Computer Sciencee

The internet today has become an unrivalled source of information where people converse on content based websites such as Quora, Reddit, StackOverflow and Twitter asking doubts and sharing knowledge with the world. A major arising problem with such websites is the proliferation of toxic comments or instances of insincerity wherein the users instead of maintaining a sincere motive indulge in spreading toxic and divisive content. The straightforward course of action in confronting this situation is detecting such content beforehand and preventing it from subsisting online. In recent times Transfer Learning in Natural Language Processing has seen an unprecedented growth. Today with the existence of transformers and various state of the art innovations, a tremendous growth has been made in various NLP domains. The introduction of BERT has caused quite a stir in the NLP community. As mentioned, when published, BERT dominated performance benchmarks and thereby inspired many other authors to experiment with it and publish similar models. This led to the development of a whole BERT-family, each member being specialized on a different task. In this paper we solve the Insincere Questions Classification problem by fine tuning four cutting age models viz BERT, RoBERTa, DistilBERT and ALBERT

Transacted Memory offers persistence, undoability and auditing. We present a Java/JML Reference Model of the Transacted Memory system on the basis of our earlier separate Z model and C implementation. We conclude that Java/JML combines the advantages of a high level specification in the JML part (based on our Z model), with a detailed implementation in the Java part (based on our C implementation). * To appear in the proceedings of Fifth Smart Card Research and Advanced Application Conference (CARDIS'02) 1 Java and all Java-based trademarks and logos are trademarks or registered trademarks of Sun Microsystems, Inc. in the U.S. or other countries, and are used under license.

As there is rapid development in computer technology; the interaction between human and computer is become a topic of research, where we can use mobile devices for data mining applications as mobile devices are user friendly and incorporates with many powerful sensors. These sensors include acceleration sensors, vision sensors, audio sensors, light sensors, temperature sensors, direction sensors, and GPS sensors. In this paper we describe the uses of android mobile accelerometers and computer for gestures recognition for hand written digit and survey of recent hand gesture recognition systems is presented. Key issues of hand gesture recognition system are presented with challenges of gesture system. Also review methods of recent gestures recognition system are presented. Index-terms Hand Gesture, GPS, Human Computer Interaction (HCI).

Journaling is a relatively new feature of modern file systems that is not yet exploited by most digital forensic tools. A file system journal caches data to be written to the file system to ensure that it is not lost in the event of a power loss or system malfunction. Analysis of journal data can identify which files were overwritten recently. Indeed, under the right circumstances, analyzing a file system journal can reveal deleted files and previous versions of files without having to review the hex dump of a drive. This paper discusses data recovery from ReiserFS and ext3, two popular journaled file systems. It also describes a Java-based tool for analyzing ext3 file system journals and recovering data pertaining to overwritten and deleted files.

We argue that the evident utility of scenario-based modeling can be greatly enhanced when enriched with a mathematically precise notion of conditionality and partiality, such as that found in Triggered Message Sequence Charts (TMSCs). Unlike traditional Message Sequence Charts, the TMSC formalism allows scenarios to be conditional and partial, supports logical as well as behavioral operators for scenario composition, and is equipped with a refinement notion drawn from traditional process theory that provides a rigorous basis for stepwise development of specifications. This paper illustrates these points via the Center TRACON Automation System for flight control.

Stock market prediction is an important topic in ?nancial engineering especially since new techniques and approaches on this matter are gaining value constantly. In this project, we investigate the impact of sentiment expressed through Twitter tweets on stock price prediction. Twitter is the social media platform which provides a free platform for each individual to express their thoughts publicly. Specifically, we fetch the live twitter tweets of the particular company using the API. All the stop words, special characters are extracted from the dataset. The filtered data is used for sentiment analysis using Naïve bayes classifier. Thus, the tweets are classified into positive, negative and neutral tweets. To predict the stock price, the stock dataset is fetched from yahoo finance API. The stock data along with the tweets data are given as input to the machine learning model to obtain the result. XGBoost classifier is used as a model to predict the stock market price. The obtained p...

In different fields of the humanities annotations of multimodal resources are a necessary component of the research workflow. Examples include linguistics, psychology, anthropology, etc. However, creation of those annotations is a very laborious task, which can take 50 to 100 times the length of the annotated media, or more. This can be significantly improved by applying innovative audio and video processing algorithms, which analyze the recordings and provide automated annotations. This is the aim of the AVATecH project, which is a collaboration of the Max Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS. In this paper we present a set of results of automated annotation together with an evaluation of their quality.

