Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the average power to distance decay rate at the 60 GHz band

Discusses the average power to distance decay rate, which has been obtained from measured data as well as from simulations. It was observed that it depends on the minimum distance between transmitter and receiver taken for its calculation. When oxygen absorption is considered apart, the decay rate decreases approximately by 0.2 to 0.3 for distances of a few hundreds of metres. The scenario can have a strong influence on the value of the decay rate, specially when changes in street length or width occur; antenna radiation patterns also have a major influence on its value. If the oxygen effect is considered apart, the decay rate should range in [2.0, 2.5], but if it is taken as part of this distance dependence, then the decay rate can be taken in [2.3, 2.8] for distances up to 250 m or in [7.0, 7.5] for distances greater than 1 km, respectively for coverage and interference purposes.
An Innovative Approach for DynamicAuthentication in Public Cloud: Using RSA,Improved OTP and MD5

The cloud computing stage gives populace the chance for sharing information resources and services along with the people through internet. In the cloud computing system, both application software and databases are moved to the large data centres, where the data should not be secure in the hands of providers. IT organizations have expressed concerns about the various security aspects that exist with the widespread implementation of cloud computing. These types of concerns originate from the fact that data is stored remotely from the customer's location. From the consumers’ perspective, cloud computing security concerns, especially data security and privacy protection issues, remain the primary inhibitor for adoption of cloud computing services. This paper describes an enhancement for the already existing data security model in cloud environment. The proposed data security model provides user authentication and data protection. This makes certain secure communication system and hiding information from others. In this model message digest based file encryption system and secure public-key encryption system using RSA for exchanging data is included. This model also includes onetime password (OTP) system for user authentication process. This structure can be easily applied with all cloud computing layers, e.g. PaaS, SaaS and IaaS.
COMPARATIVE STUDY OF SELECTIVE ENCRYPTION ALGORITHM FOR WIRELESS ADHOC NETWORK

Information Security has become an important issue in data communication. Encryption has come up as a solution, and plays an important role in information security system. This security mechanism uses some algorithms to scramble data into unreadable text which can be only being decoded or decrypted by party those possesses the associated key. These algorithms consume a significant amount of computing resources such as CPU time, memory and battery power and computation time. This paper performs comparative study of three algorithm; Full encryption algorithm, Toss-a-coin selective encryption algorithm and Probabilistic selective encryption algorithm considering certain parameters such as encryption time percentage time, encryption time, overall time and encryption proportion. Eventually, we carry out an extensive set of simulation experiments based on ns2 simulator, and our simulation indicates that the technique of selective algorithms can indeed improve the efficiency of message encryption.
Spectrum conservation techniques for future telecommunications

The author presents a quantitative method for evaluating spectrum conservation techniques and an overview of several spectrum conserving technologies and policy/regulatory considerations related to implementing spectrum-efficient technologies in the future. It is found that there are many trade-offs in communication system design factors and technology options that have an impact on spectrum efficiency. The spectrum conserving potential of a system is a function of several design factors all of which must be taken into consideration when evaluating the system's spectrum utilization efficiency. Such factors include antennas, signal processing, and RF filters. It is noted that, to ensure effective and efficient use of the spectrum, regulatory and policy procedures must be established. However, because of the economic burden on the marketplace that can be associated with requirements for spectrum efficient communication techniques, mandated regulatory controls should only be implemented where necessary to ensure the continued availability of the spectrum. <<ETX>>
An Analysis and Knowledge Representation System to attain the genuine web user usage behavior

With the explosive growth of WWW, the web mining techniques are densely concentrated to discover the relevant behaviors of the web user from the web log data. In fact the pattern discovery techniques generate many hundreds, often thousands, of patterns, that are unwanted, unexpected, disputable and unbelievable in nature. The success of representing the real knowledge out of such patterns is highly reliant on the pattern analysis stage in investigating the web user usage behavior. To retain most genuine and interesting patterns it is necessary to filter out unqualified patterns and use more sophisticated visualization techniques to present the knowledge of web user usage effectively. The authors in the present paper propose an Analysis and Knowledge Representation System (AKRS) that equally concentrates on both knowledge identification and representation. The key measures are combinedly used for the knowledge identification as a three phase filtering system, to determine the interestingness of patterns in the proposed AKRS. Initially, the objective measures applied on the patterns discovered by pattern discovery techniques to filter out the patterns that do not meet statistical strengths with the frame work of interest factor. Later, subjective measures are applied to identify the patterns that are of most genuine interestingness based on web knowledge. Finally, the heuristic measures evaluate the semantics of patterns based on both user specific objectives and utility of mined patterns. The measures of AKRS efficiently determine the correlation among the most interesting patterns. In addition, to meet the challenges in knowledge representation, like identifying relevant information, finding the depth of information and achieving the visualization competency, the proposed AKRS also designates the recent knowledge visualization techniques like multidimensional and specialized hierarchical. The AKRS amplifies the truthfulness and rate of success in representing final knowledge of web user behavior. Keywords-Pattern Analysis; objective meassures; subjective meassures; heuristic meassures; visulization techniques.
Sentiment Change Detection in Twitter Data Using R Studio

