A thorough review of trust models is carried out in this paper to reveal the key capabilities of existing trust
models and compare how they differ among disciplines. Trust decisions are risky due to uncertainties and
the loss of control. On the other hand, not trusting might mean giving up some potential benefits. Advances
in electronic transactions, mutliagent systems, and decision support systems create a necessity to develop
trust and reputation models. The development of such models will allow for trust reasoning and decisions
to be made in situations with high risk and uncertainty. In recent years, several attempts have been made to
model reputation and trust. However, perceiving trust differently and the lack of having a unified trust
definition are among the main causes of the proliferation of many trust models across different disciplines.
Working with trust
presented by Neill Allan
Thursday 9th June 2016
Collaboration, co-operation and competition - project environments through a knowledge lens
Knowledge SIG conference
SDI 2012: Leading and Managing Change for Diversity and InclusionThe Children's School
My presentation at the NAIS Summer Diversity Institute (SDI) on leading and managing change for diversity and inclusion in independent schools. This presentation's theories and strategies are applicable beyond its chosen topic of diversity and inclusion, and would benefit leaders in any area.
A PROPOSED MULTI-DOMAIN APPROACH FOR AUTOMATIC CLASSIFICATION OF TEXT DOCUMENTSijsc
Classification is an important technique used in information retrieval. Supervised classification suffers
from certain limitations concerning the collection and labeling of the training dataset. When facing Multi-
Domain classification, multiple training datasets and classifiers are needed which is relatively difficult. In
this paper an unsupervised classification system is proposed that can manage the Multi-Domain
classification problem as well. It is a multi-domain system where each domain represented by an ontology.
A document is mapped on each ontology based on the weights of the mutual tokens between them with the
help of fuzzy sets, resulting in a mapping degree of the document with each domain. An experiment carried
out showing satisfying classification results with an improvement in the evaluation results of the proposed
system compared to Apache Lucene.
A PREDICTION METHOD OF GESTURE TRAJECTORY BASED ON LEAST SQUARES FITTING MODELVLSICS Design
Implicit interaction based on context information is widely used and studied in the virtual scene. In context
based human computer interaction, the meaning of action A is well defined. For instance, the right wave is
defined turning paper or PPT in context B, And it mean volume up in context C. However, we cannot use
the context information when we select the object to be manipulated. In view of this situation, this paper
proposes using the least squares fitting curve beam to predict the user's trajectory, so as to determine what
object the user’s wants to operate. At the same time, the fitting effects of the three curves were compared,
and the curve which is more accord with the hand movement trajectory is obtained. In addition, using the
bounding box size control the Z variable to move in an appropriate location. Experimental results show
that the proposed in this paper based on bounding box size to control the Z variables get a good effect; by
fitting the trajectory of a human hand, to predict the object that the subjects would like to operate. The
correct rate is 91%.
Working with trust
presented by Neill Allan
Thursday 9th June 2016
Collaboration, co-operation and competition - project environments through a knowledge lens
Knowledge SIG conference
SDI 2012: Leading and Managing Change for Diversity and InclusionThe Children's School
My presentation at the NAIS Summer Diversity Institute (SDI) on leading and managing change for diversity and inclusion in independent schools. This presentation's theories and strategies are applicable beyond its chosen topic of diversity and inclusion, and would benefit leaders in any area.
A PROPOSED MULTI-DOMAIN APPROACH FOR AUTOMATIC CLASSIFICATION OF TEXT DOCUMENTSijsc
Classification is an important technique used in information retrieval. Supervised classification suffers
from certain limitations concerning the collection and labeling of the training dataset. When facing Multi-
Domain classification, multiple training datasets and classifiers are needed which is relatively difficult. In
this paper an unsupervised classification system is proposed that can manage the Multi-Domain
classification problem as well. It is a multi-domain system where each domain represented by an ontology.
A document is mapped on each ontology based on the weights of the mutual tokens between them with the
help of fuzzy sets, resulting in a mapping degree of the document with each domain. An experiment carried
out showing satisfying classification results with an improvement in the evaluation results of the proposed
system compared to Apache Lucene.
A PREDICTION METHOD OF GESTURE TRAJECTORY BASED ON LEAST SQUARES FITTING MODELVLSICS Design
Implicit interaction based on context information is widely used and studied in the virtual scene. In context
based human computer interaction, the meaning of action A is well defined. For instance, the right wave is
defined turning paper or PPT in context B, And it mean volume up in context C. However, we cannot use
the context information when we select the object to be manipulated. In view of this situation, this paper
proposes using the least squares fitting curve beam to predict the user's trajectory, so as to determine what
object the user’s wants to operate. At the same time, the fitting effects of the three curves were compared,
and the curve which is more accord with the hand movement trajectory is obtained. In addition, using the
bounding box size control the Z variable to move in an appropriate location. Experimental results show
that the proposed in this paper based on bounding box size to control the Z variables get a good effect; by
fitting the trajectory of a human hand, to predict the object that the subjects would like to operate. The
correct rate is 91%.
INNOVATIVE AND SOCIAL TECHNOLOGIES ARE REVOLUTIONIZING SAUDI CONSUMER ATTITUD...ijsptm
The Internet today connects about 40% of the world population. Half of these are living outside the
advanced economies, often in some countries that are quickly climbing the developmental ladder, with
diverse populations and inarguable economic potentialities including Saudi Arabia. There are 20 million
Internet users in Saudi Arabia by the end of 2016. This research examines the impact of the Internet,
innovation, disruption and the dynamics that affect adoption of electronic commerce (e-commerce) in
Saudi Arabia. The study further analyzes the influence of Internet security and its impact on the users’
decision-making process. The data have gathered through questionnaires that disseminated to 2,823 Saudi
Internet male and female users through email. The response rate was 23%. The important findings have
discussed in this study that shows that there are significant factors that are influencing the adoption of ecommerce,
including legal procedures to ease of doing business, ease of doing businesses and security
features and controls introduced by the online vendors.
MULTIMODAL BIOMETRICS RECOGNITION FROM FACIAL VIDEO VIA DEEP LEARNINGsipij
Biometrics identification using multiple modalities has attracted the attention of many researchers as it
produces more robust and trustworthy results than single modality biometrics. In this paper, we present a
novel multimodal recognition system that trains a Deep Learning Network to automatically learn features
after extracting multiple biometric modalities from a single data source, i.e., facial video clips. Utilizing
different modalities, i.e., left ear, left profile face, frontal face, right profile face, and right ear, present in
the facial video clips, we train supervised denoising auto-encoders to automatically extract robust and nonredundant
features. The automatically learned features are then used to train modality specific sparse
classifiers to perform the multimodal recognition. Experiments conducted on the constrained facial video
dataset (WVU) and the unconstrained facial video dataset (HONDA/UCSD), resulted in a 99.17% and
97.14% rank-1 recognition rates, respectively. The multimodal recognition accuracy demonstrates the
superiority and robustness of the proposed approach irrespective of the illumination, non-planar
movement, and pose variations present in the video clips.
BUILDING A SYLLABLE DATABASE TO SOLVE THE PROBLEM OF KHMER WORD SEGMENTATIONijnlc
Word segmentation is a basic problem in natural language processing. With the languages having the
complex writing system like the Khmer language in Southern of Vietnam, this problem really very
intractable, posing the significant challenges. Although there are some experts in Vietnam as well as
international having deeply researched this problem, there are still no reasonable results meeting the
demand, in particular, no treated thoroughly the ambiguous phenomenon, in the process of Khmer
language processing so far. This paper present a solution based on the syllable division into component
clusters using two syllable models proposed, thereby building a Khmer syllable database, is still not
actually available. This method using a lexical database updated from the online Khmer dictionaries and
some supported dictionaries serving role of training data and complementary linguistic characteristics.
Each component cluster is labelled and located by the first and last letter to identify entirety a syllable. This
approach is workable and the test results achieve high accuracy, eliminate the ambiguity, contribute to
solving the problem of word segmentation and applying efficiency in Khmer language processing.
ANALYSIS OF MMSE SPEECH ESTIMATION IMPACT IN WEST SUMATRA'S NOISESsipij
This study aimed to estimate the original voice signal which is interrupted by noise with MMSE method
based on Wiener filter. The Wiener filter is classified as the MMSE estimator studied by previous
researchers. The study assessed the voice signal input count down by European woman that are distorted
by two types of noises, the one is noise based on the outdoor location, sound of siren firefighter, and the
other is the indoor location noise, which represented by noise in lecturer room in campus. The two process
signal is estimated by MMSE estimator which approximated by Wiener filter that must have founded and
counted the covariance of each signal processes are related to the system. Thus the researchers tried to
estimate both types of sounds noisy European woman are due to interference noise source of fire fighter
and faculty room and assess its impact in the form of graphs vote against a function of time, the pattern
shape of the signal and SNR.
