Search results for: distributed sensor networks

Authors: Somar Boubou, Tatsuo Narikiyo, Michihiro Kawanishi

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In this work, we address the problem of 3D object recognition with depth sensors such as Kinect or Structure sensor. Compared with traditional approaches based on local descriptors, which depends on local information around the object key points, we propose a global features based descriptor. Proposed descriptor, which we name as Differential Histogram of Normal Vectors (DHONV), is designed particularly to capture the surface geometric characteristics of the 3D objects represented by depth images. We describe the 3D surface of an object in each frame using a 2D spatial histogram capturing the normalized distribution of differential angles of the surface normal vectors. The object recognition experiments on the benchmark RGB-D object dataset and a self-collected dataset show that our proposed descriptor outperforms two others descriptors based on spin-images and histogram of normal vectors with linear-SVM classifier.

Keywords: vision in control, robotics, histogram, differential histogram of normal vectors

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Authors: Mkhinini Maher, Knani Jilani

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We present in this work the performances of a mobile omnidirectional robot through evaluating its management of the redundancy of actuation. Thus we come to the predictive control implemented. The distribution of the wringer on the robot actions, through the inverse pseudo of Moore-Penrose, corresponds to a -geometric- distribution of efforts. We will show that the load on vehicle wheels would not be equi-distributed in terms of wheels configuration and of robot movement. Thus, the threshold of sliding is not the same for the three wheels of the vehicle. We suggest exploiting the redundancy of actuation to reduce the risk of wheels sliding and to ameliorate, thereby, its accuracy of displacement. This kind of approach was the subject of study for the legged robots.

Keywords: mobile robot, actuation, redundancy, omnidirectional, inverse pseudo moore-penrose, reductive control

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Authors: Ratna Elizabeth

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Motivation is a very important factor since it contributes a lot to the students’ success in learning a language. Using authentic materials is believed as a mean of increasing the motivation. The materials define as authentic if they are not specifically written for the purpose of language teaching. They are genuine spoken or written language data which are drawn from many different sources. The intention of this study is to investigate the impact of using of authentic materials on students’ motivation. A single case study is conducted to the grade 9 students who learn Indonesian Language as a Foreign Language (ILFL) at an international school in Jakarta, Indonesia. Questionnaires are also distributed to the students to know their perceptions on the using of authentic materials. The results show that the using of authentic materials has increased the students’ motivation in learning the language.

Keywords: authentic materials, ILFL, language learning, motivation

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Authors: Carla E. O. de Moraes, Gladson O. Antunes, Mauro A. Rincon

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The aim of this paper is to study the internal stabilization of the Bernoulli-Euler equation numerically. For this, we consider a square plate subjected to a feedback/damping force distributed only in a subdomain. An algorithm for obtaining an approximate solution to this problem was proposed and implemented. The numerical method used was the Finite Difference Method. Numerical simulations were performed and showed the behavior of the solution, confirming the theoretical results that have already been proved in the literature. In addition, we studied the validation of the numerical scheme proposed, followed by an analysis of the numerical error; and we conducted a study on the decay of the energy associated.

Keywords: Bernoulli-Euler plate equation, numerical simulations, stability, energy decay, finite difference method

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Authors: Eiko Takaoka, Yoshiyuki Fukushima, Koichiro Hirose, Tadashi Hasegawa

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Although all high school students in Japan are required to learn informatics, many of them do not learn this topic sufficiently. In response to this situation, we propose a support package for high school informatics classes. To examine what students learned and if they sufficiently understood the context of the lessons, a questionnaire survey was distributed to 186 students. We analyzed the results of the questionnaire and determined the weakest units, which were “basic computer configuration” and “memory and secondary storage”. We then developed a package for teaching these units. We propose that our package be applied in high school classrooms.

