A Model for Remote Access and Protection of Smartphones using Short Message Service

The smartphone usage among people is increasing rapidly. With the phenomenal growth of smartphone use, smartphone theft is also increasing. This paper proposes a model to secure smartphones from theft as well as provides options to access a smartphone through other smartphone or a normal mobile via Short Message Service. This model provides option to track and secure the mobile by locking it. It also provides facilities to receive the incoming call and sms information to the remotely connected device and enables the remote user to control the mobile through SMS. The proposed model is validated by the prototype implementation in Android platform. Various tests are conducted in the implementation and the results are discussed.Comment: 10 Pages, 11 Figure

Ability of Essential Oil Vapours to Reduce Numbers of Culturable Aerosolised Coronavirus, Bacteria and Fungi

Transmission of pathogens present in the indoor air can occur through aerosols. This study evaluated the efficacy of an evaporated mix of essential oils to reduce the numbers of culturable aerosolized coronavirus, bacterium and fungus. The essential oil-containing gel was allowed to vaporize inside a glass chamber for 10 or 20 min. Aerosols of a surrogate of SARS-CoV-2, murine hepatitis coronavirus MHV-1, Escherichia coli or Aspergillus flavus spores were produced using a colli-sion nebuliser and passed through the essential oil vapours, then collected on a six-stage Andersen sampler. The six-stages of the impact sampler capture aerosols in sizes ranging from 7 to 0.65 µm. The number of culturable microbes present in the aerosols collected in the different stages were enumerated and compared to the number of culturable microbes in control microbial aerosols that were not exposed to the evaporated essential oils. After 10 and 20 min evaporation, the essential oils reduced the numbers of culturable aerosolized coronavirus by 48% (log10 reduction = 0.3; p = 0.002 vs. control) and 53% (log10 reduction = 0.3; p = 0.001 vs. control), respectively. The essential oils vaporised for 10 min, reduced the number of viable E. coli by 51% (log10 reduction = 0.3; p = 0.032 vs. control). The Aspergillus flavus spores were mostly observed in the larger aerosols (7.00 µm to 2.10 µm) and the essential oils vaporised for 10 min reduced the number of viable spores by 72% (log10 reduction = 0.6; p = 0.008 vs. control). The vapours produced by a gel containing naturally occurring essential oils were able to significantly reduce the viable numbers of aerosolized coronavirus, bacteria and fungal spores. The antimicrobial gel containing the essential oils may be able to reduce aerosol transmission of microbes when used in domestic and workplace settings

Public transport as a driver of economic and social revitalisation in central business districts: the case of pinetown, ethekwini

Public Transport in its various forms is the most widely used form of transportation by commuters within South Africa. It caters for the travel needs of up to 70% of commuters, and therefore plays a significant role in contributing to the economic vibrancy of the country. Within the South African context, public transport has significantly contributed to the progression of urbanisation. Major cities across South Africa depend on public transport to convey commuters to the urban centres daily, ensuring that these urban areas are easily accessible and well connected to their associated outlying regions. These urban centres have also been shaped by the presence and operation of public transport. A booming industry that has emerged is the informal trade sector, who depend on the public transport industry and patrons for their livelihood. In this way public transport plays a vital role in moulding the character and culture of urban areas. Ove the past two decades, urban areas have been in a state of decline. Factors such as overcrowding, poor maintenance, delays in the provision of new roads and buildings infrastructure, among other factors, has resulted in dilapidation of infrastructure, pollution, crime, traffic congestion, all working together to make urban centres extremely chaotic and unattractive environments to be in. As a result, major businesses pull out of the urban areas, urban areas become progressively more dysfunctional, becoming a greater financial burden to government departments. In spite of this, there are still thousands of commuters who use public transport to travel to these urban centres for their livelihoods. Public Transport therefore has the potential to be a conduit to derive economic and social revitalisation in such urban areas. The Pinetown CBD within eThekwini Municipality serves as an example of a oncethriving node which has significantly degenerated. As part of the urban decay, the public transport infrastructure within the Pinetown CBD also became severely dysfunctional and is in need of major reform. Through a public transport study undertaken by the eThekwini Transport Authority’s (ETA), the solutions that were identified not only provided an improved service and infrastructure response to the public transport sector, but had the potential to provide revitalisation for businesses within the CBD, as well as to bring reform to the informal trade industry. By presenting the findings from the Pinetown study, this paper will demonstrate the way in which public transport can drive economic and social revitalisation in CBDs.Papers presented at the 40th International Southern African Transport Conference on 04 -08 July 202

