Search

Access to essential information resources through mobile devices has become a routine activity. From smart portable notebooks to tablets, smartphones to embedded devices, mobile databases are emerging as a key factor in the mobile computing ecosystem. These devices are handy and user-friendly; users can access information regardless of their geographic location, anytime, utilizing wireless and cellular communications. In addition to the convenience they offer, modern mobile systems exhibit the potential to promote the green computing paradigm and by extension a safer environment for humanity to thrive. The paper presents a concise but concrete review of mobile database systems in the green mobile computing ecosystem. The data source comprises 343 papers from notable repositories: IEEE Xplore, ACM Digital library, Springer and Science Direct. 43 papers were selected for analysis based on meeting the two preset suitability criteria: mobile databases and green computing. The study shows that there is not much literature on mobile database systems vis-à-vis the green computing ecosystem, hence, a promising research niche. The paper concludes that mobile databases are evolving rapidly and there is every possibility that their progress towards maturity could further reduce the energy consumption of mobile devices whose fundamental data store relies on these mobile databases. [ABSTRACT FROM AUTHOR]

Effective monitoring and detection of changes in forest cover are paramount for environmental stewardship and sustainable management practices. However, existing methodologies face challenges in obtaining consistent and high-quality satellite imagery, predicting deforestation-prone areas, optimizing deep learning architectures for change detection, and establishing robust evaluation metrics. This paper makes a comprehensive literature review to examine the progress in deep learning segmentation techniques and their application in change detection using satellite imagery. The key questions guide the investigation, focusing on optimization of satellite image collection, development of predictive models for deforestation risk assessment, enhancement of U-Net architectures for change detection, and establishment of evaluation metrics. Through the review, significant advancements are identified, particularly in integration of attention mechanisms and modified U-Net architectures. Contrastingly, traditional image differencing methods are surpassed by convolutional neural network (CNN) approaches, showcasing superior feature extraction and change detection accuracy. Noteworthy innovations include residual learning, attention gates and spatiotemporal encoders, which enhance segmentation performance. The findings underscore the potential of advanced methodologies to enhance detection and monitoring of changes in forest cover. By drawing insights from related fields such as urban planning and disaster monitoring, the study advocates for a holistic approach to environmental management. Ultimately, this review contributes to the evolution of deep learning techniques for change detection, with a specific focus on advancing forest cover monitoring practices. [ABSTRACT FROM AUTHOR]

The paper presents the design of an IoT-based system for preventing crop raiding by elephants. It uses state-of-the-art intrusion detection system assisted by a gauge pressure mechanism, using ceramic pressure sensors, pressure mats and related circuitry. It has been reported that use of unscientific high-voltage electrified fences around a crop field can even electrocute elephants. Hence, deterrents must be not only affordable but also nonviolent. The intrusion system alerts a control panel, which in turn sends RF alert to the monitoring hut, which further employs sound-scare techniques. This paper explores the usage of this IoT-based system for an area of 1-10 acres. Probability-based statistics has been used to produce weight-based analytics and prevent false alerts. [ABSTRACT FROM AUTHOR]

The paper present the design of an X-shaped compact wideband patch antenna with extended corners having dual slots on the patch surface for better performance suitable for millimeter frequency band. This antenna has got a novel design and is of small size to be used in wearable applications. It operates at millimeter wave band frequency, i.e., at 28.1 GHz and 43.49 GHz. The overall size of the antenna is 3.90mmx 2.90mm x 0.25mm. It is found that the proposed antenna has wideband characteristics with impedance bandwidth of 83.91% at 28.1GHz. The antenna also showed better radiation properties and low value voltage standing wave ratio (VSWR) having better efficiency. [ABSTRACT FROM AUTHOR]

Voice over Internet Protocol (VoIP) is simply the transport of voice traffic over the Internet or any IP-based packet-switched network. This is in contrast with the traditional telephone network, carrying voice data over dedicated circuit-switched transmission lines. A major challenge to implementing VoIP is to ensure sufficient bandwidth, and access to the available bandwidth is controlled and prioritized. Sufficient bandwidth is required to maintain highquality voice. On the other hand, controlling it limits bandwidth-hogging applications and guarantees access to delay-sensitive applications. The objective of this paper is to familiarize the readers with building a test VoIP lab setup using open-source tools; experimenting how different network impairments would affect VoIP quality; and explaining the lab setup activities, investigations, data analysis and research. Subsequently, the paper gives an overview of various technicalities such as operating system, servers, codec selection, signaling protocols, etc. involved in achieving network quality-of-service. [ABSTRACT FROM AUTHOR]

The paper explores the Kullback-Leibler divergence formalism (KLDF) applied to stable queue manifold. More potentially, both service time probability and cumulative functions, which make KLDF exact, are obtained. The credibility of KLDF is justified through consistency axioms. In other words, the current work provides a cutting-edge unification of information theory, combined with applied probability and divergence theory. Accordingly, this paper adds new knowledge, which extends a novel contemporary information theoretic link to some other different mathematical disciplines. The significance of Kullback-Leibler divergence (KLD) is highlighted through references to some potential applications of KLD to biometry. [ABSTRACT FROM AUTHOR]