Natural Language Toolkit (NLTK) is a generic platform to process the data of various natural (human)
languages and it provides various resources for Indian languages also like Hindi, Bangla, Marathi and so
on. In the proposed work, the repositories provided by NLTK are used to carry out the processing of Hindi
text and then further for analysis of Multi word Expressions (MWEs). MWEs are lexical items that can be
decomposed into multiple lexemes and display lexical, syntactic, semantic, pragmatic and statistical
idiomaticity. The main focus of this paper is on processing and analysis of MWEs for Hindi text. The
corpus used for Hindi text processing is taken from the famous Hindi novel “KaramaBhumi by Munshi
PremChand”. The result analysis is done using the Hindi corpus provided by Resource Centre for Indian
Language Technology Solutions (CFILT). Results are analysed to justify the accuracy of the proposed
work.
A CASE STUDY ON AUTO SOCIALIZATION IN ONLINE PLATFORMSIJMIT JOURNAL
Auto socialization Theory[1][2]is a socialization theory, introduced by Swedish Social Psychology
Professor Emeritus Lars Dencik, Roskilde University Center (RUC) on how humans socialize, attempting
to be a part of a group by using a taxonomy in three stages. Even though the theory is based on
socialization amongst minors, the adult human uses Auto socialization to navigate everyday life in all its
aspects of interaction, including communications, collaborations through online platforms. By focusing on
the Auto socialization aspect in an online context, it is possible to explain why online platforms e.g.
Facebook, World of Warcraft are so successful in maintaining and increasing the numbers of stabile
audience and why other platforms, offering learning on a massive scale, (MOOC) facing dropout rates in
the high 80 -90’s[3][4][5].
A STUDY ON QUANTITATIVE PARAMETERS OF SPECTRUM HANDOFF IN COGNITIVE RADIO NET...ijwmn
The innovation of wireless technologies requires dynamic allocation of spectrum band in an efficient
manner. This has been achieved by Cognitive Radio (CR) networks which allow unlicensed users to make
use of free licensed spectrum, when the licensed users are kept away from that spectrum. The cognitive
radio makes decision, switching from primary user to secondary user and vice-versa, based on its built-in
interference engine. It allows secondary users to makes use of a channel based on its availability i.e. on the
absence of the primary user and they should vacate the channel once the primary user re-enters and
continue their communication on another available channel and this process in the cognitive radio is
known as spectrum mobility. The main objective of spectrum mobility is that, there is no interruption
caused due to the channel occupied by secondary users and maintains a good quality of service. In order to
achieve better spectrum mobility, it is mandatory to choose an effective spectrum handoff strategy with the
capability of predicting spectrum mobility. The handoff strategy with its parameters and its impact is an
important concept in spectrum mobility but fairly explored. In this paper an empirical study on quantitative
parameters involved in spectrum mobility prediction are discussed in detail. These parameters are studied
extensively because they play a vital role in the spectrum handoff process moreover the impact of these
parameters in various handoff methods can be used to predict the effectiveness of the system.
NETWORK PERFORMANCE ENHANCEMENT WITH OPTIMIZATION SENSOR PLACEMENT IN WIRELES...ijwmn
From one side, sensor manufacturing technology and from other side wireless communication technology
improvement has an effect on the growth and deployment of Wireless Network Sensor (WSN). The
appropriate performance of WSN has abundant necessity which has dependent on the different parameters
such as optimize sensor placement and structure of network sensor. The optimized placement in WSN not
only would optimize number of sensors, but also help to reach to the more precise information. Therefore
different solutions are proposed to reduce cost and increase life time of sensor networks that most of them
are concentrated in the field of routing and information transmission. In this paper, places which they need
new sensors placement or sensor movements are determined and then with applying these changes,
performance of WSN will calculate. To achieve the optimum placement, the network should evaluate
precisely and effective criteria on the performance should extract. Therefore the criteria should be ranked
and after weighting with using AHP algorithms, with use of Geographical Information System (GIS), these
weighted criteria will combined and in the locations which WSN doesn’t have enough performance, new
sensor placement will create. New proposed method, improve 21.11% performance of WSN with sensor
placement in the low performance locations. Also the number of added sensor is 26.09% which is lowest
number of added sensors in comparison with other methods.
A NOVEL METHOD FOR PERSON TRACKING BASED K-NN : COMPARISON WITH SIFT AND MEAN...sipij
Object tracking can be defined as the process of detecting an object of interest from a video scene and
keeping track of its motion, orientation, occlusion etc. in order to extract useful information. It is indeed a
challenging problem and it’s an important task. Many researchers are getting attracted in the field of
computer vision, specifically the field of object tracking in video surveillance. The main purpose of this
paper is to give to the reader information of the present state of the art object tracking, together with
presenting steps involved in Background Subtraction and their techniques. In related literature we found
three main methods of object tracking: the first method is the optical flow; the second is related to the
background subtraction, which is divided into two types presented in this paper, then the temporal
differencing and the SIFT method and the last one is the mean shift method. We present a novel approach
to background subtraction that compare a current frame with the background model that we have set
before, so we can classified each pixel of the image as a foreground or a background element, then comes
the tracking step to present our object of interest, which is a person, by his centroid. The tracking step is
divided into two different methods, the surface method and the K-NN method, both are explained in the
paper. Our proposed method is implemented and evaluated using CAVIAR database.
DEVELOPMENT OF AN ANDROID APPLICATION FOR OBJECT DETECTION BASED ON COLOR, SH...ijma
Object detection and recognition is an important task in many computer vision applications. In this paper
an Android application was developed using Eclipse IDE and OpenCV3 Library. This application is able to
detect objects in an image that is loaded from the mobile gallery, based on its color, shape, or local
features. The image is processed in the HSV color domain for better color detection. Circular shapes are
detected using Circular Hough Transform and other shapes are detected using Douglas-Peucker
algorithm. BRISK (binary robust invariant scalable keypoints) local features were applied in the developed
Android application for matching an object image in another scene image. The steps of the proposed
detection algorithms are described, and the interfaces of the application are illustrated. The application is
ported and tested on Galaxy S3, S6, and Note1 Smartphones. Based on the experimental results, the
application is capable of detecting eleven different colors, detecting two dimensional geometrical shapes
including circles, rectangles, triangles, and squares, and correctly match local features of object and scene
images for different conditions. The application could be used as a standalone application, or as a part of
another application such as Robot systems, traffic systems, e-learning applications, information retrieval
and many others.
A NOVEL IMAGE STEGANOGRAPHY APPROACH USING MULTI-LAYERS DCT FEATURES BASED ON...ijma
Steganography is the science of hidden data in the cover image without any updating of the cover image.
The recent research of the steganography is significantly used to hide large amount of information within
an image and/or audio files. This paper proposed a new novel approach for hiding the data of secret image
using Discrete Cosine Transform (DCT) features based on linear Support Vector Machine (SVM)
classifier. The DCT features are used to decrease the image redundant information. Moreover, DCT is
used to embed the secrete message based on the least significant bits of the RGB. Each bit in the cover
image is changed only to the extent that is not seen by the eyes of human. The SVM used as a classifier to
speed up the hiding process via the DCT features. The proposed method is implemented and the results
show significant improvements. In addition, the performance analysis is calculated based on the
parameters MSE, PSNR, NC, processing time, capacity, and robustness.
ROBUST FEATURE EXTRACTION USING AUTOCORRELATION DOMAIN FOR NOISY SPEECH RECOG...sipij
Previous research has found autocorrelation domain as an appropriate domain for signal and noise
separation. This paper discusses a simple and effective method for decreasing the effect of noise on the
autocorrelation of the clean signal. This could later be used in extracting mel cepstral parameters for
speech recognition. Two different methods are proposed to deal with the effect of error introduced by
considering speech and noise completely uncorrelated. The basic approach deals with reducing the effect
of noise via estimation and subtraction of its effect from the noisy speech signal autocorrelation. In order
to improve this method, we consider inserting a speech/noise cross correlation term into the equations used
for the estimation of clean speech autocorrelation, using an estimate of it, found through Kernel method.
Alternatively, we used an estimate of the cross correlation term using an averaging approach. A further
improvement was obtained through introduction of an overestimation parameter in the basic method. We
tested our proposed methods on the Aurora 2 task. The Basic method has shown considerable improvement
over the standard features and some other robust autocorrelation-based features. The proposed techniques
have further increased the robustness of the basic autocorrelation-based method.
A COLLAGE IMAGE CREATION & “KANISEI” ANALYSIS SYSTEM BY COMBINING MULTIPLE IM...ijma
The collage is an artistic method to create a new image by combining multiple images under some rules or
conditions for collage creators. To realize a mechanism to interpret “Kansei” of the collage creator by the
combination process of multiple image-materials and a formed collage image, we propose a new system to
analyze the collage work by using a database stored to each collage creation information. The collage
works which a creator made by using this system was evaluated. And also, we clarified how to combine
image-materials to make the good collage image having specific impression.