Proposed approach to address the regulation of metered taxi and e-hailing services within the ethekwini municipality

The metered taxi and e-hailing services sector currently plays a significant role as part of the South African public transport industry. In keeping with global trends, it is evident that these services are gaining more prominence going into the future. However, the entities within this sector are experiencing conflicts and challenges with regards to licencing, enforcement, competition over destinations and commuter base, among other challenges. These challenges have unfortunately led to the manifestation of violent engagements between operators, damage to vehicles, road infrastructure, and compromised commuter safety. The eThekwini Transport Authority (ETA) undertook to address these challenges within the eThekwini Municipality (EM). From status quo assessments, it was found that the current challenges being experienced by this sector are essentially due to the current gaps in the prevailing legislation, which governs the entry, operations, and enforcement of the sector. To address the current challenges on the ground, a regulatory framework is required to formalise this sector. For the development of the required regulatory framework, a process is required which enables the integration and involvement of all role players including all tiers of governmental departments, business entities, public transport role-players and stakeholders, as well as civil society in general. The required process would need to be able to both collect the wide-ranging information to understand the nature of the sector, and then use the information to inform decision-making. A staged/phased Expression of Interest (EOI) process has been proposed by the ETA to achieve this objective. Through this process, all existing and prospective operators will be identified, information collected about the existing services and operations; analyses done to determine market demand and supply and prepare regulatory requirements which can be enforced within the Municipality. The EOI that the ETA has developed will be done mainly as an on-line activity. The EOI has to date been presented to role-players from the Metered Taxi and E-hailing services sector, who have welcomed and supported the proposed process. The proposed methodology was approved for implementation by the eThekwini Municipality’s Council. This approach to address the regulation of a dynamic and complex service industry such as the The 40th Annual Southern African Transport Conference – 4 to 7 July 2022 ___________________________________________ Metered Taxi and E-hailing sector is a first for South Africa, and it is expected to provide fruitful insights.Papers presented at the 40th International Southern African Transport Conference on 04 -08 July 202

An integrated approach of bioleaching-enhanced electrokinetic remediation of heavy metals from municipal waste incineration fly ash using Acidithiobacillus spp

Introduction: Municipal solid waste (MSW) incineration fly ash is a harmful residue formed during the incineration process. It contains high concentrations of hazardous heavy metals, such as lead, zinc, aluminum, and iron.Methodology: In this study, bioleaching integrated with an electrokinetic approach for heavy metal remediation from MSW incineration fly ash using Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans bacteria was tested.Results and discussion: The physicochemical properties of fly ash included a particle size of 26.1 μm, with the presence of heavy metals. A. ferrooxidans and A. thiooxidans produced sulphuric acid (0.0289 M and 0.0352 M) during the proliferation; this acid enhances the bioleaching of heavy metals from fly ash. The results of an integrated approach showed an 85%, 47%, 92%, 85%, 46%, 67% 11%, and 55% removal of the heavy metals K, Na, Ca, Mg, Al, Zn, Pb, and Mg, respectively, in the presence of A. ferrooxidans. Overall, these results evidenced that heavy metals were completely removed from the fly ash using an integrated approach. Therefore, this integrated approach can be used as an effective heavy metal removal method for treating fly ash in MSW

SSNN-based energy management strategy in grid connected system for load scheduling and load sharing

The proposed research work focused on energy management strategy (EMS) in a grid connected system working in islanding mode with the connected renewable energy resources and battery storage system. The energy management strategy developed provides a balancing operation at its output by utilizing perfect load sharing strategy. The EMS technique using smart superficial neural network (SSNN) is simulated, and numerical analyses are presented to validate the effectiveness of the centralized energy management strategy in a grid connected islanded system. A SSNN prediction model is unified to forecast the associated household load demand, PV generation system under various time horizons (including the disaster condition), EV availability, and status on EV section and distance. SSNN is one the most reliable forecasting methods in many of the applications. The developed system is also accounted for degradation battery model and its associated cost. The incorporation of energy management strategy (EMS) reduces the amount of energy drawn from the grid connected system when compared with the other optimized systems

Power and area efficient cascaded effectless GDI approximate adder for accelerating multimedia applications using deep learning model

