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Objective: In this study, the epidemiology, clinical features, and diagnosis of paediatric asthma in a Pakistani hospital were examined. Methods: Between January 2018 and January 2019, a cross-sectional study was carried out in the paediatrics department of the LRH hospital in Peshawar. The research gathered information on the epidemiology, clinical traits, and diagnosis of paediatric asthma. To analyze the data, descriptive statistics were used. Results: The results of the study showed that the prevalence of asthma in the study population was 54%. The most common clinical symptoms reported by the children were wheezing (62.7%), coughing (58.2%), and shortness of breath (50%). The most common diagnosis of pediatric asthma was based on clinical symptoms (77.5%), followed by spirometry (17.5%) and laboratory tests (5%). Conclusion: The findings of this study suggest that asthma is a significant health concern among the pediatric population in Pakistan.

To examine the prevalence and pattern of hypoxic-ischemic encephalopathy (HIE) in pediatric patients This retrospective, cross-sectional study was conducted in the Department of Pediatrics LRH Peshawar from Jan 2020 to July 2020 and included 50 pediatric patients newly born to 16 years old with HIE. All patients had MRIs. HIE, damage pattern, and affected regions were evaluated on the MRI. The overall prevalence of HIE was 28%. Mild to moderate HIE was the most prevalent pattern, accounting for 19% of the cases. The most common pattern of injury was global (14%), followed by focal (12%) and multifocal (2%). The most affected areas were the basal ganglia, thalamus, and cortical white matter. The results showed that HIE was 28%, with the majority of cases being moderate to mild. The most common pattern of injury was global, followed by focal and multifocal.

To assess the prevalence and treatment of malaria in children hospitalized in district hospitals in Pakistan. This study was conducted in Department of Pediatrics MMC hospital Mardan from Jan 2019 to Jan 2020. Data was collected from 100 patients aged 7 to 14 years who were admitted in district hospitals. All patients had their blood samples checked for malarial parasites and a detailed history was taken. The results were then analyzed by SPSS. The study showed that the prevalence of malaria was 10%, with fever being the most common symptom reported. The most commonly prescribed drugs were quinine, chloroquine, artesunate, and mefloquine. This study demonstrated that malaria is a public health issue in Pakistan and that prompt diagnosis and appropriate treatment are essential for successful control of the disease.

Objective: To determine the frequency of hypothyroidism in patients with pulmonary hypertension. Study Design: Observational Cross-sectional study. Setting: Department of Medicine, Sandeman Provincial Hospital, Bolan University of Medical & Health Sciences Quetta Pakistan. Period: March 2020 to March 2021. Material & Methods: Pulmonary Hypertension was defined as mPASP of >25 mm Hg at rest on transthoracic echocardiogram and hypothyroidism was labeled when TSH was high with low Free T4 and/or Free T3. Patients with congestive cardiac failure, pulmonary malignancy or pulmonary metastasis assessed by history and examination were excluded from the study. Using non-probability consecutive sampling, 186 patients of both genders, aged 20-65 years with pulmonary hypertension were included. Demographic information along with clinical variables noted, echocardiography was done and thyroid profile was sent for each patient. Results: Mean age was 41.2+11.2 years with 56 (30.1%) males and 130 (69.9%) females. The mean height, weight and BMI were 1.6+0.2 meters, 56.5+14.4 kilograms and 21.8+3.6 kg/m2 respectively. The mean mPASP was 40.2+7.1 mmHg. The mean serum TSH, free T3 and free T4 levels were 6.6+4.8 IU/L, 2.5+1.0 pmol/L and 1.1+0.4 pmol/L respectively. In our study, hypothyroidism was seen in 46 (24.7%) and was not significantly associated with age, gender, BMI or mPASP. Conclusion: Hypothyroidism was noted in about a quarter of the patients with pulmonary hypertension in this study.

Granulomatosis with polyangiitis (GPA) is an uncommon pauci-immune small-vessel necrotising granulomatous vasculitis mostly seen in age 45–60 years. We present the case of a formerly healthy 44 years old male presenting with dysuria and intermittent urinary retention for 8 months, not responding to empirical antibiotic therapy and TURP. A prostate biopsy showed necrotising granulomatous prostatitis. Urinalysis demonstrated persistent pyuria and haematuria, but cultures showed no growth. Subsequently he complained of fever, cough, dyspnoea and skin ulcers. CT of the chest showed multiple cavitatory lesions and pleural effusion. On work up, c-ANCA was positive and a diagnosis of granulomatosis with polyangiitis was established. This depicts a rarely seen presentation of prostatitis as the initial feature of GPA.