: Detecting changes in a data stream is very important area of research with several applications. we use a method for the detection and estimation of change. This strategy mainly dealing with distribution change when learning from data sequences which may vary with time. We use sliding window whose size, rather than being fixed a priori, is recomputed according to the rate of change determined from the data in the window itself. This delivers the user to guess a time-scale for change within the data stream. In this project we tend to use Jio tweets in twitter as data stream. Reliance Jio network offers cost free services, the 100% satisfaction of its customer could be a doubtful one. Though the customers are availing Jio services, they spend some amount for using other networks. If Reliance Jio fails to give the full satisfaction to its customer, it is tough to sustain its image in the systematic nation. Hence the study is undertaken for the aim of analyzing the Sentimental level of the customer of Jio network.
Bandwidth optimization for high speed data transmission over channels with severe intersymbol interference

Algorithms are presented for finding the optimal transmission bandwidth in terms of either maximizing the overall data throughput or maximizing the system performance margin, given a fixed target data rate, for high speed data transmission over channels with severe intersymbol interference. The system is constrained to have an equipartition of energy over the entire transmission band used at the input to the channel. This yields suboptimal performance relative to the system based on a water-pouring transmit energy distribution. Although the performance degradation is typically negligible, the proposed bandwidth optimization procedures offer a significant computational advantage. It is shown that the procedures apply equally well to multicarrier and single-carrier modulation/equalization techniques. The procedures are applied to the recently proposed asymmetric digital subscriber line (ADSL) service, and performance projections based on computer simulation are presented for two canonical test loops. <<ETX>>
Collision Avoidance Algorithm with Jitter in Multi- hop Cognitive Radio Network

Cognitive radio techniques make full use of spect rum resources via dynamic spectrum access technique. This paper presents a collision avoidance algorithm with the addition of jitter in multi-hop cognitive network. In a multi-hop Cognitive Radio system in which info rmation needs to be relayed over multiple wireless links and secondary users have to co-ordinate themselves in a distributed manner, an improvement in throughput i s achieved by reducing packet loss, through the addition of sm all jitter 1µs at the time of transmission for a ne twork with a set of 6 nodes. Initially we describe the multi-hop cog nitive radio network then various issues for Design of system are considered. From the result it is observed that the throughput for a multi-hop cognitive radio network achieved up to 28x 103 bits/s with the set values of 6 nodes.
Personal Adaptive Web agent: a tool for information filtering

This paper highlights the problem of information overload and recall on the WWW. It briefly mentions four categories of solutions which are: Search Engines, Personal Homepages, Information Management Tools, and Information Retrieval Agents. The paper also presents our own framework of a Personal Adaptive Web (PAW) agent and its current results. Our agent uses a real-time database, automatic text analysis, a competitive learning network, and fuzzy logic to learn the different categories of Web documents that the user is interested in, then finds and suggests new similar documents.
Incorporating Advertising Creative Strategy Into Computer-Based Business Simulations

The effects of advertising creative strategy decisions are very difficult to capture in a quantifiable, and hence, programmable model. This paper draws on the recent research in advertising grid planning models to classify advertising situations and the application functional attitude theory to develop creative strategies. The model establishes a set of theoretically ideal strategies for each type of advertising situation. The creative strategy is then evaluated in terms of the Euclidean distance between the actual and the ideal.
A modular framework for reusable research software

Research which requires developing software is burdened with the effort of developing tools to demonstrate and evaluate various topics and approaches. Often such research tools are very short-lived, giving way frequently to new tools which demonstrate new ideas and directions of the research. The result of such continuous change to the requirements and features of reasearch tools is that they are usually discarded and new tools developed when new needs arise. This thesis presents a framework on which research tools can be constructed which maximizes the reusability and maintainability of that code, and can reduce the cost of new development. Thesis Supervisor: Nancy G. Leveson Title: Professor of Aeronautics and Astronautics
A computationally efficient framework for large-scale distributed fingerprint matching