ASPHALTIC MATERIAL IN THE CONTEXT OF GENERALIZED POROTHERMOELASTICITYijsc
In this work, a mathematical model of generalized porothermoelasticity with one relaxation time for
poroelastic half-space saturated with fluid will be constructed in the context of Youssef model (2007). We
will obtain the general solution in the Laplace transform domain and apply it in a certain asphalt material
which is thermally shocked on its bounding plane. The inversion of the Laplace transform will be obtained
numerically and the numerical values of the temperature, stresses, strains and displacements will be
illustrated graphically for the solid and the liquid.
BFO – AIS: A FRAME WORK FOR MEDICAL IMAGE CLASSIFICATION USING SOFT COMPUTING...ijsc
Medical images provide diagnostic evidence/information about anatomical pathology. The growth in
database is enormous as medical digital image equipment’s like Magnetic Resonance Images (MRI),
Computed Tomography (CT), and Positron Emission Tomography CT (PET-CT) are part of clinical work.
CT images distinguish various tissues according to gray levels to help medical diagnosis. Ct is more
reliable for early tumours and haemorrhages detection as it provides anatomical information to plan radio
therapy. Medical information systems goals are to deliver information to right persons at the right time and
place to improve care process quality and efficiency. This paper proposes an Artificial Immune System
(AIS) classifier and proposed feature selection based on hybrid Bacterial Foraging Optimization (BFO)
with Local Search (LS) for medical image classification.
REAL-TIME INTRUSION DETECTION SYSTEM FOR BIG DATAijp2p
The objective of the proposed system is to integrate the high volume of data along with the important
considerations like monitoring a wide array of heterogeneous security. When a real time cyber attack
occurred, the Intrusion Detection System automatically store the log in distributed environment and
monitor the log with existing intrusion dictionary. At the same time the system will check and categorize the
severity of the log to high, medium, and low respectively. After the categorization, the system will
automatically take necessary action against the user-unit with respect to the severity of the log. The
advantage of the system is that it utilize anomaly detection, evaluates data and issue alert message or
reports based on abnormal behaviour.
DEVELOPMENT OF ARABIC NOUN PHRASE EXTRACTOR (ANPE)ijnlc
Extracting key phrases from documents is a common task in many applications. In general: The Noun
Phrase Extractor consists of three modules: tokenization; part-of-speech tagging; noun phrase
identification. These will be used as three main steps in building the new system ANPE, This paper aims at
picking Arabic Noun Phrases from a corpus of documents, Relevant criteria (Recall and Precision), will be
used as evaluation measure. On the one hand, when using NPs rather than using single terms, the system
yields more relevant documents from the retrieved ones, on the other hand, it gave low precision because
number of the retrieved documents will be decreased. At the researchers conclude and recommend
improvements for more effective and efficient research in the future.
DESIGN OF LOW POWER SAR ADC FOR ECG USING 45nm CMOS TECHNOLOGYVLSICS Design
Design of a low power Successive Approximation Register Analog to Digital Converter (SAR ADC) in
45nm CMOS Technology for biopotential acquisition systems is presented. It is designed by using a high
threshold voltage (Vt) cell to reduce power dissipation. A 10-bit SAR ADC is designed and compared with
the low resolution SAR ADC and normal threshold voltage (Vt) ADC with respect to power and delay. The
results show that high Vt SAR ADC saves power upto 67% as compared to low Vt SAR ADC without any
penalty of delay. Other performance metrics studied are the Effective Number of Bits (ENOB) and Signal to
Noise Ratio (SNR), Signal to Noise and Distortion Ratio and Spurious Free Dynamic ratio.
A NOVEL APPROACH FOR INFORMATION RETRIEVAL TECHNIQUE FOR WEB USING NLPijnlc
Webpages are loaded with vast and different kinds of information about the entities in the real-world.
Information retrieval from the Web is of a greater significance today to get the accurate queried data
within the desired time frame which is increasingly becoming difficult with each passing day. Need to
develop a system to solve entity extraction problems from the web as compared to the traditional system.
It’s critical to have a clear understanding of natural language sentence processing in the web page along
with the structure of the web page to get the correct information with speed. Here we have proposed
approach for information retrieval technique for Web using NLP where techniques Hierarchical
Conditional Random Fields (i.e. HCRF) and extended Semi-Markov Conditional Random Fields (i.e. Semi-
CRF) along with Visual Page Segmentation is used to get the accurate results. Also parallel processing is
used to achieve the results in desired time frame. It further improves the decision making between HCRF
and Semi-CRF by using bidirectional approach rather than top-down approach. It enables better
understanding of the content and page structure.
Trust is recognized as an important factor that mediates many aspects of human behavior (Camerer, 2003). Definitions of trust vary but a widely accepted one is that it is a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intentions or behavior of another. Therefore, a person (the trustor) who depends on someone else (the trustee) expects to reduce the likelihood or size of a negative outcome in some situation, such as when that dependence is misplaced, the expected value of the outcome is lower.
Trustworthy Micro-task Crowdsourcing: Challenges and OpportunitiesAlessandro Bozzon
Micro-task crowdsourcing has become a successful mean to obtain high-quality data from a large crowd of diverse people. In this context, trust between all the involved actors (i.e. requesters, workers, and platform owners) is a critical factor for acceptance and long-term success.
In this talk, I will discuss some problematic aspects of existing micro-task crowdsourcing platforms, where trust is built on fragmented, opaque, and often incomplete knowledge. I will provide examples in which the adoption of open, transparent, and socially-aware trust-building strategies have led to better crowdsourcing performance. I will then conclude with several proposals on how to increase the amount of trust cues available in crowdsourcing platforms, possibly with methods drawn from related disciplines such as user modelling and HCI.
INNOVATIVE AND SOCIAL TECHNOLOGIES ARE REVOLUTIONIZING SAUDI CONSUMER ATTITUD...ijsptm
The Internet today connects about 40% of the world population. Half of these are living outside the
advanced economies, often in some countries that are quickly climbing the developmental ladder, with
diverse populations and inarguable economic potentialities including Saudi Arabia. There are 20 million
Internet users in Saudi Arabia by the end of 2016. This research examines the impact of the Internet,
innovation, disruption and the dynamics that affect adoption of electronic commerce (e-commerce) in
Saudi Arabia. The study further analyzes the influence of Internet security and its impact on the users’
decision-making process. The data have gathered through questionnaires that disseminated to 2,823 Saudi
Internet male and female users through email. The response rate was 23%. The important findings have
discussed in this study that shows that there are significant factors that are influencing the adoption of ecommerce,
including legal procedures to ease of doing business, ease of doing businesses and security
features and controls introduced by the online vendors.
MULTIMODAL BIOMETRICS RECOGNITION FROM FACIAL VIDEO VIA DEEP LEARNINGsipij
Biometrics identification using multiple modalities has attracted the attention of many researchers as it
produces more robust and trustworthy results than single modality biometrics. In this paper, we present a
novel multimodal recognition system that trains a Deep Learning Network to automatically learn features
after extracting multiple biometric modalities from a single data source, i.e., facial video clips. Utilizing
different modalities, i.e., left ear, left profile face, frontal face, right profile face, and right ear, present in
the facial video clips, we train supervised denoising auto-encoders to automatically extract robust and nonredundant
features. The automatically learned features are then used to train modality specific sparse
classifiers to perform the multimodal recognition. Experiments conducted on the constrained facial video
dataset (WVU) and the unconstrained facial video dataset (HONDA/UCSD), resulted in a 99.17% and
97.14% rank-1 recognition rates, respectively. The multimodal recognition accuracy demonstrates the
superiority and robustness of the proposed approach irrespective of the illumination, non-planar
movement, and pose variations present in the video clips.
BUILDING A SYLLABLE DATABASE TO SOLVE THE PROBLEM OF KHMER WORD SEGMENTATIONijnlc
Word segmentation is a basic problem in natural language processing. With the languages having the
complex writing system like the Khmer language in Southern of Vietnam, this problem really very
intractable, posing the significant challenges. Although there are some experts in Vietnam as well as
international having deeply researched this problem, there are still no reasonable results meeting the
demand, in particular, no treated thoroughly the ambiguous phenomenon, in the process of Khmer
language processing so far. This paper present a solution based on the syllable division into component
clusters using two syllable models proposed, thereby building a Khmer syllable database, is still not
actually available. This method using a lexical database updated from the online Khmer dictionaries and
some supported dictionaries serving role of training data and complementary linguistic characteristics.
Each component cluster is labelled and located by the first and last letter to identify entirety a syllable. This
approach is workable and the test results achieve high accuracy, eliminate the ambiguity, contribute to
solving the problem of word segmentation and applying efficiency in Khmer language processing.
