Search results for: mobile ad-hoc networks

Authors: Chun-Chuan Yang, Jeng-Yueng Chen, Yi-Ting Mai, Hsieh-Hua Liu

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By introduction of Relay Nodes (RNs), LTE-Advanced can provide enhanced coverage and capacity at cell edges and hot-spot areas. The authors have been researching the issue of power saving in mobile communications technology such as WiMax and LTE for some years. Based on the idea of Load-Based Power Saving (LBPS), three efficient power saving schemes for the user equipment (UE) were proposed in the authors’ previous work. In this paper, three revised schemes of the previous work in order to integrate RN and UE in power saving are proposed. Simulation study shows the proposed schemes can achieve significantly better power saving efficiency than the standard based scheme at the cost of moderately increased delay.

Keywords: DRX, LTE-A, power saving, RN

Procedia PDF Downloads 518

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

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Authors: Sara Ignoto, Elena M. Scalisi, Carmen Sica, Martina Contino, Greta Ferruggia, Antonio Salvaggio, Santi C. Pavone, Gino Sorbello, Loreto Di Donato, Roberta Pecoraro, Maria V. Brundo

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The new fifth generation technology (5G), which should favor high data-rate connections (1Gbps) and latency times lower than the current ones (<1ms), has the characteristic of working on different frequency bands of the radio wave spectrum (700 MHz, 3.6-3.8 GHz and 26.5-27.5 GHz), thus also exploiting higher frequencies than previous mobile radio generations (1G-4G). The higher frequency waves, however, have a lower capacity to propagate in free space and therefore, in order to guarantee the capillary coverage of the territory for high reliability applications, it will be necessary to install a large number of repeaters. Following the introduction of this new technology, there has been growing concern in recent years about the possible harmful effects on human health and several studies were published using several animal models. This study aimed to observe the possible short-term effects induced by 5G-millimeter waves on heartbeat of early life stages of Danio rerio using DanioScope software (Noldus). DanioScope is the complete toolbox for measurements on zebrafish embryos and larvae. The effect of substances can be measured on the developing zebrafish embryo by a range of parameters: earliest activity of the embryo’s tail, activity of the developing heart, speed of blood flowing through the vein, length and diameters of body parts. Activity measurements, cardiovascular data, blood flow data and morphometric parameters can be combined in one single tool. Obtained data are elaborate and provided by the software both numerical as well as graphical. The experiments were performed at 27 GHz by a no commercial high gain pyramidal horn antenna. According to OECD guidelines, exposure to 5G-millimeter waves was tested by fish embryo toxicity test within 96 hours post fertilization, Observations were recorded every 24h, until the end of the short-term test (96h). The results have showed an increase of heartbeat rate on exposed embryos at 48h hpf than control group, but this increase has not been shown at 72-96 h hpf. Nowadays, there is a scant of literature data about this topic, so these results could be useful to approach new studies and also to evaluate potential cardiotoxic effects of mobile radiofrequency.

Keywords: Danio rerio, DanioScope, cardiotoxicity, millimeter waves.

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Authors: Abbas Al-Refaie

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The research examines the factors that affect customer churn (CC) in the Jordanian telecom industry. A total of 700 surveys were distributed. Cluster analysis revealed three main clusters. Results showed that CC and customer satisfaction (CS) were the key determinants in forming the three clusters. In two clusters, the center values of CC were high, indicating that the customers were loyal and SC was expensive and time- and energy-consuming. Still, the mobile service provider (MSP) should enhance its communication (COM), and value added services (VASs), as well as customer complaint management systems (CCMS). Finally, for the third cluster the center of the CC indicates a poor level of loyalty, which facilitates customers churn to another MSP. The results of this study provide valuable feedback for MSP decision makers regarding approaches to improving their performance and reducing CC.