Biometric features have been widely implemented to be utilized for forensic and civil applications. Amongst many different kinds of biometric characteristics, the fingerprint is globally accepted and remains the mostly used biometric characteristic by commercial and industrial societies due to its easy acquisition, uniqueness, stability and reliability. There are currently various effective solutions available, however the fingerprint identification is still not considered a fully solved problem mainly due to accuracy and computational time requirements. Although many of the fingerprint recognition systems based on minutiae provide good accuracy, the systems with very large databases require fast and real time comparison of fingerprints, they often either fail to meet the high performance speed requirements or compromise the accuracy. For fingerprint matching that involves databases containing millions of fingerprints, real time identification can only be obtained through the implementation of optimal algorithms that may utilize the given hardware as robustly and efficiently as possible. There are currently no known distributed database and computing framework available that deal with real time solution for fingerprint recognition problem involving databases containing as many as sixty million fingerprints, the size which is close to the size of the South African population. This research proposal intends to serve two main purposes: 1) exploit and scale the best known minutiae matching algorithm for a minimum of sixty million fingerprints; and 2) design a framework for distributed database to deal with large fingerprint databases based on the results obtained in the former item.
Hourly Wind Speed Prediction using ARMA Model and Artificial Neural Networks

In this paper, a comparison study is presented on artificial intelligence and time series models in 1-hour-ahead wind speed forecasting. Three types of typical neural networks, namely adaptive linear element, multilayer perceptrons, and radial basis function, and ARMA time series model are investigated. The wind speed data used are the hourly mean wind speed data collected at Binalood site in Iran. Simulation results indicate the ability of the proposed methods in 1-hour-ahead wind speed forecasting in Binalood of Iran.
Vocal Communication of Emotional Meaning Among Normal and Disturbed Children

In this study, both normal and disturbed Mexican boys, speaking whatever words came to mind, attempted to communicate the emotions of happiness, sadness, love, and anger. After the initial recording of these simulations of affective state, an electronic filtering device (designed to remove verbal meaning while leaving intact the tonal aspects of speech) was employed to render the vocal expressions unintelligible. Subsequent to filtering, the speech samples recorded by the normal and disturbed children (“senders”) were played to other normal and disturbed boys (“receivers”) of corresponding age. When both heard the speech samples from the normal senders, normal receivers were able to identify the emotional content more accurately than disturbed receivers. However, disturbed receivers performed more accurately than normals when judging the speech from the disturbed senders. This highly significant interaction indicated that “who communicates to whom” seems to be a crucial factor in the vocal transmission of emotion.
In-pipe inch-worm pneumatic flexible robot

A pneumatic flexible robot prototype for pipes inspection was built. A dynamic model which takes into account the flexibility, damping and friction was developed. Numerous experiments were carried out in order to characterize the robot and in order to provide the input for the numerical model. The model was validated by comparing the experimental and numerical robot gait in time. The robot motion for different pipes network geometry is presented.
Demand response solutions Based on connected appliances

The Internet of Things (IoT) paradigm brings an opportunity for advanced Demand Response (DR) solutions. Indeed, it enables visibility and control on the various appliances that may consume, store or generate energy within a home. In this thesis, we consider solutions having the capability to produce direct control decisions at different granularities based on variables measured at homes. Control schemes are driven by an optimization based on utility functions. These functions are defined based on a generic approach that considers load’s flexibility and the impact of control decisions on users. The proposed approach does not impose any restrictions on the type of controlled appliances nor on the granularity of control decisions. This enables joint control of heterogeneous loads. We consider three types of control architectures, namely centralized, partially distributed and fully distributed solutions. Schemes based on these architectures differ in the distribution of decision making among entities involved in the control and data that is made available to these entities. Numerical analysis shows the trade-offs of proposed solutions from a performance, scalability and complexity perspectives.
Interactive pattern analysis and classification systems: A survey and commentary

Starting with the era of learning machines, reasons are presented for the current emergence of graphics-oriented interactive pattern analysis and classification systems (IPACS) as a general approach to practical pattern-recognition problems. A number of representative systems and their application to a wide variety of patterns are surveyed. Various aspects of alternative hardware and software implementations are commented upon and computational algorithms and mappings relevant to interactive analysis and classification of patterns are discussed.
Practical application of object oriented techniques to designing neural networks for short-term electric load forecasting

