Optimizing Wireless Connectivity: A Deep Neural Network-Based Handover Approach for Hybrid LiFi and WiFi Networks.

A Hybrid LiFi and WiFi network (HLWNet) integrates the rapid data transmission capabilities of Light Fidelity (LiFi) with the extensive connectivity provided by Wireless Fidelity (WiFi), resulting in significant benefits for wireless data transmissions in the designated area. However, the challenge of decision-making during the handover process in HLWNet is made more complex due to the specific characteristics of electromagnetic signals' line-of-sight transmission, resulting in a greater level of intricacy compared to previous heterogeneous networks. This research work addresses the problem of handover decisions in the Hybrid LiFi and WiFi networks and treats it as a binary classification problem. Consequently, it proposes a handover method based on a deep neural network (DNN). The comprehensive handover scheme incorporates two sets of neural networks (ANN and DNN) that utilize input factors such as channel quality and the mobility of users to enable informed decisions during handovers. Following training with labeled datasets, the neural-network-based handover approach achieves an accuracy rate exceeding 95%. A comparative analysis of the proposed scheme against the benchmark reveals that the proposed method considerably increases user throughput by approximately 18.58% to 38.5% while reducing the handover rate by approximately 55.21% to 67.15% compared to the benchmark artificial neural network (ANN); moreover, the proposed method demonstrates robustness in the face of variations in user mobility and channel conditions.

Effect of carbon allotropes and thickness variation on the EMI shielding properties of PANI/NFO@CNTs and PANI/NFO@RGO ternary composite systems.

The innovative design of thin, multiphase flexible composite systems with good mechanical properties, low density and improved EMI shielding properties at low filler content has become a key area of research. In this work, we report the low temperature synthesis of three-dimensional ternary composites (PANI/NFO@CNTs and PANI/NFO@RGO) by oxidative chemical polymerization of aniline in the presence of two different binary composites, viz. NFO@CNTs and NFO@RGO. Enhanced impedance matching is achieved by varying the ratio of the carbon allotropes (CNTs and RGO) to the ferrite component. The synthesis of NFO, PANI/NFO@CNTs and PANI/NFO@RGO is validated by XRD and FTIR spectroscopy. Field emission scanning electron microscopy (FE-SEM) confirmed the synthesis of core-shell structures of PANI/NFO@CNTs and PANI/NFO@RGO, where the binary composites (NFO@CNTs and NFO@RGO) serve as a core onto which a tubular PANI layer was coated. Shielding effectiveness of 22.36 dB (99.41% attenuation) is exhibited by the ternary composite PANI/NFO@CNTs (8 : 1), while for PANI/NFO@RGO (20 : 1) a total shielding effectiveness of 31 dB equivalent to 99.92% attenuation was observed at a thickness of 2 mm. The ternary composite PANI/NFO@RGO (20 : 1) 4 mm showed a maximum SET of 43 dB corresponding to 99.996% attenuation of incident EM waves. The enhanced EMI shielding properties of the synthesized ternary composite systems are accredited to good impedance matching, effective dielectric and magnetic loss mechanisms and good conductivity, which facilitate multiple reflections and scattering of incident radiation.

Synergistic effect of perovskites and nitrogen-doped carbon hybrid materials for improving oxygen reduction reaction.

A fundamental understanding of the electrochemical behavior of hybrid perovskite and nitrogen-doped (N-doped) carbon is essential for the development of perovskite-based electrocatalysts in various sustainable energy device applications. In particular, the selection and modification of suitable carbon support are important for enhancing the oxygen reduction reaction (ORR) of non-platinum group metal electrocatalysts in fuel cells. Herein, we address hybrid materials composed of three representative N-doped carbon supports (BP-2000, Vulcan XC-72 and P-CNF) with valid surface areas and different series of single, double and triple perovskites: Ba0.5Sr0.5Co0.8Fe0.2O3-δ, (Pr0.5Ba0.5)CoO3-δ, and Nd1.5Ba1.5CoFeMnO9-δ (NBCFM), respectively. The combination of NBCFM and N-doped BP-2000 produces a half-wave potential of 0.74 V and a current density of 5.42 mA cm-2 at 0.5 V versus reversible hydrogen electrode, comparable to those of the commercial Pt/C electrocatalyst (0.76 V, 5.21 mA cm-2). Based on physicochemical and electrochemical analyses, we have confirmed a significant improvement in the catalytic performance of low-conductivity perovskite catalyst in the ORR when nitrogen-doped carbon with enhanced electrical conductivity is introduced. Furthermore, it has been observed that nitrogen dopants play active sites, contributing to additional performance enhancement when hybridized with perovskite.

