Automatic Intruder Combat System: A way to Smart Border Surveillance

Security and safeguard of international borders have always been a dominant issue for every nation. A large part of a nation’s budget is provided to its defense system. Besides wars, illegal intrusion in terms of terrorism is a critical matter that causes severe harm to nation’s property. In India’s perspective, border patrolling by Border Security Forces (BSF) has already been practiced from a long time for surveillance. The patrolling parties are equipped with high-end surveillance equipments but yet an alternative to the ply of huge manpower and that too in harsh environmental conditions hasn’t been in existence. An automatic mechanism for smart surveillance and combat is proposed in this paper as a solution to the above-discussed problems. Smart surveillance requires automatic intrusion detection in the surveillance video, which is achieved by using optical flow information as motion features for intruder/human in the scene. The use of optical flow in the proposed smart surveillance makes it robust and more accurate. Use of a simple horizontal feature for fence detection makes system simple and faster to work in real-time. System is also designed to respond against the activities of intruders, of which auto combat is one kind of response

Implementation of Banker’s Algorithm Using Dynamic Modified Approach

Banker’s algorithm referred to as resource allocation and deadlock avoidance algorithm that checks for the safety by simulating the allocation of predetermined maximum possible of resources and makes the system into s-state by checking the possible deadlock conditions for all other pending processes. It needs to know how much of each resource a process could possibly request. Number of processes are static in algorithm, but in most of system processes varies dynamically and no additional process will be started while it is in execution. The number of resources are not allow to go down while it is in execution. In this research an approach for Dynamic Banker's algorithm is proposed which allows the number of resources to be changed at runtime that prevents the system to fall in unsafe state. It also give details about all the resources and processes that which one require resources and in what quantity. This also allocates the resource automatically to the stopped process for the execution and will always give the appropriate safe sequence for the given processes

Effects of soot deposition and slot erosion on the mist film-cooling of a flat plate in the presence of upstream ramp

In the present work, the numerical analysis is conducted on the film cooling of a flat plate with the air and mist injection from a slot. The effect of soot deposition and erosion of the cooling slot has been investigated in the presence of an upstream ramp. Simulations are performed at blowing ratios, M = 1, 1.5 and 2 with the slot angles, θ = 30°, 45° and 60°. The effect of presence of upstream ramp is studied by varying ramp angles from α = 5° to 15°. The numerical study is carried out on Eulerian-Eulerian framework. Thermal phase change model based on the evaporation and condensation is used to account heat and mass transfer. It is found that the film cooling effectiveness is better for the mist injection as compared to the air injection. Soot deposition on the cooling slot has a significant influence on the film cooling effectiveness. The soot deposition is not always adversely affecting the film cooling effectiveness. Moreover, the film cooling effectiveness decreases for the eroded slot for all the investigated slot angles and ramp angles for mist injection. An increment in the film cooling effectiveness is observed for 0 < x/2w < 15 in the presence of the upstream ramp; thereafter film cooling decreases as compared to the case without the upstream ramp. The optimum slot angle to inject the mist is found to be θ = 45°

AUTONOMOUS TRAFFIC PREDICTION: A DEEP LEARNING-BASED FRAMEWORK FOR SMART MOBILITY

The term deep learning-based framework for smart mobility refers to a concept or research article that suggests a framework for traffic pattern prediction using deep learning methods in the context of smart mobility. To improve traffic prediction skills and create more intelligent and effective transportation systems, the Autonomous traffic prediction: A deep learning-based framework for smart mobility idea proposes to make use of the potential of deep learning algorithms. In this study, a new Improved Spider Monkey Swarm Optimized Generative Adversarial Network (ISMSO-GAN) approach is introduced to forecast autonomous traffic for smart mobility. In this case, the GAN's classification effectiveness is increased by using the ISMSO method. The Regional Transportation Management Center's traffic dataset for Twin Cities' metro freeways is used to assess the success of the suggested approach. The noisy data from raw data samples are removed using the Adaptive Median Filter (AMF) filter. To extract the properties from the segmented data, a Kernel Principal Component Analysis (KPCA) is performed. The results of the research show that recommended methodology beats earlier approaches in terms of accuracy, Mean Square Error (MSE), Mean Absolute Error (MAE), and Prediction Rate. Our proposed method might considerably enhance traffic management and maximize resource allocation

Large Eddy Simulations for Film Cooling Assessment of Cylindrical and Laidback Fan-Shaped Holes With Reverse Injection

The large eddy simulations (LES) are performed to access the film cooling performance of cylindrical and reverse shaped hole for forward and reverse injection configurations. In the case of reverse/backward injection, the secondary flow is injected in such a way that its axial velocity component is in the direction opposite to mainstream flow. The study is carried out for a blowing ratio (M =1), density ratio (DR =2.42), and injection angle (α = 35 deg). Formation of counter-rotating vortex pair (CRVP) is one of the major issues in the film cooling. This study revealed that the CRVP found in the case of forward cylindrical hole which promotes coolant jet "liftoff" is completely mitigated in the case of the reverse shaped hole. The coolant coverage for reverse cylindrical and reverse shaped holes is uniform and higher. The reverse shaped hole shows promising results among investigated configurations. The lateral averaged film cooling effectiveness of reverse shaped hole is 1.16-1.42 times higher as compared to the forward shaped holes. The improvement in the lateral averaged film cooling effectiveness of reverse cylindrical hole (RCH) injection over forward cylindrical hole (FCH) injection is 1.33-2 times

