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Vanadium redox flow batteries are a promising technology for energy storage, yet the mechanism of the kinetically limiting V2+/V3+ redox reaction remains poorly understood. Here, we elucidate the i...

In recent years the Deep generative networks have made it easy to create real face swaps in images and videos with less traces of manipulation, significantly improving the quality of these deepfakes. This improvement in fake media have gained more concern as for their use in fake terrorism, blackmail etc. This has drawn attention of both industry and government to distinguish and restrict their utilization. In spite of the way that these AI generated fake media produce realistic images upon detailed assessment, the proposed method can find some features that are unnatural which are not visible to the naked eyes. This paper uses a method known as frequency domain analysis after which a classifier will be used to differentiate the real and fake image. This paper evaluates our method on dataset of deepfake images collected from different website. Our work can show promising performance for detecting these deepfake images.

Road transport is the most widely used means of transportation around the world. With this high use of road transport, the safety of travellers’ becomes the prime concern for any governing authority. While some safety concerns arise from driver errors and environmental factors, most cases are a result of poor maintenance of these roads. Potholes, specifically, are one of the leading causes of road accidents throughout the world and need to be taken care of immediately, by the authorities. This paper presents a solution that makes use of civilians’ mobile sensors, along with image-based alternatives to detect potholes in real-time, using Machine Learning. The concerned authorities are then notified about the same through a web-based portal, to take the necessary action. The solution also incorporates pivoting existing complaints, location tagging and prioritization. Additionally, the solution provides a forecast of the likelihood of issues regarding potholes, constantly updating time series data of the locations.

Stock market plays a huge role in the economy of our country. Several attempts have been made to analyse and predict the stock market. While the existing systems try to exploit the patterns of stock prices using historical data, they do not take into the account the poor performance of the system. Moreover, there is no system which provides user specific trading strategies. The proposed solution explores filtration and different trading strategies using RoCE and Fuzzy Logic to solve the problem and predict the portfolio values. It also takes into consideration the sentiment aspect of trading using NLP and combines the two to efficiently to perform trading for even those users who have smattering knowledge about stock market thereby making it suitable for everyone.

The limited supply of fuels has driven us towards the development of electrical vehicles across the globe. As of now the plugging in type of charging system is being used to charge the batteries of EVs. For such system, user has to carry cables and needs to keep waiting to get the batteries charged. Also, the operation is not effective in snow and during rains. So, in this paper, we have implemented the method of inductive power transfer to charge the batteries of EV even when they are moving which can completely reduce the range anxiety problems with the help of road/track electrification for dynamic charging of electrical vehicles.

This paper presents the recognition of hardwritten signatures. This is troublesome as even the human eye does not have that much visual capacity to distinguish everything in the manually written signature. It is hard for people to recognize the original and the fashioned ones. By utilizing profound realization which utilizes the refined reproduction of human cerebrum, we can recognize the fraud done in signature with higher precision. Confirmation of signature may be achieved using either offline or online mode, depending on the program. Digital systems use contextual data from a target taken at the moment of making the target. Disconnected structures hack away at the mark’s image tested. A methodology for offline signature authentication actually utilizes a number of simple geometric highlights based on form. The highlights that are considered are area, eccentricity, center of gravity, pressure, pen up/down, and inclination. Before extricating the highlights, preprocessing of a filtered picture is important to detach the marked part and to expel any fake commotion present.

The research on this topic was important primarily because of the high rate of accidents due to negligence of the traffic signs present. This led to finding ways of creating an alert system for each vehicle which would ensure the safety of those driving the vehicle. Not only should it ensure the safety of the drivers, but also of all the pedestrians and animals through their detection. Many methods were studied including SSD, R-FCN, orthodox neural networks but the implementation of YOLO (You Only Look Once) was carried out because of the efficiency in the image processing rate and the accuracy of the object detection even with custom datasets. The datasets considered include GTSRB, COCO and Bosch for Traffic Signs, Human Detection and Traffic Light detection respectively. The model is trained along with a pre-trained YOLO dataset comprising of 80 classes. The execution results in an accuracy of 91.12% at an image processing speed of 30 fps beating all the methods present including SSD, R-FCN and R-CNN. The above accuracy is the average accuracy obtained on combining the 3 custom datasets, which independently has a much higher accuracy when trained on YOLO.

