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We offer a critical inquiry into the faltering entry of an anthropomorphised AI (ro)bot, an algorithm without physical or visual form, into the workplace in a media consultancy company. While living a digital life in the virtual world, the ro(bot) was given a human name. We highlight the unexpected consequences the humanisation of an early form of artificial intelligence (AI) has on the affects circulating between people and the new technology and between members of different organisational groups. We argue that anthropomorphising technologies such as AI influences the affective life of organisations and amplifies existing discontent between organisational members, complicating the introduction of the technology. Focusing on human–AI interaction, our analysis reveals a rift between managers who are excited and hopeful about the future capabilities of AI and employees who are frustrated and angry about its present shortcomings. We conclude that collective affects play a central role in contemporary technology-driven organisations in which the role people play in relation to the avalanche of AI technologies is often neglected. [ABSTRACT FROM AUTHOR]

In this paper, a process workflow for Bot is created using robotic process automation (RPA), associated with artificial intelligence that is used to stream line the administrative tasks and alleviate stress levels of faculty in handling administrative tasks while teaching in higher education. These activities are must for National Academic Audit Council (NAAC) accreditation and All India Survey on Higher Education (AISHE) surveys, which strive to bring quality in teaching higher education by shaping educational policies. Therefore, ensuring the accuracy of this data is paramount to avoid misleading decisions. The Bot automatically gathers student results from the website and saves them into individual files, eliminating the need for human intervention. It is trained to find the related file of student and update his results of upcoming semesters or backlogs. The Bot efficiently manages folders during file saving to enhance retrieval. Additionally, it maintains pertinent student details such as community, caste, and religion, beneficial for educational policy surveys aiming for improved quality. Moreover, it generates and updates reports post each process execution, ensuring data integrity, and can be trained for statistical analysis to predict student outcomes. The UiPath tool is used in the design and testing of the developed Bot. [ABSTRACT FROM AUTHOR]

Objective. The purpose of the research is to develop and implement a Telegram bot for effective task management using the functionality of the Telegram API. Method. The study is based on database design techniques. Result.The paper describes the process of developing and optimizing a Telegram bot for effective task management. As part of the research, an application was developed, implemented in Python using the Telegram API and using the PostgreSQL DBMS to store data as part of the workflow. The system is designed to optimize the workflow, manage tasks in the system and delegate them to users. A database has been designed, where the structure and relationships between data are defined, ensuring efficient storage and access to information, taking into account the needs of the application. Conclusion.The phased implementation of functionality, from task management, user notification systems, to data processing and analysis, allows us to obtain a fully functional system with a wide range of capabilities. To clarify the functions and capabilities of the bot, a demonstration of the application was carried out, reflecting the functionality of the system.

The study highlights lenders' concerns in light of the challenges faced by special purpose vehicles (SPVs), executing road projects under public-private partnerships in India. In the process, it aims to strengthen the regulatory framework of project financing. While there have been a few studies that discussed some of the critical aspects in project financing before the projects are actually financed by lenders, this study conducts an ex-post facto examination of such aspects. We collated the lenders' concerns through unstructured interviews. Then, we examined them using content analysis, and further validated them, using information contained in the financial statements and credit rating reports of the concerned SPVs. Lenders highlighted land acquisition challenges and project clearances from government agencies as key concerns. The results of this study are of help to the policymakers as these would enable them to strengthen the PPP framework for the development of road infrastructure. [ABSTRACT FROM AUTHOR]

This article has examined the impact of selected macroeconomic variables on economic growth in the Bay of Bengal Initiative for Multi-sectoral, Technical and Economic Cooperation (BIMSTEC). Thus, quarterly data have been considered over a period from 2000 to 2021. The study has taken into consideration the Cobb-Douglas production function as a model specification to examine the above issue. It has been found that agricultural production is an important macroeconomic determinant to justify economic growth in BIMSTEC and its members. However, foreign direct investment is a significant macroeconomic factor for economic growth in BIMSTEC and also in India. Moreover, GDP in Bhutan, Sri Lanka and Thailand is positively and significantly affected by the balance of trade. [ABSTRACT FROM AUTHOR]

Borderline ovarian tumors (BOTs), which are a special type of epithelial tumor of the ovary, lie between benign and malignant tumors and have low malignant potential. Due to the fact that the early symptoms of these tumors are relatively subtle, they are not easy to diagnose clinically. This study explores advancements in clinical detection methods and provides a comprehensive overview of molecules such as cell migration factors, cell transcription factors, cell damage repair factors, cell cycle regulators, and tumor suppressor genes that are related to the development of BOTs and their related mechanisms in recent years, thus aiming to provide more sensitive, specific, and efficient differential diagnosis and treatment plans for patients to improve their prognosis and survival outcomes.