Keywords: cluster analysis, telecom industry, switching cost, customer churn

Procedia PDF Downloads 322

Authors: Juan Alfredo Guevara Carrio, Swamy Toolahalli Thipperudra, Riddhi Naik Dharmeshbhai, Sergio Graniero Echeverrigaray, Jose Vitorio Emiliano, Antonio Helio Castro

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In order to advance the hydrogen economy, several industrial sectors can potentially benefit from the trillions of stimulus spending for post-coronavirus. Blending hydrogen into natural gas pipeline networks has been proposed as a means of delivering it during the early market development phase, using separation and purification technologies downstream to extract the pure H₂ close to the point of end-use. This first step has been mentioned around the world as an opportunity to use existing infrastructures for immediate decarbonisation pathways. Among current technologies used to extract hydrogen from mixtures in pipelines or liquid carriers, membrane separation can achieve the highest selectivity. The most efficient approach for the separation of H₂ from other substances by membranes is offered from the research of 2D layered materials due to their exceptional physical and chemical properties. Graphene-based membranes, with their distribution of pore sizes in nanometers and angstrom range, have shown fundamental and economic advantages over other materials. Their combination with the structure of ceramic and geopolymeric materials enabled the synthesis of nanocomposites and the fabrication of membranes with long-term stability and robustness in a relevant range of physical and chemical conditions. Versatile separation modules have been developed for hydrogen separation, which adaptability allows their integration in industrial prototypes for applications in heavy transport, steel, and cement production, as well as small installations at end-user stations of pipeline networks. The developed membranes and prototypes are a practical contribution to the technological challenge of supply pure H₂ for the mentioned industries as well as hydrogen energy-based fuel cells.

Keywords: graphene nano-composite membranes, hydrogen separation and purification, separation modules, indsutrial prototype

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Authors: Jae Moon Lee

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In general, algorithms to find continuous k-nearest neighbors have been researched on the location based services, monitoring periodically the moving objects such as vehicles and mobile phone. Those researches assume the environment that the number of query points is much less than that of moving objects and the query points are not moved but fixed. In gaming environments, this problem is when computing the next movement considering the neighbors such as flocking, crowd and robot simulations. In this case, every moving object becomes a query point so that the number of query point is same to that of moving objects and the query points are also moving. In this paper, we analyze the performance of the existing algorithms focused on location based services how they operate under gaming environments.

Keywords: flocking behavior, heterogeneous agents, similarity, simulation

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Erica Lima

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The objective of this paper is to discuss relevant points about teaching translation in Brazilian universities and the possible impacts of blogs and social networks to translator education today. It is intended to analyze the curricula of Brazilian translation courses, contrasting them to information obtained from two social networking groups of great visibility in the area concerning essential characteristics to become a successful profession. Therefore, research has, as its main corpus, a few undergraduate translation programs’ syllabuses, as well as a few postings on social networks groups that specifically share professional opinions regarding the necessity for a translator to obtain a degree in translation to practice the profession. To a certain extent, such comments and their corresponding responses lead to the propagation of discourses which influence the ideas that aspiring translators and recent graduates end up having towards themselves and their undergraduate courses. The postings also show that many professionals do not have a clear position regarding the translator education; while refuting it, they also encourage “free” courses. It is thus observed that cyberspace constitutes, on the one hand, a place of mobilization of people in defense of similar ideas. However, on the other hand, it embodies a place of tension and conflict, in view of the fact that there are many participants and, as in any other situation of interlocution, disagreements may arise. From the postings, aspects related to professionalism were analyzed (including discussions about regulation), as well as questions about the classic dichotomies: theory/practice; art/technique; self-education/academic training. As partial result, the common interest regarding the valorization of the profession could be mentioned, although there is no consensus on the essential characteristics to be a good translator. It was also possible to observe that the set of socially constructed representations in the group reflects characteristics of the world situation of the translation courses (especially in some European countries and in the United States), which, in the first instance, does not accurately reflect the Brazilian idiosyncrasies of the area.

Keywords: cyberspace, teaching translation, translator education, university

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Authors: Tomas Seidl

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'Enjoy the Czech traditions with all sences!' is the main communication headline of one of the major current marketing project representing the intangible cultural heritage of the Czech Republic to its visitors. The project CZ.1.06/4.1.00/12.08915 and CZ.1.06/4.1.00/12.08916 which is solved in the period 2013-2015 is co-financed form the EU financial sources from the Integrated Operational Programme. The primary goal of the project was to analyze the dislocation and potential of the intangible cultural heritage in the Czech Republic. Further goal was to prepare a useful regionalization. An as solution based on the outcomes the creative and media strategy was created and prepared. The processor – CzechTourism expect the following web and mobile application development and successful marketing campaign in 2015.