Keywords: computer science unplugged, computer science outreach, high school curriculum, experimental evaluation

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Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

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This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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Authors: Gamal Shiha, Waleed Samir, Zahid Azam, Premashis Kar, Saeed Hamid, Shiv Sarin

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A simple, rapid and non-invasive electromagnetic sensor (C-FAST device) was- patented; for diagnosis of HCV RNA. Aim: To test the validity of the device compared to standard HCV PCR. Subjects and Methods: The first phase was done as pilot in Egypt on 79 participants; the second phase was done in five centers: one center from Egypt, two centers from Pakistan and two centers from India (800, 92 and 113 subjects respectively). The third phase was done nationally as multicenter study on (1600) participants for ensuring its representativeness. Results: When compared to PCR technique, C-FAST device revealed sensitivity 95% to 100%, specificity 95.5% to 100%, PPV 89.5% to 100%, NPV 95% to 100% and positive likelihood ratios 21.8% to 38.5%. Conclusion: It is practical evidence that HCV nucleotides emit electromagnetic signals that can be used for its identification. As compared to PCR, C-FAST is an accurate, valid and non-invasive device.

Keywords: C-FAST- a valid and reliable device, distant cellular interaction, electromagnetic signal detection, non-invasive diagnosis of HCV

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Authors: Hassan Mahasneh, Abu Sesay

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We propose the use of relay terminals at the cell edge of an LTE-based cellar system. Each relay terminal is equipped with an omni-directional antenna. We refer to this scheme as the Omni-Relay (OR) scheme. The OR scheme coordinates the inter-cell interference (ICI) stemming from adjacent cells and increases the desired signal level at cell-edge regions. To validate the performance of the OR scheme, we derive the average signal-to-interference plus noise ratio (SINR) and the average capacity and compare it with the conventional universal frequency reuse factor (UFRF). The results show that the proposed OR scheme provides higher average SINR and average capacity compared to the UFRF due to the assistance of the distributed relay nodes.

Keywords: the UFRF scheme, the OR scheme, ICI, relay terminals, SINR, spectral efficiency

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Tina Wu, Andrew Martin

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The expansion of the Internet of Things (IoT) brings a new level of threat. Attacks on IoT are already being used by criminals to form botnets, launch Distributed Denial of Service (DDoS) and distribute malware. This opens a whole new digital forensic arena to develop forensic methodologies in order to have the capability to investigate IoT related crimes. However, existing proposed IoT forensic models are still premature requiring further improvement and validation, many lack details on the acquisition and analysis phase. This paper proposes an enhanced theoretical IoT digital forensic model focused on identifying and acquiring the main sources of evidence in a methodical way. In addition, this paper presents a theoretical acquisition framework of the different stages required in order to be capable of acquiring evidence from IoT devices.

Keywords: acquisition, Internet of Things, model, zoning

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Authors: Kimberley Kershaw, Denis Hyams-Ssekasi

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Although there is a wealth of information about refugees and Asylum seekers, Refugee job opportunities continue to be one of the most hotly contested areas and less researched within the social sciences. Refugees are a vital asset in the society due to their experiences, skills, and competences. However, society perceives them differently, and as such, their prior lived experiences are often underutilised. This research study gleans from the work conducted during the Refugee Employment Support Clinic delivered for 12 weeks within a University setting in the North West of England. The study is conducted using three perspectives, refugees, students, and researchers, allowing for identification of the challenges encountered by the refugees concerning job opportunities. Through the utilisation of the qualitative research method, the study has found that refugees experience a wide range of issues unrelated to their skills, prior experience, and education but rather due to the red tapes connected to their legal identity labelling. Refugees struggle to build reliable employment networks that appreciate and acknowledge their capabilities and talents, impacting their ability to navigate the labour market and classism. Notably, refugees are misunderstood within their new societies, and little care is taken to understand the unique struggles they face with respect to securing paid work in their industry or field of work due to their lack of experience in the UK. Unlike other European countries, it is evident that the UK has no strategic approach to enhancing the chances of paid or voluntary work for refugees. A clinic like this provided lenses for comprehending how refugees can be better supported with employment related opportunities. By creating a safe and conducive platform for honest and open discussion about employment and through collaborative approaches with local community agencies, doors were opened for social and professional networks to be built. The study concluded that there is a need for local communities and education establishments to be more aware of the prevailing challenges and in a position to support at all stages of their asylum claim in order for the perceptions of distrust and uncertainty around refugees to be minimised.