ANALYSIS OF MMSE SPEECH ESTIMATION IMPACT IN WEST SUMATRA'S NOISESsipij
This study aimed to estimate the original voice signal which is interrupted by noise with MMSE method
based on Wiener filter. The Wiener filter is classified as the MMSE estimator studied by previous
researchers. The study assessed the voice signal input count down by European woman that are distorted
by two types of noises, the one is noise based on the outdoor location, sound of siren firefighter, and the
other is the indoor location noise, which represented by noise in lecturer room in campus. The two process
signal is estimated by MMSE estimator which approximated by Wiener filter that must have founded and
counted the covariance of each signal processes are related to the system. Thus the researchers tried to
estimate both types of sounds noisy European woman are due to interference noise source of fire fighter
and faculty room and assess its impact in the form of graphs vote against a function of time, the pattern
shape of the signal and SNR.
Natural Language Toolkit (NLTK) is a generic platform to process the data of various natural (human)
languages and it provides various resources for Indian languages also like Hindi, Bangla, Marathi and so
on. In the proposed work, the repositories provided by NLTK are used to carry out the processing of Hindi
text and then further for analysis of Multi word Expressions (MWEs). MWEs are lexical items that can be
decomposed into multiple lexemes and display lexical, syntactic, semantic, pragmatic and statistical
idiomaticity. The main focus of this paper is on processing and analysis of MWEs for Hindi text. The
corpus used for Hindi text processing is taken from the famous Hindi novel “KaramaBhumi by Munshi
PremChand”. The result analysis is done using the Hindi corpus provided by Resource Centre for Indian
Language Technology Solutions (CFILT). Results are analysed to justify the accuracy of the proposed
work.
A CASE STUDY ON AUTO SOCIALIZATION IN ONLINE PLATFORMSIJMIT JOURNAL
Auto socialization Theory[1][2]is a socialization theory, introduced by Swedish Social Psychology
Professor Emeritus Lars Dencik, Roskilde University Center (RUC) on how humans socialize, attempting
to be a part of a group by using a taxonomy in three stages. Even though the theory is based on
socialization amongst minors, the adult human uses Auto socialization to navigate everyday life in all its
aspects of interaction, including communications, collaborations through online platforms. By focusing on
the Auto socialization aspect in an online context, it is possible to explain why online platforms e.g.
Facebook, World of Warcraft are so successful in maintaining and increasing the numbers of stabile
audience and why other platforms, offering learning on a massive scale, (MOOC) facing dropout rates in
the high 80 -90’s[3][4][5].
A STUDY ON QUANTITATIVE PARAMETERS OF SPECTRUM HANDOFF IN COGNITIVE RADIO NET...ijwmn
The innovation of wireless technologies requires dynamic allocation of spectrum band in an efficient
manner. This has been achieved by Cognitive Radio (CR) networks which allow unlicensed users to make
use of free licensed spectrum, when the licensed users are kept away from that spectrum. The cognitive
radio makes decision, switching from primary user to secondary user and vice-versa, based on its built-in
interference engine. It allows secondary users to makes use of a channel based on its availability i.e. on the
absence of the primary user and they should vacate the channel once the primary user re-enters and
continue their communication on another available channel and this process in the cognitive radio is
known as spectrum mobility. The main objective of spectrum mobility is that, there is no interruption
caused due to the channel occupied by secondary users and maintains a good quality of service. In order to
achieve better spectrum mobility, it is mandatory to choose an effective spectrum handoff strategy with the
capability of predicting spectrum mobility. The handoff strategy with its parameters and its impact is an
important concept in spectrum mobility but fairly explored. In this paper an empirical study on quantitative
parameters involved in spectrum mobility prediction are discussed in detail. These parameters are studied
extensively because they play a vital role in the spectrum handoff process moreover the impact of these
parameters in various handoff methods can be used to predict the effectiveness of the system.
NETWORK PERFORMANCE ENHANCEMENT WITH OPTIMIZATION SENSOR PLACEMENT IN WIRELES...ijwmn
From one side, sensor manufacturing technology and from other side wireless communication technology
improvement has an effect on the growth and deployment of Wireless Network Sensor (WSN). The
appropriate performance of WSN has abundant necessity which has dependent on the different parameters
such as optimize sensor placement and structure of network sensor. The optimized placement in WSN not
only would optimize number of sensors, but also help to reach to the more precise information. Therefore
different solutions are proposed to reduce cost and increase life time of sensor networks that most of them
are concentrated in the field of routing and information transmission. In this paper, places which they need
new sensors placement or sensor movements are determined and then with applying these changes,
performance of WSN will calculate. To achieve the optimum placement, the network should evaluate
precisely and effective criteria on the performance should extract. Therefore the criteria should be ranked
and after weighting with using AHP algorithms, with use of Geographical Information System (GIS), these
weighted criteria will combined and in the locations which WSN doesn’t have enough performance, new
sensor placement will create. New proposed method, improve 21.11% performance of WSN with sensor
placement in the low performance locations. Also the number of added sensor is 26.09% which is lowest
number of added sensors in comparison with other methods.
A NOVEL METHOD FOR PERSON TRACKING BASED K-NN : COMPARISON WITH SIFT AND MEAN...sipij
Object tracking can be defined as the process of detecting an object of interest from a video scene and
keeping track of its motion, orientation, occlusion etc. in order to extract useful information. It is indeed a
challenging problem and it’s an important task. Many researchers are getting attracted in the field of
computer vision, specifically the field of object tracking in video surveillance. The main purpose of this
paper is to give to the reader information of the present state of the art object tracking, together with
presenting steps involved in Background Subtraction and their techniques. In related literature we found
three main methods of object tracking: the first method is the optical flow; the second is related to the
background subtraction, which is divided into two types presented in this paper, then the temporal
differencing and the SIFT method and the last one is the mean shift method. We present a novel approach
to background subtraction that compare a current frame with the background model that we have set
before, so we can classified each pixel of the image as a foreground or a background element, then comes
the tracking step to present our object of interest, which is a person, by his centroid. The tracking step is
divided into two different methods, the surface method and the K-NN method, both are explained in the
paper. Our proposed method is implemented and evaluated using CAVIAR database.
DEVELOPMENT OF AN ANDROID APPLICATION FOR OBJECT DETECTION BASED ON COLOR, SH...ijma
Object detection and recognition is an important task in many computer vision applications. In this paper
an Android application was developed using Eclipse IDE and OpenCV3 Library. This application is able to
detect objects in an image that is loaded from the mobile gallery, based on its color, shape, or local
features. The image is processed in the HSV color domain for better color detection. Circular shapes are
detected using Circular Hough Transform and other shapes are detected using Douglas-Peucker
algorithm. BRISK (binary robust invariant scalable keypoints) local features were applied in the developed
Android application for matching an object image in another scene image. The steps of the proposed
detection algorithms are described, and the interfaces of the application are illustrated. The application is
ported and tested on Galaxy S3, S6, and Note1 Smartphones. Based on the experimental results, the
application is capable of detecting eleven different colors, detecting two dimensional geometrical shapes
including circles, rectangles, triangles, and squares, and correctly match local features of object and scene
images for different conditions. The application could be used as a standalone application, or as a part of
another application such as Robot systems, traffic systems, e-learning applications, information retrieval
and many others.
A NOVEL IMAGE STEGANOGRAPHY APPROACH USING MULTI-LAYERS DCT FEATURES BASED ON...ijma
Steganography is the science of hidden data in the cover image without any updating of the cover image.
The recent research of the steganography is significantly used to hide large amount of information within
an image and/or audio files. This paper proposed a new novel approach for hiding the data of secret image
using Discrete Cosine Transform (DCT) features based on linear Support Vector Machine (SVM)
classifier. The DCT features are used to decrease the image redundant information. Moreover, DCT is
used to embed the secrete message based on the least significant bits of the RGB. Each bit in the cover
image is changed only to the extent that is not seen by the eyes of human. The SVM used as a classifier to
speed up the hiding process via the DCT features. The proposed method is implemented and the results
show significant improvements. In addition, the performance analysis is calculated based on the
parameters MSE, PSNR, NC, processing time, capacity, and robustness.
ROBUST FEATURE EXTRACTION USING AUTOCORRELATION DOMAIN FOR NOISY SPEECH RECOG...sipij
Previous research has found autocorrelation domain as an appropriate domain for signal and noise
separation. This paper discusses a simple and effective method for decreasing the effect of noise on the
autocorrelation of the clean signal. This could later be used in extracting mel cepstral parameters for
speech recognition. Two different methods are proposed to deal with the effect of error introduced by
considering speech and noise completely uncorrelated. The basic approach deals with reducing the effect
of noise via estimation and subtraction of its effect from the noisy speech signal autocorrelation. In order
to improve this method, we consider inserting a speech/noise cross correlation term into the equations used
for the estimation of clean speech autocorrelation, using an estimate of it, found through Kernel method.
Alternatively, we used an estimate of the cross correlation term using an averaging approach. A further
improvement was obtained through introduction of an overestimation parameter in the basic method. We
tested our proposed methods on the Aurora 2 task. The Basic method has shown considerable improvement
over the standard features and some other robust autocorrelation-based features. The proposed techniques
have further increased the robustness of the basic autocorrelation-based method.