Keywords: traditions, intangible cultural heritage, Czech Republic, CzechTourism, digital performance

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Authors: Sariyapa Kantawan, Muanfun Kongsomsawaeng

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Chanthaburi River community is an old mixed-culture village established in the 16th century. The town advanced more rapidly than others due to the ease of transportation at the time, which used the river as a road. Therefore, the province's first road begins here, propelling it to become an important commercial and trading center for almost a century. As a result of diverse culture, the architecture has been affected by Western, Thai, Chinese, and Vietnamese, resulting in a new and distinctive style. To share the realm of memory, digital media enable the city to communicate its history and culture. This article describes a project that combines the concepts of digital storytelling and augmented reality and connects them to Chanthaburi River Community Culture by using QR codes as makers to display 3D models on mobile screens.

Keywords: digital storytelling, community culture, river community, cultural heritage, augmented reality

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Authors: Mohammed Alruwaili‬

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Nowadays, renewable energy resources are playing an important role in replacing traditional energy resources such as fossil fuels by integrating solar energy with conventional energy. Concerns about the environment led to an intensive search for a renewable energy source. The Rapid growth of distributed energy resources will have prompted increasing interest in the integrated distributing network in the Kingdom of Saudi Arabia next few years, especially after the adoption of new laws and regulations in this regard. Photovoltaic energy is one of the promising renewable energy sources that has grown rapidly worldwide in the past few years and can be used to produce electrical energy through the photovoltaic process. The main objective of the research is to study the impact of PV in distribution networks based on real data and details. In this research, site survey and computer simulation will be dealt with using the well-known computer program software ETAB to simulate the input of electrical distribution lines with other variable inputs such as the levels of solar radiation and the field study that represent the prevailing conditions and conditions in Diriah, Riyadh region, Saudi Arabia. In addition, the impact of adding distributed generation units (DGs) to the distribution network, including solar photovoltaic (PV), will be studied and assessed for the impact of adding different power capacities. The result has been achieved with less power loss in the loop distribution network from the current condition by more than 69% increase in network power loss. However, the studied network contains 78 buses. It is hoped from this research that the efficiency, performance, quality and reliability by having an enhancement in power loss and voltage profile of the distribution networks in Riyadh City. Simulation results prove that the applied method can illustrate the positive impact of PV in loop distribution generation.

Keywords: renewable energy, smart grid, efficiency, distribution network

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Authors: Jose A. Diaz-Olivares, Nafise Mahdavian, Farhad Abtahi, Kaj Lindecrantz, Abdelakram Hafid, Fernando Seoane

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Despite new recommendations and guidelines for the evaluation of occupational risk assessments and their prevention, work-related musculoskeletal disorders are still one of the biggest causes of work activity disruption, productivity loss, sick leave and chronic work disability. It affects millions of workers throughout Europe, with a large-scale economic and social burden. These specific efforts have failed to produce significant results yet, probably due to the limited availability and high costs of occupational risk assessment at work, especially when the methods are complex, consume excessive resources or depend on self-evaluations and observations of poor accuracy. To overcome these limitations, a pervasive system of risk assessment tools in real time has been developed, which has the characteristics of a systematic approach, with good precision, usability and resource efficiency, essential to facilitate the prevention of musculoskeletal disorders in the long term. The system allows the combination of different wearable sensors, placed on different limbs, to be used for data collection and evaluation by a software solution, according to the needs and requirements in each individual working environment. This is done in a non-disruptive manner for both the occupational health expert and the workers. The creation of this solution allows us to attend different research activities that require, as an essential starting point, the recording of data with ergonomic value of very diverse origin, especially in real work environments. The software platform is here presented with a complimentary smart clothing system for data acquisition, comprised of a T-shirt containing inertial measurement units (IMU), a vest sensorized with textile electronics, a wireless electrocardiogram (ECG) and thoracic electrical bio-impedance (TEB) recorder and a glove sensorized with variable resistors, dependent on the angular position of the wrist. The collected data is processed in real-time through a mobile application software solution, implemented in commercially available Android-based smartphones and tablet platforms. Based on the collection of this information and its analysis, real-time risk assessment and feedback about postural improvement is possible, adapted to different contexts. The result is a tool which provides added value to ergonomists and occupational health agents, as in situ analysis of postural behavior can assist in a quantitative manner in the evaluation of work techniques and the occupational environment.