This paper introduces a modeling level-oriented approach for BIM studies according to the abstraction of generated information structures. Models for different abstraction levels are necessary to define patterns, describe rules, store information and define data exchange needs, as well as to create of basic units that describe the constructive elements and design information. The effectiveness of the approach for BIM integration and cooperation is deeply related with coordination among different modeling levels. The ...

In the context of the 4 industrial revolution, the knowledge and management of the precise topological and geographical location of industrial equipment is a growing necessity. However, a holistic concept for topology and location management in processand factory automation networks down to the field level is yet unknown. In this work, existing network and location management mechanisms are surveyed for suitability in industrial automation networks. Special attention is given to the inclusion of the non-TCP/IP protocol IO-Link to integrate sensors and actuators on the field level into a holistic network management concept. Since the proposed solution is based on established standards, it can be easy integrated it into existing implementations.

In recent years, we have seen dramatic progress in the field of Hand Gesture Recognition, yet these applications have some drawback. Keeping in view the trend of making application more interactive and simple, easy to use as well as cost efficient, a Hand Gesture Recognition based system is developed to allow interactive control of application using hand gesture. This paper presents a framework for hand gesture recognition based system which controls the mobile application. The working of this framework is based on the information fusion of 3 Axis Accelerometer (ACC) and Surface Electromyography (SEMG) sensors. A Gaussian Mixture Model (GMM) and Fast Dynamic Time Warping Algorithm (FDTW) are utilised to get the final result. In addition the system including a wearable hand gesture sensing device which is worn on the forearm and an algorithmic framework for the smart phone to recognise the hand gesture. The Armband which is worn on the forearm is able to manipulate 11 predefined gest...

In clinical conclusion, the expectation of an illness plays a significant role in breaking down the medical pictures. An undesirable sudden cell development in any piece of the organ is known as a tumor. Tumor might be benign or malignant. Harmful/malignant tumors are viewed to be very risky. Along these lines, the early detection of even the Architectural Distortion (AD) of the tissue cells helps forestalling cancer. In ladies, breast cancer is treated as the most critical issue. There are different specialist studies about the prediction of breast cancer malignant growth. This paper plots to survey and analyze different deep learning procedures that are explicitly considered on breast cancer

Public key infrastructure is used in most networks requiring user authentication, digital signature, cryptographic confidentiality, and non repudiation of information. The main protocols and architectures used in a PKI are the public key cryptosystem and the RSA digital signature. Their robustness is based on the difficulty to obtain prime factors of a large composite number. Notwithstanding, if the primes generated by a PKI are predictable or represent a small set of possible primes, the security of the PKI certificate is compromised. This article is part of a line of research aiming to develop auditing tools of PKI performance and to detect anomalies in the generation and distribution of prime values delivered by OpenSSL, if such anomalies are present.

Pipelines are regarded as the lifelines of the national economy of most oil producing countries. This is because these pipelines which cover thousands of kilometers are used to transport large volumes of refined and unrefined petroleum products, crude oil and natural gas. These pipelines often come under terrorist attacks and vandalism which can lead to pollution problems, theft of the contents of the pipeline and huge economic loss. In view of this, it is very necessary that these pipelines are monitored from time to time to forestall these losses. Manual monitoring of pipelines is a very expensive process and also dangerous especially in hazardous environments. Remote monitoring of these pipelines involves monitoring the pipelines from remote locations. This research work monitors pipelines by using remote monitoring to wirelessly monitor the pipelines in real time and reports to the control center whenever it gets a value above the threshold value. The parameters monitored are te...