One-third of the total food produced gets wasted according to the Food And Agriculture Association of the United Nations. This wastage accounts for 1.3 billion tonnes and the scarcity of food is one of the major concerns globally. This paper presents comprehensive research on various factors that lead to the wastage of food in the retail sector. And a robust methodology is proposed which aims at reducing the waste to as minimal as possible in this sector. A method is proposed which integrates the inventory prediction and forecasting technique with smart dustbins which uses state of the art object detection technique to analyze the waste that gets thrown into bins in order to provide with insights to help optimize the use of raw materials that are used in preparing food and further redistribution and valorization of unpredictable waste. Thus producing minimal food waste.

Ragging has claimed hundreds of innocent lives and has ruined the careers of thousands of students. A total of 717 cases of ragging were reported in the English print media alone across the country from January 2007 to September 2013. However, the media reports tend to focus on extreme cases and do not reveal the true extent of ragging. Moreover, in the absence of empirical data, it is difficult to understand the processes involved in, and the ramifications of, ragging. This study examines the prevalence and types of ragging practices in educational institutions. The study covered 10,632 students from 37 educational institutions spread across 12 states in India. Findings show that almost 40 per cent students admitted to having experienced some kind of ragging. College-wise analysis of the results showed marked variations in the prevalence of ragging among colleges, thus pointing to the role of institutional factors in the occurrence of ragging. Variations in responses are also seen based on the kind of course pursued, gender, and place of residence of student, thus indicating that these are critical factors in influencing the prevalence, severity and kinds of ragging practices.

A canal wall down mastoidectomy (CWDM) is an effective technique for eradication of chronic suppurative otitis media (atticoantral disease) or cholesteatomas. A retrospective study was conducted at R.D. Gardi Medical college between 2015 and 2017 to evaluate the outcome of CWDM for patients with atticoantral type of CSOM. All new cases of MRM/RM which fulfilled the selection criteria were reviewed. The main outcome measures were the hearing outcome and status of dry ear postoperatively. 60 patients of CWDM (32 male, 28 female) were included for analysis. All patients in our study were between 7 and 52 years with mean age 28.38 years. The ossicular chain was eroded in all the cases. Improvement in Air–Bone–Gap was seen in 11 (18.33%), no change in 38 (63.33%) and 11 (18.33%) had deteriorated. In post operative outcome study of our 60 patients, 76.66% of the patients had dry healed cavity and non healed cavity was found to be in 23.33% of the patients. On analysis of data and comparison with other studies it was found that there are three important factors which influence hearing results and the outcome of surgery—status of ossicular chain, presence or absence of cholesteatoma, recurrence or residual disease.

Images are among the most common and popular representations of data. Digital images are used for professional and personal use ranging from official documents to social media. Thus, any Organization or individual needs to store and share a large number of images. One of the most common issues associated with using images is the potentially large file-size of the image. Advancements in image acquisition technology and an increase in the popularity of digital content means that images now have very high resolutions and high quality, inevitably leading to an increase in size. Image compression has become one of the most important parts of image processing these days due to this. The goal is to achieve the least size possible for an image while not compromising on the quality of the image, that gives us the perfect balance. Therefore, to achieve this perfect balance many compression techniques have been devised and it is not possible to pinpoint the best one because it is really dependent on the type of image to be compressed. So here we are going to elaborate on converting images into binary images and the Run length Encoding (RLE) algorithm used for compressing binary images. Now, RLE is itself a very effective and simple approach for compression of images but, sometimes, the size of an image actually increases after RLE algorithm is applied to the image and this is one of the major drawbacks of RLE. In this research paper we are going to propose an extension or maybe an upgradation to RLE method which will ensure that the size of an image never exceeds beyond its original size, even in the worst possible scenario

Images are among the most common and popular representations of data. Digital images are used for professional and personal use ranging from official documents to social media. Thus, any Organization or individual needs to store and share a large number of images. One of the most common issues associated with using images is the potentially large file-size of the image. Advancements in image acquisition technology and an increase in the popularity of digital content means that images now have very high resolutions and high quality, inevitably leading to an increase in size. Storage limitations on any device mean that only a small number of such images can be stored. Moreover, transmitting and uploading larger images takes up more time and bandwidth. Image compression has thus emerged as a vital part of image processing. The need of the hour is to reduce the size of the image as much as possible ,while maintaining a high level of quality and preserving all the details in the image. Compressed images can also be transmitted faster and require less bandwidth. In this paper we will be discussing two compression techniques- "Lempel–Ziv–Welch (LZW)" and "Run length Encoding (RLE))" and how to implement them. We will then compare them based on certain parameters.