Keywords: ergonomics, mobile technologies, risk assessment, smart textiles

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Authors: Ying-Lun Tseng Chiu-Ying Chen

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Taiwan's Mental Health Act was amended at the end of 2022; they added regulations regarding refusing compulsory treatment by patients with mental illnesses. In addition, not only by an examination committee, the judge must also assess the patient's need for compulsory treatment. Additionally, the maximum of compulsory hospitalization has been reduced from an unlimited period to a maximum of 60 days. They aim to promote the healthcare autonomy of individuals with mental illnesses in Taiwan and prevent their silenced voice in medical decision-making while they still possess rationality. Furthermore, they plan to use community support and social care networks to replace the current practice of compulsory treatment in Taiwan. This study uses qualitative research methodology, utilizing interview guidelines to inquire about the experiences of Taiwanese who have undergone compulsory hospitalization, compulsory community treatment, and compulsory medical care. The interviews aimed to explore their feelings when they were subjected to compulsory medical intervention, the inside of their illness, their opinions after treatments, and whether alternative medical interventions proposed by them were considered. Additionally, participants also asked about their personal life history and their support networks in their lives. We collected 12 Taiwanese who had experienced compulsory medical interventions and were interviewed 14 times. The findings indicated that participants still possessed rationality during the onset of their illness. However, when they have other treatments to replace compulsory medical, they sometimes diverge from those of the doctors and their families. Finally, doctors prefer their professional judgment and patients' families' option. Therefore, Taiwanese mental health patients' power of decision-making still needs to improve. Because this research uses qualitative research, so difficult to find participants, and the sample size rate was smaller than Taiwan's population, it may have biases in the analysis. So, Taiwan still has significant progress in enhancing the decision-making rights of participants in the study.

Keywords: medical decision making, compulsory treatment, medical ethics, mental health act

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Authors: Saleh Alshehri

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Human skin detection is a vital step in many applications. Some of the applications are critical especially those related to security. This leverages the importance of a high-performance detection algorithm. To validate the accuracy of the algorithm, image databases are usually used. However, the suitability of these image databases is still questionable. It is suggested that the suitability can be measured mainly by the span the database covers of the color space. This research investigates the validity of three famous image databases.

Keywords: image databases, image processing, pattern recognition, neural networks

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Authors: Karel Borovec, Jerzy Gorecki, Tadeas Ochodek

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Combustion of solid fuels is one of the main sources of mercury in the environment. To reduce the amount of mercury emitted to the atmosphere, it is necessary to modify or optimize old purification technologies or introduce the new ones. Effective reduction of mercury level in the flue gas requires the use of speciation systems for mercury form determination. This paper describes tests and provides comparison of two industrial portable and continuous systems for mercury speciation in the flue gas: Durag HM-1400 TRX with a speciation module and the Portable Continuous Mercury Speciation System based on the SGM-8 mercury speciation set, made by Nippon Instruments Corporation. Additionally, the paper describes a few analytical problems that were encountered during a two-year period of using the systems.

Keywords: continuous measurement, flue gas, mercury determination, speciation

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Authors: Netanel Stern

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Artificial intelligence (AI) algorithms have emerged as powerful tools in the field of psychiatry, offering new possibilities for enhancing diagnosis and treatment outcomes. This article explores the utilization of AI algorithms in psychiatry, highlighting their potential to revolutionize patient care. Various AI algorithms, including machine learning, natural language processing (NLP), reinforcement learning, clustering, and Bayesian networks, are discussed in detail. Moreover, ethical considerations and future directions for research and implementation are addressed.