Towards A Measure Of General Machine Intelligence

To build general-purpose artificial intelligence systems that can deal with unknown variables across unknown domains, we need benchmarks that measure how well these systems perform on tasks they have never seen before. A prerequisite for this is a measure of a task's generalization difficulty, or how dissimilar it is from the system's prior knowledge and experience. If the skill of an intelligence system in a particular domain is defined as it's ability to consistently generate a set of instructions (or programs) to solve tasks in that domain, current benchmarks do not quantitatively measure the efficiency of acquiring new skills, making it possible to brute-force skill acquisition by training with unlimited amounts of data and compute power. With this in mind, we first propose a common language of instruction, a programming language that allows the expression of programs in the form of directed acyclic graphs across a wide variety of real-world domains and computing platforms. Using programs generated in this language, we demonstrate a match-based method to both score performance and calculate the generalization difficulty of any given set of tasks. We use these to define a numeric benchmark called the generalization index, or the g-index, to measure and compare the skill-acquisition efficiency of any intelligence system on a set of real-world tasks. Finally, we evaluate the suitability of some well-known models as general intelligence systems by calculating their g-index scores.Comment: 31 pages, 15 Figures, 3 Tables; Sample Data and g-index Reference Code at https://github.com/mayahq/g-index-benchmark; g-index toy environment at https://github.com/mayahq/flatland; version 2 added a section about the toy environment; version 3 compressed images to reduce file size; version 4 updated description of flatland toy environmen

EFFECT OF GAMMA IRRADIATION TECHNIQUE ON THE MICROBIAL AND NUTRITIONAL QUALITY OF EDIBLE BAMBOO SHOOT (Dendrocalamus asper) FOR SHELF-LIFE ENHANCEMENT

The present investigation was performed to evaluate the potential of gamma radiation as a postharvest technology to preserve bamboo shoots. For this, Dendrocalamus asper shoots were gamma irradiated in the dose range of 0.5 to 5.0 kGy followed by storage at 5 ± 2 °C temperature dipped into 2% NaCl solution. Acceptability of the irradiated product was assessed based on microbial, physicochemical, and organoleptic attributes as well as induced radioactivity (food safety parameter). Results of the study revealed that a dose of 2.5 kGy was sufficient to complete removal of microbial load from the bamboo shoot up to 4 log reductions when compared with the unirradiated sample. No significant changes were found in physicochemical parameters including protein, pH, moisture, HCN content, and minerals. Organoleptic evaluation for different parameters were was within the acceptable criteria up to 240 days, hence 2.5 kGy doses of irradiation had the best preservation effect on the bamboo shoots of D. asper. The result of this study suggests that irradiation could be a potential method for maintaining the quality of bamboo shoots during storage

Endoscopic management of retrocalcaneal pain: a prospective observational study

Background: In an effort to reduce morbidity and complications of open surgery, an endoscopic technique was used for the management of the conditions leading to retrocalcaneal pain. With this purpose, the current study was undertaken to evaluate results of endoscopic management of retrocalcaneal pain using American orthopaedic foot and ankle score (AOFAS).Methods: 20 patients (26 heels) in the age group 18-80 years presenting with retrocalcaneal pain not responding to conservative management underwent endoscopic decompression of the retrocalcaneal bursae and excision of bony spurs. Two portals were created, one laterally and one medially, over the posterosuperior portion of the calcaneus to gain access to the retrocalcaneal space. The inflamed bursal tissue was identified and removed, and the prominent bone was resected. The functional outcome was evaluated pre and postoperatively with the AOFAS.Results: 70% patients have retrocalcaneal bursitis, 20% Haglund’s deformity as confirmed on lateral view of ankle X-ray and only 10% of non-insertional tendinosis. Mean operative time was 54.95 minutes. Mean duration of hospital stay was 3.90±0.64 and the mean follow-up was 66 days (range 30-180 days). The average AOFAS score improved from 65.60 points pre-operatively to 96.80 points at final follow-up. There were fifteen excellent results, seven good results, two fair results and two poor results.Conclusions: Endoscopic procedure for retrocalcaneal bursitis and Haglund deformity seemed to be a safe and efficacious option for surgical treatment of retrocalcaneal pain

Transverse cerebellar diameter: a reliable predictor of gestational age

Objectives: To determine accuracy of transverse cerebellar diameter (TCD) measurement in the prediction of gestational age (GA) in normal fetuses; to develop reference chart for TCD according to GA in Indian population. Design: A retrospective cross-sectional study. Method: Ultrasonographic measurements in 300 singleton pregnant women included biparietal diameter (cm), head circumference (cm), abdominal circumference (cm), femur length (cm) and transverse cerebellar diameter (cm). Reference chart with mean TCD for corresponding gestational age (GA) in weeks was developed. Results: Statistically significant relationship found between TCD and gestational age (R2=0.92, p=0.0006). Regression formulae based on TCD with other parameter can be used to predict gestational age of foetus. When TCD is compared with findings in other studies in different ethnic population, it is found that there is significant difference exists. Conclusion: In normally developing fetuses the TCD has linear correlation with advancing gestational age. A separate reference chart is required for every different population because ethnicity, nutrition and environmental factors can have impact on normal TCD values. This will help to avoid misinterpretation of data to determine gestational age