A COLLAGE IMAGE CREATION & “KANISEI” ANALYSIS SYSTEM BY COMBINING MULTIPLE IM...ijma
The collage is an artistic method to create a new image by combining multiple images under some rules or
conditions for collage creators. To realize a mechanism to interpret “Kansei” of the collage creator by the
combination process of multiple image-materials and a formed collage image, we propose a new system to
analyze the collage work by using a database stored to each collage creation information. The collage
works which a creator made by using this system was evaluated. And also, we clarified how to combine
image-materials to make the good collage image having specific impression.
ASPHALTIC MATERIAL IN THE CONTEXT OF GENERALIZED POROTHERMOELASTICITYijsc
In this work, a mathematical model of generalized porothermoelasticity with one relaxation time for
poroelastic half-space saturated with fluid will be constructed in the context of Youssef model (2007). We
will obtain the general solution in the Laplace transform domain and apply it in a certain asphalt material
which is thermally shocked on its bounding plane. The inversion of the Laplace transform will be obtained
numerically and the numerical values of the temperature, stresses, strains and displacements will be
illustrated graphically for the solid and the liquid.
BFO – AIS: A FRAME WORK FOR MEDICAL IMAGE CLASSIFICATION USING SOFT COMPUTING...ijsc
Medical images provide diagnostic evidence/information about anatomical pathology. The growth in
database is enormous as medical digital image equipment’s like Magnetic Resonance Images (MRI),
Computed Tomography (CT), and Positron Emission Tomography CT (PET-CT) are part of clinical work.
CT images distinguish various tissues according to gray levels to help medical diagnosis. Ct is more
reliable for early tumours and haemorrhages detection as it provides anatomical information to plan radio
therapy. Medical information systems goals are to deliver information to right persons at the right time and
place to improve care process quality and efficiency. This paper proposes an Artificial Immune System
(AIS) classifier and proposed feature selection based on hybrid Bacterial Foraging Optimization (BFO)
with Local Search (LS) for medical image classification.
REAL-TIME INTRUSION DETECTION SYSTEM FOR BIG DATAijp2p
The objective of the proposed system is to integrate the high volume of data along with the important
considerations like monitoring a wide array of heterogeneous security. When a real time cyber attack
occurred, the Intrusion Detection System automatically store the log in distributed environment and
monitor the log with existing intrusion dictionary. At the same time the system will check and categorize the
severity of the log to high, medium, and low respectively. After the categorization, the system will
automatically take necessary action against the user-unit with respect to the severity of the log. The
advantage of the system is that it utilize anomaly detection, evaluates data and issue alert message or
reports based on abnormal behaviour.
DEVELOPMENT OF ARABIC NOUN PHRASE EXTRACTOR (ANPE)ijnlc
Extracting key phrases from documents is a common task in many applications. In general: The Noun
Phrase Extractor consists of three modules: tokenization; part-of-speech tagging; noun phrase
identification. These will be used as three main steps in building the new system ANPE, This paper aims at
picking Arabic Noun Phrases from a corpus of documents, Relevant criteria (Recall and Precision), will be
used as evaluation measure. On the one hand, when using NPs rather than using single terms, the system
yields more relevant documents from the retrieved ones, on the other hand, it gave low precision because
number of the retrieved documents will be decreased. At the researchers conclude and recommend
improvements for more effective and efficient research in the future.
DESIGN OF LOW POWER SAR ADC FOR ECG USING 45nm CMOS TECHNOLOGYVLSICS Design
Design of a low power Successive Approximation Register Analog to Digital Converter (SAR ADC) in
45nm CMOS Technology for biopotential acquisition systems is presented. It is designed by using a high
threshold voltage (Vt) cell to reduce power dissipation. A 10-bit SAR ADC is designed and compared with
the low resolution SAR ADC and normal threshold voltage (Vt) ADC with respect to power and delay. The
results show that high Vt SAR ADC saves power upto 67% as compared to low Vt SAR ADC without any
penalty of delay. Other performance metrics studied are the Effective Number of Bits (ENOB) and Signal to
Noise Ratio (SNR), Signal to Noise and Distortion Ratio and Spurious Free Dynamic ratio.
A NOVEL APPROACH FOR INFORMATION RETRIEVAL TECHNIQUE FOR WEB USING NLPijnlc
Webpages are loaded with vast and different kinds of information about the entities in the real-world.
Information retrieval from the Web is of a greater significance today to get the accurate queried data
within the desired time frame which is increasingly becoming difficult with each passing day. Need to
develop a system to solve entity extraction problems from the web as compared to the traditional system.
It’s critical to have a clear understanding of natural language sentence processing in the web page along
with the structure of the web page to get the correct information with speed. Here we have proposed
approach for information retrieval technique for Web using NLP where techniques Hierarchical
Conditional Random Fields (i.e. HCRF) and extended Semi-Markov Conditional Random Fields (i.e. Semi-
CRF) along with Visual Page Segmentation is used to get the accurate results. Also parallel processing is
used to achieve the results in desired time frame. It further improves the decision making between HCRF
and Semi-CRF by using bidirectional approach rather than top-down approach. It enables better
understanding of the content and page structure.
Trust is recognized as an important factor that mediates many aspects of human behavior (Camerer, 2003). Definitions of trust vary but a widely accepted one is that it is a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intentions or behavior of another. Therefore, a person (the trustor) who depends on someone else (the trustee) expects to reduce the likelihood or size of a negative outcome in some situation, such as when that dependence is misplaced, the expected value of the outcome is lower.
Trustworthy Micro-task Crowdsourcing: Challenges and OpportunitiesAlessandro Bozzon
Micro-task crowdsourcing has become a successful mean to obtain high-quality data from a large crowd of diverse people. In this context, trust between all the involved actors (i.e. requesters, workers, and platform owners) is a critical factor for acceptance and long-term success.
In this talk, I will discuss some problematic aspects of existing micro-task crowdsourcing platforms, where trust is built on fragmented, opaque, and often incomplete knowledge. I will provide examples in which the adoption of open, transparent, and socially-aware trust-building strategies have led to better crowdsourcing performance. I will then conclude with several proposals on how to increase the amount of trust cues available in crowdsourcing platforms, possibly with methods drawn from related disciplines such as user modelling and HCI.
The Mediating Role of Group Cohesion in the Relationship between Interpersona...inventionjournals
The phenomenon of interpersonal trust holds a significant place in management literature and its potential and possibilities gather momentum with every attempt of research and discourse on the topic.This paper attempts to foresee the impact of interpersonal trust on group cohesion and team effectiveness. This study intends to empirically validate the mediating role of group cohesion in the relationship between interpersonal trust and team effectiveness. It is envisaged that this study based on primary data collected from 177 scientists from three nationalized research and development organizations in central Kerala, South India and carried out during the time period of June to September 2016 ,will add to our understanding of the link between interpersonal trust,group cohesion and team effectiveness.Partial Least Squares (PLS) was used to authorize the relationship among the variables. Findings of the study are conferred, together with limitations and suggestions for future research. This empirical study reiterates through its analysis and results that there is significant relationship between interpersonal trust and group cohesion. The study provides a deeper and richer understanding in explaining the relationship between group cohesion and team effectiveness. This study portrays that group cohesion partially intercedes the relationship between Interpersonal trust and team effectiveness
TRUST BASED PARTICIPANT DRIVEN PRIVACY CONTROL IN PARTICIPATORY SENSINGijasuc
Widespread use of sensors and multisensory personal devices generate a lot of personal information.
Sharing this information with others could help in various ways. However, this information may be
misused when shared with all. Sharing of information between trusted parties overcomes this problem.
This paper describes a model to share information based on interactions and opinions to build trust
among peers. It also considers institutional and other controls, which influence the behaviour of the
peers. The trust and control build confidence. The computed confidence bespeaks whether to reveal
information or not thereby increasing trusted cooperation among peers.
EXPLORING KEY ELEMENTS REQUIRED FOR ORGANIZATIONAL TRUST AND THE CONSEQUENTIA...IJMIT JOURNAL
This paper focuseson the status of organizational trust in Muscatand its impact on organizational learning (OL) which is based on the willingness of employees sharing knowledge gathered through experience to improve organizational performance and sustainable competitiveness [1]. Online structured questionnaire andMicrosoft Excel used to collect and analyze the data showed significant organizational trust exist
within organizations including organizational transparency, management style, employees’ welfare and support, and job security. But still, minimalOL and sharing was happening contradicting theories that suggest organizational trust leads to important group collaboration, willingness of employees to share
knowledge gathered through their experience and its close link to OL. Lack of compassion and being too controlling at timeswere also raisedas concerns and existing knowledge sharing technological support were also not having much impact. Bringing people together for more effective communications among teams and promoting knowledge sharing culture can lead the way.
Trust is the most fundamental building block of any relationship whether in business, politics, marriage, family or friendships. In the real world, trust signifies different things to different people but it frequently boils down to one point: trust is essential to your success.