Keywords: AI, software engineering, psychiatry, neuroimaging

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Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

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In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: camshift algorithm, computer vision, Kalman filter, object tracking

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Authors: Elena Maria Scalisi, Roberta Pecoraro, Martina Contino, Sara Ignoto, Carmelo Iaria, Santi Concetto Pavone, Gino Sorbello, Loreto Di Donato, Maria Violetta Brundo

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5G Technology is evolving to satisfy a variety of service requirements that may allow high data-rate connections (1Gbps) and lower latency times than current (<1ms). In order to support a high data transmission speed and a high traffic service for eMBB (enhanced mobile broadband) use cases, 5G systems have the characteristic of using different frequency bands of the radio wave spectrum (700 MHz, 3.6-3.8 GHz and 26.5-27.5 GHz), thus taking advantage of higher frequencies than previous mobile radio generations (1G-4G). However, waves at higher frequencies have a lower capacity to propagate in free space and therefore, in order to guarantee the capillary coverage of the territory for high reliability applications, it will be necessary to install a large number of repeaters. Following the introduction of this new technology, there has been growing concern over the past few months about possible harmful effects on human health. The aim of this preliminary study is to evaluate possible short term effects induced by 5G-millimeter waves on embryonic development and early life stages of Danio rerio by Z-FET. We exposed developing zebrafish at frequency of 27 GHz, with a standard pyramidal horn antenna placed at 15 cm far from the samples holder ensuring an incident power density of 10 mW/cm2. During the exposure cycle, from 6 h post fertilization (hpf) to 96 hpf, we measured a different morphological endpoints every 24 hours. Zebrafish embryo toxicity test (Z-FET) is a short term test, carried out on fertilized eggs of zebrafish and it represents an effective alternative to acute test with adult fish (OECD, 2013). We have observed that 5G did not reveal significant impacts on mortality nor on morphology because exposed larvae showed a normal detachment of the tail, presence of heartbeat, well-organized somites, therefore hatching rate was lower than untreated larvae even at 48 h of exposure. Moreover, the immunohistochemical analysis performed on larvae showed a negativity to the HSP-70 expression used as a biomarkers. This is a preliminary study on evaluation of potential toxicity induced by 5G and it seems appropriate to underline the importance that further studies would take, aimed at clarifying the probable real risk of exposure to electromagnetic fields.

Keywords: Biomarker of exposure, embryonic development, 5G waves, zebrafish embryo toxicity test

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Authors: Elizabeth Malebogo Mosepele

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Road transport has become increasingly common in the world; people rely on road networks for transportation purpose on a daily basis. However, environmental impact of roads on surrounding landscapes extends their potential effects even further. This study investigates the impact of road network on natural vegetation. The study will provide baseline knowledge regarding roadside vegetation and would be helpful in future for conservation of biodiversity along the road verges and improvements of road verges. The general hypothesis of this study is that the amount and condition of road side vegetation could be explained by road network conditions. Remote sensing techniques were used to analyze vegetation conditions. Landsat 8 OLI image was used to assess vegetation cover condition. NDVI image was generated and used as a base from which land cover classes were extracted, comprising four categories viz. healthy vegetation, degraded vegetation, bare surface, and water. The classification of the image was achieved using the supervised classification technique. Road networks were digitized from Google Earth. For observed data, transect based quadrats of 50*50 m were conducted next to road segments for vegetation assessment. Vegetation condition was related to road network, with the multinomial logistic regression confirming a significant relationship between vegetation condition and road network. The null hypothesis formulated was that 'there is no variation in vegetation condition as we move away from the road.' Analysis of vegetation condition revealed degraded vegetation within close proximity of a road segment and healthy vegetation as the distance increase away from the road. The Chi Squared value was compared with critical value of 3.84, at the significance level of 0.05 to determine the significance of relationship. Given that the Chi squared value was 395, 5004, the null hypothesis was therefore rejected; there is significant variation in vegetation the distance increases away from the road. The conclusion is that the road network plays an important role in the condition of vegetation.