Mutual Coupling Reduction through Defected Ground Structure in Circularly Polarized, Dielectric Resonator-Based MIMO Antennas for Sub-6 GHz 5G Applications.

This paper describes a singly-fed circularly polarized rectangular dielectric resonator antenna (RDRA) for MIMO and 5G Sub 6 GHz applications. Circular polarization was achieved for both ports using a novel-shaped conformal metal strip. To improve the isolation between the radiators, a "S" shaped defective ground plane structure (DGPS) was used. In order to authenticate the estimated findings, a prototype of the suggested radiator was built and tested experimentally. Over the desired band, i.e., 3.57-4.48 GHz, a fractional impedance bandwidth of roughly 36.63 percent (-10 dB as reference) was reached. Parallel axial ratio bandwidth of 28.33 percent is achieved, which is in conjunction with impedance matching bandwidth. Between the ports, isolation of -28 dB is achieved Gain and other far-field parameters are also calculated and found to be within their optimum limits.

LPWAN Key Exchange: A Centralised Lightweight Approach.

The Internet of Things (IoT) is one of the fastest emerging technologies in the industry. It includes diverse applications with different requirements to provide services to users. Secure, low-powered, and long-range transmissions are some of the most vital requirements in developing IoT applications. IoT uses several communication technologies to fulfill transmission requirements. However, Low Powered Wide Area Networks (LPWAN) transmission standards have been gaining attention because of their exceptional low-powered and long-distance transmission capabilities. The features of LPWAN transmission standards make them a perfect candidate for IoT applications. However, the current LPWAN standards lack state-of-the-art security mechanism s because of the limitations of the IoT devices in energy and computational capacity. Most of the LPWAN standards, such as Sigfox, NB-IoT, and Weightless, use static keys for node authentication and encryption. LoRaWAN is the only LPWAN technology providing session key mechanisms for better security. However, the session key mechanism is vulnerable to replay attacks. In this paper, we propose a centralized lightweight session key mechanism for LPWAN standards using the Blom-Yang key agreement (BYka) mechanism. The security of the session key mechanism is tested using the security verification tool Scyther. In addition, an energy consumption model is implemented on the LoRaWAN protocol using the NS3 simulator to verify the energy depletion in a LoRaWAN node because of the proposed session key mechanisms. The proposed session key is also verified on the Mininet-WiFi emulator for its correctness. The analysis demonstrates that the proposed session key mechanism uses a fewer number of transmissions than the existing session key mechanisms in LPWAN and provides mechanisms against replay attacks that are possible in current LPWAN session key schemes.

Cyber-Security Threats and Side-Channel Attacks for Digital Agriculture.

The invention of smart low-power devices and ubiquitous Internet connectivity have facilitated the shift of many labour-intensive jobs into the digital domain. The shortage of skilled workforce and the growing food demand have led the agriculture sector to adapt to the digital transformation. Smart sensors and systems are used to monitor crops, plants, the environment, water, soil moisture, and diseases. The transformation to digital agriculture would improve the quality and quantity of food for the ever-increasing human population. This paper discusses the security threats and vulnerabilities to digital agriculture, which are overlooked in other published articles. It also provides a comprehensive review of the side-channel attacks (SCA) specific to digital agriculture, which have not been explored previously. The paper also discusses the open research challenges and future directions.

A Method for Cheating Indication in Unproctored On-Line Exams.