Keywords: refugees, employment, community, classism, education

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Authors: P. Řehoř, D. Holátová, V. Doležalová

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Paper deals with analysis of strategic management methods in non-profit making organization in the Czech Republic. Strategic management represents an aggregate of methods and approaches that can be applied for managing organizations - in this article the organizations which associate owners and keepers of non-state forest properties. Authors use these methods of strategic management: analysis of stakeholders, SWOT analysis and questionnaire inquiries. The questionnaire was distributed electronically via e-mail. In October 2013 we obtained data from a total of 84 questionnaires. Based on the results the authors recommend the using of confrontation strategy which improves the competitiveness of non-profit making organizations.

Keywords: strategic management, non-profit making organization, strategy analysis, SWOT analysis, strategy, competitiveness

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Authors: T. M. Al Muhareb

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Any organization should take into consideration the customers’ satisfaction while providing any service to their customers. The quality of services is always considered as the main aspect that attracts the customers’ attention and helps the airports to develop their services and operations. King Khalid International Airport is considered as the gateway of the Kingdom of Saudi Arabia. Therefore, the aim of this paper was to identify the quality service in the departure area at in King Khalid Airport. The SERVQUAL questionnaire was distributed among the passengers in King Khalid International Airport and the respondents have reached to 500 passengers. The results that are obtained from the SERVQUAL questionnaire showed that the quality of airport’s services is low.

Keywords: service quality, SERVQUAL methodology, King Khalid International Airport (KKIA), customers’ satisfaction

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Authors: Rahul Ganpat Mapari, D. G. Wakde

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In this paper, a proposed approach to improve the power factor of single-phase rectifiers and to regulate the output voltage against the change in grid voltage and load is presented. This converter topology is evaluated on the basis of performance and its salient features like simplicity, low cost and high performance are discussed to analyze its applicability. The proposed control strategy is bridgeless, transformer-less and output current sensor-less and consists of only two Bi-directional IGBTs and two diodes. The voltage regulation is achieved by a simple voltage divider to communicate to a controller to control the duty cycles of PWM. A control technique and operational procedure are also developed, both theoretically and experimentally. The experimental results clearly verify the theoretical analysis from the prototype connected to grid unity.

Keywords: Active Rectifier (AC-DC), power factor, single phase, voltage regulation

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Authors: Ji-Yeul Bae, Hyung Mo Bae, Jihyuk Kim, Hyung Hee Cho

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An air to air infrared missile poses a significant threat to the survivability of an aircraft due to an advanced sensitivity of sensor and maneuverability of the missile. Therefore, recent military aircraft is equipped with MAW (Missile Approach Warning) to take an evasive maneuver and to deploy countermeasures like chaff and flare. In this research, an effect of MAW sensitivity and resulting evasive maneuver on the survivability of the fighter aircraft is studied. A single engine fighter jet with Mach 0.9 flying at an altitude of 5 km is modeled in the research and infrared signature of the aircraft is calculated by numerical simulation. The survivability is assessed in terms of lethal range. The MAW sensitivity and maneuverability of an aircraft is used as variables. The result showed that improvement in survivability mainly achieved when the missile approach from the side of the aircraft. And maximum 30% increase in survivability of the aircraft is achieved when existence of the missile is noticed at 7 km distance. As a conclusion, sensitivity of the MAW seems to be more important factor than the maneuverability of the aircraft in terms of the survivability.

Keywords: air to air missile, missile approach warning, lethal range, survivability

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Authors: Kolesnik Nadezda A.