As today’s mobile workforce and business environment expand to include a variety of users, the organization’s Virtual Private Network (VPN) is increasingly susceptible to security issues. Current VPN solutions on different operating systems are exposed to a large number of data breaches by hackers. This paper aims at implementing multiple convenient and secured ways to deploy, monitor and manage all user history, analyze their behavior and context, and automate their levels of access to corporate systems and resources. A software was written to observe, detect and record selected network activities such as repeated login attempts, username and password authenticity, status of VPN ports and IP addresses, and so on. The user interfaces were created using Javafx. Java programming language interfaced with Python was used for the logical parts, and H2 development tool was used for the database. Multiple servers in different locations are configured to check these network conditions and alert the Network Administrator via sms, email or other alarm system between once-per-minute and once-per-hour for the purposes of analysis and mitigation. The software further enables two-way communications between a chat client and a chat server based on Transmission Control Protocol (TCP). [ABSTRACT FROM AUTHOR]

The paper focuses on a novel hybrid strategy of using artificial intelligence (AI), real-time imaging, and predictive analysis for forest fire detection (Liu et al., 2020). Such approach drastically cuts operational costs, time, and the necessary manpower, using real-time imaging of AI and analytics (studies that use sensors and drones) and predictive algorithm via neuro-fuzzy Logic. The AI deep learning technology is well suited for areas with dense vegetation, giving valuable maps. They gather the information necessary for producing satellite images. In particular, the neuro-fuzzy Logic model collects and processes the data obtained from real-time satellite, drones and other observations. This makes a direct transition from staff-controlled UAS to robots. The synergistic combination of these techniques increases real-time detection and prediction accuracy, which in turn provides a robust solution for effective disaster management and early intervention in forest ecosystems. [ABSTRACT FROM AUTHOR]

Permanently shadowed regions (PSRs) on the moon are expected to contain large amounts of water and ice, which is crucial for sustainable exploration of the moon and beyond. However, there is limited information about small-scale features and ice distribution within the PSRs due to low resolution and/or poor quality of the orbital imagery captured. This paper proposes a method to use the existing general-purpose algorithm, Block-Matching and 3D Filtering (BM3D), to denoise the noisy crater images. [ABSTRACT FROM AUTHOR]

Many countries have been facing the problem of how to represent the economic downtime, economic crashing or economic recession in order to make appropriate decision or policy intervention. For this purpose, the paper estimates mobile telecommunication demand for 10 years of 27 countries using Ordinary Least-Square (OLS) method with qualitative information as dummy variable. The dummy variable examines the economic crashing time in South Korea during 1997. The paper uses price of mobile (mobile cellular monthly subscription) in telecommunication industry, income of consumers and investment as three independent variables, while the number of mobile cellular telephone subscribers per 100 inhabitants is used as dependent variable. The results indicate that the higher the income, the higher would be the demand for mobile cellular telephone subscribers per 100 inhabitants and investment has no effect as t-statistic is less than 2. In the same manner, the dummy variable has no statistical significance at 5% level on the demand for mobile telecommunication during economic crashes. This implies that the effect of economic crash or economic downtime in South Korea in 1997 is statistically insignificant in relation to demand for mobile telecommunication. [ABSTRACT FROM AUTHOR]

Monitoring the activities of examinees during examination is very challenging. The paper recognizes and classifies activities of examinees as suspicious or normal during examination using machine learning techniques. The processing and analysis of image data follows a typical sequence of distinct steps referred to as the vision pipeline. Data was acquired with a surveillance camera and frames extracted from the videos. Preprocessing activities include selecting the required frames from frame sequences, and cropping and segmenting foreground/background object. Video conversion to frame was accomplished with MATLAB scripts, while segmentation of image frames was achieved with GrabCut algorithm. Shape/pose features were extracted from objects using Histogram of Oriented Gradient (HOG) and Regionprop algorithms, and represented in feature vectors that were fed into Support Vector Machine (SVM) classifier. Holdout validation technique was used for the classifier training and tested from the given datasets. 70% of the dataset was used for training, while 30% was used for testing. The model gave an accuracy of 98.1% and 100%, respectively, for each examination scenario. The model accuracy was visualized in confusion matrix and the Receiver Operating Characteristic (ROC). MATLAB software was used as the simulation environment. The model demonstrated excellent performance, indicating that the system can adequately complement the efforts of invigilators in examination invigilation. [ABSTRACT FROM AUTHOR]

Significant power losses and a subpar voltage profile compromise the performance of radial distribution networks. The radial distribution system's performance can be upgraded by utilizing different techniques. The paper thoroughly analyzes two least expensive techniques--network reconfiguration and capacitor placement--for diminishing power losses and upgrading the radial distribution system's voltage profile, which boosts the system's performance. The methodology involves formulating an objective function that minimizes the overall real power loss in a radial distribution network while subject to equality and inequality requirements, which are addressed by dingo optimization algorithm for each technique. A standard IEEE 33-bus network was utilized as a test case, and simulations were performed utilizingMATLAB/SIMULINK package. The results demonstrate that network reconfiguration outperformed capacitor placement technique, with total real power loss diminishing by 36.76% versus 34.44% for capacitor placement technique. Further, the minimum voltage magnitude is compared with capacitor placement technique, which was 0.9393 pu; the least voltage magnitude compared with network reconfiguration technique was 0.9824 pu. Therefore, network reconfiguration is a smart choice for improving the efficiency of radial distribution networks. [ABSTRACT FROM AUTHOR]