Objective: To determine frequency of hyponatremia in liver cirrhosis patients presenting with hepatic encephalopathy. Study Design: Descriptive Cross-sectional study. Setting: Department of Medicine, Sandeman Provincial Hospital, Bolan University of Medical and Health Sciences Quetta. Period: June 2020 to December 2020. Material & Methods: Cirrhosis was characterised on Ultrasound abdomen with altered liver parenchyma, shrunken liver and coarse echo texture. HE was defined as a spectrum of neuropsychiatric abnormalities diagnosed clinically with adequate history taking and physical examination. After taking informed consent from the patients’ attendants, 172 patients of liver cirrhosis presenting with HE were enrolled. Detailed clinical history and examination along with investigations were done. Hyponatremia was defined as serum sodium level 3 days was seen in 47 (27.3%) while 125 (72.7%) had stay of >3 days. It was observed that 14 (8.1%) patients expired. Hyponatremia was found in 69 (40.1%). Conclusion: Hyponatremia was a common feature in liver cirrhosis patients presenting with hepatic encephalopathy. Furthermore a significant association of hyponatremia was seen with hospital stay and all-cause mortality.

Background: Neonatal encephalopathy is a diverse and clinically well-known syndrome. The objectives of this study were to determine the prevalence and determinants of hypoxic-ischemic encephalopathy (HIE) in perinatal asphyxia population of District Mardan, Pakistan. Materials & Methods: This cross-sectional study was conducted in Department of Pediatrics, Bacha Khan Medical College, Mardan, Pakistan from 1st January 2017 to 30th June 2017. 160 term neonates with perinatal asphyxia were included. Sex, age groups, gestational age, mode of delivery, weight groups and presence of HIE were variables. Presence of HIE was dependent while five demographic variables were independent variables respectively for five chi-square tests of association. Results: Mean age of sample of 160 infants was 2.537±1.26 (1-7, range 6) days, mean gestational age was 38.681±1.24 weeks and mean weight 3.275±0.36 kg. Out of 160 infants with perinatal asphyxia, 16 (8.16%, 95%CI 7.35-13.46) had HIE (HIE). These positive 16 cases included 11 (6.88%) boys & 5 (3.12%) girls, 15 (9.38%) of 1-3 & one (0.62%) of 4-7 days, 14 (8.75%) of gestational age 37-39 & two (1.25%) of >39 weeks, 15 (9.38%) with vaginal delivery & one (0.62%) with C-section and 14 (8.75%) of ≤3 & two (1.25%) of >3 kg weight groups. There was association between presence of HIE and weight groups, but not with sex, age groups, gestational age and mode of delivery. Conclusion: We found 10% prevalence of HIE in perinatal asphyxia population of District Mardan, Pakistan. The prevalence was higher in boys than girls, in age group 1-3 days than 4-7 days, in gestational age ≤37-39 than >39 weeks, in vaginal than C-section delivery and in weight group ≤3 kg than >3 kg group. There was association between presence of HIE and weight groups, but not with sex, age groups, gestational age and mode of delivery.

Single Cell Omics (SCO) is an evolving field in biomedical research which offers prime application in neurosciences. The human nervous system is complex and shows variability in cell types. It includes neurons (functional components), glial cells (supporting cells), astrocytes (provide nourishment), oligodendrocytes (synthesize myelin sheath), and microglia (defense mechanism). To understand the functional and disease states of the nervous system, it is essential to investigate them at the single-cell level. It has been estimated that every 1 in 9 people is affected by mental or neurological disorders, including psychological disorders (generally referred to as mental disorders), psychotic disorders (involving psychosis), and neurological disorders (involving neurological factors), globally. These disorders have multifactorial etiology and are caused by genetic and environmental factors. Every disorder has distinct pathophysiology affecting multiple brain regions. SCO has excellent potential to provide insight regarding the diagnosis, pathophysiology, and treatment of neurological disorders. The stringent well directed SCO methods enhance the understanding of complex nervous system disorders, such as meningitis, stroke, schizophrenia, Parkinson’s disease, and Alzheimer’s disease, which paves the way for future research.