Introduction: Dynamic chest radiography (DCR) is a novel technology that allows real time observation of respiratory kinetics and measurement of lung volumes during the respiratory cycle. Aim: To correlate measurements of lung area during deep inspiration on posteroanterior (PA) and lateral DCR images and derived lung volume with Total Lung Capacity (TLC) measured using whole body plethysmography. Methods: DCR images from 15 healthy volunteers obtained during deep breathing were analysed. A standardised protocol was used to measure maximal PA right lung apex-diaphragm distance, total PA lung area and lateral lung area during maximum inspiration. These values were used to derive lung volumes as previously described (1). The results were correlated with volunteers’ TLC. Pearson correlation coefficients were applied to determine correlations. Results: DCR measured PA lung area and calculated lung volume during maximal inspiration correlated significantly with TLC (r=1, p Conclusion: DCR measurements during deep breathing correlates with TLC measured using conventional method. DCR offers the prospect of measuring lung function with minimal patient effort. Larger studies are required. Reference: 1. A Method for the Determination of Total Lung Capacity from Posteroanterior and Lateral Chest Roentgenograms.’ American Review of Respiratory Disease, 96(3), pp. 548–552

Introduction: Dynamic chest radiography (DCR) is a novel technology that allows real time observation of respiratory kinetics and measurement of lung volumes during different parts of the respiratory cycle. Changes in lung area during respiration have been shown to correlate with vital capacity and total lung capacity.1 Aim: To correlate measurements of lung area during tidal and deep breathing on posteroanterior (PA) DCR images with spirometry measurements made on a group of healthy volunteers and COPD patients. Methods: Data from 21 DCR image sequences obtained during tidal and deep breathing from 13 patients (5 healthy volunteers, 8 COPD patients) were analysed. Standard protocols were used to measure lung area during maximum inspiration during both tidal and deep breathing. Model based partial coefficients, correcting for the effect of the type of breathing (deep or tidal) were evaluated. Pearson’s correlation coefficients were investigated over the average of the type of breathing. Results: On analysis of data averaged over the type of breathing, correlations between total lung area at maximal inspiration and both FEV1 and FEV1 % predicted were significant (p Conclusion: Relatively simple analysis of DCR image sequences offers the opportunity to obtain lung function data at the same time as obtaining the anatomical information provided by a chest x-ray. Reference: 1. Okhura N et al Evaluation of Pulmonary Function Using Dynamic Chest Radiographs: The Change Rate in Lung Area Due to Respiratory Motion Reflects Air Trapping in COPD, American Journal of Respiratory and Critical Care Medicine 2018;197:A3893

Aims To evaluate the dose-effect association between COVID-19 vaccination and probability of turning RT-PCR positive and to assess the correlation between disease severity and vaccination status. Methods A single centre cross-sectional study was conducted amongst 583 individuals presenting to COVID-19 testing clinic and 55 hospitalized COVID-19 patients. Vaccination status was assessed by the number of doses and duration since the last dose. Disease severity was evaluated by the requirement of hospitalisation and ICU admission/death. The association between the vaccination status and development of disease and its severity were statistically analyzed. Results The mean age of the population was 36.6 years and 82.6% had no comorbidities. The odds of turning RT-PCR positive was 0.17(95% CI: 0.11–0.27) among the clinical suspects who had taken both doses of the vaccine at least 14 days before (fully vaccinated). The odds of hospitalisation was 0.12(95% CI: 0.03–0.45) and ICU admission/death was 0.07(95% CI: 0.01–0.36) among fully vaccinated individuals. The protective role of vaccination was observed to start 14 days after receiving the first dose. Conclusions COVID-19 vaccination provides dose-dependent protection against the development of the disease. It also lowers the risk of hospitalisation and ICU admission/death in RT-PCR positive patients in a dose-dependent manner.