Keywords: Chi squared, geographic information system, multinomial logistic regression, remote sensing, road side vegetation

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Authors: Rishabh Nagpal, Riya Uchagaonkar, Venkata Naga Narasimha Ashish Mernedi, Ahmed Hambaba

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The rapid evolution of technology in the communication sector continually seeks to bridge the gap between different communities, notably between the deaf community and the hearing world. This project develops a comprehensive American Sign Language (ASL) recognition system, leveraging the advanced capabilities of convolutional neural networks (CNNs) and vision transformers (ViTs) to interpret and translate ASL in real-time. The primary objective of this system is to provide an effective communication tool that enables seamless interaction through accurate sign language interpretation. The architecture of the proposed system integrates dual networks -VGG16 for precise spatial feature extraction and vision transformers for contextual understanding of the sign language gestures. The system processes live input, extracting critical features through these sophisticated neural network models, and combines them to enhance gesture recognition accuracy. This integration facilitates a robust understanding of ASL by capturing detailed nuances and broader gesture dynamics. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing diverse ASL signs, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced ASL recognition system and lays the groundwork for future innovations in assistive communication technologies.

Keywords: sign language, computer vision, vision transformer, VGG16, CNN

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Authors: Sanjit Kumar Paul, A. A. Mamun, M. R. Amin

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The Linear propagation of the dust-acoustic wave in a dusty plasma consisting of Boltzmann distributed electrons and ions and mobile charge fluctuating positive dust grains has been investigated by employing the reductive perturbation method. It has been shown that the dust charge fluctuation is a source of dissipation and its responsible for the formation of the dust-acoustic waves in such a dusty plasma. The basic features of such dust-acoustic waves have been identified. It has been proposed to design a new laboratory experiment which will be able to identify the basic features of the dust-acoustic waves predicted in this theoretical investigation.

Keywords: dust acoustic waves, dusty plasma, Boltzmann distributed electrons, charge fluctuation

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Authors: H. Yousefnia, A. Golabi Dezfuli, S. Zolghadri, M. Hosntalab

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Peptide receptor radionuclide therapy is nowadays used for the treatment of various abnormalities with somatostatin receptors. In this study, 166Ho-DOTATOC was prepared and the best conditions for its radiolabeling was obtained. For this purpose, a certain of DOTATOC was added to a vial containing 166Ho. various experiments by varying ligand concentration, pH, temperature and time were performed to determine the best conditions. Radiochemical purity of the complex was assessed by instant thin layer chromatography method utilizing 0.9% NaCl as the mobile phase. 166Ho-DOTATOC was prepared with radiochemical purity of higher than 95% at the optimized condition (pH=4, temperature: 95° C, time:30 min). In 0.9% NaCl, free Ho cation was developed at Rf of 0.8 while the complex was remained at the front of the paper.

Keywords: Ho-166, neuroendocrine, octreotide, quality control

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Tarek Aly

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The shoulder is the most mobile joint whose stability requires the interaction of both dynamic and static stabilizers. Its wide range of movement predisposes to a high susceptibility to dislocation, accounting for nearly 50% of all dislocations. This trauma typically results in ligament injury (e.g., labral tear, capsular strain) or bony fracture (e.g., loss of glenoid or humeral head bone), which frequently causes recurrent instability. Patients with significant glenoid defects may require Latarjet procedure, which involves transferring the coracoid to the antero-inferior glenoid rim. In spite of outstanding results, 15 to 30% of cases suffer complications. In this article, we discuss the diagnosis of recurrent shoulder instability, the surgical technique and various complications of Latarjet procedure.

Keywords: recurrent, anterior gleno-humeral instability, latarjet, unstable shoulder

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Authors: Srinaath Anbu Durai, Wang Zhaoxia

Abstract:

Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data.