The legislation of the Republic of Belarus currently establishes the same legal force for identical documents on paper and in electronic form, which have a mandatory requisite - an electronic digital signature. The article considers the system for managing public keys of electronic digital signature in the Republic of Belarus, as well as the concepts and definitions associated with this system. The technical normative legal acts in the field of cryptographic protection of electronic documents are analyzed. The necessity of verification of certificates of public keys of electronic digital signature is substantiated. Possible variants of the procedure for verifying public key certificates are described, their advantages and disadvantages are shown. An online service for checking public key certificates has been developed using open cryptographic libraries and public tools.

a botnet is a group of devices which are controlled by the Attacker and used for fraud, scam and cyber-attacks. The attacker is also known as Bot-herder. The Bots are used to conduct many activities varies from stealing user credentials, sending spam, stealing data, ransom ware, fraudulently clicking on ads or distributed denial-of-service (DDoS) attacks. The traffic made up by bots is increasing day by day, now nearly a quarter of the whole traffic. Detecting them becomes an uphill task as the time passes. Bot developers are adopting new technologies at a rapid rate in an effort to avoid bot detection. While some bot problems are industry-specific, researchers found out that bot problems run across all industries. The top five industries which are targeted with bad bot traffic are the financial, education, IT & services industries, marketplaces, and government. This assessment paper briefs the different botnet detection methods that exist at present. The main aim of this paper is to give the insight knowledge of various bots and their implications on the present cyber world and also shedding some light on the current methods using to detect them... [ABSTRACT FROM AUTHOR]

The Gesture Controlled Bot is a robotic device capable of being operated through hand gestures. Its primary objective is to aid individuals with physical disabilities in manoeuvring their wheelchairs or automobiles using hand motions. The wheelchair's movement is controlled by a differential mechanism, which involves rotating the fourth and rear wheels in a counter clockwise direction on one side while rotating the other pair of wheels clockwise. This enables the wheelchair to rotate on its own axis without any forward or backward movement. [ABSTRACT FROM AUTHOR]

One of the active areas of research trends is recognizing emotions in images. This project aims to identify facial emotions. The research concept in Emotion Recognition is included in the flow of our emotion recognition. These involve image acquisition, image pre-processing, face detection, feature extraction, and classification, with the machine being applied after the emotion have been classified. Our framework relies on already-existing still images. This project aims to improve automated facial emotion recognition and build interaction between the system and the user (bot). [ABSTRACT FROM AUTHOR]

This paper focused on the provision of an affordable and less weight prosthetic arm for the Zimbabwe an population. There search concentrated on improving the amputees' living standards by means of providing them with a useful artificial arm which can perform tasks as a normal human arm. The literature review was thoroughly done by investigating the latest prostatic arms available in the market. The V model o revolutionary prototyping was used in there search project to account for every component of the prosthetic limb. The V-model is a type of software development life cycle (SDLC)paradigm where processes run sequentially in a V-shape. The Ruoko bot is flexible and affordable thanthe current artificial prosthetic available. The prosthetic limb has an Arduino board which allows the useof an artificial intelligence algorithm to determine which signal of the brain's waves should be translated into bodily motion by anEEGheadband. [ABSTRACT FROM AUTHOR]

Social networks have captured the attention of many people worldwide. However, these services have also attracted a considerable number of malicious users whose aim is to compromise the digital assets of other users by using messages as an attack vector to execute different types of cyberattacks against them. This work presents an approach based on natural language processing tools and a convolutional neural network architecture to detect and classify four types of cyberattacks in social network messages, including malware, phishing, spam, and even one whose aim is to deceive a user into spreading malicious messages to other users, which, in this work, is identified as a bot attack. One notable feature of this work is that it analyzes textual content without depending on any characteristics from a specific social network, making its analysis independent of particular data sources. Finally, this work was tested on real data, demonstrating its results in two stages. The first stage detected the existence of any of the four types of cyberattacks within the message, achieving an accuracy value of 0.91. After detecting a message as a cyberattack, the next stage was to classify it as one of the four types of cyberattack, achieving an accuracy value of 0.82.