Approximate computing is an upsurging technique to accelerate the process through less computational effort while keeping admissible accuracy of error-tolerant applications such as multimedia and deep learning. Inheritance properties of the deep learning process aid the designer to abridge the circuitry and also to increase the computation speed at the cost of the accuracy of results. High computational complexity and low-power requirement of portable devices in the dark silicon era sought suitable alternate for Complementary Metal Oxide Semiconductor (CMOS) technology. Gate Diffusion Input (GDI) logic is one of the prompting alternatives to CMOS logic to reduce transistors and low-power design. In this work, a novel energy and area efficient 1-bit GDI-based full swing Energy and Area efficient Full Adder (EAFA) with minimum error distance is proposed. The proposed architecture was constructed to mitigate the cascaded effect problem in GDI-based circuits. It is proved by extending the proposed 1-bit GDI-based adder for different 16-bit Energy and Area Efficient High-Speed Error-Tolerant Adders (EAHSETA) segmented as accurate and inaccurate adder circuits. The proposed adder’s design metrics in terms of delay, area, and power dissipation are verified through simulation using the Cadence tool. The proposed logic is deployed to accelerate the convolution process in the Low-Weight Digit Detector neural network for real-time handwritten digit classification application as a case study in the Intel Cyclone IV Field Programmable Gate Array (FPGA). The results confirm that our proposed EAHSETA occupies fewer logic elements and improves operation speed with the speed-up factor of 1.29 than other similar techniques while producing 95% of classification accuracy

The Role of Hla Genes in Immune Response, Disease Susceptibility, and Social Behaviours: A Comprehensive Review

Major Histocompatibility Complexes (MHC), which assist to code for proteins that distinguish between self and non-self, are significantly influenced by the Human Leukocyte Antigen (HLA) genes. Particularly important in the suppression of immune response are the HLA genes. The bulk of the genes in the MHC region shows considerable variation. The two most important functions of HLA molecules are selection of T cell accumulation and the formation and control of immunological responses. The causes of HLA-G gene-associated illnesses and the underlying mechanisms are still up for dispute. The HLA-G gene has an impact on social behaviour as well. Numerous polymorphisms have been connected to heightened susceptibility to the beginning of autoimmune illnesses as well as heightened disease severity. The lifetime of some HLA genes is shorter.Genetic background, environmental circumstances, and certain polymorphisms have been linked to increased illness severity. certain HLA genes have shorter life spans than others, and vice versa. The major functional elements of HLA-G in both normal and autoimmune disorders are summarized in this study

Tuning the Anthranilamide Peptidomimetic Design to Selectively Target Planktonic Bacteria and Biofilm

There is a pressing need to develop new antimicrobials to help combat the increase in antibiotic resistance that is occurring worldwide. In the current research, short amphiphilic antibacterial and antibiofilm agents were produced by tuning the hydrophobic and cationic groups of anthranilamide peptidomimetics. The attachment of a lysine cationic group at the tail position increased activity against E. coli by >16-fold (from >125 μM to 15.6 μM) and greatly reduced cytotoxicity against mammalian cells (from ≤20 μM to ≥150 μM). These compounds showed significant disruption of preformed biofilms of S. aureus at micromolar concentrations

Sentiment analysis on COVID-19 Twitter data streams using deep belief neural networks

Social media is Internet-based by design, allowing people to share content quickly via electronic means. People can openly express their thoughts on social media sites such as Twitter, which can then be shared with other people. During the recent COVID-19 outbreak, public opinion analytics provided useful information for determining the best public health response. At the same time, the dissemination of misinformation, aided by social media and other digital platforms, has proven to be a greater threat to global public health than the virus itself, as the COVID-19 pandemic has shown. The public's feelings on social distancing can be discovered by analysing articulated messages from Twitter. The automated method of recognizing and classifying subjective information in text data is known as sentiment analysis. In this research work, we have proposed to use a combination of preprocessing approaches such as tokenization, filtering, stemming, and building N-gram models. Deep belief neural network (DBN) with pseudo labelling is used to classify the tweets. Top layers of the base classifiers are boosted in the pseudo labelling strategy, whereas lower levels of the base classifiers share weights for feature extraction. By introducing the pseudo boost mechanism, our suggested technique preserves the same time complexity as a DBN while achieving fast convergence to optimality. The pseudo labelling improves the performance of the classification. It extracts the keywords from the tweets with high precision. The results reveal that using the DBN classifier in conjunction with the bigram in the N-gram model outperformed other models by 90.3 percent. The proposed approach can also aid medical professionals and decision-makers in determining the best course of action for each location based on their views regarding the pandemic