Integrating intermittent renewables like solar and wind to meet rising energy demand has necessitated the development of low-cost energy storage technologies like flow batteries for ensuring grid reliability. Aqueous redox flow batteries (RFBs) are a promising technology for storing energy on a large scale and releasing it based on demand. RFBs store energy in different oxidation states of species dissolved in electrolytes, which undergo charge transfer by accepting or donating electrons on the electrodes’ surface to store and release electricity. Several aqueous RFBs based on 3d transition metal ion redox couples have been demonstrated. Most of these RFBs employ acidic electrolytes and use porous carbon felts as electrodes due to their high surface area.1 The anions in these electrolytes affect the structure of the reactive species in solution by altering the metal ion coordination sphere. Additionally, these anions influence the charge transfer process either by getting adsorbed on the electrode surface and changing the number of available sites for the reaction, or changing the energy of the adsorbed intermediate. However, there is a lack of systematic study that identifies these structures and simultaneously looks at the adsorbed intermediates to understand the reaction mechanism in the presence of anions, hindering the design of novel electrolytes and electrocatalysts to control the charge transfer. In this work, we study the influence of anions on the V2+/V3+ redox couple by identifying the structures of V2+ and V3+ complexes and conducting kinetic measurements on a controlled glassy carbon surface in various acidic electrolytes (HClO4, H2SO4, HCl, HBr, and HI) to get mechanistic insights of V2+/V3+ charge transfer. We choose V2+/V3+ because of its enormous potential as negative electrode in aqueous vanadium-based RFBs and the similarity in the observed kinetic enhancement in the presence of chloride anions, as also seen for Cr2+/Cr3+, Fe2+/Fe3+, and Cu+/Cu2+ redox couples,2 suggesting the possible similarity in the reaction mechanism. Using a combination of extended X-ray absorption fine structure, UV-Vis spectroscopy, and density functional theory calculations, we show that V2+ exists as [V(H2O)6]2+ in all electrolytes, while V3+ exists as a mixture of [V(H2O)6]3+ and [V(H2O)5SO4]+ in H2SO4, and [V(H2O)6]3+, [V(H2O)5X]2+, and [V(H2O)4X2]+ (X = Cl, Br, and I) in HCl, HBr, and HI. We evaluate the exchange current densities (io ) and apparent activation energies (Ea ) in these electrolytes using a rotating disk electrode setup. We show that the io follows the order H2SO4 < HCl < HClO4 < HBr < HI, while the Ea follows the order of H2SO4 > HClO4 > HCl > HBr > HI. This difference in orders of io and Ea for HCl and HClO4 occurs because io has a contribution from both apparent frequency factor and Ea , highlighting the need to consider both apparent frequency factor and Ea independently to infer mechanistic insights. We show that anions influence the V2+/V3+ kinetics by changing the energetics of the adsorbed intermediate. This is identified by the decreasing Ea with increasing adsorption energy of the *[anion-V3+] intermediate. Because the adsorption energy of the intermediate follows the same order as anion polarizability,3 it also explains the use of anion polarizability to explain the kinetic behavior of these redox couples in previous studies. The apparent frequency factor follows the order opposite to the coverage of anions on glassy carbon, indicating the coverage is not responsible for the observed trends in V2+/V3+ activity in these acidic electrolytes. We compare the trends in adsorption energy of similarly forming intermediates during charge transfer for these other kinetically similar behaving redox couples (Cr2+/Cr3+, Fe2+/Fe3+, and Cu+/Cu2+) to rationalize trends in their inner-sphere charge transfer behavior. Further, we highlight how our findings show that electrocatalyst and electrolyte engineering to tune the intermediate’s energy is a viable strategy to control the charge transfer by comparing V2+/V3+ kinetic measurements on various metal electrocatalysts. REFERENCES: Dunn, B. et al. Sci. Mag. 334, 928–935 (2011). Agarwal, H. et al. ACS Energy Lett. 4, 2368–2377 (2019). Anbar, M. et al. J. Phys. Chem. 69, 973–977 (1965).

Summary Vanadium redox flow batteries suffer from inefficiencies partly due to the kinetics of the V2+/V3+ reaction, for which lack of mechanistic understanding hinders electrolyte and electrocatalyst design to improve reaction rates. Here, we provide insights into the V2+/V3+ reaction in HClO4, H2SO4, HCl, HBr, and HI. We identify the V2+ and V3+ structures in these electrolytes using extended X-ray absorption fine structure, UV-vis, and density functional theory; this includes the hydrated structures of V2+ and V3+ in water (i.e., without anion complexation). We show that V2+/V3+ kinetics correlate with the energy of vanadium intermediate bound to carbon through a bridging anion (∗[bridge−V3+]). The anion-induced kinetic enhancement is from a decreased activation energy because of changing ∗[bridge−V3+] energy. The ∗[bridge−V3+] energy increases in the order of anion polarizability (OH−

The exponential growth in the tele-density in India and around the world has put forth a lot of challenges for the network operators. The customers look for good signal reception, fast data speeds, and call quality while choosing their cell phone operators. The aim of this study is to obtain an optimum number of telecommunications towers using data science algorithms like mean shift, SVM classification, and K-means algorithm and practically implemented it using Android application. We propose a new method for optimizing the position of cell towers to get the coverage area of the widest service through three stages: Clustering, classification, and positioning. The proposed cell phone tower placement scheme involves data extraction from cell phone users through an Android application and the analysis of the data to obtain a set of possible candidate sites for establishing a base station.