A Local Area Network (LAN) is a private communication network for connecting computers and devices in a circumscribed location. This paper explains the design and implementation of LAN for a Hotel named 'Greenwich'. The network topology is achieved with the help of nodes such as Server, Routers, Switches, PCs, Wireless Devices, WLANs and Ethernet cables. The paper also deals with a few other topics like Server Configuration (HTTP, DNS, FTP and Email Servers), IP Address Configuration, transmission of packets among the devices in the network, working of IP phones and also how Virtual LANs can help in separating sectors in a network. All routers of all the floors are connected to the Internet. The entire network topology of Hotel Greenwich is simulated with the help of a simulating software called Cisco Packet Tracer (CPT). The implemented design is of primary level and can be enhanced for higher levels. [ABSTRACT FROM AUTHOR]

With the appearance of more and more bandwidth consuming applications in today's mobile data services market, telecom operators can no longer rely on price to attract and retain subscribers. Seamless roaming has become an important value-added service for improving back-end billing, subscriber relationships, bandwidth preservation through aggregation, quality of service and revenue generation. The paper presents the Mobile IP framework and methodology for supporting seamless global roaming within a geographic mobility domain. The goals and challenges of secured and seamless roaming solution are investigated. The responsibility of individual layers of the TCP/IP protocol stack is ill-defined with respect to mobility. The paper highlights the need for an adaptive generic algorithm to select, optimize and maintain transparent network connectivity for mobile users on the move, despite changing connection types and locations in a heterogeneous network environment. [ABSTRACT FROM AUTHOR]

Image segmentation is a process of dividing the image into some distinct regions. These regions are specially coherent in nature and have similar attributes. This technique is widely used for image analysis and to interpret the desired feature. The paper studies the Hidden Markov Random Fields (HMRF) and finds its Expectation Maximization (EM) algorithms. The main idea behind developing HMRF is to adjoin the "data faithfulness" and "model smoothness" which has very similar nature with the active contours, Gradient Vector Flow (GVF), graph cuts and random walks. The paper also uses HMRF-EM along with the Gaussian mixture models, and then color image segmentation process. These algorithms are implemented in MATLAB. In color image segmentation experiments, it is observed that the results obtained from HMRF segmentation are much smoother than the direct k-means clustering. The segmented object is much closer to the original shape than clustering. The segmentation time for Bacteria 1, Bacteria 2, SAR and brain images is 0.35, 0.43, 0.12 and 0.12, respectively. The accuracy for Bacteria 1, Bacteria 2, SAR and brain images is 97.70%, 98.06%, 98.89% and 97.35%, respectively. [ABSTRACT FROM AUTHOR]

The paper makes a survey of the optical fiber network installed at Deenbandhu Chhotu Ram University of Science and Technology (DCRUST) using reliability analysis, cost-benefit analysis and performance evaluation. Various reliability modeling-related aspects to calculate the reliability of the system have been analyzed. The proposed Markov model includes two units: one is operative unit and the other is hotstandby unit. Hotstandby unit is an optical fiber-based ring which acts as a protection ring. Operative unit is Optical Fiber Cable (OFC) of DCRUST. If working path (operative unit) fails, communication is done through protection path (hotstandby); if both units fail, then the whole system fails. Inspection, repair and replacement are done by regular repairman. The paper also includes a study of various measures of system effectiveness, different reliability parameters to evaluate profit and other measures related to the system. Graphical analysis between various system parameters has also been made. [ABSTRACT FROM AUTHOR]

The paper investigates the impact of sample points on SINR-based m-coverage probability in the context of 6G networks, considering the evolving landscape of mobile network architecture. Signal-Interference-Noise Ratio (SINR) is a critical metric for assessing cellular network performance. Conventionally, it is believed that increasing sample points significantly improves SINR coverage probability, especially within the range of 2^6 to 2^10. To explore this assertion, advanced simulations are conducted in both single-tier and multi-tier networking scenarios, employing the Poisson point process to spatially distribute nodes. The evaluation focuses on SINR values less than 1, using five distinct sample points. Surprisingly, the results reveal a remarkable finding: beyond an increment value of 2^2, increasing sample points has minimal impact on SINR-based m-coverage probability for both single-tier and multi-tier networks. This intriguing observation challenges the traditional understanding of the relationship between sample points and SINR coverage probability. The study's insights have significant implications for designing and optimizing 6G networks, guiding network planners in making informed decisions regarding resource allocation and computational tradeoffs. As 6G technology ushers in a transformative era of interconnectedness, understanding the saturation point of SINR coverage probability becomes pivotal for unleashing its full potential, fostering global connectivity and enabling innovative applications. [ABSTRACT FROM AUTHOR]