COVID-19 has disrupted every field of life and education is not immune to it. Student learning and examinations moved on-line on a few weeks notice, which has created a large workload for academics to grade the assessments and manually detect students' dishonesty. In this paper, we propose a method to automatically indicate cheating in unproctored on-line exams, when somebody else other than the legitimate student takes the exam. The method is based on the analysis of the student's on-line traces, which are logged by distance education systems. We work with customized IP geolocation and other data to derive the student's cheating risk score. We apply the method to approx. 3600 students in 22 courses, where the partial or final on-line exams were unproctored. The found cheating risk scores are presented along with examples of indicated cheatings. The method can be used to select students for knowledge re-validation, or to compare student cheating across courses, age groups, countries, and universities. We compared student cheating risk scores between four academic terms, including two terms of university closure due to COVID-19.

A Novel Hybrid Approach Based on Deep CNN Features to Detect Knee Osteoarthritis.

In the recent era, various diseases have severely affected the lifestyle of individuals, especially adults. Among these, bone diseases, including Knee Osteoarthritis (KOA), have a great impact on quality of life. KOA is a knee joint problem mainly produced due to decreased Articular Cartilage between femur and tibia bones, producing severe joint pain, effusion, joint movement constraints and gait anomalies. To address these issues, this study presents a novel KOA detection at early stages using deep learning-based feature extraction and classification. Firstly, the input X-ray images are preprocessed, and then the Region of Interest (ROI) is extracted through segmentation. Secondly, features are extracted from preprocessed X-ray images containing knee joint space width using hybrid feature descriptors such as Convolutional Neural Network (CNN) through Local Binary Patterns (LBP) and CNN using Histogram of oriented gradient (HOG). Low-level features are computed by HOG, while texture features are computed employing the LBP descriptor. Lastly, multi-class classifiers, that is, Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbour (KNN), are used for the classification of KOA according to the Kellgren-Lawrence (KL) system. The Kellgren-Lawrence system consists of Grade I, Grade II, Grade III, and Grade IV. Experimental evaluation is performed on various combinations of the proposed framework. The experimental results show that the HOG features descriptor provides approximately 97% accuracy for the early detection and classification of KOA for all four grades of KL.

Adversarial Attack and Defence through Adversarial Training and Feature Fusion for Diabetic Retinopathy Recognition.

Due to the rapid growth in artificial intelligence (AI) and deep learning (DL) approaches, the security and robustness of the deployed algorithms need to be guaranteed. The security susceptibility of the DL algorithms to adversarial examples has been widely acknowledged. The artificially created examples will lead to different instances negatively identified by the DL models that are humanly considered benign. Practical application in actual physical scenarios with adversarial threats shows their features. Thus, adversarial attacks and defense, including machine learning and its reliability, have drawn growing interest and, in recent years, has been a hot topic of research. We introduce a framework that provides a defensive model against the adversarial speckle-noise attack, the adversarial training, and a feature fusion strategy, which preserves the classification with correct labelling. We evaluate and analyze the adversarial attacks and defenses on the retinal fundus images for the Diabetic Retinopathy recognition problem, which is considered a state-of-the-art endeavor. Results obtained on the retinal fundus images, which are prone to adversarial attacks, are 99% accurate and prove that the proposed defensive model is robust.

A Comprehensive Open-Source Simulation Framework for LiFi Communication.

Light Fidelity (LiFi) is a new candidate for wireless networking that utilizes the visible light spectrum and exploits the existing lighting infrastructure in the form of light-emitting diodes (LEDs). It provides point-to-point and point-to-multipoint communication on a bidirectional channel at very high data rates. However, the LiFi has small coverage, and its optical gain is closely related to the receiver's directionality vis-à-vis the transmitter, therefore it can experience frequent service outages. To provide reliable coverage, the LiFi is integrated with other networking technologies such as wireless fidelity (WiFi) thus forming a hybrid system. The hybrid LiFi/WiFi system faces many challenges including but not limited to seamless integration with the WiFi, support for mobility, handover management, resource sharing, and load balancing. The existing literature has addressed one or the other aspect of the issues facing LiFi systems. There are limited free source tools available to holistically address these challenges in a scalable manner. To this end, we have developed an open-source simulation framework based on the network simulator 3 (ns-3), which realizes critical aspects of the LiFi wireless network. Our developed ns-3 LiFi framework provides a fully functional AP equipped with the physical layer and medium access control (MAC), a mobility model for the user device, and integration between LiFi and WiFi with a handover facility. Simulation results are produced to demonstrate the mobility and handover capabilities, and the performance gains from the LiFi-WiFi hybrid system in terms of packet delay, throughput, packet drop ratio (PDR), and fairness between users. The source code of the framework is made available for the use of the research community.

