It requires true paradigm shift i.e., liberalization over a wide band of spectrum as well as a growth path to more and greater capability. This work contributes towards the design and implementation of an open spectrum access (OSA) feature to unlicensed users thus offering a frequency agile radio platform that is capable of performing spectrum sensing over a wideband. Thus, an ultra-wideband (UWB) radio, which has the intelligence of spectrum sensing only, unlike the cognitive radio with complete intelligence, is named as a Smart Software Radio (SSR). The spectrum sensing mechanism is implemented based on energy detection. Simulation results show the accuracy and validity of this method.

Keywords: cognitive radio, energy detection, software radio, spectrum sensing

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Authors: Alireza Pour Ebrahimi, Vahid Abasi

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Recently by the extension of internet usage, Research on the intrusion detection system takes a significant importance. Many of improvement systems prevent internal and external network attacks by providing security through firewalls and antivirus. In recently years, intrusion detection systems gradually turn from host-based systems and depend on O.S to the distributed systems which are running on multiple O.S. In this work, by considering the diversity of computer networks whit respect to structure, architecture, resource, services, users and also security goals requirement a fully distributed collaborative intrusion detection system based on peer to peer architecture is suggested. in this platform each partner device (matched device) considered as a peer-to-peer network. All transmitted information to network are visible only for device that use security scanning of a source. Experimental results show that the distributed architecture is significantly upgradeable in respect to centralized approach.

Keywords: network, intrusion detection system, peer to peer, internal and external network

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Mamata Mohanty, J. T. Shahu

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The in-situ deep mixing is an effective ground improvement technique which involves columnar inclusion into soft ground to increase its bearing capacity and reduce settlement. The first part of the study presents the results of unconfined compression on cement-admixed clay prepared at different cement content and subjected to varying curing periods. It is found that cement content is a prime factor controlling the strength of the cement-admixed clay. Besides cement content, curing period is important parameter that adds to the strength of cement-admixed clay. Increase in cement content leads to significant increase in Unconfined Compressive Strength (UCS) values especially at cement contents greater than 8%. The second part of the study investigated the bearing capacity of the clay ground improved by a group of end-bearing column using model tests under plain-strain condition. This study mainly focus to examine the effect of cement contents on the ultimate bearing capacity and failure stress of the improved clay ground. The study shows that the bearing capacity of the improved ground increases significantly with increase in cement contents of the soil-cement columns. A considerable increase in the stiffness of the model ground and failure stress was observed with increase in cement contents.

Keywords: bearing capacity, cement content, curing time, unconfined compressive strength, undrained shear strength

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Authors: Yosra Mefteh Rekik

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A computational agent-based model of financial markets stresses interactions and dynamics among a very diverse set of traders. The growing body of research in this area relies heavily on computational tools which by-pass the restrictions of an analytical method. The main goal of this research is to understand how the stock market operates and behaves how to invest in the stock market and to study traders’ behavior within the context of the artificial stock markets populated by heterogeneous agents. All agents are characterized by adaptive learning behavior represented by the Artificial Neuron Networks. By using agent-based simulations on artificial market, we show that the existence of heterogeneous agents can explain the price dynamics in the financial market. We investigate the relation between market diversity and market efficiency. Our empirical findings demonstrate that greater market heterogeneity play key roles in market efficiency.

Keywords: agent-based modeling, artificial stock market, heterogeneous expectations, financial stylized facts, computational finance

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Authors: Bruno Vilić Belina, Ivan Župan

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Smart industry concepts and digital transformation are very popular in many industries. They develop their own digital platforms, which have an important role in innovations and transactions. The main idea of smart industry digital platforms is central data collection, industrial data integration, and data usage for smart applications and services. This paper presents the development of a digital platform for building critical infrastructure protection systems in smart industries. Different service contraction modalities in service level agreements (SLAs), customer relationship management (CRM) relations, trends, and changes in business architectures (especially process business architecture) for the purpose of developing infrastructural production and distribution networks, information infrastructure meta-models and generic processes by critical infrastructure owner demanded by critical infrastructure law, satisfying cybersecurity requirements and taking into account hybrid threats are researched.