The development of intelligent motors heavily depends on lane detection. The paper proposes track detection to address issues like truncated detection accuracy of conventional techniques and poor real-time performance of sub-part of Machine Learning-based procedures. The proposed lane detection set of rules outperformed both traditional methods and Deep Learning-based methodologies in terms of accuracy, realtime performance, detection performance and interference resistance. Correct reputation cost and average processing time showed significant improvements. The provided set of guidelines is deemed to be essential for promoting the technological level of intelligent driver assistance and intelligent driver protection. [ABSTRACT FROM AUTHOR]

The paper proposes a truncated design for microstrip antenna of 5G satellite network applications. There are three different antennas with different dielectric materials designed in S, C and K-bands of frequency. The dielectric materials consist of FR-4 and beryllia with a dielectric constant of 4.3 and 6.5, respectively. There are different ways to feed the antenna, and coaxial probe feed is used in this paper. The calculation of dimensions of the patch, substrate and ground plane are discussed. The proposed design of the truncated path antennas is simulated in Computer Simulation Technology (CST) microwave studio. The characteristics of the antenna like VSWR, S-parameters, gain, radiation pattern, etc. are evaluated. [ABSTRACT FROM AUTHOR]

Liver cancer is the main source of death in the globe. Manual cancer tissue diagnosis is monotonous and troublesome. Hence, the paper fosters a high-exactness automatic diagnosis strategy for liver cancer growth. The image processing approach can utilize Computer Aided Diagnosis (CAD) for the arrangement of liver malignant growth to help the specialist. The CAD system is used to give a robotized approach to deal with successful arrangement of liver malignancy using feasible arrangements. Early affirmation and finding of liver growth are crucial for the space of liver cancers. Medical image processing is utilized to isolate tumors in a non-prominent way. Different strategies for recognizing liver tumors dependent upon abnormal lesion size and shape have been made. In like manner, automatic procedures for dividing the liver and liver tumors are pursued in clinical practice. This paper examines out a combination of liver malignant growth determination algorithms and philosophies. [ABSTRACT FROM AUTHOR]

In today’s world, everyone wants everything just by saying, therefore, audio plays a vital role. The paper discriminates between music and speech and proposes a related feature for retrieval of information, human interface with machine and editing the video. An attempt has been made, where a model is simulated using average cepstrum, wherein the human consciousness has the tendency of picking the cepstral changes that are larger. The data, i.e., cepstrum, will be reduced in magnitude exponentially if it is away from the mean value. Experiments are performed by comparing the classification of the feature between the proposed feature and existing features. This type of dynamic classification demonstrates that the test database for the proposed features has good quality of music and speech classification. [ABSTRACT FROM AUTHOR]

The paper designs a hybrid method for image fusion technique. The proposed algorithm is a combination of Directional Discrete Cosine Transform (DDCT) and Principal Component Analysis (PCA) technique. The proposed algorithm gives better results compared to other traditional techniques like Discrete Wavelet Transform (DWT) and segmentation. The multiple problems in image fusion like image noise, image pixel quality, etc. are identified using image filter. The paper also uses impulse filter to reduce image noise and improve pixel quality. [ABSTRACT FROM AUTHOR]

The paper proposes a compact-sized coronavirus-shaped Microstrip Patch Antenna (MPA) for wireless communication. A 15-20 GHz band of frequency is employed to analyze the effect of the shape on antenna's performance and characteristics. A low-cost FR4 dielectric substrate is used in the design and implementation of the coronavirus-shaped antenna, with suitable dimensions. The proposed antenna has six patterns depending upon the band of frequencies, and the same have been analyzed. The results show that the realized gain is better than -15 dB when using frequencies around 17 GHz, and total efficiency is about 70%. CST microwave software is used for designing and analysis. [ABSTRACT FROM AUTHOR]

The paper designs a low-power hybrid 1-bit full adder circuit. A new XNOR logic is designed using Complimentary Metal Oxide Semiconductor (CMOS) logic and pass transistor logic. CMOS weak inverters improve the power consumption. Carry logic is designed using transmission gates which reduces the carry propagation path. The proposed full adder is designed in 180 nm technology and post-layout simulations are done using Cadence Virtuoso. Power consumption and delay are performance parameters of the proposed full adder calculated and showed superiority over existing technology. [ABSTRACT FROM AUTHOR]

The paper proposes different techniques to design and implement a 32-bit Arithmetic and Logic Unit (ALU) such as implementation of 32-bit ALU for Digital Signal Processor (DSP) processor core, multifunctional processor, cryptographic processor and Wi-Fi enabled 32-bit ALU, reversible gate, Feedback Switch Logic (FSL) and clock gating. The number of operations increases in ALU, due to which the complexity of operation increases and causes an increase in power consumption also. To reduce the power consumption in ALU, the paper designs the ALU with clock gating. All these designs are implemented on FPGA. [ABSTRACT FROM AUTHOR]