Social networks have captured the attention of many people worldwide. However, these services have also attracted a considerable number of malicious users whose aim is to compromise the digital assets of other users by using messages as an attack vector to execute different types of cyberattacks against them. This work presents an approach based on natural language processing tools and a convolutional neural network architecture to detect and classify four types of cyberattacks in social network messages, including malware, phishing, spam, and even one whose aim is to deceive a user into spreading malicious messages to other users, which, in this work, is identified as a bot attack. One notable feature of this work is that it analyzes textual content without depending on any characteristics from a specific social network, making its analysis independent of particular data sources. Finally, this work was tested on real data, demonstrating its results in two stages. The first stage detected the existence of any of the four types of cyberattacks within the message, achieving an accuracy value of 0.91. After detecting a message as a cyberattack, the next stage was to classify it as one of the four types of cyberattack, achieving an accuracy value of 0.82. [ABSTRACT FROM AUTHOR]

Technological changes and disruptions do transform organizations to look at new alternatives to grow business with the help of Artificial Intelligence (Al). However, this may not be the same in every sector or industry or business. Knowledge creation and organizational well-being are generally the positive effects of Appreciative Intelligence. While Artificial intelligence is pervading routine and repetitive tasks and jobs, prudent HR leaders need to realign strategies to balance between Human resource requirement and investment in newer technologies, Al, ML and BOT investments in an organization for a long term vision and growth of a modem business unit. Strategies of Human resource management with optimization and balance between people and technology is a crux for the success of revenue growth and sustaining in market place. There are several options available to a practising professional to optimize and one has to have a long term view to select a particular strategy. This paper also focuses on greater changes and adaptation occurred during and post COVID time period and future changes expected based on both interviews of corporate leaders and own experiences in the industry. Greater and faster changes are happening in Physical work place. Physical work place, premises are shrinking and there is a blend of online, work from home and a few days office visits are gaining momentum reducing the base cost and establishment cost modem organizations. Future is clearly indicating a Lean but effective workforce ably supported by Bots and technology. [ABSTRACT FROM AUTHOR]

L’avvento di Internet, prima, e dei social media, poi, ha permesso uno scambio di contenuti con dei volumi ed una velocità in precedenza impensabili. All’interno di quelle che sono a tutti gli effetti delle “piazze digitali” operano anche i cosiddetti socialbot, dei programmi che, una volta forniti delle credenziali di accesso di un account, sono in grado di gestirlo in autonomia dando, però, l’impressione di essere una persona vera. La loro rapidità e precisione di reazione nei social network rendono questi agenti software pericolosamente utili per la diffusione di contenuti favorevoli od ostili. Il recente impiego dei socialbot all’interno del dibattito elettorale e politico di diverse nazioni e le sue conseguenze hanno posto l’urgenza che i legislatori statali intervengano contro questo fenomeno. Sull’esempio delle riforme adottate o proposte da diverse nazioni nel mondo, nonché della cornice d’azione predisposta dalle autorità europee, vengono presentati alcuni spunti per poter contrastare il cosiddetto “problema bot” declinato in questi particolari caratteri di propaganda politica.

This article is about the optimization of fixed assets inventory by means of Telegram bot. The feature of the systems which are realized with the help of bots is the ease of use and minimization of resources spent on software storage, which greatly simplifies the interaction with the system. One of today’s popular platforms for deploying bots is the Telegram messenger. Purpose – create a tool for inventory of fixed assets, interaction with the database, creation of reports in Excel format and carrying out stock-taking with the help of QR code recognition. Method or methodology of the work. The article considers the method that implements the inventory of fixed assets and carrying out an inventory. For the implementation it is used: the SQLite database and the programming language Python. Result: developed a unique tool that implements the functions of adding, storing and interacting with the data of fixed assets. Scope of the results: object data stored in the database is reasonable to use for inventory and monitoring the current balance of fixed assets.

The use of sentinel woody plants in experimental plantings, Botanical Gardens and Arboreta has been experimentally validated as a tool for identifying possible unknown future threats prior to their introduction into new countries. Sentinel Plantings were recently established in Italy, France, Switzerland, China and South Africa, using a common experimental design. The plantings included various tree and shrub species of broadleaves and conifers. Two planting types were established, each with different objectives. In-patria plantings using native plants aim to estimate, in absence of any phytosanitary treatments, the associations and infestation rates of native insects susceptible to be exported to other countries with that particular commodity. Ex-patria plantings using non-native plants are relevant to identify native insect species capable of switching to the non-native plant that would otherwise be impossible to predict prior to its introduction. In the frame of the EU project HOMED, we have implemented this concept, widening the use of this tool simultaneously to many different countries and continents