Keywords: cybersecurity, critical infrastructure, smart industries, digital platform

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Authors: Fatiha Besahraoui, M'hamed Guezzoul, Kheira Chebbah, M'hamed Bouslama

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SnO₂ thin film is characterized by Atomic Force Microscopy (AFM) and Photoluminescence Spectroscopies. AFM images show a dense surface of columnar grains with a roughness of 78.69 nm. The PL measurements at 7 K reveal the presence of PL peaks centered in IR and visible regions. They are attributed to radiative transitions via oxygen vacancies, Sn interstitials, and dangling bonds. A bands diagram model is presented with the approximate positions of intrinsic point defect levels in SnO₂ thin films. The integrated PL measurements demonstrate the good thermal stability of our sample, which makes it very useful in optoelectronic devices functioning at room temperature. The unusual behavior of the evolution of PL peaks and their full width at half maximum as a function of temperature indicates the thermal sensitivity of the point defects present in the band gap. The shallower energy levels due to dangling bonds and/or oxygen vacancies are more sensitive to the temperature. However, volume defects like Sn interstitials are thermally stable and constitute deep and stable energy levels for excited electrons. Small redshifting of PL peaks is observed with increasing temperature. This behavior is attributed to the reduction of oxygen vacancies.

Keywords: transparent conducting oxide, photoluminescence, intrinsic point defects, semiconductors, oxygen vacancies

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Authors: Di Wei, Xing Hu, Yangjun Chen, Baofeng Li, Hong Chen

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To achieve the research purpose of guiding the spatial morphology design of blocks through the indicators to obtain a good wind environment, it is necessary to find the most suitable type and value range of each urban spatial morphology indicator. At present, most of the relevant researches is based on the numerical simulation of the ideal block shape and rarely proposes the results based on the complex actual block types. Therefore, this paper firstly attempted to make theoretical speculation on the main factors influencing indicators' effectiveness by analyzing the physical significance and formulating the principle of each indicator. Then it was verified by the field wind environment measurement and statistical analysis, indicating that Porosity(P₀) can be used as an important indicator to guide the design of block wind environment in the case of deep street canyons, while Frontal Area Density (λF) can be used as a supplement in the case of shallow street canyons with no height difference. Finally, computational fluid dynamics (CFD) was used to quantify the impact of block height difference and street canyons depth on λF and P₀, finding the suitable type and value range of λF and P₀. This paper would provide a feasible wind environment index system for urban designers.

Keywords: urban spatial morphology indicator, urban microclimate, computational fluid dynamics, block ventilation, correlation analysis

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Authors: Mohammad Zaid, Md. Rehan Sadique

Abstract:

Underground structures are an integral part of urban infrastructures. Tunnels are being used for the transportation of humans and goods from distance to distance. Terrorist attacks on underground structures such as tunnels have resulted in the improvement of design methodologies of tunnels. The design of underground tunnels must include anti-terror design parameters. The study has been carried out to analyse the rock tunnel when subjected to internal blast loading. The finite element analysis has been carried out for 30m by 30m of the cross-section of the tunnel and 35m length of extrusion of the rock tunnel model. The effect of tunnel diameter and overburden depth of tunnel has been studied under internal blast loading. Four different diameters of tunnel considered are 5m, 6m, 7m, and 8m, and four different overburden depth of tunnel considered are 5m, 7.5m, 10m, and 12.5m. The mohr-coulomb constitutive material model has been considered for the Quartzite rock. A concrete damage plasticity model has been adopted for concrete tunnel lining. For the trinitrotoluene (TNT) Jones-Wilkens-Lee (JWL) material model has been considered. Coupled-Eulerian-Lagrangian (CEL) approach for blast analysis has been considered in the present study. The present study concludes that a shallow tunnel having smaller diameter needs more attention in comparison to blast resistant design of deep tunnel having a larger diameter. Further, in the case of shallow tunnels, more bulging has been observed, and a more substantial zone of rock has been affected by internal blast loading.

Keywords: finite element method, blast, rock, tunnel, CEL, JWL

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Authors: A. Assif

Abstract:

This paper presents the modeling of a prototype distribution static compensator (D-STATCOM) for voltage sag and swell mitigation in an unbalanced distribution system. Here the concept that an inverter can be used as generalized impedance converter to realize either inductive or capacitive reactance has been used to mitigate power quality issues of distribution networks. The D-STATCOM is here supposed to replace the widely used StaticVar Compensator (SVC). The scheme is based on the Voltage Source Converter (VSC) principle. In this model PWM based control scheme has been implemented to control the electronic valves of VSC. Phase shift control Algorithm method is used for converter control. The D-STATCOM injects a current into the system to mitigate the voltage sags. In this paper the modeling of D¬STATCOM has been designed using MATLAB SIMULINIC. Accordingly, simulations are first carried out to illustrate the use of D-STATCOM in mitigating voltage sag in a distribution system. Simulation results prove that the D-STATCOM is capable of mitigating voltage sag as well as improving power quality of a system.

Keywords: D-STATCOM, voltage sag, voltage source converter (VSC), phase shift control

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