Deployment of sensor nodes is an essential issue in wireless sensor networks (WSNs). The first step involves effective deployment of sensor nodes in the target area based on predetermined location to ensure guaranteed quality of surveillance. One of the hardest tasks in a WSN is figuring out how to route data from source to destination. Sensors gather data from the sensor network area and transmit it to various locations, and a large number of nodes must be deployed in a proper way. There are numerous deployment techniques available to enhance localization success rates and accuracy. The paper examines significant research findings related to sensor deployment, while also outlining key findings with examples of supporting applications. Finally, the unique characteristics and requirements of these deployment techniques for sensor nodes in 5G-integrated traditional WSNs are discussed. [ABSTRACT FROM AUTHOR]

In the last few years, wireless communication technologies have undergone several advancements. In this context, Unmanned Aerial Vehicles (UAVs) play a vital role. It is a big challenge to get accurate data with minimum collision in UAVs. The features of Direct Sequence Spread Spectrum (DSSS) like multiple access and antijamming are useful to get accurate data with minimum collision. DSSS can transmit and control data. DSSS is a common technique for data transmission. As the number of users increases, DSSS may not be sufficient to transmit and control data. To overcome this problem, we propose a novel hybrid technique for data transmission. The paper introduces a hybrid approach with the combination of Time Division Multiple Access (TDMA) with DSSS. TDMA can divide the frame into equal time slots, so it is easy to access more number of users with minimum data collision. In DSSS, the user data is multiplied with Barker code for spreading and TDMA allocates time slots to each user to allow the same frequency channel by dividing the signal into time slots. The paper uses 13-bit Barker code with the spread spectrum, i.e.,13 users can allow at a time and Bit Error Rate (BER) is evaluated. The work can be carried out in MATLAB. [ABSTRACT FROM AUTHOR]

Digital Hearing Aid (DHA) device selectively filters sound signals in subbands. Gain is added as per hearing loss mentioned in audiogram. DHA uses digital filters and amplifies processed signal, and this signal is transferred to the ear. Multiple DHA manufacturing companies all over world have innovative and miniature DHA devices in their product range. They do rigorous research and development to improve product functionalities. Most of them use design method of digital filters using selective amplification by adding gain to subband where patients have hearing loss. Nowadays, DHAs are more customized to individual patient hearing loss characteristics. Most of the available hearing aid designs use filter banks with fixed subbands. The paper focuses on reducing the complexity of the algorithms improving DHA user experience in changing noise and proposes a single reconfigurable transfer function type of digital Finite Impulse Response (FIR) filter to achieve a best fitting to audiogram as per the specifications with IEC 60118-15 standard, and the processed signals are tested with ITU-TPESQ standards. The paper uses International Speech Test Signal (ISTS) standard speech audio signal to test designed filter, and the results are found to be very satisfactory compared with the fixed filter banks. The paper discusses combined or reconfigured transfer function approach for use in DHA devices and design of reconfigurable FIR filter bank with adjusting different parameters in terms of requirements of DHA. [ABSTRACT FROM AUTHOR]

Green communication technology provides energy-saving implementation of mobile communication network in the fast growing digital communication field. Power consumption at the cellular base station has become an important problem in mobile wireless communication. The paper proposes a new algorithm based on green communication technology for solving the power issue, power reduction at the cellular base station transceiver with consideration of Quality-of-Service (QoS) and equality conditions of each cellular subscriber. The paper uses Orthogonal Space-Time Block Code (OSTBC) component carrier for downlink transmission of the base station. The simulation results prove that the proposed scheme provides better energy-saving scheme compared to other energy-saving schemes. [ABSTRACT FROM AUTHOR]

Microstrip array antennae are the ultimate solution for a variety of system applications, including air traffic control and collision avoidance radar. A microstrip antenna array is used since it is easy to design and fabricate. It has small size, light weight and high gain. Microstrip antenna array design is an important area of research in radar system that can meet the subject requirement. Microstrip antennae are used in a variety of wireless applications, including radars, wireless sensor networks, cellular phones and in medical applications. The paper proposes a design of different microstrip array antennae for weather radar system. Corporate feeding technique is incorporated for the design of an array. The proposed antennae resonate at 5.8 GHz. [ABSTRACT FROM AUTHOR]

This paper proposes a feature optimization and detection method based on the bee scout algorithm and derived support vector machine (DSVM). The DSVM approach reduces network training time by removing unused features. First, the raw EEG data is decomposed using discrete wavelet transform (DWT) into a sequence of frequencies. Before the feature extraction procedure, the spatiotemporal component of the decomposed EEG signal is represented as a twodimensional spectrogram using the shifting. To extract features, four pre-trained SVMs are employed. Dimensional reduction and feature selection are accomplished by bee scout-based EEG channel selection and DSVM approach. The proposed algorithm is tested on MAHNOB dataset. The results suggest that the proposed algorithm is more efficient than existing algorithms. [ABSTRACT FROM AUTHOR]

