The paper discusses that tweet sentiment of key investors can be considered as an additional attribute to the other fundamental properties of the stock. We demonstrate how the sentiments when considered improves the forecasting accuracy of predicting stock valuation. Various experimental analysis on time series and regression based statistical models are considered. We also design predictive experiments and show which statistical measures to consider in these regression models for effectively predicting the close price of the stock. Finally, we provide some future direction where we plan to take this research forward and conclude with some closing remarks.

Object-oriented software systems contain large number of modules which make unit testing, integration testing, and system testing very difficult and challenging. While the aim of unit testing is to show that individual modules are working properly and the aim of the system testing is to determine whether the whole system meets its specifications, the aim of integration testing is to uncover errors in the interactions between system modules. However, it is generally impossible to test all connections between modules because of time and budget constraints. Thus, it is important to focus the testing on the connections presumed to be more error-prone. The goal of this work is to guide software testers where in a software system to focus when performing integration testing to save time and resources. This paper proposes a new approach to predict and rank error-prone connections. We use method level metrics that capture both dependencies and internal complexity of methods. We performed experiments on several Java applications and used error seeding techniques for evaluation. The experimental results showed that our approach is effective for selecting the test focus in integration testing.

Managers recognize that software development project teams need to be developed and guided.Although technical skills are necessary, non-technical (NT) skills are equally, if not more, necessary for project success.Currently, there are no proven tools to measure the NT skills of software developers or software development teams.Behavioral markers (observable behaviors that have positive or negative impacts on individual or team performance) are beginning to be successfully used by airline and medical industries to measure NT skill performance.The purpose of this research is to develop and validate the behavior marker system tool that can be used by different managers or coaches to measure the NT skills of software development individuals and teams.This paper presents an empirical study conducted at the Software Factory where users of the behavior marker tool rated video clips of software development teams.The initial results show that the behavior marker tool can be reliably used with minimal training.

Managers recognize that software development teams need to be developed. Although technical skills are necessary, non-technical (NT) skills are equally, if not more, necessary for project success. Currently, there are no proven tools to measure the NT skills of software developers or software development teams. Behavioral markers (observable behaviors that have positive or negative impacts on individual or team performance) are successfully used by airline and medical industries to measure NT skill performance. This research developed and validated a behavior marker system through an empirical study conducted at the Software Factory where users of the behavior marker tool rated video clips of software development teams. The initial results show that the behavior marker tool can be reliably used with minimal training.

Heterogeneous Sensor Networks are more powerful and efficient than homogeneous sensor networks. It has been shown that homogeneous sensor networks perform poorly because of routine limits and scalability. In our research, we consider to use heterogeneous topology to securely route data in a wireless sensor network. The given area of interest is initially partitioned into Voronoi clusters, where low-end nodes make clusters with high-end nodes. Each cluster has just one high-end node and a number of low-end nodes. Voronoi clusters are driven by the distance between the nodes, but our routing method the “Improved Tree Routing” uses hop count to route the data in the network. However, Voronoi clusters leave out some gaps in the topology. To cover those gaps we used a new meta-heuristic called Tabu search. With Tabu search we adjust the low-end nodes in the Voronoi clusters using cyclic exchange, pairwise exchange, and single moves. Only a few researchers thought of designing routing techniques with embedded security. In our approach we added security to Improved Tree routing. Through simulation, we show that Voronoi-Tabu clustering technique in conjunction with Secure Improved Tree routing performs better than directed diffusion, and LEACH routing protocols. Additionally, the security technique is performing better than E-G, LEAP, and SBK security methods. Simulation results show that the described method increases throughput, and reduces energy utilization and network delays.

Teamwork is essential in industry and a university is an excellent place to assess which skills are important and for students to practice those skills. A positive teamwork experience can also improve student learning outcomes. Prior research has established that teams with high levels of social sensitivity tend to perform well when completing a variety of specific, short-team, collaborative tasks. Social sensitivity is the personal ability to perceive and understand the feelings and viewpoints of others, and it is reliably measurable. Our hypothesis is that, social sensitivity can be a key component in positively mediating teamwork task activities and member satisfaction. Our goal is to bring attention to the fact that social sensitivity is an asset to teamwork. We report the results from an empirical study that investigates whether social sensitivity is correlated with the effectiveness of processes involved in teamwork and team member satisfaction in an educational setting. The results support our hypothesis that the social sensitivity is highly correlated with team effectiveness. It suggests, therefore, that educators in computer-related disciplines, as well as computer professionals in the workforce, should take the concept of social sensitivity seriously as an aid or obstacle to team performance and the teamwork experience.