Evaluating AI is a challenging task, as it requires an operative definition of intelligence and the metrics to quantify it, including amongst other factors economic drivers, depending on specific domains. From the viewpoint of AI basic research, the ability to play a game against a human has historically been adopted as a criterion of evaluation, as competition can be characterized by an algorithmic approach. Starting from the end of the 1990s, the deployment of sophisticated hardware identified a significant improvement in the ability of a machine to play and win popular games. In spite of the spectacular victory of IBM's Deep Blue over Garry Kasparov, many objections still remain. This is due to the fact that it is not clear how this result can be applied to solve real-world problems or simulate human abilities, e.g., common sense, and also exhibit a form of generalized AI. An evaluation based uniquely on the capacity of playing games, even when enriched by the capability of learning complex rules without any human supervision, is bound to be unsatisfactory. As the internet has dramatically changed the cultural habits and social interaction of users, who continuously exchange information with intelligent agents, it is quite natural to consider cooperation as the next step in AI software evaluation. Although this concept has already been explored in the scientific literature in the fields of economics and mathematics, its consideration in AI is relatively recent and generally covers the study of cooperation between agents. This paper focuses on more complex problems involving heterogeneity (specifically, the cooperation between humans and software agents, or even robots), which are investigated by taking into account ethical issues occurring during attempts to achieve a common goal shared by both parties, with a possible result of either conflict or stalemate. The contribution of this research consists in identifying those factors (trust, autonomy, and cooperative learning) on which to base ethical guidelines in agent software programming, making cooperation a more suitable benchmark for AI applications.

Cardiovascular disease (CVD) is a leading cause of death and a major contributor to disability. Early detection of cardiovascular disease using ANFIS has the potential to reduce costs and simplify treatment. This study aims to develop a prediction model using ANFIS (Adaptive Neuro-Fuzzy Inference System) for early detection of cardiovascular disease. The dataset used consists of 500 data with 12 features, including various risk factors such as blood sugar levels, cholesterol, uric acid, systolic blood pressure, diastolic blood pressure, body mass index (BMI), age, smoking habits, lifestyle, genetic factors, and gender, and one label feature. This study compares cardiovascular disease prediction models using machine learning methods, namely Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), and ANFIS. The development of the KNN algorithm involves the value of K=5 with the Euclidian distance measure. The SVM algorithm used a kernel cache of 200 and a convergence epsilon of 0.001. The ANFIS model was built using 500 data sets divided into training (70%) and testing (30%) data, with learning rate variations of 0.01, 0.05, 0.1, 0.2, and 0.5. The results of testing the early detection model show for SVM, the accuracy value is 0.760, the precision value is 0.839, and the recall value is 0.671. For the KNN model, the accuracy value is 0.758, the precision value is 0.768, and the recall value is 0.771. As for the ANFIS model, the accuracy value reaches 0.989, precision value 0.996, and recall value 0.988. The model using ANFIS has the highest performance. Further study of the model using ANFIS with learning rate variations shows that a learning rate of 0.1 provides the most optimal performance.

In collaborative environments, coordination is an essential matter to the specification of activities, which are described as sets of interdependent tasks. An extensible framework encompassing coordination mechanisms to specify tasks interdependencies is initially presented. These mechanisms are formally modeled using Petri nets and, along with a Petri net representation for the tasks to be performed, can be used to create a model to evaluate the environment. The use of this framework is illustrated in the context of a learning environment based on collaborative Web document construction.

The coordination of interdependencies among activities in collaborative environments is a very important and difficult task. In this paper we present a set of coordination mechanisms for the specification and control of interaction among collaborative activities. To model these mechanisms, we use high level Petri nets, which have proven to be an adequate approach to evaluate the behavior of a computer supported collaborative system before its implementation.

This paper presents the development of a web application, which aims to provide a platform for white paper authors to upload and have their documents reviewed by industry experts and scholars. The web app will utilize Ethereum block chain technology to provide security and authenticity to the uploaded white papers, which will be converted into non-fungible tokens to ensure their uniqueness. The authors will have the ability to self-upload their white papers onto a secured IPFS (Inter Planetary File System) database and use ERC721 (Ethereum Request for Comments) protocols to mint them as non-fungible tokens. In addition, the web app will allow white paper authors to receive crowdfunded support from users holding ETH in their web3 wallets. With our unique authentication system utilizing decentralized techniques, the Paper Publication Portal ensures that only verified authors can publish their work, enhancing both the security and credibility of the platform.

An absolute prerequisite for the management of large investigating methods to build high-level monitoring computer networks is the ability to measure their systems that are built on top of existing monitoring performance. Unless we monitor a system, we cannot tools. Due to the heterogeneous nature of the hope to manage and control its performance. In this underlying systems at NASA Langley Research Center, paper, we describe a network monitoring system that we use an object-oriented approach for the design, we are currently designing and implementing. Keeping, first, we use UML (Unified Modeling Language) to in mind the complexity of the task and the required model users' requirements. Second, we identify the flexibility for future changes, we use an object-oriented existing capabilities of the underlying monitoring design methodology. The system is built using the system. Third, we try to map the former with the latter. APIs offered by the HP OpenView system.