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The research aims to elaborate inter-organizational network relationships management model to maximize value co-creation. We propose a network management framework that requires evaluation of network partners with respect to their position and role in network; and elaboration of appropriate relationship development strategy with partners in network. Empirical research and approval is based on the case study method, including structured in-depth interviews with the companies from b2b market.

Keywords: inter-organizational networks, value co-creation, model, B2B market

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Authors: Rasim Alguliev, Farhad Yusifov

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Considering the international experience, conceptual and architectural principles of forming of electron government are researched and some suggestions were made. The assessment of monitoring of forming processes of electron government, intellectual analysis of web-resources, provision of information security, electron democracy problems were researched, conceptual approaches were suggested. By taking into consideration main principles of electron government theory, important research directions were specified.

Keywords: electron government, public administration, information security, web-analytics, social networks, data mining

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Authors: Ching-Sung Wang, Teng-Wei Wang, Zhen-Ting Zheng

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This study mainly concerns a safety device designed for child care. When children are out of sight or the caregivers cannot always pay attention to the situation, through the functions of this device, caregivers can immediately be informed to make sure that the children do not get lost or hurt, and thus, ensure their safety. Starting from this concept, a device is produced based on the relatively low-cost Bluetooth piconet system and a three-axis gyroscope sensor. This device can transmit data to a mobile phone app through Bluetooth, in order that the user can learn the situation at any time. By simply clipping the device in a pocket or on the waist, after switching on/starting the device, it will send data to the phone to detect the child’s fall and distance. Once the child is beyond the angle or distance set by the app, it will issue a warning to inform the phone owner.

Keywords: children care, piconet system, three-axis gyroscope, distance detection, falls detection

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Authors: Javad Yarmahmoudi, Alireza Mirzaee

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Many active and passive structural health monitoring (SHM) techniques have been developed for detection of the defects of plates. Generally, riveted joints hold the plates together and their failure may create accidents. In this study, well known active and passive methods were modified for the evaluation of the health of the riveted joints between the plates. The active method generated Lamb waves and monitored their propagation by using lead zirconate titanate (PZT) disks. The signal was analyzed by using the wavelet transformations. The passive method used the Fiber Bragg Grating (FBG) sensors and evaluated the spectral characteristics of the signals by using Fast Fourier Transformation (FFT). The results indicated that the existing methods designed for the evaluation of the health of individual plates may be used for inspection of riveted joints with software modifications.

Keywords: structural health monitoring, SHM, active SHM, passive SHM, fiber bragg grating sensor, lead zirconate titanate, PZT

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Srushti R. Joshi, Ujjwal Rakesh, Spoorthi Sripad

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The rapid advancement of remote sensing technologies has revolutionized plant health monitoring, offering valuable insights for precision agriculture and environmental management. This paper presents a comprehensive comparative analysis between the widely employed normalized difference vegetation index (NDVI) and state-of-the-art hyperspectral sensors in the context of plant health assessment. The study aims to elucidate the weigh ups of spectral resolution. Employing a diverse range of vegetative environments, the research utilizes simulated datasets to evaluate the performance of NDVI and hyperspectral sensors in detecting subtle variations indicative of plant stress, disease, and overall vitality. Through meticulous data analysis and statistical validation, this study highlights the superior performance of hyperspectral sensors across the parameters used.

Keywords: normalized difference vegetation index, hyperspectral sensor, spectral resolution, infrared

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Authors: Shubhakar Gupta, Dhruv Prakash, Apoorv Mehta

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In this project, we design a modular robot capable of using and switching between multiple methods of propulsion and classifying terrain, based on an Inertial Measurement Unit (IMU) input. We wanted to make a robot that is not only intelligent in its functioning but also versatile in its physical design. The advantage of a modular robot is that it can be designed to hold several movement-apparatuses, such as wheels, legs for a hexapod or a quadpod setup, propellers for underwater locomotion, and any other solution that may be needed. The robot takes roughness input from a gyroscope and an accelerometer in the IMU, and based on the terrain classification from an artificial neural network; it decides which method of propulsion would best optimize its movement. This provides the bot with adaptability over a set of terrains, which means it can optimize its locomotion on a terrain based on its roughness. A feature like this would be a great asset to have in autonomous exploration or research drones.