Cyber-attacks on the internet are not a new phenomenon. Hackers are always looking for ways to breach the security of the internet. Good researchers continuously develop solutions to the problems of breaches in security. Human interaction proofs are also one of the most affordable solutions to problems. The completely automated public Turing test to tell computers and humans apart (CAPTCHA) has a wide range of applications, including website authentication, preventing bogus email registration, preventing bogus online polls, preventing bogus ticket booking, and so on. CAPTCHAs come in various formats, but text-based schemes are the most common. Unfortunately, these text-based CAPTCHAs are available in foreign languages and have a high success rate. The usability of these foreign language-based schemes for native people is also very low. These days, Hindi CAPTCHAs are available, but before using them, we must test the security of these schemes. In this study, ten different coloured CAPTCHAs are broken using the k-nearest neighbours, the support vector machine, and the random forest classifiers. The breaking rate for two-colour schemes is 90%, while the breaking rate for multi-colour schemes is 93%. The solving time for the support vector machine and the random forest classifier ranges from 0.06 s to 0.09 s and 0.1 to 0.2 s in the case of two-colour schemes. For multi-colour schemes, it ranges from 0.06 s to 0.09 s and 0.09 s to 0.2 s for the support vector machine and random forest classifier, respectively. [ABSTRACT FROM AUTHOR]

Reinforcement Learning is one of the many machine learning paradigms. With no labelled data, it is concerned with balancing the exploration and exploitation of an environment with one or more agents present in it. Recently, many breakthroughs have been made in the creation of these agents for video game machine learning development, especially in first-person shooters with platforms such as ViZDoom, DeepMind Lab, and Unity's ML-Agents. In this paper, we review the state-of-the-art of creation of Reinforcement Learning agents for use in multiplayer deathmatch first-person shooters. We selected various platforms, frameworks, and training architectures from various papers and examined each of them, analysing their uses. We compared each platform and training architecture, and then concluded whether machine learning agents can now face off against humans and whether they make for better gameplay than traditional Artificial Intelligence. In the end, we thought about future research and what researchers should keep in mind when exploring and testing this area. [ABSTRACT FROM AUTHOR]

Agriculture is one of the most important sectors for India and Indian economy. It contributes about 17% to the total GDP of our country and provides employment to over 60% of the population as one of the primary occupations in the country. Indian agriculture has registered an impressive growth over last few decades. For a major sector in Indian agriculture, farmers depend upon artificial watering system other than rainwater and natural water sources. Irrigation has proven to be more efficient watering system for farmers over the years. Irrigation helps to increase productivity even in low rainfall. The productivity of irrigated land is higher compared to un-irrigated land. In areas that have irregular precipitation, irrigation improves crop growth and quality. But farmers face different problems while using the irrigation systems e.g., lack of mechanism. During the rabi season which is between October and February farmers face a major problem in irrigation specially at night time. In this season plants need extra water other than the rainwater or naturally provided one. Now a days farmers use latest technology for irrigating a land using sprinkler irrigations. Government also promotes the irrigation systems in farms by providing various subsidies on sprinklers sets which plays an important role in preferences by the farmers to the use of sprinkler irrigations. For the agriculture purposes, 75% of electricity supply is usually distributed during night time This supply is generally provided in shifts of about 8 hours only. In case of irrigation systems, 80% of farmer has more than two sets of sprinkler type of irrigation. One set of a sprinkler is capable of irrigating more than one acre land in a single night (one set includes 30 pipes and 8 sprinklers plus 5 as extras). So, the farmers who have two or more sets of sprinklers, they assemble a position of sprinklers in shifts during day time while the power supply is given at night time. The main issue begins after 1st shift ends and 2nd shift starts, as due to such arrangement of sprinkler, farmers have to change the valve manually in night time nearly at 3 am (due to the 8-hour shift of power supply). This is one of hardest tasks for the farmers as it is already as dangerous to enter the field at night time as it can get and the reptiles impose the living risks. Plus, during rabi season it is of no help that on an average, the temperature can drop as low as 14 degrees Celsius which is again adverse for the health of farmers. Another risky factor for farmers, who have to enter the farms at night for the irrigation purposes is attacks from wild animals. According to a report by Times of India, 7794 claims of crop damages were registered only in Maharashtra region till the last September. These attacks by wild life sometimes lead to the injuries to farmers and result in fatal situations specially if occurred at night time. Other than this, farmers are also exposed to the danger of electric shocks due to improper voltage supplied. As a solution to this issue and for the convenience of the farmers, our team has built a systembot which will automate the change in the shifts of sprinklers using valves[1]. The Bot helps the farmer to access the sprinklers and monitor the water flow through these pipes remotely. Our aim is to provide a system which will change the shifts of sprinklers automatically according to the time period of the shifts required and power supply at a low budget. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The identification of risks in construction projects gives advance indications of the potential risks that may occur during project planning, construction or management. Therefore, identifying those risks and preparing the necessary plans to respond to them is a key detail for the success of the project from its failure. The projects implemented in the manner of a Build Operate Transfer (BOT) contract are accompanied by many risks due to the multiplicity of parties and the multiplicity of their responsibilities, as well as the size of those projects because they are usually associated with infrastructure projects. The aim of this research is to identify the most prominent risks in BOT contracts and the planned response against each risk. The adopted methodology is through conducting interviews and a closed questionnaire (included 77 out of 100 respondents), and the adoption of statistical analysis through the SPSS program and the scale of relative importance.The relative importance index technique was used to rank the risks according to their importance and discuss the reasons for their classification. The results showed a list of the most important risks that would be generated if the BOT contract was applied to transportation projects in Iraq, as well as the appropriate planned response to each risk based on historical information for previous BOT projects.