This paper illustrates the use of object oriented programming (OOP) techniques for the design of neural networks (NNs) for short-term load forecasting. A load forecasting model has been developed using a multilayer perceptron NN with an appropriately modified backpropagation learning algorithm. The model produces a simultaneous forecast of the load in the 24 hours of the forecast day concerned. The technique has been tested on data provided by the Italian Power Company ENEL and the promising results obtained through the application of OOPNN-based approach show the effectiveness of this new approach.
Modelling relevance-driven language evolution

Computational modelling has proven a useful method to study the emergence of language-like communication systems. However, most existing models abstract away from the two facts that (1) language use exhibits pragmatic plasticity 1 and (2) linguistic knowledge is an integral part of human conceptual knowledge. This paper introduces a basic architecture for a model that overcomes these shortcomings by incorporating elements of Relevance Theory and Cognitive Semantics.
The EngD Second Year Report

Disclaimer: This report is substantially the result of my own work except where explicitly indicated. This report must not be copied or distributed due to the sensitive nature of the material contained herein. The biological datasets and related findings documented within this report are confidential and owned by a scientific consortium. Therefore, they should not form the subject of further work without the explicit permission of the consortium.
Implementation of a Digital Assistant System for Early Dementia Patients using Social Network Service Function

In this paper, a digital assistant system was designed and implemented to help the patients of early dementia, their families and their caregivers. Traditional digital assistant systems are mainly patient-oriented ones which mainly focus on patient status monitoring, patient emergency identification, and peripheral control using IoT technology. On the other hand, the system proposed in this paper focused on maintaining Received (April 27, 2017), Review Result (May 15, 2017) Accepted (May 22, 2017), Published (July 31, 2017) 24252, Dept. Electronic Engineering, Hallym Univ., Hallym Daehak-gil 1, Chunchon, Korea email: kevin@hallym.ac. kr 24252, Dept. Electronic Engineering, Hallym Univ., Hallym Daehak-gil 1, Chunchon, Korea email: jin202478@gmail.com 04763, Dept. Electronic Engineering, Hanyang Univ., Wangsimri-ro, Seongdonggu, Seoul, Korea email: gmlwns_0@naver.com 4 (Corresponding Author) 24252, Dept. Electronic Engineering, Hallym Univ., Hallym Daehak-gil 1, Chunchon, Korea email: spark@hallym.ac. kr Implementation of a Digital Assistant System for Early Dementia Patients using Social Network Service Function Copyright c 2017 HSST 430 the relationship between the patient and the people around him/her by using social network service technology to minimize the social disruption of the patient. It also provides recall therapy, light therapy, cognitive training, which are known to be helpful in relieving the progression of dementia during daily life. Considering that the patients with early dementia are not familiar with the operation of digital information equipment, we added voice and video interfaces in addition to the screen touch interface so that patients can use the service easily. The system implemented in this paper is designed as an open architecture, so it is easy to add new services.
A multi-agent collaborative personalized web mining system model.

The Internet and world wide web (WWW) have in recent years, grown exponentially in size and in terms of the volume of information that is available on it. In order to effectively deal with the huge amount of information on the web, so called web search engines have been developed for the task of retrieving useful and relevant information for its users. Unfortunately, these web search engines have not kept pace with the boom growth and commercialization of the web. The main goal of this dissertation is the development of a model for a collaborative personalized meta-search agent (COPEMSA) system for the WWW. This model will enable the personaliza-tion of web search for users. Furthermore, the model aims to leverage on current search engines on the web as well as enable collaboration between users of the search system for the purposes of sharing useful resources between them. The model also employs the use of multiple intelligent agents and web content mining techniques. This enables the model to autonomously retrieve useful information for it's user(s) and present this information in an effective manner. In order to achieve the above stated, the COPEMSA model employs the use of multiple intelligent agents. COPEMSA consists of five core components: a user agent, a query agent, a community agent, a content mining agent and a directed web spider. The user agent learns about the user in order to introduce personal preference into user queries. The query agent is a scaled down meta-search engine with the task of submitting the personalized queries it receives from the user agent to multiple search services on the WWW. The community agent enables the search system to communicate and leverage on the search experiences of a community of searchers. The content mining agent is responsible for analysis of the retrieved results from the WWW and the presentation of these results to the system user. Finally, a directed web spider is used by the content mining agent to retrieve the actual web pages it analyzes from the WWW. In this dissertation an additional model is also presented to deal with a specific problem all web spidering software must deal with namely content and link encapsulation. Die Internet en wêreld wye web (WWW) het oor die afgelope paar jaar eksponensiëel gegroei in terme van groote asook inligtings volume. Om effektief die groot hoeveelheid inligting op die web te hanteer het sogenaamde web …