Modelling of Chest Wall Motion for Cardiorespiratory Activity for Radar-Based NCVS Systems.

Chest wall motion can provide information on critical vital signs, including respiration and heartbeat. Mathematical modelling of chest wall motion can reduce an extensive requirement of human testing in the development of many biomedical applications. In this paper, we propose a mathematical model that simulates a chest wall motion due to cardiorespiratory activity. Chest wall motion due to respiration is simulated based on the optimal chemical-mechanical respiratory control-based mechanics. The theory of relaxation oscillation system is applied to model the motion due to cardiac activity. The proposed mathematical chest wall model can be utilized in designing and optimizing different design parameters for radar-based non-contact vital sign (NCVS) systems.

Hybrid Electrochemical Deposition Route for the Facile Nanofabrication of a Cr-Poisoning-Tolerant La(Ni,Fe)O3-δ Cathode for Solid Oxide Fuel Cells.

Cr poisoning of cathode materials is one of the main degradation issues hampering the operation of solid oxide fuel cells (SOFCs). To overcome this shortcoming, LaNi0.6Fe0.4O3-δ (LNF) has been developed as an alternative cathode material owing to its superior chemical stability in Cr environments. In this study, we develop a hybrid electrochemical deposition technique to fabricate a nanostructured LNF-gadolinium-doped ceria (GDC) (n-LNF-GDC) cathode with enhanced active reaction sites for the oxygen reduction reaction. For this purpose, Fe and Ni cations are co-deposited onto an electrically conductive carbon nanotube-modified GDC backbone by electroplating, whereas La cations are successively deposited through a chemically assisted electrodeposition method. The proposed method involves a low-temperature (900 °C) calcination step of electrodeposited cations, which avoids the need of fabricating a GDC diffusion barrier layer which is otherwise needed to avoid the formation of insulating phases (e.g., La2Zr2O7) when fabricating by conventional high-temperature (≥1000 °C) sintering. Scanning electron microscopy images reveal a unique nanofibrous structure of n-LNF-GDC, which is believed to play an instrumental role in enhancing the electrochemical characteristics by increasing the active triple-phase boundaries. An anode-supported SOFC with the n-LNF-GDC cathode showed the superior performance of 0.984 W cm-2 at an intermediate temperature of 750 °C as compared to the power densities of 0.495 and 0.874 W cm-2 produced by LNF-GDC and state-of-the-art La0.6Sr0.4Co0.2Fe0.8O3-δ (LSCF)-GDC composite cathodes fabricated by conventional sintering. A short-term accelerated Cr-poisoning durability test indicated good electrochemical stability of n-LNF-GDC, whereas LSCF exhibited severe degradation. The electrochemically engineered nanostructured n-LNF-GDC can serve as an effective cathode for SOFCs to achieve high performance and long-term durability.

A novel application of breadth first algorithm for achieving collision free memory mapping.

We are living in the world of handheld smart devices including smart phones, mini computers, tablets, net-books and others communication devices. The telecommunication standards used in these devices includes error correction codes which are integral part of current and future communication systems. To achieve the higher data rate applications, the turbo and Low Density Parity Check (LDPC) codes are decoded on parallel architecture which in turn raises the memory conflict issue. In order to get the good performance, the simultaneous access to the entire memory bank should be performed without any conflict. In this article we present breadth first technique applied on transportation modeling of the problem for solving the collision issue of Turbo decoders in order to get optimized architecture solution.

Visible Light Communication: A System Perspective-Overview and Challenges.

Visible light communication (VLC) is a new paradigm that could revolutionise the future of wireless communication. In VLC, information is transmitted through modulating the visible light spectrum (400⁻700 nm) that is used for illumination. Analytical and experimental work has shown the potential of VLC to provide high-speed data communication with the added advantage of improved energy efficiency and communication security/privacy. VLC is still in the early phase of research. There are fewer review articles published on this topic mostly addressing the physical layer research. Unlike other reviews, this article gives a system prespective of VLC along with the survey on existing literature and potential challenges toward the implementation and integration of VLC.