Team work is the norm in major development projects and industry is continually striving to improve team effectiveness. Researchers have established that teams with high levels of social sensitivity tend to perform well when completing a variety of specific collaborative tasks. Social sensitivity is the personal ability to perceive, understand, and respect the feelings and viewpoints of others, and it is reliably measurable. However, the tasks in recent research have been primarily short term, requiring only hours to finish, whereas major project teams work together for longer durations and on complex tasks. Our claim is that, social sensitivity can be a key component in predicting the performance of teams that carry out major projects. Our goal is to determine if previous research, which was not focused on students or professionals in scientific or technical fields, is germane for people in computing disciplines. This paper reports the results from an empirical study that investigates whether social sensitivity is correlated with the performance of student teams on large semester-long projects. The overall result supports our claim that the team social sensitivity is highly correlated with successful team performance. It suggests, therefore, that educators in computer-related disciplines, as well as computer professionals in the workforce, should take the concept of social sensitivity seriously as an aid or obstacle to productivity.

In many applications of Wireless Sensor Networks (WSN), the source of an event needs to be protected. In resource constrained WSN, providing source anonymity is a challenging task. A traditional approach for hiding source in WSN is to let all nodes generate dummy data packets even if they have no event to report. However, this kind of approach introduces large overhead. In order to reduce the large overhead of sending dummy data packets, we propose using a much shorter control packet to achieve source anonymity. The short control packets are used to coordinate the transmissions of dummy data packets, which prevent revealing the source node and hence provides source anonymity in WSN. We evaluate the performance of our anonymity scheme via ns-2 simulations. The simulations show that our scheme has much less traffic overhead than an existing anonymity scheme.

The performance of wireless networks can be significantly improved by multi-channel communications compared with single-channel communications since the use of multiple channels can reduce interference influence. In this paper, we study interference-aware topology control in IEEE 802.11-based multichannel wireless mesh networks with dynamic traffic. Channel assignment is one of the most basic and important issues in such networks. Different channel assignments can lead to different network topologies. Based on a novel definition of co-channel interference, we formally define and present an effective heuristic for the minimum interference robust topology design problem which seeks a channel assignment for the given network such that the induced network topology is 2-connected and has minimum network interference.

Security is an important issue for sensor networks deployed in hostile environments, such as military battlefields. The low cost requirement precludes the use of tamper resistant hardware on tiny sensor nodes. Hence, sensor nodes deployed in open areas can be compromised and used to carry out various attacks on the network. In this paper, we consider the collision attack that can be easily launched by a compromised (or hostile) node: a compromised node does not follow the medium access control protocol and cause collisions with neighbor transmissions by sending a short noise packet. This attack does not consume much energy of the attacker but can cause a lot of disruptions to the network operation. Due to the wireless broadcast nature, it is not trivial to identify the attacker. In this paper, we propose a distributed scheme that is based on low-cost hardware and can effectively identify the source of a collision attack. Our scheme is based on analyzing physical-layer Received Signal Strength Index (RSSI) readings. We show that correct identification of an adversarial node can be achieved with greater than 85% accuracy. We further present a technique that degrades gracefully as the background noise increases.

User mobility in pervasive computing makes it fundamentally different from traditional desktop computing. Accordingly, the system configurations, such as resource allocation and routing, are extremely dynamic since available resources and users' needs may change when users are moving around different locations. There have been extensive works on the resource allocation for the users' needs. However, previous works did not consider complex situations, such as conflicting relations between different applications. This paper models a pervasive computing system from three parts: available network resources, available applications, and conflicting relations of the applications. To configure the system according to the dynamical changes, our work focuses on how to find the best set of applications, under the network resource and QoS routing constraints, to achieve the maximum system benefit for the users. We first propose an optimal solution using integer linear programming (ILP) scheme. Then a simple and effective heuristic is presented for better scalability. Extensive simulation results demonstrate that our ILP and heuristic achieve very good performance.

Establishing pair-wise keys in wireless sensor networks is a challenging task due to the hostile environment and limited resources in sensor nodes. Many key management schemes have been proposed for sensor networks. However, most existing schemes are designed for homogeneous sensor networks where all of the nodes have the same or similar capabilities. Research has shown that better performance can be achieved by forming a heterogeneous sensor network. In this paper, we present an efficient post-deployment key management scheme designed for heterogeneous sensor networks. The scheme does not assume any prior knowledge about sensor deployment and location. Our scheme takes advantage of a few powerful high-end sensor nodes and achieves efficient and effective key establishment in a sensor network. The performance evaluation shows efficiency and effectiveness measures for our scheme.