The paper studies the approaches to detecting, evaluating and categorizing plant diseases from digital images in the visible spectrum using appropriate processing techniques. Despite the fact that disease symptoms might appear anywhere on the plant, only approaches that looked at obvious symptoms in leaves and stems were examined. This was designed for various reasons: to keep the report short and because methods dealing with roots, seeds, and fruits have some unique characteristics that would necessitate a separate survey. The concepts chosen are organized into three categories based on their goal: detection, severity quantification and categorization. Each classification is further categorized based on the algorithm's primary technical solution. The paper also examines and contrasts the benefits and drawbacks of different prospective strategies. Image acquisition, image preprocessing, feature extraction and neural network-based categorization are a few of the techniques included. Researchers working on both vegetable pathology and pattern recognition can benefit from this study, which provides a detailed and accessible summary of this vital field of research. [ABSTRACT FROM AUTHOR]

The L-Band Digital Aeronautical Communications System (LDACS) 1 is an alternative to the current Very High Frequency (VHF) technology which meets the needs of upcoming demands. LDACS1, an Orthogonal Frequency Division Multiplexing (OFDM), operates in the L-Band between 960 and 1167 MHz frequencies installed in the middle of two Distance Measuring Equipment (DME) channels with 500 kHz spectral gap. In this paper--LDACS1 OFDM and LDACS1 2 x 2 Multiple Input Multiple Output (MIMO) are designed and simulated without any interference. The DME interference is introduced only to the LDACS1 OFDM, and significant degradation in the performance is observed. The pulse blanking technique helps in lowering the interference in the LDACS1 OFDM system, resulting in a performance close to the performance in the interference-free case. The Bit Error Rate (BER) performances for the conditions with and without interference and pulse blanking are compared. An improvement in the BER performance is seen with respect to design of LDACS1 2 x 2 MIMO system. [ABSTRACT FROM AUTHOR]

The 3rd Generation Partnership Project (3GPP) created a data storage architecture to create a truly distributed system in 5G, where structured data and unstructured data can be stored at central repositories. The Unstructured Data Storage Function (UDSF) will be used as data storage architecture and offers services for data storage, manipulation and retrieval to every Network Function (NF) within the 5G Service-Based Architecture (SBA) (Ahmed et al., 2018). In this paper, the implementation of UDSF has been explained. The UDSF can be used by any NFs to store local data within the centralized repository. The UDSF will be used for achieving a fully stateless AMF (Access and Mobility Function) that achieves higher reliability and load distribution in the network. [ABSTRACT FROM AUTHOR]

Image enhancement is necessary for satellite and medical pictures. The paper discusses numerous methods for improving satellite images. Minute details within an image can be discerned through the application of image enhancement techniques. Satellite-acquired images often suffer distortions due to atmospheric impediments. In order to address these challenges, various digital image enhancement techniques, including edge enhancement, contrast enhancement, resolution enhancement and brightness preservation, can be employed. The primary objective of enhancing satellite images is to manipulate them in a manner that enhances the amount of information contained in the resultant image compared to the original. [ABSTRACT FROM AUTHOR]

The use of podcast and Web radio episodes as a medium for delivery of course materials in educational institutions has attracted tremendous attention following the Covid-19 pandemic. In this paper, a Web application is written to facilitate the generation, editing, downloading and sharing of prerecorded lecture materials as a part of blended teaching and learning delivery in educational institutions. The podcast and Internet radio application receive live audio from an audio streaming server and play it out to the receiver or audience over the Web instead of over the air. The software automatically updates online multimedia content at set intervals as new and additional podcasts arrive from the originating source, and produce bespoke broadcasts, talks, discussions, messages, live music, news and entertainment activities throughout the day. The methodology adopted for the research is Component-Based Engineering (CBSE) model. The programming languages, components and tools used include HTML, Cascading Style Sheets (CSS) and JavaScript for front-end; MongoDb for database; Nodejs for Server side; Adobe audition and Aimp for recording input; streaming encoder; and a server side host. With this delivery medium, registered students, parents, families and community can download podcast episodes on-demand, and listen to scheduled radio broadcasts on their mobile devices, digital music players or computers at a time of their choice, thus improving instruction and learning. [ABSTRACT FROM AUTHOR]

The paper presents an analytical comparison of different types of multipliers like booth, array and wallace tree multipliers based on different performance metrics such as power, area and speed by reducing the partial products. Partial products are mainly responsible for complexity and area, so the paper focuses on reducing the partial product stage. It is found that wallace tree multiplier is best among all the above multipliers. As the multiplier size increases, the complexity also increases in wallace tree, so booth multiplier is best for large size. [ABSTRACT FROM AUTHOR]

In recent Radio Frequency (RF) systems, optimized feeder lines are used to minimize signal loss and improve impedance matching. The paper designs an optimized feeder line for low-profile antennas using RF toolbox in MATLAB software. Conventional feed-based impedance matching techniques are often complex to design, and sometimes loss occurs due to impedance mismatch. For that external matching technique, i.e., quarter-wave transformer is essential. In addition, various parameters such as reflection coefficient, Voltage Standing Wave Ratio (VSWR), return loss and S11 are considered to determine the best impedance matching. RF toolbox provides a comprehensive set of functions and algorithms to design, analyze and optimize RF systems and circuits, including microstrip antennas and matching networks. [ABSTRACT FROM AUTHOR]