In recent days, data resources such as documents, PDFs, texts, power points, applications, softwares, graphics, images, audios, songs, animations, videos, etc. are shared in many websites for improving knowledge of the people. Website owner are managing these content which are uploaded by registered users in the websites with help of code developers and it's a tedious process .Several websites are earning more money from the resource provider and advertiser for the publishing the information and adds in their website. Compare to resource provider, website owners are financially benefitted. We proposed a system to manage the website content easily and improve the financial status of resource providers. Content Management System is used for managing the website content and it's an effective tool which allows the users to share and manage the information easily through the use of web browsers. The website owner provides amount for the resource providers according to usage of resource by other users.

In this paper, we describe EMMA (E-Mail Management Assistant), an e-mail system that addresses the process of e-mail management, from initially sorting messages into virtual folders, to prioritizing, reading, replying (automatically or semi-automatically), archiving and deleting mail items. EMMA attains a high degree of accuracy on email classification by using a rule-based approach known as Ripple Down Rules (RDR) as the basis of rule construction. In contrast to traditional rule-based systems, RDR systems provide extensive help to the user in defining rules and maintaining the consistency of a rule base, making EMMA easy to use. We discuss the results of evaluating the usability of EMMA on a trial of independent users.

A distributed system is one in which components located at networked computers communicate and coordinate their actions only by passing messages. Now days Distributed system face different type of problems. One of those problems is load balancing in distributed system. A lot of improvement in hardware is being done. But in this paper we are representing a software technique in which a heuristic is designed to optimize the query processing with the help of cost optimization. Cost of query processing is depending on different parameter. With the help of all parameter we have design a heuristic (A mathematical equation) which helps to have best query sequencing and designing to have optimum load balancing in distributed environment. For the representation of query operation sequencing we use the concept of operator tree.

Pendidikan inklusif adalah suatu sistem pendidikan yang menyertakan semua anak secara bersama-sama dalam suatu proses pembelajaran dengan layanan pendidikan yang layak dan sesuai dengan kebutuhan individu siswa tanpa membedakan anak dari latar belakang suku, ras, status sosial, kemampuan ekonomi, status politik, bahasa, gografis, jenis kelamin, agama/kepercayaan dan perbedaan kondisi fisik atau mental. Penelitian ini bertujuan mendeskripsikan tentang upaya mengembangkan kemampuan bahasa dalam mengenal angka melalui media geometri warna. Jenis penelitian yang digunakan adalah jenis penelitian kualitatif dimana peneliti hanya berupaya mengembangkan kemampuan bahasa dengan konsep mengucap pada anak berkebutuhan khusus (ABK) tuna daksa melalui media geometri warna, peneliti berusaha mengkaji dan merefleksikan secara mendalam tentang anak tuna daksa menggunakan media geometri warna terhadap kemampuan bahasa anak dalam proses belajar mengajar di sekolah dengan Subjek penelitian ini berjum...

One of the elements that have popularized and facilitated the use of geographical information on a variety of computational applications has been the use of Web maps; this has opened new research challenges on different subjects, from locating places and people, the study of social behavior or the analyzing of the hidden structures of the terms used in a natural language query used for locating a place. However, the use of geographic information under technological features is not new, instead it has been part of a development and technological integration process. This paper presents a state of the art review about the application of geographic information under different approaches: its use on location based services, the collaborative user participation on it, its contextual-awareness, its use in the Semantic Web and the challenges of its use in natural languge queries. Finally, a prototype that integrates most of these areas is presented.

SQL injection attack is one of the most serious security vulnerabilities in many Databases Managements systems. Most of these vulnerabilities are caused by lack of input validation and SQL parameters used particularity at this time of technology revolution. The results of a SQL injection attack (SQLIA) are unpleasant because the attacker could wipe the entire contents of the victim's database or shut it down. As such, SQLIA can be used as important weapons in cyber warfare. As an attempt of breaching of number of application data bases systems two SQL injection techniques were used to successful locating vulnerable points during this research which are Blind Text Injection Differential and Error based Exploitation. The motivations behind were to find out where the databases systems are most likely to face an attack and proactively shore up those weaknesses before exploitation by hackers. The success of both techniques is a result of poor web server (online database server) desig...