Keywords: sentiment analysis, Covid-19, housing price prediction, tweets, social media, Singapore HDB, behavioral economics, neural networks

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Authors: Mohammad Altaf Hossain

Abstract:

A growing body of literature in urban studies has presented that urban precarity has been a lived experience for low-income groups of people in the cities of the Global South. It does not necessarily mean that cities in the Global North, where advanced capitalist economies exist, avoided the adverse realities of urban precarity. As a multifaceted condition, it creates other associated precariousness in lives -for example, economic deprivation, mental stress, and housing precarity. The interrelations between urbanity and precarity have been ubiquitous regardless of the developed and developing countries. People, mainly manual labourers with low incomes, go through uncertainties in every aspect of life. By analysing qualitative data and embracing structure-agency interaction, this paper intends to present how Bangladeshi migrants experience housing precarity in Dublin. Continued population growth and political economy factors such as labour market inequality, financialisation of the private rental sector, and the impact of cuts to government funding for social housing provision are combined to produce a housing supply crisis, affordability, and access in the city. As a result, low-income people practice informality in securing jobs and housing. The macro-structural components of this analysis include the Irish housing policy, the European labour market, the immigration policy, and the financialised housing market. The micro-structural components of South Asian communities’ experiences include social networks and social class. Access to social networks and practices of informality play a significant role in enabling them to negotiate urban precarity, including housing crises and income insecurity. In some cases, the collective agency of ethnic diaspora communities plays a vital role in negotiating with structural constraints.

Keywords: housing precarity, housing pathways, migration, agency, Dublin

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Authors: Chrysavgi Papagianni

Abstract:

The tension between global and local has been a usual topic in discussions regarding globalization. Instead of reproducing the usual ‘gloom and doom’ arguments surrounding many of these discussions, the present paper will focus on Emirati film production and more particularly on the work of the acclaimed director Nojoom Alghanem, in order to highlight how local culture can, in fact, become a force of resistance, or else a medium of localization. As a matter of fact, Alghanem’s films, especially Sounds of the Sea, Hamama and Nearby Sky are apt examples of a localizing force in action as they tap into the audience’s dormant memories of the pre-oil past, in a country that has been swept by unprecedented development and globalization in the last 60 years. What becomes evident is that the remediation of memories in Alghanem’s films makes them more ‘mobile’ and thus allows them to circulate better in today’s network society.

Keywords: culture, film, globalization, identity

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Authors: Elmahdi Mohammadine, Ahouzi Esmail, Najid Abdellah

Abstract:

This contribution aims to present a new protected hybrid WDM/TDM PON architecture using Wavelength Selective Switches and Optical Line Protection devices. The objective from using these technologies is to improve flexibility and enhance the protection of GPON networks.

Keywords: Wavlenght Division Multiplexed Passive Optical Network (WDM-PON), Time Division Multiplexed PON (TDM-PON), architecture, Protection, Wavelength Selective Switches (WSS), Optical Line Protection (OLP)

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Authors: Anurag Saxena, Alkesh Agrawal, Dinesh Kumar

Abstract:

The next generation mobile communication systems i.e. fourth generation (4G) was developed to accommodate the quality of service and required data rate. This project focuses on multiple access technique proposed in 4G communication systems. It is attempted to demonstrate the IDMA (Interleave Division Multiple Access) technology. The basic principle of IDMA is that interleaver is different for each user whereas CDMA employs different signatures. IDMA inherits many advantages of CDMA such as robust against fading, easy cell planning; dynamic channel sharing and IDMA increase the spectral efficiency and reduce the receiver complexity. In this, performance of IDMA is analyzed using QC-LDPC coding scheme further it is compared with LDPC coding and at last BER is calculated and plotted in MATLAB.

Keywords: 4G, QC-LDPC, CDMA, IDMA

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Authors: S. Chebbi, A. Meddeb

Abstract:

The distribution networks are often exposed to harmful incidents which can halt the electricity supply of the customer. In this context, we studied a real case of a critical zone of the Tunisian network which is currently characterized by the dysfunction of its plan of protection. In this paper, we were interested in the harmonization of the protection plan settings in order to ensure a perfect selectivity and a better continuity of service on the whole of the network.

Keywords: distribution network Gabes-Tunisia, continuity of service, protection plan settings, selectivity

Procedia PDF Downloads 507