Objective: The study was conducted on the incidence of meconium aspiration syndrome which is still high in the developing world and contributing significantly to the neonatal mortality. The study was aimed to know the risk factors contributing to meconium aspiration syndrome and neonatal outcome in a tertiary hospital (Punjab) Department of pediatric Medicine PAK Emirates Military hospital Rawalpindi in the Pakistan. Materials and Methods: It was a hospital based cross sectional study This descriptive case series was carried at Department of Peadiatric Medicine PAK Emirates Military hospital Rawalpindi in the Pakistan over a period of one year, from Jan 2019 to Dec 2020, involving 2820 patients; All live newborns born through meconium-stained liquor were enrolled and all the details regarding the mother and neonate were recorded. Odd’s ratio and bivariate analysis was done to assess the risk factors for meconium aspiration syndrome. Results: Out of all the deliveries 12.4% were born through meconium-stained amniotic fluid and meconium aspiration syndrome developed in 5 .6% of the neonates. Low Apgar score and premature rupture of membranes was significantly associated with the risk of occurrence of meconium aspiration syndrome. Neonates who developed meconium aspiration syndrome had mortality of 6.7% Conclusion: The Perinatal asphyxia and premature rupture of membranes were significantly associated with the development of meconium aspiration syndrome and neonates who developed meconium aspiration syndrome had high mortality.

Purpose: To study serum electrolyte derangements among children with acute diarrhea presenting with dehydration. Methodology: Cross-sectional and descriptive study in department of Pediatrics, MMC Hospital, Mardan (Pakistan) for from 01-02-2020 to 31-10-2020. A total of 390 children having acute diarrhea with dehydration were included. Five milliliters (5mls) of blood was drawn and estimation of serum Sodium and potassium levels were done. Findings: In 390 cases, 218 (55.9%) were males while 1 72 (44.1%) were females. The mean age was 2.5±1.5 years. Out of 390 cases, 2(0.51%) had no dehydration, some dehydration was noted in 218 (55.9%) cases while 170 (43.59%) cases had severe dehydration. Hypernatremia was noted in 218 (55.9%) cases and hypokalemia was noted in 77(19.74%) cases. Conclusion: High rate of hyponatremia and hypokalemia was seen in our study in children with acute diarrhea and dehydration. Hyponatremia and hypokalemia was significantly associated with age, gender and grades of dehydration.

Energy is the bridge connecting the economy and the environment and electric energy is an important guarantee for social production. In order to respond to the national dual-carbon goals, a new power system is being constructed. Effective carbon emission forecasts of power energy are essential to achieve a significant guarantee for low carbon and clean production of electric power energy. We analyzed the influencing factors of carbon emissions, such as population, per capita gross domestic product (GDP), urbanization rate, industrial structure, energy consumption, energy structure, regional electrification rate, and degree of opening to the outside world. The original Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model was improved, and the above influencing factors were incorporated into the model for modeling analysis. The ridge regression algorithm was adopted to analyze the biased estimation of historical data. The carbon emission prediction model of Shanghai electric power and energy based on elastic relationship was established. According to the “14th Five-Year” development plan for the Shanghai area, we set up the impact factor forecast under different scenarios to substitute into the forecast models. The new model can effectively assess the carbon emissions of the power sector in Shanghai in the future.

Background: Urinary tract infections (UTIs), which impact 8% of girls and 2% of boys by age seven and have a repeat rate of 10% to 30%, are common in infants and young children. Infantile colic is a very difficult condition for parents to manage. Objective: To discover the prevalence of uti among patients who appear with neonatal distress Material And Methods: 126 male and female painful babies participated in the research. Khyber Teaching Hospital's paediatrics division, Peshawar. Duration: from January 1, 2020, to August 1, 2019, inclusive. Each infant had two clear middle pee samples collected two hours apart to be tested for UTIs. The UTI was considered positive if the child had a history of temperature >99 °F, dysuria, and more than five WBC per HPF or >10 4 CFU/HPF on pee culture. Results: Children in this research ranged in age from 6 weeks to 6 months, with a mean age, weight, and height of 3.1501.42 months, 4.9790.82 kg, and 56.6503.08 cm, respectively. Men made up the overwhelming bulk of the cases. (69.8 per cent). 61.1 per cent of mothers breastfed their babies, while 38.9 per cent used bottles to nurse them. The prevalence of urinary tract infections among individuals was 8.7%. Conclusion: The frequency of UTI among babies who appear with diarrhoea is 8.7%, it can be inferred. This research emphasises the value of early newborn UTI detection and therapy and the requirement for preventative steps to lower the risk of UTI in this group. Keywords: frequency, Infantile colic, urinary tract infection