Centralized systems management approaches have been recently investigated in the academia and implemented in the industry aiming to facilitate the deployment of disk images to groups of machines. The old approach of installing and configuring each machine individually is most of the time impractical and error-prone. However, no study to date has sought to investigate different design alternatives for storage systems supporting centralized disk image management, or evaluate their performance and scalability. In this paper, we first propose the notion of stackable storage as a mechanism to organize disk images on centralized storage servers, and show how this mechanism would help the system administrator to perform typical management tasks. We next discuss different design options by varying three key components of the stackable storage design space. Finally, we prototype the design options and evaluate their performance behavior and scalability.

System" capable of using system models to ensure command safety while monitoring system performance, and develop and test a "Cognitive Firewall" and "Cognitive Supervisor." This system is tested in theory and practice for three threat models. As the Internet of Things (IoT) grows by leaps and bounds fusing the digital and physical, it must address security challenges to assure safe, continued growth. 1 To date, the proliferation of increasingly-connected devices has not been met with a commensurate increase in dependability and resilience. 2 Today's IoT includes overly-permissive or excessively-inhibited systems, a problem that grows as we put increasingly sensitive and valuable devices on the Internet. The resulting complexity makes IoT difficult to use, while exposing Internet infrastructure to unnecessary risks ranging from Distributed Denial of Service (DDoS) attacks 3 to power generation and distribution threats. 4,5 Yet, we welcome helpful IoT devices into our homes and workplaces -the same devices that compromise the integrity of critical systems.

This paper presents an application titled "Rapid Response Fall Detection System" RRFD. This application aims to detect when a cyclist has suffer an accident, and alerts the emergency contacts about the accident. “RRFD” uses the cellphone built-in accelerometer for fall detection, and the GPS to provide an accurate location. When a fall is detected, the application sends an alert via text message to previously selected contacts. Any sudden fall will activate the application and send the text with information of whether the rider requires assistance and / or immediate medical help. In the event that the cyclist is unable to request assistance or help, it provides the route and location of the cyclist using various tools of high accuracy. Keywords—Fall detection, cyclist, accelerometer, GPS, emergency. Digital Object Identifier (DOI): http://dx.doi.org/10.18687/LACCEI2017.1.1.441 ISBN: 978-0-9993443-0-9 ISSN: 2414-6390

This paper describes the main components of MiPad (Multimodal Interactive PAD) and especially its distributed speech processing aspects. MiPad is a wireless mobile PDA prototype that enables users to accomplish many common tasks using a multimodal spoken language interface and wireless-data technologies. It fully integrates continuous speech recognition and spoken language understanding, and provides a novel solution for data entry in PDAs or smart phones, often done by pecking with tiny styluses or typing on minuscule keyboards. Our user study indicates that the throughput of MiPad is significantly superior to that of the existing pen-based PDA interface. Acoustic modeling and noise robustness in distributed speech recognition are key components in MiPad's design and implementation. In a typical scenario, the user speaks to the device at a distance so that he or she can see the screen. The built-in microphone thus picks up a lot of background noise, which requires MiPad be noise robust. For complex tasks, such as dictating e-mails, resource limitations demand the use of a client-server (peer-to-peer) architecture, where the PDA performs primitive feature extraction, feature quantization, and error protection, while the transmitted features to the server are subject to further speech feature enhancement, speech decoding and understanding before a dialog is carried out and actions rendered. Noise robustness can be achieved at the client, at the server or both. Various speech processing aspects of this type of distributed computation as related to MiPad's potential deployment are presented in this paper. Recent user interface study results are also described. Finally, we point out future research directions as related to several key MiPad functionalities.

The image is encrypted and decrypted using modular operations such as addition and multiplication. The operations like rotation and ex-or implemented to increase the complexity of the encryption algorithms. All these implemented and simulated in Xilinx ISE. Area, delay of encryption and decryption are tabulated and compared.

The future of India will be formed in the lecture hall. Whereas India has made great steps in refining the education system but much still remains to be complete. If you see the current situation then you will find that there is a torrent of advanced technology all over the world but our education system is not helping due to the absence of information and information of teachers, students, and the organization. The students have their own limitations, teachers have their owned and the organization is also confessing the fact that the education system is really in a poor form today. The aim of this paper is to skeleton how information technology can help to make an education system that is based on the ideologies of helping teachers, students, and management to be effective in what they do, improving the superiority and significance of teaching-learning process.