Micromorphological investigation of leaf epidermis and seeds of Vitaceae from Pakistan using light microscopy and scanning electron microscopy.

This present study is the first report on the detailed foliar epidermal anatomy and micromorphology of seeds of five species of Vitaceae from Pakistan using light microscopy (LM) and scanning electron microscopy (SEM). The studied species occur at various localities particularly higher altitude. Qualitative and quantitative leaf micromorphological characters investigated here are related to shape and size of epidermal cells, anticlinal wall pattern, stomatal pore, guard cell, stomatal complex, subsidiary cells, and trichomes. Variations in size and shape were observed in the studied species. Irregular, polygonal and elongated epidermal cells with straight or undulate margins, stomata anomocytic type, and trichomes nonglandular, unicellular to multicellular in all the studied plants. Seed micromorphological qualitative characters studied are shape of margins, integument cell, apical notch, chalaza, anticlinal wall thickness, and quantitative characters are number of seeds per berry, length, and width of seed, length to width ratio. The detailed distribution and microscopic characteristics investigated of family Vitaceae has a distinguished role in identification at genus and species level and may provide evidence in the determination of taxonomic rank of the family in the phylogenetic tree. This study possesses potential for plant taxonomists to further evaluate the species for phytochemical studies and physiology. RESEARCH HIGHLIGHTS: Light microscopy and scanning electron microscopy was used for the micromorphological investigation of family Vitaceae Qualitative and quantitative characteristics were studied Variation in microscopic features of leaf epidermis and seeds Identification of species based on micromorphological characters.

Microscopic investigations of some selected species of Papilionaceae through SEM and LM from Skardu valley, northern Pakistan.

Pollen morphology of 10 species and foliar epidermal anatomy of eight species of Papilionaceae from Skardu valley, northern Pakistan has been estimated for the first time. The present study was commenced with an aim to provide a detailed account of the pollen morphology by scanning electron microscopy and foliar epidermal anatomy by light microscopy. The pollen aperture was tricolporate with reticulate exine in the selected species. Stomata types are actinocytic, paracytic, and anomocytic. Irregular or polygonal with undulate or straight walls, epidermal cells were reported. A unique diversity was observed in the foliar trichomes that show the taxonomic significance of the discrimination of taxa. Non-glandular trichomes were observed in the selected species which are unicellular with thin, long and pointed apical cells. Pollen and foliar micro morphological characters proved to be helpful for the identification of taxa at a specific level.

Synergy Estimation for Myoelectric Control Using Regularized NMF.

This paper investigates the problem of achieving robust control for assistive devices using surface electromyogram. We propose the use of regularized non-negative factorization using alternating least square algorithm for the estimation of muscle synergies. The proposed algorithm is tested for 3 different degrees of freedom only one active at a time, providing 97.6 - 99.5% accuracy and when compared with previously proposed methodology it reduces the delay time by 45%.

Ethnobotany of medicinal plants in district Mastung of Balochistan province-Pakistan.

ETHNOPHARMACOLOGICAL RELEVANCE: The aim of this study was to document the medicinal uses of plants in district Mastung of Balochistan province, Pakistan. The ethnobotanical results contain quantitative information on medicinal plants diversity documented for the first time in the area. MATERIALS AND METHODS: The information was collected through semi-structured interviews, rapid appraisal approach, open ended questionnaire and personal observations. Results were analyzed using quantitative indices of information consent factor (ICF), fidelity level (FL), use value (UV), frequency citation (FC) and relative frequency citation (RFC). RESULTS: In total of 102 plant species belonging to 47 families were reported for the medicinal purposes. Asteraceae was found to be dominant family in terms of species in the area with 11 species. The whole plant and leaves were noted as most frequently used parts (24%). Decoction (31% with 40 species) was the most commonly used preparation method. Highest ICF value (1) was recorded for antidote category. 100% fidelity level was found for four plant species i.e. Achillea welhemsii, Caralluma tuberculata, Citrullus colocynthis, and Seripidium quettense. The highest use value was reported for the Acroptilon repens (0.5) while highest RFC value was calculated for Berberis balochistanica and Citrullus colocynthis (0.18). Highest use report was calculated for Caralluma tuberculata, Citrullus colocynthis, Malva neglecta and Mentha longifolia with five use reports for each. CONCLUSIONS: The area is rich in medicinal plants and these plants are still commonly used for medicinal purposes among the people in their daily lives. However, there is a gradual loss of traditional knowledge about these plants in new generation. This study provides basis for the conservation of the local flora, its use as food and medicine. It also provides various socio-economic dimensions associated with the common people.