Forecasting academic performance of student has been a substantial research inquest in the Educational Data-Mining that utilizes Machine-learning (ML) procedures to probe the data of educational setups. Quantifying student academic performance is challenging because academic performance of students hinges on several factors. The in hand research work focuses on students’ grade and marks prediction utilizing supervised ML approaches. The data-set utilized in this research work has been obtained from the Board of Intermediate & Secondary Education (B.I.S.E) Peshawar, Khyber Pakhtunkhwa. There are 7 areas in BISEP i.e., Peshawar, FR-Peshawar, Charsadda, Khyber, Mohmand and Upper and Lower Chitral. This paper aims to examine the quality of education that is closely related to the aims of sustainability. The system has created an abundance of data which needs to be properly analyzed so that most useful information should be obtained for planning and future development. Grade and marks forecasting of students with their historical educational record is a renowned and valuable application in the EDM. It becomes an incredible information source that could be utilized in various ways to enhance the standard of education nationwide. Relevant research study reveals that numerous methods for academic performance forecasting are built to carryout improvements in administrative and teaching staff of academic organizations. In the put forwarded approach, the acquired data-set is pre-processed to purify the data quality, the labeled academic historical data of student (30 optimum attributes) is utilized to train regression model and DT-classifier. The regression will forecast marks, while grade will be forecasted by classification system, eventually analyzed the results obtained by the models. The results obtained show that machine learning technology is efficient and relevant for predicting students performance.

Nanotechnology has opened a new era for scientists and engineers to build nanomaterials with diverse applications. Nowadays, nanotechnology plays a vital role in each and every sector due to its extraordinary physical and chemical properties. It deals with development and synthesis of variety of nanoparticles (NPs), which ranging from 1 to 100 nm. The major approaches used for the synthesis of NPs are top to bottom and bottom to up which mainly included physical, chemical and biological methodologies. This mini review highlights synthesis of NPs through various approaches specifically targeted biological route.

Multiple energy carriers can be coupled as an Integrated Energy System (IES) through interconnection technologies. Unexpected risks will be transferred with the growing coupling of energy systems, mainly stemming from the uncertainties in different energy sectors. It is imperative to coordinate the operation of different energy systems to improve energy efficiency and ensure energy security. With the close integration of different energy systems, it is necessary to couple these different energy markets to achieve the holistic energy supply economy. On the other hand, uncertainties in the energy systems will bring the financial risk for the operator of IES. A risk-averse stochastic market clearing model for the IES is proposed to study the operating strategy aiming at minimizing the operation cost. While the financial risk imposed by the wind power uncertainties is restricted to a predefined level. Simulations results are provided to verify that the proposed model can improve market efficiency and handle the trade-off between cost and risk.

Melanoma is considered a fatal type of skin cancer. However, it is sometimes hard to distinguish it from nevus due to their identical visual appearance and symptoms. The mortality rate because of this disease is higher than all other skin-related consolidated malignancies. The number of cases is growing among young people, but if it is diagnosed at an earlier stage, then the survival rates become very high. The cost and time required for the doctors to diagnose all patients for melanoma are very high. In this paper, we propose an intelligent system to detect and distinguish melanoma from nevus by using the state-of-the-art image processing techniques. At first, the Gaussian filter is used for removing noise from the skin lesion of the acquired images followed by the use of improved K-mean clustering to segment out the lesion. A distinctive hybrid superfeature vector is formed by the extraction of textural and color features from the lesion. Support vector machine (SVM) is utilized for the classification of skin cancer into melanoma and nevus. Our aim is to test the effectiveness of the proposed segmentation technique, extract the most suitable features, and compare the classification results with the other techniques present in the literature. The proposed methodology is tested on the DERMIS dataset having a total number of 397 skin cancer images: 146 are melanoma and 251 are nevus skin lesions. Our proposed methodology archives encouraging results having 96% accuracy.

Background Dengue is a vector-borne disease endemic to Pakistan as well as to Khyber Pakhtunkhwa. A total of 300 confirmed cases of dengue were reported in District Khyber in 2019, where a prompt response was initiated by the Disease Surveillance and Response Unit. Subsequently, a study was planned to identify the risk factors associated with dengue and to propose recommendations for containment of the disease. Objective This study aimed to assess the risk factors associated with dengue in District Khyber and to provide recommendations for improving the existing system and preventing dengue. Methods A case-control study was conducted in District Khyber from September 2 to November 24, 2019. Cases were enrolled from health care facilities based on predefined criteria, which included the presence of clinical signs and symptoms as well as laboratory confirmation of dengue NS1 antigen. Controls were enrolled from the community at a case-control ratio of 1:2. Data were collected using a pretested questionnaire in face-to-face interviews. Results A total of 300 cases were enrolled; 87% (263) of cases were men. This study found that 45% (269/601; odds ratio [OR] 15, 95% CI 9.9-24.07; P Conclusions Dengue is a preventable disease and can be controlled by the proper use of bed nets and mosquito repellents, modification of sleeping habits, and improvement in family structure. Dengue management training for health care personnel and community awareness are recommended.