With the improvement in IT industry, more and more application of computer software is introduced in teaching and learning. In this paper, we discuss the development process of such software. Diabetic Retinopathy is a common complication for diabetic patients. It may cause sight loss if not treated early. There are several stages of this disease. Fundus imagery is required to identify the stage and severity of the disease. Due to the lack of proper dataset of the fundus images and proper annotation, it is very difficult to perform research on this topic. Moreover, medical students are often facing difficulty with identifying the diseases in later stage of their practice as they may not have seen a sample of all of the stages of Diabetic Retinopathy problems. To mitigate the problem, we have collected fundus images from different geographic area of Bangladesh and designed an annotation software to store information about the patient, the infection level and their locations in the images. Sometimes, it is difficult to select all appropriate pixels of the infected region. To resolve the issue, we have introduced a K nearest neighbor (KNN) based technique to accurately select the region of interest (ROI). Once an expert (ophthalmologist) has annotated the images, the software can be used by the students for learning.

An analysis of some long text if authors are unknown or if it was written by one author is still an interesting problem and it could be done using methods of data analysis and data mining, and using structural analysis. In the paper, it is described a system of modified Self-Organizing Maps working on probabilistic sequences built from a text. The sequences were built on letters and on words as n-grams, 1 ≤ n ≤ 4. The system is trained to input sequences and after the training it determines text parts with anomalies (some different characteristics) using a cumulative error and a complex analysis. In tested long texts the system was successful, it covered a composition of texts.

In the paper, there are analyzed and compared results of usable methods for discrepancies detection based on character n-gram profiles (the set of character n-gram normalized frequencies of a text) for English and Arabic documents. English and Arabic texts were analyzed from many statistical characteristics point of view. We covered some statistical differences between both languages and we applied some heuristics for measurements of text parts dissimilarities. The results for each text can call for an attention to the text (or not) if the text parts were written by the same author. We evaluate some Arabic and English documents and show its parts they contain discrepancies and they need some following analysis for plagiarism detection. The analysis depends on selected parameters prepared in experiments.

Texts (books, novels, papers, short messages) are sequences of sentences, words or symbols. Each author has an unique writing style. It can be characterized by some collection of attributes obtained from texts. The text verification is the case of an authorship verification where we have some text and we analyze if all parts of this textwere written by the same (unknown or known) author. In this paper, there are analyzed and compared results of two developed methods for a text verification based on ngrams of symbols and on local histograms of words. The results of a symbol n-gram method and a method of word histograms for a dissimilarities searching in text parts of each text are analyzed and evaluated. The searched dissimilarities call for an attention to the text (or not) if the text parts were written by the same author or not. The attention depends on selected parameters prepared in experiments. Results illustrate usability of the methods to dissimilarities searching in text parts.

A new virtual memory management algorithm WSCLOCK has been synthesized from the local working set (WS) algorithm, the global CLOCK algorithm, and a new load control mechanism for auxiliary memory access. The new algorithm combines the most useful feature of WS-a natural and efti:ctive load control that prevents thrashing-with the simplicity and efficiency of CLOCK. Studies are presented to show that the performance of WS and WSCLOCK are equivalent, even if the savings in overhead are ignored.

The history of computing is expressed through AutoCAD as an accretion of ideas and inventions, each of which was a breakthrough in its time. Learning to use AutoCAD, or any CAD system, is augmented by an understanding of the historical context of its development. In contrast to a "deconstructivist" criticism of AutoCAD that avoids all historical context, this paper discusses the user interface of AutoCAD placed in its historical context by combining facts of history with personal reminiscences. The paper answers mysteries about AutoCAD such as "Why a black screen?", "Why LISP?", "Why a command line?", "Why layers, pens and line types?", and "Why 2D?" An understanding of context and history is a starting point for understanding, mastering, and improving software.

This study investigates the conversational strategies employed in cyber blackmail cases from a forensic linguistics perspective. By analyzing authentic data from criminal investigations, the research identifies patterns in the language offenders use to manipulate, threaten, and control their victims in digital environments. The study focuses on various types of blackmail, including financial and sexual extortion (sextortion), examining how linguistic choices such as threats, commands, flattery, and manipulation are strategically used. Gender differences in the use of these strategies are also investigated. A qualitative and quantitative approach combines discourse analysis with statistical tools such as chi-square tests. Findings confirm that Directives/Commands dominate the strategy of cyber blackmail among males and female blackmailers, while compliments is the least employed strategies. Moreover, the analysis indicates statistically significant differences in strategy use between male and female blackmailers.