When scaling up photo-electrochemical processes to larger areas than conventionally studied in the laboratory, substrate performance must be taken into consideration and in this work, a methodology to assess this via an uncomplicated 2 dimensional model is outlined. It highlights that for F-doped SnO2 (FTO), which is ubiquitously used for metal oxide photoanodes, substrate performance becomes significant for moderately sized electrodes (5 cm) under no solar concentration for state of the art Fe2O3 thin films. It is demonstrated that when the process is intensified via solar concentration, current losses become quickly limiting. Methodologies to reduce the impact of substrate ohmic losses are discussed and a new strategy is proposed. Due to the nature of the photo-electrode current-potential relationship, operation at a higher potential where the photo-current saturates (before the dark current is observed) will lead to a minimum in current loss due to substrate performance. Crucially, this work outlines an additional challenge in scaling up photo-electrodes based on low conductivity substrates, and establishes that such challenges are not insurmountable.

Energy demand is increasing due to the world’s growing population and rising quality of life, accompanied by increasing CO2 emissions. A shift towards renewable energy sources like solar and wind is needed to sustainably meet our growing energy requirements. However, the intermittent nature of renewable resources creates the need for energy storage technologies, which would store excess energy and then supply this stored energy when it is needed. Pumped hydroelectric is the most used electrical energy storage method, but is limited to specific geographical regions, leading to a push towards development of redox flow batteries (RFBs). Despite the unique ability of RFBs to decouple energy and power density while having high current densities, their commercial viability is limited by high costs. In particular, All Vanadium Redox Flow Batteries (VRFBs, i.e., (VO2+/VO2 +//V2+/V3+)) have received much interest due to the use of the common element vanadium that removes the issue of cross-contamination, leading to higher Coulombic efficiencies. The sluggish kinetics of V2+/V3+ redox couple on the negative electrode (Reaction 1), however, is found to limit VRFBs efficiency.1 Thus, improving V2+/V3+ kinetics can lead to higher current densities, reducing the overall cost of energy storage. Studies indicate the V2+/V3+ reaction is an inner sphere electron transfer based on differences in activity on certain surfaces,2 but there is a lack of the mechanistic understanding needed to further improve rates. V2+→ V3+ + e‾ (Reaction 1) Eº = −0.255 V vs SHE Traditionally, VRFBs use porous graphite felts with sulfuric acid (H2SO4) as an electrolyte, often without accurate area estimates needed for obtaining normalized current densities. Recent studies have shown increased stability of V ions and higher energy capacities for mixed H2SO4 and HCl electrolytes,3 but the effect of electrolyte on kinetics is also not well understood. Here, we study the V2+/V3+ reaction kinetics on a controlled electrode surface in H2SO4 and HCl, and show that the kinetics increase with State of Charge (SoC) and in the presence of Cl-, where Cl- also changes the V3+ coordination shell as detected by UV-Vis. We use a polished glassy carbon disk as the reaction surface, with high conductivity and controlled electrochemical surface area as compared to graphite felts. We find the V2+/V3+ reaction rates are independent of the total vanadium ion concentration, but instead depend on SoC. SoC was estimated by deconvoluting the individual V2+ and V3+ concentrations from UV-Vis. Exchange current densities for oxidation (iO,oxidation ) decrease with decreasing SoC, whereas Tafel slopes for oxidation (boxidation ) remain constant with SoC. Rate measurements at varied temperature (23.3 – 40.0 °C) were conducted to evaluate effective activation energies (Ea ) for the V2+/V3+ reaction at different SoC by two independent measurements, a) iO,oxidation and b) Charge Transfer Resistance (Rct ). The two independent methods for determining Ea matched closely, and show that Ea increases with decreasing SoC (Figure 1). This dependence of Ea on SoC along with high magnitudes (42 – 44 kJ mol-1 for 50% SoC, as compared to ∼13 kJ mol-1 for the outer sphere ferri-ferrocyanide redox couple4) confirms V2+/V3+ is an inner sphere reaction. This variation of iO,oxidation and Ea with SoC is indicative of a mechanism involving an adsorbed V intermediate affecting reaction kinetics. We measure higher iO,oxidation in HCl compared to H2SO4, which we hypothesize is due to a change in the coordination shell of the reacting specie, leading to formation of a different transition state with lower Ea . V2+ and V3+ ions in pure water typically exist as [V(H2O)6]2+ and [V(H2O)6]3+ (Oh symmetry) respectively with six labile water molecules constituting their first coordination sphere.5 We use UV-Vis to determine the structure of the coordination shell with anions present, by a shift in peak locations (based on ligand field strength) and absolute absorbance (depicting changes in molecular symmetry). The V2+ UV-Vis spectra remained unchanged in H2SO4, HCl, and mixed acid electrolytes of varied concentrations, indicating [V(H2O)6]2+ was the dominant species, with no anions in the first coordination sphere. However, the UV-Vis spectra of V3+ had a shift in peak locations with reduced absolute absorbance in HCl relative to H2SO4, indicating formation of a different V3+ complex, which we hypothesize is related to the change in redox kinetics. References: Aaron, D. et al. ECS Electrochem. Lett. 2, 29–31 (2013). Bourke, A. et al. J. Electrochem. Soc. 163, A5097–A5105 (2016). Li, L. et al. Adv. Energy Mater. 1, 394–400 (2011). Daum, P. H. et al. Anal. Chem. 41, 51 (1969). Richens, D. T. The Chemistry of Aqua Ions: Synthesis, structure and reactivity, 230–235 (1997). Figure 1