New dicoumarol sodium compound: crystal structure, theoretical study and tumoricidal activity against osteoblast cancer cells.

BACKGROUND: Enormous interest had been paid to the coordination chemistry of alkali and alkaline metal ions because of their role inside body viz; their Li(+)/Na(+) exchange inside the cell lead to different diseases like neuropathy, hypertension, microalbuminuria, cardiac and vascular hypertrophy, obesity, and insulin resistance. It has been presumed that alkali metal ions (whether Na(+) or K(+)) coordinated to chelating ligands can cross the hydrophobic cell membrane easily and can function effectively for depolarizing the ion difference. This unique function was utilized for bacterial cell death in which K(+) has been found coordinated valinomycin (antibiotic). RESULTS: Distinct sodium adduct (1) with dicoumarol ligand, 4-Hydroxy-3-[(4-hydroxy-2-oxo-4a,8a-dihydro-2H-chromen-3-yl)-phenyl-methyl]-chromen-2-one (L) is isolated from the saturated solution of sodium methoxide. Single crystal X-ray diffraction studies of the adduct reveals that sodium is in the form of cation attached to a methoxide, methanol and a dicoumarol ligand where carbonyl functional groups of the coumarin derivative are acting as bridges. The sodium compound (1) is also characterized by IR, (1)H-NMR, and (13)C{(1)H}-NMR spectroscopic techniques. The composition is confirmed by elemental analysis. DFT study for 1 has been carried out using B3LYP/6-13G calculations which shown the theoretical confirmation of the various bond lengths and bond angles. Both the compounds were studied subsequently for the U2OS tumoricidal activity and it was found that L has LD50 value of 200 µM whereas the sodium analog cytotoxicity did not drop down below 60%. CONCLUSION: A sodium analogue (1) with medicinally important dicoumarol ligand (L) has been reported. The crystal structure and DFT study confirm the formation of cationic sodium compound with dicoumarol. The ligand was found more active than the sodium analog attributed to the instability of 1 in solution state. Coumarin compound with sodium was observed to be less cytotoxic than the ligand, its LD50 value never dropped below 60%.

Synthesis, characterization, in vitro antimicrobial, and U2OS tumoricidal activities of different coumarin derivatives.

BACKGROUND: Coumarin and its derivatives are biologically very active. It was found that the enhanced activities are dependent on the coumarin nucleus. Biological significance of these compounds include anti-bacterial, anti-thrombotic and vasodilatory, anti-mutagenic, lipoxygenase and cyclooxygenase inhibition, scavenging of reactive oxygen species, and anti-tumourigenic. Our interest in medicinal chemistry of dicoumarol compounds have been developed by keeping in view the importance of coumarins along with its derivatives in medicinal chemistry. All the synthesized compounds were fully characterized by spectroscopic and analytical techniques and were screened for antimicrobial and U2OS bone cancer activities. RESULTS: 4-hydroxycoumarin was derivatized by condensing with different aldehydes yielding the dicoumarol and translactonized products. Elemental analyses, ESI(+,-) MS, 1H and 13C{1H}-NMR, infrared spectroscopy and conductance studies were used to characterize the synthesized compounds which revealed the dicoumarol and dichromone structures for the compounds. The compounds were screened against U2OS cancerous cells and pathogenic micro organisms. The compounds with intermolecular H-bonding were found more active revealing a possible relationship among hydrogen bonding, cytotoxicity and antimicrobial activities. CONCLUSION: Coumarin based drugs can be designed for the possible treatment of U2OS leukemia.