Nowadays, most information and communication technologies target literate users and neglect the 800 million illiterate individuals around the world. Although there have been several attempts to develop systems that he...
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A revolutionary approach for enhancing driving efficiency and safety in intelligent transportation systems (ITS) is deploying autonomous vehicles. Vehicle-to-everything (V2X) technology facilitates interactions betwee...
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An advanced hybrid renewable energy collecting and storage system prototype that utilizes water flow as its primary power source. Additionally, the system incorporates an energy monitoring system based on the Internet...
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Industrial and distribution service problems that belong to combinatorial optimization include vehicle routing with Vehicle Routing Problem. This research builds a framework and implements it in a multi-class optimiza...
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Load balancing and scheduling are essential components of cloud computing that aim to optimize resource allocation and utilization. In a cloud environment, multiple virtual machines and applications compete for shared...
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The conventional approach to scalp inspection in the hairdressing industry relies on manually interpreting scalp symptom images. Hairdressers provide treatments based on visual assessment, leading to potential inaccur...
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Endocrine tumors are malignant tumors that get up inside the endocrine system, a network of glands and organs responsible for producing hormones that affect the physiological procedures of the frame. Although endocrin...
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ISBN:
(纸本)9798350383348
Endocrine tumors are malignant tumors that get up inside the endocrine system, a network of glands and organs responsible for producing hormones that affect the physiological procedures of the frame. Although endocrine tumors are usually unusual, early detection is critical for successful treatment. Due to the lack of reliable medical markers for endocrine tumors, early detection is mainly predicated on imaging and laboratory tests. However, these checks may be luxurious and can be hard to interpret. In recent years, time collection analysis (TSA) has been gaining popularity as a powerful device for the early detection of unclassified endocrine tumors. Time series analysis is a form of statistical evaluation that applies mathematical fashions to datasets by converting data values over a hard and fast time frame. It's miles used to discover trends in the facts, making it possible to discover abnormal behavior that could indicate contamination. This method has been shown to have a high degree of accuracy. It may provide insight into, in any other case, unclassified endocrine tumors, making an allowance for the set-off detection and remedy. In this paper, we discuss the capacity of time collection evaluation inside the early detection of unclassified endocrine tumors, alongside the demanding situations and opportunities associated with its use. Time series evaluation has been established to be a powerful tool for the early detection of unclassified endocrine tumors. By presenting perception into patterns and developments in temporal information, this method allows studies to pinpoint regions of molecular change from which ability biomarkers can be diagnosed. The technique is predicated on measuring and analyzing adjustments inside the gene expression levels of regulation networks over time. This method has been used to become aware of adjustments within the expression of pathways related to G protein-coupled receptors and pathways associated with endocrinology. Moreove
Hyperspectral pictures are complicated information items with high spectral resolution, making their categorization and analysis timeingesting and challenging. Traditional strategies for classifying hyperspectral pix ...
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ISBN:
(纸本)9798350383348
Hyperspectral pictures are complicated information items with high spectral resolution, making their categorization and analysis timeingesting and challenging. Traditional strategies for classifying hyperspectral pix may be unreliable and gradually attributable to the presence of diverse noise resources and a high range of pixels. This paper proposes a new unsupervised classification approach for hyperspectral pictures using function extraction and fuzzy common sense. The method starts by first using feature extraction techniques on the hyperspectral pictures to lessen the dimensionality of the facts. Numerous characteristic extraction algorithms, including primary thing analysis (PCA) and impartial component evaluation (ICA), are tested to determine which function extraction algorithms yield satisfactory effects. The reduced function area is then used as an entry for the fuzzy category system. The bushy common sense device is used to classify the hyperspectral pix into distinctive classes according to the extracted capabilities. Experimental results display that the proposed method achieves proper effects for the category venture with classification accuracy accomplishing as high as 79%. The proposed technique demonstrates advanced performance over conventional category strategies in terms of each accuracy and speed. Hyperspectral pics (HSI) offer valuable statistics approximately the environment and the functions gift inside it. But, the sheer quantity of facts present in HSI makes guide evaluation of those photos a time-eating and exhausting project. As such, there is a growing demand for robust and reliable automated techniques to analyze HSI. In this context, unsupervised tactics for classifying HSI have gained interest due to their ability to examine facts without requiring manually categorized education facts. Fuzzy logic is one method being explored for unsupervised HSI type due to its capability to assign more than one label to pixels of the image and its r
Currently,security-critical server programs are well protected by various defense techniques,such as Address Space Layout Randomization(ASLR),eXecute Only Memory(XOM),and Data Execution Prevention(DEP),against modern ...
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Currently,security-critical server programs are well protected by various defense techniques,such as Address Space Layout Randomization(ASLR),eXecute Only Memory(XOM),and Data Execution Prevention(DEP),against modern code-reuse attacks like Return-oriented Programming(ROP)***,in these victim programs,most syscall instructions lack the following ret instructions,which prevents attacks to stitch multiple system calls to implement advanced behaviors like launching a remote *** this kind of gadget greatly constrains the capability of code-reuse *** paper proposes a novel code-reuse attack method called Signal Enhanced Blind Return Oriented Programming(SeBROP)to address these *** SeBROP can initiate a successful exploit to server-side programs using only a stack overflow *** leveraging a side-channel that exists in the victim program,we show how to find a variety of gadgets blindly without any pre-knowledges or reading/disassembling the code ***,we propose a technique that exploits the current vulnerable signal checking mechanism to realize the execution flow control even when ret instructions are *** technique can stitch a number of system calls without returns,which is more superior to conventional ROP ***,the SeBROP attack precisely identifies many useful gadgets to constitute a Turing-complete *** attack can defeat almost all state-of-the-art defense *** SeBROP attack is compatible with both modern 64-bit and 32-bit *** validate its effectiveness,We craft three exploits of the SeBROP attack for three real-world applications,i.e.,32-bit Apache 1.3.49,32-bit ProFTPD 1.3.0,and 64-bit Nginx *** results demonstrate that the SeBROP attack can successfully spawn a remote shell on Nginx,ProFTPD,and Apache with less than 8500/4300/2100 requests,respectively.
In this paper, we will discuss how a secure link-sharing system based on QR codes was created and put into operation. In recent years, QR codes have grown in popularity since they expedite link sharing and provide use...
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