Background: Thalassemia is more prevalent in India. The main treatment of Thalassemia is blood transfusion. But the transfusion of blood has many side effects like iron overload, transfusion related infections etc. The objectives of the study were to assess the adequacy of blood transfusion for thalassemic patients and to determine the magnitude of transfusion transmitted infections among those patients.Methods: A cross sectional study was conducted in Murshidabad Medical College and Hospital, West Bengal for 1 month with the sample size of 116. The blood samples from the patients were taken from the patients attending for blood transfusion in transfusion centre of Murshidabad Medical College and Hospital for two weeks dated from 24.04.2017 to 05.05.2017 to check for the hemoglobin, ferritin level and hepatitis B, C and HIV infection.Results: Among the 116 patients, even after transfusion, 94% of the study participants have their hemoglobin levels below 7 gm/dl. Only 2 individuals got their hemoglobin levels more than 9 gm/dl and only 1 patient got HIV infection post transfusion which accounts for 0.9% of study population.Conclusions: Frequent Hb estimation will help to maintain the adequacy of blood transfusion and proper screening of the blood before transfusion can help in reducing these transfusion transmitted infections.

There are many traditional techniques through which diseases can be detected. Nadi Pareeksha is one of the most effective traditional techniques amongst them. Diseases can be detected using this technique by sensing various features of the pulse. This technique was originally implemented using the three fingers of human hand namely: the index, middle and ring finger. The exponential growth in the Artificial Intelligence domain has led to the creation of intelligent devices which can sense the pulse rate and detect diseases. In this paper, we are going to study their implementation and get to know about the various diseases which can be detected through them.

To improve the life of disabled people by use of automated tools, many scientists and organizations have been doing research on designing various products. One such intelligent product is the Voice Controlled Wheelchair. Many methods have been used to design it, each method uses a different hardware and hence providing specific functionalities. In this paper we examine few of the implemented methods and then propose a new model based on the concept of Artificial Intelligence which uses Raspberry Pi, for controlling the device, infrared and ultrasonic sensors for robust obstacle detection, USB microphone for voice input. Thus, enhancing the hardware used in previous models and at the same time achieving cost efficiency.

We have studied the effects of δ-p-doping on the operating characteristics of quantum dot (QD) lasers. It is well known that increasing δ-p-doping in a laser core increases both the internal loss and threshold current. For QD lasers however, it has the beneficial effects of increasing differential efficiency and saturated ground state gain. A further consequence of increased δ-p-doping is an ultra low linewidth enhancement factor (LEF) that can be tuned through zero and even made negative with increased doping at low injected current densities.