首页期刊导航|International Journal of Vehicle Information and Communication Systems
期刊信息/Journal information
International Journal of Vehicle Information and Communication Systems
Inderscience Enterprises Ltd.
Inderscience Enterprises Ltd.
1471-0242
International Journal of Vehicle Information and Communication Systems/Journal International Journal of Vehicle Information and Communication SystemsEI
查看更多>>摘要：Bug approaches are popular for mobile robot navigation in challenging environments. Traditional bug approach follows a virtual straight line from source to target location and exhibits obstacle boundary. This behaviour of the bug approach consumes more travel time towards target location. In addition, obstacles with larger size situated in central-left or central-right side of the virtual straight line between source and target location create navigation problems for bug approaches. A modified bug (m-Bug) controller has been proposed and realised for mobile robot path navigation with a better solution in MATLAB and V-REP simulation environments. With range sensors, the proposed controller was found to exhibit better-optimised travel time and path length in the given environments. Different static environments with single and multiple obstacles have been considered for testing the proposed controller. Various simulation results and comparative analysis highlight the superiority of the controller.
查看更多>>摘要：Lately, there is a drastic change in the telecommunication industry due to emergence of Internet of Things (IoT). Machine to Machine (M2M) plays a very important role in enabling IoT. As the LTE is mainly suitable for Human-to-Human (H2H) communication, MTC faces some challenges in LTE like radio resource management and uplink-scheduling algorithms are not suitable for MTC. In this paper, we use a queuing theory and propose a packet scheduler, which would model the regular and event-driven traffic and schedule the jobs in queue for request processing. Then using the Markov Chain process, we calculate the queue length and determine the blocking probability. If there is high blocking probability and still there are some requests in queue, then those requests will be processed in virtual server for maximum network usage.
N. Sharath BabuGunti Hemanth SantoshS.R.C.H. Murthy TommandruM. Shiva Kumar...
13页
查看更多>>摘要：Mobile Edge Computing is one of the prominent technologies in 5G communication to improve throughput, scalability and reliability. In this work, area efficient and high-speed multipliers are implemented using finite field (Galois field) arithmetic which are widely utilised by edge computing devices. The performance of finite field multiplication operation is closely related to finite field elements representation. The proposed polynomial-based finite field bit parallel systolic array multiplier is able to achieve almost double the speed of existing multipliers. There is a considerable reduction in area and power for the proposed word-level normal basis finite field multiplier compared to the existing multipliers. The results clearly indicate that the proposed method improves the efficiency of finite field multipliers in terms of area, delay or power consumption. In order to process the real-time data efficiently, both the local computing and data offloading are carried out in developing a joint computation algorithm. The trade-off analysis between local computing and data offloading shows that local computing plays a more important role when the data size is small, but data offloading is preferred when the data size increases.
查看更多>>摘要：Nanomaterials and nanodevices have a major impact in the development of many innovative systems and they are the potential replacement for CMOS technology devices. Nanoelectronic sensors are highly essential in the development of hybrid electric vehicles and autonomous systems. This research paper focuses on the synthesis of ZnO nanoparticles and development of nanoelectronic sensing elements for automotive applications and hybrid electric vehicles. Environment friendly ZnO nanoparticles are utilised in this work to avoid harmful gases. ZnO nanoparticles are synthesised using Aloe Vera extracts through mediated synthesis route. Structural and morphological characteristics are experimentally studied using various spectroscopic and microscopic measures. ZnO nanomaterial elements and LPG sensing properties were systematically investigated to check the suitability for electric vehicle applications. The effects of operating temperature on gas response, resistance and sensitivity characteristics are analysed using various experiments. The performance of our nanoelectronic sensing element is found to be superior to similar sensing elements in terms of working temperature, percentage response, response time and recovery time.
Adinarayana SalinaE. IlavarasanYogeswara Rao Kalla
15页
查看更多>>摘要：Analysing huge volume of data from the social media tweets on product reviews provides a better understanding of any product. Exploring customer opinions from tweets is helpful to find the strengths and weaknesses of different products and features. There are several studies on product recommendations from Twitter product reviews. In this paper, Internet of Things-based two level product recommendation framework (TLPRF) is proposed to efficiently handle large amount of Twitter users' product reviews data. TLPRF consists of a Raspberry Pi microcomputer as an IoT mining machine and it is programmed to generate a feature level opinion summary. Feature level opinion is found to be useful in accomplishing the product ranking. Based on the customer interest in the product purchase request, a normalised ranking of each matching product is calculated from the feature-wise opinion summary and the product with maximum ranked score is recommended to Twitter user. The proposed TLPRF is found to be superior to similar other approaches in terms of accuracy, precision, recall and f-measure.
Kavita WaghDipak B. KhandgaonkarG. Sreenivasa RajuSudhir S. Kanade...
12页
查看更多>>摘要：Human tracking is a challenging task and a significant part of the design of an intelligent surveillance system. Though the existing tracking techniques accomplished the reasonable outcomes in terms of accuracy and robustness, there is a scope for improving the tracking performance. In this paper, vote mapping of patched confidence methodology is used with the consecutively increasing number of patches. The system aims to provide robustness to occlusion and global scene changes by utilising the number of patches from the bounding box of an image. An individual patch is tracked by kernelised correlation filter and applied to the vote mapping methodology. The consecutively increasing number of patch approach and vote mapping provide robustness to the occlusion in real time tracking scenarios. The qualitative and quantitative analysis reveals the superiority of the proposed vote mapping-based tracker over the existing kernel-based trackers.
Marka ChandrikaSachu AlekhyaD. HaripriyaPrathibhachand Bellamkonda...
11页
查看更多>>摘要：Visually impaired persons are not able to read the text content on their own and most of them struggle to live independently. Braille reading system, audio tactile and digital speech synthesiser have been developed for the visually impaired persons. But always it is not possible to have Braille, audio and video form of printed work. Many researchers used optical character recognition (OCR) tools with IoT technology to improve the reading capability of poor eyesight persons. However, this approach is not comfortable for the reader as there is a possibility of missing certain words by reader during image to text conversion. A handy and cost effective text reader is proposed in this work to help the people to read on their own using text to speech technology. A camera interfaced with Raspberry Pi is used to capture the alphabets and numbers from the document and converted to text by PyTesseract OCR. The accuracy of the reader is 98% with the distance of 15 cm to 23 cm during day and night. The text document can be a handwritten script with minimum font size of 10 and it can be placed in any orientation.
查看更多>>摘要：The effective detection of distributed denial of service is still a challenging task and the impact of such attacks is usually harmful. According to recent studies, there has been a perception that machine learning can have remarkable impact on network security, mainly in network traffic analysis. It is useful to study and analyse network traffic behaviour consistently using large and real time datasets and train them to build a network model using advanced machine learning techniques. These techniques are capable of detecting both known and unknown attacks. Here, we propose a hybrid classifier model which can detect both known and unknown attacks by using two stage classifiers. The results obtained on benchmark data sets indicate that the proposed model is a highly useful classifier for detecting different types of transmission control protocol flooding-based distributed denial of service attacks with a reduced number of false positives.
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