In wireless sensor networks (WSNs), the energy and computational capacity of the sensor nodes are limited and they are deployed in a hostile environment. An adversary can easily compromise a sensor node and injects false data into the network. This injection of false data drastically depletes the energy of the nodes designated on the route for forwarding the source data. Many filtering methods have been proposed to tackle the security issues but they also increase the communication cost by exchanging the control keying messages which consumes more energy with in the network. Fuzzy logic for TICK was proposed to reduce the communication cost and increase the energy efficiency of the en-route nodes by selecting the re-encrypting nodes efficiently and avoiding the exchange of control keying messages in the network. Membership functions in the fuzzy system need to be optimized in order to use the fuzzy inferencing more efficiently. We propose an optimized fuzzy membership functions method by using genetic algorithm. The genetic algorithm determines the optimal membership functions which help in selecting the most favourite re-encrypting nodes in TICK based wireless sensor network. Simulation results show that the proposed method optimizes the membership functions and achieves better energy conservation at sensor nodes.

One of the important resources required for various Natural Language Processing (NLP) applications like machine translation, information retrieval and text mining, is annotated text corpora. Text corpora annotation process requires parts of speech (POS) tags to mark different parts of text with grammatical annotations in order to identify linguistic properties of a word, sentence or discourse. The process of marking text items is based on two main features 1) grammatical category and 2) context of text (word, sentence or discourse) i.e. relationship with adjacent and related text. Saraiki being one of oldest languages is still resource scarce language in recorded literature as well as in computational context. According to our study, at present, there is no tagset defined for Saraiki language. This work presents first hierarchical POS (MPOST) tag set for the Saraiki language which is designed to be used in morphological, syntactic and lexical annotations of Saraiki language corpora.

Motorcycle is a complex machine, and its riding requires mental alertness along with mind and body coordination. On the road, motorcyclists are subjected to excessive level of noise (> 90 dBA). High noise exposure can impair the motor task functioning. The assessment of motor task (dexterity) of motorcyclists under noise exposure has not been examined formerly as well as their psychological health profiling. Therefore, this study is aimed to investigate the effects of noise-induced motor task functioning among young motorcyclists (19 – 24 yrs.). The controlled laboratory experiment was conducted on undergraduate university motorcyclists ( n = 60; 30 males, 30 females). Two groups were formed experimental (Exp-G; n = 30) and a controlled (Con-G; n = 30). The Exp-G operated motor activity test under 85-90 dBA motorcycle noise exposure, while Con-G exposed to controlled noise (65 dBA) levels. The sound level was examined concurrently by calibrated (114 dBA) Sound Level Meter. Purdue Pegboard battery test was used to measure motor task functioning consisting four subtests (Dominant Hand; Non-Dominant Hand; Both Hands; Assembly). The Independent sample t -test was used across all subtests to examine the comparison effect of motor task function (dexterity) between Exp-G and Con-G, and amongst genders. Result showed that the Con-G had significantly good quality presentation ( p 0.05). Based on mean values, male participants of the Exp-G performed better under high noise levels than females, while among Con-G, females performed better. The results demonstrated significant effect of motorcycle noise on decreased motor task functioning of the participants (Exp-G). Therefore, it concludes that on-road excessive noise level exposure can hinder the motor task functioning and can contribute to impair the reaction time on excruciating hazardous position.

Improving a vehicle driver’s performance decreases the damage caused by, and chances of, road accidents. In recent decades, engineers and researchers have proposed several strategies to model and improve driving monitoring and assistance systems (DMAS). This work presents a comprehensive survey of the literature related to driving processes, the main reasons for road accidents, the methods of their early detection, and state-of-the-art strategies developed to assist drivers for a safe and comfortable driving experience. The studies focused on the three main elements of the driving process, viz. driver, vehicle, and driving environment are analytically reviewed in this work, and a comprehensive framework of DMAS, major research areas, and their interaction is explored. A well-designed DMAS improves the driving experience by continuously monitoring the critical parameters associated with the driver, vehicle, and surroundings by acquiring and processing the data obtained from multiple sensors. A discussion on the challenges associated with the current and future DMAS and their potential solutions is also presented.