Die folgende Graphic Novel ist ein Auszug aus dem vollautomatisierten Puppentheater Von einem der auszog eine Wohnung in Berlin zu finden. Ein Automatisierungsdrama in drei Akten – 3. Akt: In letzter Konsequenz von Clemens Schöll (2019/2020). Für die vorliegende Fassung wurde das Bildmaterial der filmischen Dokumentation sowie der 3D-Scans mit Unterstützung verschiedener automatisierter Softwarekomponenten transformiert. Wie in der Puppentheater-Vorlage wird mithilfe von Automatisierungsprozessen über Automatisierung gesprochen: Wer hat welche Zugänge, wer stellt Regeln auf und wer profitiert von Automatisierung?

Borderline ovarian tumor (BOT) accounts for 15–20% of all epithelial ovarian tumors. Concerns have arisen about the clinical and prognostic implications of BOT with exophytic growth patterns. We retrospectively reviewed all cases of BOT patients surgically treated from 2015 to 2020. Patients were divided into an endophytic pattern (with intracystic tumor growth and intact ovarian capsule) and an exophytic pattern (with tumor growth outside the ovarian capsule) group. Among the 254 patients recruited, 229 met the inclusion criteria, and of these, 169 (73.8%) belonged to the endophytic group. The endophytic group showed more commonly an early FIGO stage than the exophytic group (100.0% vs. 66.7%, p < 0.001). Furthermore, tumor cells in peritoneal washing (20.0% vs. 0.6%, p < 0.001), elevated Ca125 levels (51.7% vs. 31.4%, p = 0.003), peritoneal implants (0 vs. 18.3%, p < 0.001), and invasive peritoneal implants (0 vs. 5%, p = 0.003) were more frequently observed in the exophytic group. The survival analysis showed 15 (6.6%) total recurrences, 9 (5.3%) in the endophytic and 6 (10.0%) patients in the exophytic group (p = 0.213). At multivariable analysis, age (p = 0.001), FIGO stage (p = 0.002), fertility-sparing surgery (p = 0.001), invasive implants (p = 0.042), and tumor spillage (p = 0.031) appeared significantly associated with recurrence. Endophytic and exophytic patterns in borderline ovarian tumors show superimposable recurrence rates and disease-free survival. [ABSTRACT FROM AUTHOR]

There are quintillions of data on deoxyribonucleic acid (DNA) and protein in publicly accessible data banks, and that number is expanding at an exponential rate. Many scientific fields, such as bioinformatics and drug discovery, rely on such data; nevertheless, gathering and extracting data from these resources is a tough undertaking. This data should go through several processes, including mining, data processing, analysis, and classification. This study proposes software that extracts data from big data repositories automatically and with the particular ability to repeat data extraction phases as many times as needed without human intervention. This software simulates the extraction of data from web-based (point-and-click) resources or graphical user interfaces that cannot be accessed using command-line tools. The software was evaluated by creating a novel database of 34 parameters for 1360 physicochemical properties of antimicrobial peptides (AMP) sequences (46240 hits) from various MARVIN software panels, which can be later utilized to develop novel AMPs. Furthermore, for machine learning research, the program was validated by extracting 10,000 protein tertiary structures from the Protein Data Bank. As a result, data collection from the web will become faster and less expensive, with no need for manual data extraction. The software is critical as a first step to preparing large datasets for subsequent stages of analysis, such as those using machine and deep-learning applications. [ABSTRACT FROM AUTHOR]