Keywords: modular robotics, terrain detection, terrain classification, neural network

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Authors: Tsugunosuke Sakai, Haruya Tamaki, Ryuichi Yoshida, Ryohei Egusa, Etsuji Yamaguchi, Shigenori Inagaki, Fusako Kusunoki, Miki Namatame, Masanori Sugimoto, Hiroshi Mizoguchi

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We aim to develop a full-body interaction game that could let children cooperate and interact with other children in small groups. As the first step for our aim, the objective of the full-body interaction game developed in this study is to make interaction between children. The game requires two children to jump together with the same timing. We let children experience the game and answer the questionnaires. The children using several strategies to coordinate the timing of their jumps were observed. These included shouting time, watching each other, and jumping in a constant rhythm as if they were skipping rope. In this manner, we observed the children playing the game while cooperating with each other. The results of a questionnaire to evaluate the proposed interactive game indicate that the jumping game was a very enjoyable experience in which the participants could immerse themselves. Therefore, the game enabled children to experience cooperation with others by using body movements.

Keywords: children, cooperation, full-body interaction game, kinect sensor

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Authors: Sergio Saponara, Luca Fanucci, Riccardo Cassettari, Ruggero Piernicola, Marco Righetto

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The paper presents an innovative networked radar system for detection of obstacles in a railway level crossing scenario. This Monitoring System (MS) is able to detect moving or still obstacles within the railway level crossing area automatically, avoiding the need of human presence for surveillance. The MS is also connected to the National Railway Information and Signaling System to communicate in real-time the level crossing status. The architecture is compliant with the highest Safety Integrity Level (SIL4) of the CENELEC standard. The number of radar sensors used is configurable at set-up time and depends on how large the level crossing area can be. At least two sensors are expected and up four can be used for larger areas. The whole processing chain that elaborates the output sensor signals, as well as the communication interface, is fully-digital, was designed in VHDL code and implemented onto a Xilinx Virtex 6.

Keywords: radar for safe mobility, railroad crossing, railway, transport safety

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Authors: Shiuh-Jer Huang, Yu-Sheng Hsu

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On-board available parking space detecting system, parking trajectory planning and tracking control mechanism are the key components of vehicle backward auto-parking system. Firstly, pair of ultrasonic sensors is installed on each side of vehicle body surface to detect the relative distance between ego-car and surrounding obstacle. The dimension of a found empty space can be calculated based on vehicle speed and the time history of ultrasonic sensor detecting information. This result can be used for constructing the 2D vehicle environmental map and available parking type judgment. Finally, the auto-parking controller executes the on-line optimal parking trajectory planning based on this 2D environmental map, and monitors the real-time vehicle parking trajectory tracking control. This low cost auto-parking system was tested on a model car.

Keywords: vehicle auto-parking, parking space detection, parking path tracking control, intelligent fuzzy controller

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Authors: Odette Umugiraneza, Etienne Nzaramyimana

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Confidence and beliefs are the main contributors to the improvement of teachers’ mathematical knowledge. The objective of this study was to investigate teachers’ confidence and beliefs towards technology use in teaching mathematics subjects in the Musanze District. The data were collected using closed and open questions. These were distributed to 118 secondary school senior 1 to 6 mathematics teachers in Musanze district. The findings revealed that the teachers’ confidence about the use of technology in teaching mathematics needs improvement. Apart from confidence, almost a third of the teachers convoyed negative beliefs that technology plays great importance in promoting the understanding of mathematics. Teachers as knowledge transmitters are required to join various professional courses towards technology integration in the teaching of mathematics, to improve the effectiveness of teaching and learning.