Trust Recovery in the Team by David Clutterbuck.pdfAlex Clapson
Once trust is broken in a team, it is hard to recover. Yet the requirement to collaborate remains as strongly as ever.
If they learn from the breakdown of that relationship, they become a wiser person, better able to trust and be trusted.
Building Psychological Safety is the key to rebuilding trust.
In society, there is a growing call for trust in technology. Just think about the data leaks and privacy issues that hit the news almost on a daily basis. Organizations tackle these issues through risk management practices and implementing controls and measures to ensure meeting the risk appetite of the organization. But the implications go further, last year the Dutch privacy watchdog stated that organizations should be very careful in using Google cloud services due to their poor privacy practices. This is not only challenging for the vendor but also for the clients using the services. Another example is Apple. They are doubling down on privacy in their iCloud and iOS offerings, so users trust them more as a brand, which increases their market share.
This raises several questions: What is trust? When do we decide to trust someone or something? And how can you become trusted? Do we overlook what trust really means, or do we have an innate sense for “trust”? But how does that work for organizations consisting of hundreds or thousands of people and complex business-to-business structures?
In a world characterized by varying shades of gray, the demarcation between truth and deception can often blur, posing a challenging ethical dilemma. This article explores the intricate interplay between honesty and deceit, shedding light on the factors that make this line so elusive.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Knowledge engineering: from people to machines and back
TRUST: DIFFERENT VIEWS, ONE GOAL
1. International Journal of Security, Privacy and Trust Management (IJSPTM) Vol 6, No 1, February 2017
DOI : 10.5121/ijsptm.2017.6101 1
TRUST: DIFFERENT VIEWS, ONE GOAL
Mubarak Almutairi
College of Computer Science & Engineering, University of Hafr Albatin, Hafr Albatin,
Saudi Arabia
ABSTRACT
A thorough review of trust models is carried out in this paper to reveal the key capabilities of existing trust
models and compare how they differ among disciplines. Trust decisions are risky due to uncertainties and
the loss of control. On the other hand, not trusting might mean giving up some potential benefits. Advances
in electronic transactions, mutliagent systems, and decision support systems create a necessity to develop
trust and reputation models. The development of such models will allow for trust reasoning and decisions
to be made in situations with high risk and uncertainty. In recent years, several attempts have been made to
model reputation and trust. However, perceiving trust differently and the lack of having a unified trust
definition are among the main causes of the proliferation of many trust models across different disciplines.
1. INTRODUCTION
Despite its usefulness in both human and artificial societies, trust was and will continue to be a
risky proposition. Trust has been always an integral component of human social life and actions.
The advances in autonomous intelligent systems, communications, and electronic transactions
motivated the execution of research regarding trust and reputation in order to span the spatial and
temporal separation among the partners involved in a social interaction or an exchange of
commodities or goods.
Reputation is used as a means to build and update trust after a certain number of successful
transactions [3, 15, 28, 29, 34, 40, 102]. Anonymity, uncertainty, risk, lack of control, and
potential opportunism are key elements in most online transactions. Using trust evaluation and
models to compensate for the lack of information and control in online environments will allow
one to make decisions in regard to whom to trust and engage within a transaction or cooperative
action. Some of the associated risks with online transactions include the exchange of some
personal information, the absence of the physical goods, the non-immediate exchange of goods
and money, and how secure the transaction media is [8, 41, 42, 54].
Trust is inevitably involves uncertainty. In general, uncertainty is the absence of credible
knowledge about future events. Trust is supposed to assure an agent that the desirable course of
events will be realized in the unknowable future, as if being guaranteed from past knowledge. As
Luhmann [81] wrote, “trust rests on illusion. In actuality, there is less information available than
would be required to give assurance of success. The actor willingly surmounts this deficit of
information”. A trustful person can comprehend new experiences and carry out actions that have
been previously undesirable or unachievable. This is due to the fact that when trusting, in favour
of an inner confidence, one simplifies the complexity of the outer world and removes any
uncertainties.
When trusting, we allow ourselves to be vulnerable to others by depending on them to achieve or
care for something we value. This interdependence relationship occurs when it is in the mutual
benefit for both parties to fulfill their obligations towards the achievement of their common goal.
2. International Journal of Security, Privacy and Trust Management (IJSPTM) Vol 6, No 1, February 2017
2
In this case, no party has a dominant power over the other. While engaging in a dependence
relationship, none of the parties is willing to exploit its situation. The realization of this
dependency relationship by the trustee will put him or her in a relatively more powerful situation
[81]. If properly used, this kind of power will strengthen the trust relationship. Some trustees
might refrain from using this power to avoid the negative consequences associated with
exploiting the dependent trustor.
Section 2 reviews trust definitions from different disciplines. In Section 3, different approaches to
modeling trust are explained. Section 4 highlights the common shortcomings of the current
approaches to modeling trust and suggests ways of improving them. Some concluding remarks
and insights are given in Section 5.
2. TRUST DEFINITIONS FROM DIFFERENT DISCIPLINES
Different disciplines handle trust differently according to their own perceptions and what fits their
specific goals. In order to consolidate sensible measures of trust, one needs to step back and
analyze why different disciplines view trust differently. What follows is a thorough review of the
existing trust definitions from different disciplines like, Psychology [9, 76, 80, 104, 105],
Sociology [18, 48, 52, 78, 81, 118], Philosophy [6, 32, 63, 68, 101], Economics [25, 57, 85, 124,
130], Finance [45, 61], Marketing [39, 49, 50, 93, 117], Management [51, 69, 82, 88, 91, 123], E-
Commerce [71, 89, 90], and Computer Science [8, 36, 44, 100, 112].
2.1. TRUST IN PSYCHOLOGY
In his 1973 book, M. Deutsch defines trust as confidence that one will find what is desired from
another person rather than what is feared [37]. Many researchers find this definition to be a
specific characteristic of a relationship. Deutsch, however, presents many other aspects of trust in
his 1973 work. He presents trust as being connected to despair, innocence, social conformity,
virtue, gambling, risk-taking and faith, among others.
From a psychological perspective, risk in trust is approached as one of the characteristics of
individuals. While some people are willing to take risks, there are some who are too cautious and
distrustful to take any chances. Trusting behavior depends on how individuals perceive an
ambiguous path or unclear situation. In such cases, the occurrence of a good or bad result is
dependent on other’s actions. Knowing that a negative result is more harmful than a good one, a
trusting decision should be made.
The use of the word “perceive” in the previous paragraph is to emphasize the subjective nature of
trust. If trust is based on individual perception, it is likely that the same situation will be seen
differently by different individuals. Estimates of chances and expected gains or losses are
subjective. Thus, some individuals might make unwise risks, thereby acting as if they are taking
chances while, in fact, they are trusting unwisely.
2.2. TRUST IN SOCIOLOGY
The sociology of trust has been investigated from different angles: rational choices, culture,
functionality, symbolic interaction, and others. Trust is a social relationship subject to its own
special system of rules [81]. Trust occurs within interactions that are influenced by both
personality and social systems [78]. Most sociologists agree with: “the clear and simple fact that,
without trust, the everyday social life which we take for granted is simply not possible” [52, p.
32]. We always find ourselves in a condition of uncertainty about and uncontrollability of future
3. International Journal of Security, Privacy and Trust Management (IJSPTM) Vol 6, No 1, February 2017
3
actions. We have no way of knowing and controlling what others will do independently of our
own actions and we are not even sure how they will react to ours. In general, uncertainty and risk
are integral components of human interactions that can’t be ignored or avoided.
In situations in which we have to act in spite of uncertainty and risk, the third factor that comes to
the fore is that of trust [118]. Trusting becomes a crucial strategy for dealing with an uncertain
and uncontrollable future. Since there is no way of knowing what is in the minds of others, we
need trust to deal with an unknown future and others’ uncontrollable actions.
When participating in uncertain and uncontrollable conditions, we take risks, we gamble, and we
make bets about the future and the actions of the others. A simple and general definition of trust
is: “trust is a bet about the future contingent actions of others” [118, p. 25]. In this sense, trust
consists of two main components: beliefs and commitments. First, it involves specific
expectations: “trust is based on an individual’s theory as to how another person will perform on
some future occasion” [52, p. 33]. When placing trust, we behave as if we know the future.
Second, trust involves commitment through action or roughly speaking, placing a bet. Thus:
“trust is the correct expectations about the actions of other people that have a bearing on one’s
own choice of action when that action must be chosen before one can monitor the actions of those
others” [48, p. 51]. In order to have a better and deeper understanding of trust, we need to pay
attention to the mental and subjective attitudes of the trusting person. It is important to focus on
what happens in an individual’s mind when trusting someone else.