The research presented in this paper addresses the issue of bridging conceptual differences between the theories and practice of various disciplines in the AEC industry. The authors propose an application logic that works as a framework in assisting the evaluation process of multidisciplinary design. Parametric design templates assist in channeling and integrating information generated during the design process.

Diabetic Retinopathy (DR) is a related malady with diabetes and primary driver of sightlessness in diabetic patients. Epidemiological overview categorizes DR among four significant reasons for sight impedance. DR is a microvascular entanglement in which meager retinal veins may blast, bringing about vision misfortune. In this condition veins in retina swells and may blast in severe extreme condition. Operative medication is timely discovery by steady screenings that is by emphasizing the determination of retinal images using appropriate image processing techniques such as, Preprocessing of retinal image, image segmentation using sobel edge detector, local features extraction like mean, standard deviation, variance, Entropy, histogram values and so on. For classification of retina, system uses K-Nearest Neighbor (KNN) classifier. By adopting this approach, The classification of normal and abnormal images of retina is easy and will reduce the number of reviews for the ophthalmologists...

In order to solve issues with trust-based influencer marketing campaigns on Online Social Networks (OSNs), this article presents the INFLUTRUST architecture. By using a Fusion Learning Method, the framework gives the influencers the ability to choose items from the OSN platforms on their own for advertising. To allow influencers to choose an OSN platform on their own, the Fusion Learning algorithm takes into account the financial incentives offered by the OSN platforms, the influencers' advertising profit, and the influencers' degree of confidence in the OSN platforms. Direct and indirect trust which comes from prior exchanges and social connections between the influencers and the OSN platforms, respectively are also included in the influencers' trust models. Through a multilateral negotiating approach that encourages rivalry among the influencers, the OSN platforms distribute prizes.

A novel approach that seamlessly integrates human action recognition and object detection in hybrid deep learning architectures for the enhancement of accuracy in shoplifting prevention and detection remains largely unexplored to date. This innovative concept has a transformative potential in the security surveillance domain. While both ConvLSTM and CNN_LSTM hybrid techniques possess strong spatio-temporal information processing capabilities, the study explored the effect of the simultaneous application of spatial and temporal data in a ConvLSTM architecture in comparison to the isolated capturing of intricate optical patterns and time dynamics in CNN_LSTM composite structure. Both models were trained and tested on a common annotated dataset of normal shopping behaviour, suspicious activity and shoplifting that explicitly differentiated precrime behavioural cues from shoplifting activity. The ConvLSTM attained an 80% accuracy outperforming 69% accuracy for CNN_LSTM. The study unveils the excellent capability of ConvLSTM in processing sequential optical data paving way for advanced smart surveillance techniques. Future research can focus on leveraging transfer learning and integration with lightweight architectures like YOLO for refined real-time detections.

Diabetes is a chronic condition that could lead to a global health care disaster. 382 million people worldwide have diabetes, according to the International Diabetes Federation. This will double to 592 million by 2035. Diabetes is a condition brought on by elevated blood glucose levels. The symptoms of this elevated blood sugar level include frequent urination, increased thirst, and increased hunger. One of the main causes of stroke, kidney failure, heart failure, amputations, blindness, and kidney failure is diabetes. Our bodies convert food into sugars, such as glucose, when we eat. Our pancreas is then expected to release insulin. Insulin acts as a key to unlock our cells, allowing glucose to enter and be used by us as fuel. However, this mechanism does not function in diabetes. The most prevalent forms of the disease are type 1 and type 2, but there are other varieties as well, including gestational diabetes, which develops during pregnancy. Data science has an emerging topic ca...

CampusERP is an implementation of an ERP System, which will be used primarily in educational institutes such as Engineering Colleges. There will be both Web and Flutter Application for Centralized Management of Educational Institutes. Main Goal of the project is to digitize day to day activities of an Educational Institute, further reducing load on teaching as well as non-teaching staff. This project will have primarily two main Users that would be Teacher and Student. The complete system revolves around these two users. Every module that is available in this project is some way or other beneficial to these two types of users. This project has two main modules that is Student Central Platform and Teacher Central Platform which act as base for all the other modules present.