The modern communication systems need development in antennas which have large bandwidth and low profile. Profile is the physical size of the antenna and it should be as small as possible for easy installation and operation. The paper deals with design aspects of square microstrip patch antenna with proximity feed and its properties. In this paper, simulations are carried out on C-band square microstrip patch antenna that suits Wi-Fi and bluetooth applications. With the adjusted parameters, the designed antenna exhibits maximum gain of 7 dBi and return loss -40 dB at center frequency 5 GHz. Desired patch antenna design was simulated using ANSYS HFSS software. The substrate material used for designing of microstrip patch antenna is RT Duroid 5880 and the thickness of the substrate is 1.6 mm. [ABSTRACT FROM AUTHOR]

Nowadays, Internet of Things (IoT) makes everything interconnected and perceived as the succeeding specialized rebellion. There are numerous applications of IoT such as smart automation at home, smart city, smart vehicle parking, in various agriculture fields, industrial automation process and health monitoring system. In human health monitoring system, IoT makes health equipment more effective by permitting real-time intensive care of patient health, in which various sensors take statistics of the patient and diminish humanoid error. IoT is emerging as a most important platform for numerous amenities and applications. In IoT, health monitoring system monitors patient's health remotely outside the hospital settings. This system continuously uploads patient's report on cloud system which helps the doctor to study in detail the variations in the patient's health conditions. Remote health monitoring structure is totally built on Global System for Mobile (GSM) network. By means of this system, the time period of both doctor and patients is saved; in addition, the surgeon can also assist in an emergency situation. The paper describes various techniques of human health monitoring system using IoT devices. Raspberry Pi and FPGA platform are mostly used to set up a platform for human health monitoring. [ABSTRACT FROM AUTHOR]

Human face finding and tracing is a technique to define whether a human face is existing or not in a framing image. Different from human face recognition which discriminates dissimilar faces, face discovery simply designates whether a human face is contemporary in a framing image or not. Face following determines the particular position or movement of human faces. The paper describes some famous and important algorithms and techniques which are used for face detection, tracing and recognition. Human face detection and recognition is the most important space of biometrics system (Muhammet and Resul, 2013). Biometric techniques are frequently used for substantiation process to isolate fingerprint, eye iris, retina, etc. The paper evaluates numerous procedures and methods for the fruitful detection, tracking and recognition of human face. [ABSTRACT FROM AUTHOR]

In this paper, the polling mechanism of IEEE 802.11n standard is examined with the objective of reducing the delay induced by polling a large number of stations in crowded hotspot. This standard, also known as high speed Wireless Local Area Network (WLAN), is competent to become carrier Wi-Fi in the Evolved Packet Core (EPC). Scheduling algorithms are playing a major role in yielding QoS in high speed wireless networks of next generation. IEEE 802.11n standard has some support for Quality of Service (QoS)-based scheduling, but one that focuses on polling is not dealt with much in detail. Polling is a centralized scheduling which is initiated by the Access Point (AP) to poll user stations. Most of the proposed polling mechanisms introduce delay when the number of stations under a given access point increases. The aim of this paper is to introduce new polling algorithm based on two-level priority queues to reduce the polling delay in a crowded WLAN hotspot. This in turn assures the QoS guarantees for delay-sensitive applications. The new algorithm is named as Smart_Poll. The paper also discusses the performance estimation of the proposed smart polling by comparing it with traditional polling. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is advancing rapidly, and this has improved the efficiency of many businesses and industries, including the transportation industry. AI in transportation might minimize travel, lower emissions and make roadways safer. Some examples of AI technologies used in the transportation sector include: Artificial Neural Networks (ANN), Genetic Algorithms (GA), Simulated Annealing (SA), Artificial Immune System (AIS), Ant Colony Optimizer (ACO) and Bee Colony Optimizer (BCO). The paper explores how AI is being used to address some of the most pressing issues in transportation today, including traffic control and safety. The limitations of AI transport are also discussed. [ABSTRACT FROM AUTHOR]

Transmission Control Protocol (TCP) is a communications standard that enables application programs and computing devices to exchange messages over a network. Since the 1970s, several TCP variants have been introduced to deal with the fast increasing network capacities, especially in high Bandwidth Delay Product (high-BDP) networks. The significance of this protocol stems from its numerous congestion management mechanisms, which manipulate TCP sending rates and force TCP to respond to congestion alerts. This is a transport layer protocol that interacts with the Internet Protocol (IP), which defines how devices send data packets to one another. The paper makes a comparative analysis of TCP variants like TCP Tahoe, TCP Reno, TCP New Reno, TCP Vegas and TCP Sack over different routing protocols like AODV, DSDV and DSR, considering factors such as Packet Delivery Ratio (PDR), Delay (milliseconds), and Throughput (Megabits per second), while the mobile nodes are in motion (considering different speeds) using the Network Simulation (NS-2) software. [ABSTRACT FROM AUTHOR]