2.3. TRUST IN PHILOSOPHY
Trust and distrust are subjective attitudes that affect our thinking and feelings [63]. When
trusting, we are more likely to let ourselves be vulnerable to others and allow ourselves to depend
on others. Trust is a cooperative activity in which we engage so that we can assist one another in
the care of goods [6]. We trust others when we afford them the opportunity to care for something
we value. We trust things as well as people. While trusting things is based on the properties of the
things that we know in advance, trusting people is based on past experiences. When we trust, we
hold expectations toward another person. To expect is to look forward to something without
anticipating disappointment. When holding expectations of another, we project into the future,
making an inference about the sort of person someone is going to be in the future. When trusting,
the expectations alone are not enough but we must anticipate that the other has good intentions
and the ability to carry out what is expected of him or her.
In order to trust someone, we need to have a sense of his or her values. A person who lacks
commitment to any values or principles doesn’t give us the ability to predict either good or bad
intentions or treatment. Knowing the other’s values, commitments, and loyalty will help us to
decide to what extent risk would be involved if we count on that person. We trust others more
fully when we believe that they have positive feelings towards us personally and not just as
members of some group. Trust is a risky business because people whom we trust can let us down
and we are vulnerable to harm when they do so. It is important to accept the risks of trust and try
to handle them rather than taking the simplistic view that trust is always good. Sometimes we
trust too easily and risk a great deal in doing so [32, 63]. Our trust is generally based on
experiences with other people. On the basis of those experiences, we construct a characterization
or picture of them but in reality they are free agents with different characterizations that go
beyond our beliefs about them.
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2.4. TRUST IN ECONOMICS
The study of trust and reputation in a free economy tries to address the relationship between trust
and competition. By supplying quality goods at competitive prices, firms are building good
reputations in order to secure their future market position and share. Firms will refrain from being
concerned about the short-term profits when compared to building a good reputation and long-
term profits thereafter.
In free-markets economy, consumers are faced with the dilemma of getting quality good for the
least prices from profit-maximizing entities (firms). The trade-off between the price of goods and
their quality is bridged by means of good reputation and trust between the consumer and the
goods’ providers. Some of the pioneers in this field are [26, 27, 47, 65, 66, 77, 103, 114, 116,
120, 121].
2.5. TRUST IN FINANCE
The allocation of financial resources to certain activities includes buying assets, investments, and
loans. These activities, and all financial activities, in general, are associated with some risk and
uncertainty due to one of the involved parties not honoring his or her obligations. For example,
borrowing money for a specific investment is highly related to the future ability of the borrower
to pay back the loan. This highly depends on the trustworthiness and the associated evaluation of
risks. Jensen and Meckling [70] strongly believe that trust, reputation, and social bonds will
always be present in such interactions. The formation of trust and what factors would affect it
were a topic for research in finance. Hart [64] studied trust within agency theory. Others, like
Shapiro and Stiglitz [115], investigated the ethical side of trust in terms of the reliability of one of
the parties. This required importing some of the sociological concepts such as social capital and
social networks [55, 56, 57, 58]. Guth and Kliemt [62] analyzed the evolution of trust in a simple
game of trust between a buyer and a seller.
2.6. TRUST IN MARKETING
Studying trust relationship between a marketer and a customer is a key factor in the relationship
between the two. Most of the research in this area focuses on the customer’s trust [93]. The
research of trust in marketing dates back to the 1970s. Establishing a high level of trust in a
marketing relationship allows the two parties to focus more on long lasting term benefits [49].
Some of the developed marketing theories are based on trust [93]. Trust could assume different
phases like, the trust between the firm and its marketers [119], the marketers and the customers,
and the customers and the firm [113]. These three trust phases interact and affect each other one
way or another [93]. This explains why most marketing researchers have included trust in their
relationships channel models where a vendor provides a service or a good to a distributor who
resells it to the end user [50].
2.7. TRUST IN MANAGEMENT
Different parties within an organization need to work together to accomplish specific goals at
both the personal and the organizational levels. This often requires some teamwork and
dependence on others to execute certain assigned tasks. Risk will be always present in such
relationships due to a lack of knowledge to do a specific task or the unwillingness to do it [88].
The presence of trust will reduce the risks associated with group interactions. However, some of
the problems associated with trust in such environments are: lack of a specific definition of trust,
difficulties of defining the boundaries of each task, lack of well defined regulations governing the
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interactions between the different inter-organization parties, and the unclear relationship between
trust antecedents and consequences. There are some studies suggesting that trust is highly
influenced by factors of which some are individual and others are organizational. In his 1998
work, Doney and Cannon [39] suggested that social values and norms, besides behavioral
attitudes, are key factors in trust. The length and the type of the relationship between the different
parties within an organization and between the different organizations, the presence of previous
interactions, and the interpersonal relations, if any, are other factors suggested by Inkpen and
Currall [69]. Gill and Butler [51] focused on the presence of some personal knowledge or quality
for fulfilling some delegated tasks. Therefore, they define trust as an elaboration from current
qualities as the most reliable for attaining a future goal. Some hidden factors or mental processes
could be accounted for in explaining the high levels of trust for entities interacting for the first
time [91]. Trust leads to some interdependencies which will eventually involve some sort of
sharing of the control and management of things we care for [69]. Nevertheless, trust has not been
appreciated enough within the management field. This is in part because managers didn’t devote
sufficient time, energy, or resources to creating it within their organizations or because they look
at it as a matter of strategic choice [123].
2.8. TRUST IN E-COMMERCE
Trust in electronic transactions goes beyond risk and uncertainty to include other factors like lack
of information, lack of control, ease of use, privacy and security issues [13, 31]. On-line
transactions and exchange relationships are not only characterized by uncertainty, but also by
secrecy, lack of control and potential fraud, thereby making risk and trust crucial elements of
electronic commerce [21].
The process of buying over the internet being perceived as risky, presents numerous risks for
consumers during and after the transaction itself. Online firms may be located in different
locations of the country or even in different countries. This requires a non-immediate exchange of
information, goods, and money. As a result, some sensitive information is exchanged online like,
personal and financial information. The limited history about the seller prior to the interaction
adds to the risk and uncertainty involved in this transaction [8].
Some of the system-dependent uncertainties go beyond the control of the parties involved in the
transaction. These are environment related uncertainties which could be characterized as
exogenous. Generally speaking, the concept of exogenous uncertainties refers to the uncertainties
of the world [67]. The environment dynamics and system complexity are two main factors when
considering exogenous uncertainties. In the context of electronic commerce, exogenous
uncertainty relates to the potential technological errors or security gaps that can’t be avoided [10,
11, 12]. The utilization of encrypted transactions, firewalls, authentication mechanisms and
privacy seals are means of reducing the effects of system uncertainties [100]. Transaction-specific
uncertainties are caused by decisions of parties exchanging information over the transaction
media. The consumer may interpret the uncertainties as seller’s potential behavior in the
transaction process. In computer mediated transactions, element of personal interaction like body
language, gestures, and facial expressions are eliminated.
In general, the more trust present in a given situation, the less additional information is needed to
make a certain decision. On the other hand, if there is little or no trust, there will be a need for
complete information in order to reduce system-dependent and transaction-specific uncertainties.
Uncertainties are perceived differently and, hence, the level of the perceived uncertainties
influences the needed balance between trust and information [122]. Trust and additional
information could be seen as means to reduce uncertainties [81, 123].
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2.9. TRUST IN COMPUTER SCIENCE AND INFORMATION SYSTEMS
Computer scientists tried to formalize the measures of knowledge derived from sociology and
psychology into agents’ architectures. One can understand trust as an attitude of an agent who
believes that another agent has a given property. Therefore, one can analyze the meaning of trust
as a function of the attributed properties [46]. For instance, the property may be that the agent one
trusts fulfills his obligations, like the case of a buying agent. Properties one considers are the
ability of the agent to do the job, to make decisions, or just to deliver information [36].
With the emergence of electronic commerce, trust issues became important for many people.
Generally speaking, it is agreed that in order for electronic commerce to become successful, most
people have to trust it. The person's trust in a transaction is determined by the trust in the counter
party and the trust in the transaction media based on the assumption that party and media trust
supplement each other. If there is not sufficient party trust, then the media trust and its control
protocols should be brought in to supplement the party trust [38]. Trust in the counter party can
be defined as "The subjective probability by which an individual A expects that another
individual B performs a given action on which its welfare depends" [45, p. 56]. According to this
definition, it could be argued that trust has both objective and subjective attributes. The first
depends on the media structure, such as the functionality of the control mechanisms in place. The
second depends on personal experiences in dealing with a specific party, or with specific
procedures and control protocols.
2.10. TRUST AS A GLOBAL VIEW
Gambetta (2000) attempted to gather different thoughts regarding trust from many areas [5, 48].
The most important aspect of their work is the use of values. On the other hand, using explicit
values for trust can be problematic due to the subjectivity of trust in which the same value could
be seen differently by different agents. Yet the use of values for measuring trust allows one to talk
more precisely about certain circumstances or behaviors concerning trust. Also, it permits a
straightforward implementation of the formulation.