Keywords: knowledge, technology, teachers’ confidence, beliefs, barriers of technology use

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Authors: Mora Kestelman

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This paper analyzes various family groups of vulnerable populations as regards their family, educational, labor trajectory and sociability from a relational and historical approach based on archive research and fieldwork. Therefrom, their position and life projects are reconsidered as regards the planning and design of the habitat in which they are immersed. It concludes that a critical review of objectivity and subjectivity emphasizes the nonrational, often unconscious, forces that drive human and non-human relationships to configure identities, which, thus, permanently become constituent to the subjects.

Keywords: social psychology, urban planning, self concept, social networks, identity theory

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Authors: Bo Yang, Christopher Monterola

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Urban intersection control without the use of the traffic light has the potential to vastly improve the efficiency of the urban traffic flow. For most proposals in the literature, such lightless intersection control depends on the mass market commercialization of highly intelligent autonomous vehicles (AV), which limits the prospects of near future implementation. We present an efficient lightless intersection traffic control scheme that only requires Level 1 AV as defined by NHTSA. The technological barriers of such lightless intersection control are thus very low. Our algorithm can also accommodate a mixture of AVs and conventional vehicles. We also carry out large scale numerical analysis to illustrate the feasibility, safety and robustness, comfort level, and control efficiency of our intersection control scheme.

Keywords: intersection control, autonomous vehicles, traffic modelling, intelligent transport system

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Authors: Chithra A. V., Somoshree Datta, Sandeep Nithyanandan

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Sign Language Recognition (SLR) is the process of interpreting and translating sign language into spoken or written language using technological systems. It involves recognizing hand gestures, facial expressions, and body movements that makeup sign language communication. The primary goal of SLR is to facilitate communication between hearing- and speech-impaired communities and those who do not understand sign language. Due to the increased awareness and greater recognition of the rights and needs of the hearing- and speech-impaired community, sign language recognition has gained significant importance over the past 10 years. Technological advancements in the fields of Artificial Intelligence and Machine Learning have made it more practical and feasible to create accurate SLR systems. This paper presents a distinct approach to SLR by framing it as a video classification problem using Deep Learning (DL), whereby a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) has been used. This research targets the integration of sign language recognition into healthcare settings, aiming to improve communication between medical professionals and patients with hearing impairments. The spatial features from each video frame are extracted using a CNN, which captures essential elements such as hand shapes, movements, and facial expressions. These features are then fed into an RNN network that learns the temporal dependencies and patterns inherent in sign language sequences. The INCLUDE dataset has been enhanced with more videos from the healthcare domain and the model is evaluated on the same. Our model achieves 91% accuracy, representing state-of-the-art performance in this domain. The results highlight the effectiveness of treating SLR as a video classification task with the CNN-RNN architecture. This approach not only improves recognition accuracy but also offers a scalable solution for real-time SLR applications, significantly advancing the field of accessible communication technologies.

Keywords: sign language recognition, deep learning, convolution neural network, recurrent neural network

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Authors: Bekir Dogan

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The genus Jurinea is one of the larger genera within Asteraceae, comprising about 200 species. Jurinea is naturally distributed in central Asia, Turkey, Iran and the Mediterranean region. Jurinea has 23 species within the Mediterranean and Irano-Turanian phytogeographic regions of Turkey. Jurinea brevicaulis is locally endemic in Turkey. It grows Erzincan province in Turkey. Between 2005 and 2007, as a part of a revisional study of Jurinea in Turkey, the author carried out extensive field studies and herbaria and collected an enough number of specimens. In the field, the specimens' GPS coordinates, habitat and relevant field observations were recorded. International Union for Conservation of Nature (IUCN) threat category was given. The present study reviews the chorology of the Jurinea brevicaulis in Turkey based on recent taxonomic revision and available specimen data.

Keywords: Asteraceae, endemic, Jurinea, Turkey

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