Wireless mobile communication is entering the era of 5G technology very rapidly. This increasing demand for wireless communication is basically due to very simple installation and maintenance as compared to other wired network technologies. Therefore, rapidly increasing demand for broadband and high-speed mobile communication requires a very high-speed network which fulfils all the requirements of growing broadband wireless services. The only promising solution of the future wireless high-speed mobile communication is transmission of Radio Frequency (RF) signals on optical fiber. This results in a very high-speed network called Radio over Fiber (RoF) network, which is basically a combination of wired network and wireless services, in which RF signal is transmitted over the optical fiber by modulating the light with RF signal which contains the required information. RoF technology has become the backbone of the future broadband 5G wireless network. For RoF architecture, improvement in RoF link performance is the most challenging feature. In this paper, an overview of RoF architecture is elaborated with various RoF link performance improvement techniques. The comparison in terms of advantage and limitation of every performance improvement technique is summarized. The paper concludes with various research opportunities available in this area. [ABSTRACT FROM AUTHOR]

In the last decade, a lot of research has been done in the field for improving the Spectral Efficiency (SE) of the cellular wireless communicating channels. Multiple-Input and Multiple-Output (MIMO) technologies play a significant role in improving the overall efficiency of the system. The entire world is facing the major challenge of bandwidth crunch. Therefore, any work or contribution, which can improve the efficiency of the communication system, is a significant contribution to society. The paper presents a brief classification of the massive MIMO system designs, and the challenges are addressed. Initially, the MIMO system is introduced to increase SE by increasing the degree of freedom in space domain by multiple antennas. A large number of transmit-antennas provide more spectral and Energy Efficiency (EE) than conventional MIMO system. Then the massive MIMO system capacity bounds are evaluated considering the hardware impairment in the system. It is found that the performance of the channel estimation is essential for improving the overall efficiency of the massive MIMO system design. Mathematical modeling is given for evaluating the channel capacity; capacity is calculated and MIMO performance is evaluated. [ABSTRACT FROM AUTHOR]

Energy efficiency is an important issue in the proposed next-generation wireless communications as it severely affects human life on the earth. Two factors have mainly become an energy concern in the past decade: global warming due to CO2 emission and sea-level rise. Further, this issue has become a graver concern due to the ever increasing demand for data rates, spectral efficiency and quality of service combined with massive IoT communications. Therefore, there is a need for developing green mobile communications by 2020, which can ensure reduced energy consumption and increased battery life, besides increased capacity to enable massive deployment of small cell base stations. The proposed wireless communication network with the above features is referred to as an energy-efficient green mobile communication (5G). The paper surveys various technologies for realization of green mobile communication. Various technologies proposed for the realization of 5G are simultaneous wireless power and information transfer, massive Multiple Input Multiple Output (MIMO), millimeter waves and beamforming. An analysis has also been carried out in the case of the proposed massive MIMO antennas and beamforming technique as a case study of energy-efficient architecture. [ABSTRACT FROM AUTHOR]

Detection and removal of rain in the image are a complicated and critical problem due to difficulty of rain and its negative effects on the image. The paper proposes a novel, efficient and simple algorithm for detection and removal of rain from the image using Lo gradient minimization that can commonly eliminate rain pixels from the image. The algorithm is easy to use and successful in spotting and removing rain of sequential images. This method does not depend on local features but as an alternative locates necessary edges globally. This relevant edge information will wait until all other information is extracted in this manner and then rain pixels are removed. Next, to improve contrast in images, intensity enhancing is done using histogram adjustment technique. To compare this result with other techniques, quality index has been measured for the rain removal image. Experimental results showed that the proposed algorithm is extremely efficient as it removes rain successfully for even light and heavy rain in the image. [ABSTRACT FROM AUTHOR]

The cooperative communication system has gained lots of interest due to effective utilization of the allotted spectrum. Spectrum sensing techniques are a key factor for the cooperative communication system. A number of sensors are deployed to sense the spectrum hole. The group or clusters of the sensor are used to make out the decision about the spectrum hole. The presence of malicious sensor affects the performance of spectrum sensing. In this paper, the trust on the group or cluster has been identified based on the fuzzy classification. The fuzzy classifier takes the input in terms of reporting cluster trust value, neighborhood trust value and primary weight index. The membership values of these three linguistic variables are used by fuzzy interference system to decide the trust value of the group or cluster. The number of malicious user has been introduced during the simulation and performance has been identified. The Eigenvalue-based spectrum sensing is also simulated in this paper and the effect of different SNRs on the decision accuracy is shown. [ABSTRACT FROM AUTHOR]

The paper proposes an optimized and energy-efficient Ad Hoc On-Demand Distance Vector (AODV) routing protocol for Mobile Ad Hoc Network (MANET) based on dynamic forwarding probability, in which the Route Request (RREQ) packets are randomly controlled to increase the network lifetime and reduce packet loss in the flooding algorithm. The results are assessed using various network performance factors after implementing and integrating them into Network Simulator (NS2). According to the simulation findings, the proposed technique effectively reduced RREQ propagation messages. It is more efficient, has a longer network lifetime, and uniformly utilizes nodal residual energy, enhancing network throughput and minimizing routing overhead when compared to regular and modified AODV protocols. [ABSTRACT FROM AUTHOR]