In his research, Gambetta [48, p. 217] defines trust as “a particular level of subjective probability
with which an agent assesses that another agent or group of agents will perform a particular
action both before he can monitor such action or independently of his capacity ever to be able to
monitor it and in a context in which it affects his own action”. This definition excludes certain
aspects which are important to trust like referring only to the trust relationship between the agents
themselves and not, for example, the agents and the environment. It also excludes those agents
whose actions have no effect on the decision of the truster, despite the fact that trust is present.
An interesting point in Gambetta’s work is the concern regarding competition and cooperation. In
some cases, cooperation is not good, such as the cooperation among thieves or drug dealers, while
it is very desirable among policemen. Then, it is beneficial to find “the optimal mixture of
cooperation and competition rather than deciding at which extreme to converge” [48, p. 215]. In
competitive situations, cooperation is of great importance since “even to compete in a mutually
non-destructive way one needs at some level to trust one’s competitors to comply with certain
rules” [48, p. 215]. Despite the importance of using values for trust, Gambetta didn’t develop the
idea in any concrete fashion [86].
3. APPROACHES TO MODELING TRUST
Different approaches have been used in an attempt to model trust, of which some have
commercial applications and others are only meant for academic purposes. Some of these
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modeling attempts are only informative while others are conceptual. In the following sections,
different approaches for modeling trust are classified based on their underlying methodologies.
3.1. SIMPLE SCORING
Considered a relatively simple approach, some basic mathematical operators like, multiplication
and addition, are used to compute trust values. The average and the weighted average are the two
most common methods in this category. Getting direct ranking or feedback from the users and
then averaging all the responses is a simple and intuitive way of the many techniques used in e-
commerce [3]. A slightly modified version of this technique is being used in e-Bay [40]. Both
positive and negative scores are summed separately and then subtracting the total negatives from
the total positives to get the overall score. The values often used are 1, 0, and -1 for the positive,
neutral, and negative ratings, respectively. In some cases, the weighted average is being
implemented to put more emphases on the most recent transactions or to highlight some factors
more than others.
3.2. STATISTICAL
When using this technique, a history of all previous interactions is maintained. This history is
combined with the new interactions to compute the overall trust value using statistical
approaches. The most common approach is Bayesian. The Bayesian system takes a binary input
and utilizes the beta-Probability Density Function (PDF) to compute the updating. Within the
PDF distribution, the two parameters ( ,α β ) refer to the positive and negative ratings,
respectively [72, 74, 95, 97, 125].
The Bayesian system starts with 1 assigned to both parameters and keeps updating after each
interaction. While this provides a sound theoretical basis for computing a trust value, it might not
be easily understood by average users.
3.3. LINGUISTIC
Sometimes, it is easier describing the level of trust using some linguistic terms rather than
numerical values. Using fuzzy or probabilistic approaches, those linguistic terms could be
matched with appropriate or approximated numerical values that are easy to calculate and
program. Al-Mutairi et al. [2] used the linguistic terms absolutely low, very low, low, fairly low,
medium, fairly high, high, very high, and absolutely high to describe the trust level. This enables
the agent to calculate the trustworthiness of another agent before engaging with it in an
interaction. Fuzzy logic is used to match those linguistic terms with approximated values to carry
on some computations and obtain the overall expected trust value. This also depends on some
other factors like the importance of the interaction for a specific agent, the expected value, the
availability of other alternatives, and the risk attitudes of the agent.
3.4. COGNITIVE
This technique tries to mimic the human way of thinking and reasoning about trust. It attempts to
go beyond sensible things and explore what transpires in the mind of one when trusting [7]. This
is highly linked to one’s belief and social community. For an inner feeling or confidence one may
or may not trust another person. The thresholds of what is trustworthy or not will be different for
different agents. Some authors [73] use the belief theory to predict a trust value. Belief theory is a
framework based on probability theory where the total of the probabilities doesn’t necessarily add
up to 1. This is in part due to the presence of some uncertainties. It is important to mention that
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transitivity is an underlying assumption in most of the models in this category where an agent is
considered as trustworthy if referred to as trustworthy by other agent or agents.
3.5. FUZZY
When using fuzzy logic to evaluate trust, it is possible to refer to trust using a linguistic label that
describes a specific fuzzy function rather than using numerical values. The trust level can have
different memberships to different fuzzy sets like belonging to trustworthy and very trustworthy
with memberships of 0.4 and 0.6, respectively. The models proposed by Al-Mutairi et al. [2],
Manchala [84], and Sabater and Sierra [106, 107, 108] are good examples of this type of
modeling.
3.6. FLOW CHAINS
The main assumption underlying in this category of models is transitivity. By that, one means that
if agent a trusts agent b, agent b trusts agent c, then agent a must trust agent c. It could be as
simple as an interaction between three agents or through long chains and loops of iterative deals.
However, it could be the case that trust values from different agents are assigned different
weights depending on the previous history of that particular agent. More interaction chains
through a particular agent means higher trust value and vice versa [4]. In web semantics, the more
hyperlinks to a site the higher its rank and more hyperlinks out of that page the less its rank [14,
99]. Makino [83] used the same concept to calculate the reputation based on the number of
citations in a research environment.
4. DISCUSSION
Table 1 shows a chronological summary of some of the existing work in trust modeling. From
this extensive review, one can highlight the following issues for further investigation when
modeling trust.
4.1. UNRATED TRANSACTIONS
Though sighted as one of the most common ways of evaluating the rules of trust, feedback is not
always given for all transactions [102]. This is in part due to the following:
• Lack of incentive (no direct benefits of providing feedback).
• Retaliation from the seller or service provider in response to negative feedback.
• Competition for a limited service or commodity.
• Feedback mechanism is lengthy or not easy to use.
• Ignorance.
Thinking of feedback as only being important in case it is negative (a way of warning others)
while neglecting the positive ones could give a misleading trust value. For example, on e-Bay,
assume that only 50 out 1000 transactions are assigned a negative feedback (the remaining 950
are positive). The score will be 950 when all transactions are given a feedback while the score for
the same seller will be 750 if only 800 out of the 950 positive transactions are reported. This will
cause the positive feedback ranking for this seller to drop from 0.95% in the first case to only
0.75% in the second case.
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4.2. MISLEADING FEEDBACK
Feedback could be misleading when, for some reason, it is unfair or not justified whether they are
positive or negative [34]. Some of the sited reasons for having a false positive feedback are:
• Reciprocation: a positive feedback for a positive feedback in return.
• Being rewarded with a discounted price.
• Building a good reputation through prearranged fake interactions.
• In contrast, false negative feedback could be due to:
• Based on a specific identity of a specific agent whether it is because of a previous
interaction history or personal reasons.
• Blaming the seller or the service provider for a shortcoming on behalf of the buyer or the
service recipient.
• Reasons that are beyond the control of the seller which could be related to the transaction
media or the delivery system.
The process of providing feedback is a very subjective issue that is hard to monitor and control
[92].
4.3. IDENTITY VERIFICATION
One of the risks associated with electronic environments is verifying that an agent is what he or
she is claiming to be [128]. Some of the identity associated risks are:
• Stolen verification information (username and passwords).
• Identity change to escape from a past transaction history.
• Validating the information supplied during the registration process.
Based on the assumption that trust is the result of acquired cumulative reputation over a period of
time through a number of interactions, not being able to verify the agents’ identities will give a
misleading trust index [23].
4.4. BEHAVIORAL CHANGES
When showing good intentions, regardless of the current low trust index, agents need to be given
a chance to recover and start a corrective process [74]. An agent might start with a low trust index
for one or more of the following reasons:
• Focusing on the short term benefits and not worrying about a long lasting one.
• Lack of knowledge about the importance of building a good reputation on the virtual
environments.
• Reasons that are related to the transaction media which is beyond the control of the agent.
• Change of the service provider’ management in order to recover from the current
situation.
• Change of the service type or product.
• Behavioral changes over time.
Giving more weight on the most recent transactions, like for the past six months or last year
without entirely neglecting the past interactions [16, 17], will give a more reflective index of the
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agent’s current situation. This will also allow one to analyze any behavioral trends over a period
of time.
5. SUMMARY
From this extensive review, one can appreciate the importance of trust across many disciplines.
However, trust research is still in its early stages and varies greatly depending on the trust context
and use. Most of the models are based on feedback through direct interactions or conveyed
through a third party. Though agreeing on the importance of direct experiences, there are more
factors that contribute to trust that should be taken into consideration. By its nature, trust is
complex, multidimensional, and subjective. It might be time to merge traditional game theoretic
approaches with cognitive, sociological, and psychological ones in order to better understand and
model trust. Due to the variations in defining and using trust, as of now, there is no single set of
unified trust data that could be tested and compared among the different trust models. Testing and
comparing trust models are still an arbitrary issue. Developing test data sets and general test
frameworks will enable fine tuning and improving some of the proposed models. It will also
allow researchers to examine which model works better for which uses.
Table 1. Chronological Summary Of Existing Trust Models.
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Table 1. (continued)
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