For spins chains to be useful for quantum information processing tasks, the interaction between the spin chain and its environment generally needs to be suppressed. In this paper, we propose the use of strong static and oscillating control fields in order to effectively remove the spin chain-environment interaction. We find that our control fields can also effectively transform the spin chain Hamiltonian. In particular, interaction terms which are absent in the original spin chain Hamiltonian appear in the time-averaged effective Hamiltonian once the control fields are applied, implying that spin-spin interactions can be engineered via the application of static and oscillating control fields. This transformation of the spin chain can then potentially be used to improve the performance of the spin chain for quantum information processing tasks. For example, our control fields can be used to achieve almost perfect quantum state transfer across a spin chain even in the presence of noise. As another example, we show how the use of particular static and oscillating control fields not only suppresses the effect of the environment, but can also improve the generation of two-spin entanglement in the spin chain., Essentially the published version

Phasor Measurement Units (PMUs) are normally used in Wide Area Measurement System (WAMS) for vast applications, such as monitoring the transmission system status over bulky areas including the control and protection. Therefore, this paper reviews the power system protection in relation to the synchronized PMUs and the applications of phasor estimation techniques. Furthermore, the paper elaborates the research works on the applications of PMU for diverse features. The structure and types of PMUs are described utilizing the mathematical modeling of simple Discrete Fourier Transform (DFT) with Recursive and Non-Recursive estimation methods. The paper also presents the results of some published studies for two algorithms (Recursive and Non-Recursive). The review has revealed that the Non-Recursive algorithm is more accurate and gives robust estimation results.

In this study, fly ash (FA) was derived from extracted sugarcane bagasse solid waste (ESBSW) and chemically modified to apply as an adsorbent. Impact of activated FA particles (200 and 250 µm) and adsorbent bed height (4, 6 and 8 mm) on pollutant removal efficiency was evaluated. ESBSW was combusted in laboratory-scale gasifier operated at 1000 °C for 1 h. The black solid residue was sieved to obtain the desired particle size followed by activation with 10% and 15% sulfuric acid. Wastewater samples collected from the drainage site of BUITEMS were analyzed and treated with the prepared adsorbent. ESBSW-FA 250 activated with 15% H 2 SO 4 with 8 mm bed height showed high efficiency. Where, 94.37%, 95.1% and 63.5% removal efficiency of chemical oxygen demand (COD), total solids (TS) and turbidity was attained, respectively. The pH of treated water was neutral. ESBSW has shown great potential to be used as a precursor for valuable byproducts. It's recycling for adsorbent preparation will economically and environmentally benefit the sugar industry.

Tracking drivers’ eyes and gazes is a topic of great interest in the research of advanced driving assistance systems (ADAS). It is especially a matter of serious discussion among the road safety researchers’ community, as visual distraction is considered among the major causes of road accidents. In this paper, techniques for eye and gaze tracking are first comprehensively reviewed while discussing their major categories. The advantages and limitations of each category are explained with respect to their requirements and practical uses. In another section of the paper, the applications of eyes and gaze tracking systems in ADAS are discussed. The process of acquisition of driver’s eyes and gaze data and the algorithms used to process this data are explained. It is explained how the data related to a driver’s eyes and gaze can be used in ADAS to reduce the losses associated with road accidents occurring due to visual distraction of the driver. A discussion on the required features of current and future eye and gaze trackers is also presented.

In heterogeneous networks, network selection by nature is a multi-dimensional problem. Many parameters need to be considered for handover decision making. Apart from handover accuracy and efficiency, an important consideration is the scalability and signaling overhead of such handover algorithms. In this article we propose to break down a Simple Additive Weighting (SAW) based heterogeneous handover algorithm in two parts. The execution of the first part is carried out in an independent and proactive manner prior to the actual handover, assuming three different handover architectures. The handover architectures are differentiated based upon the level of the distribution of the handover algorithm among multiple network components. The Media Independent Handover (MIH) and its different services are used to retrieve and share information among MIH enabled nodes and for conformity among heterogeneous network standards. The proposed algorithm is evaluated with respect to handover accuracy, handover delay efficiency and signaling overhead. The evaluation is carried out for all three handover architectures using simulations. Only handovers between Wi-Fi (IEEE 802.11) and WiMAX (IEEE 802.16) networks are considered. But the handover framework is general and can be extended to consider other wireless and mobile communication networks.