Most research works in routing and design of optical networks assume that the optical medium can carry data signals without any bit error. However, physical impairments of the optical signal introduced by optical fibers and components, e.g., power loss, noise, and dispersions, impose fundamental constraints in WDM networks, and must be taken into consideration in the routing and design problems of WDM networks. Only through 3R (optical-electrical-optical) regeneration (reamplification, reshaping, retiming) with OEO conversion can a lightpath be recovered from those impairments. Because 3R regenerators are costly devices and the OEO conversion can affect the efficiency of optical networks we need to use the regenerators efficiently and effectively. In this paper, we study the problem of placing the minimum number of regenerators to accommodate all requests with the consideration of physical impairments. We first propose a novel ILP formulation for an optimal solution and a benchmark for this problem. We then provide an effective heuristic for large-sized WDM networks. Simulation results show that our schemes have good performance in terms of network design and running time.

The p-cycle design problem has been extensively studied because it can provide both ring-like fast self-protection speed and spare capacity efficiency of path protection scheme. However, p-cycle provisioning for dynamic traffic has not been fully addressed. Most related works have not considered link capacity in the construction of p-cycles, which may cause problems in practice because the protection paths may not have enough backup bandwidth. In this paper, with the consideration of link capacity, we present a sufficient and necessary condition that guarantees p-cycles for providing enough protection bandwidth. Based on this condition, we propose an effective solution to provide connections for dynamic requests with the property that each link used for a connection is protected by a p-cycle. Simulation results show that our dynamic p-cycle provisioning solution outperforms the traditional path protection scheme.

Most existing research regarding sensor network security considers homogenous sensor networks. To achieve better security and performance, we adopt a heterogeneous sensor network (HSN) model that consists of physically different types of sensor nodes. In this paper, we present an efficient key distribution scheme for HSNs, which takes advantage of powerful high-end sensor nodes. The scheme establishes a secure communication topology in the network in an efficient and secure manner. We show that the scheme has smaller memory requirements than a popular key distribution scheme and it is more resilient against the node compromise attack.

This paper presents an aspect-oriented approach to integrated elicitation of functional and security requirements based on use case-driven development. We identify security threats with respect to use cases and adopt threat mitigations for preventing or reducing security threats. To capture crosscutting nature of threats and mitigations, we specify them as aspects that encapsulate pointcuts and advice. A threat (mitigation) pointcut is a collection of join points in use cases at which the use cases are threatened (secured); whereas threat/mitigation advice describes how a threat can become an attack (can be mitigated). Eliciting threats and mitigations as aspects provides a structured way for separating functional and security concerns

Sensor nodes are unreliable small devices with limited energy supply, and sensors may run out of power or fail over time. A sensor network should have self-healing capability to handle coverage holes, routing voids and disconnections caused by random sensor locations and sensor failures. To provide self-healing capabilities in sensor networks while keeping the cost low, we propose to deploy a small number of mobile sensors in addition to a large number of static sensors. A mobile sensor may receive multiple requests from different areas. In this paper, we present a distributed decision making algorithm based on fuzzy logic. The distributed algorithm has low computation requirement and is robust to incomplete information. Our extensive simulations demonstrate the self-healing capabilities provided by mobile sensors, and the good performance of the distributed decision making algorithm.

Design-level vulnerabilities are a major source of security risks in software. To improve trustworthiness of software design, this paper presents a formal threat-driven approach, which explores explicit behaviors of security threats as the mediator between security goals and applications of security features. Security threats are potential attacks, i.e., misuses and anomalies that violate the security goals of systems' intended functions. Security threats suggest what, where, and how security features for threat mitigation should be applied. To specify the intended functions, security threats, and threat mitigations of a security design as a whole, we exploit aspect-oriented Petri nets as a unified formalism. Intended functions and security threats are modeled by Petri nets, whereas threat mitigations are modeled by Petri net-based aspects due to the incremental and crosscutting nature of security features. The unified formalism facilitates verifying correctness of security threats against intended functions and verifying absence of security threats from integrated functions and threat mitigations. As a result, our approach can make software design provably secured from anticipated security threats and, thus, reduce significant design-level vulnerabilities. We demonstrate our approach through a systematic case study on the threat-driven modeling and verification of a real-world shopping cart application.

This paper presents a formal approach to threat-driven modeling and verification of secure software using aspect-oriented Petri nets. Based on the behavior model of intended functions, we identify and build formal models of security threats, which are potential misuses and anomalies of the intended functions that violate security goals. Threat mitigations are further modeled in an aspect-oriented paradigm. Taking Petri nets as a formal basis for modeling behaviors, threats, and mitigations as a whole, we verify properties of and consistency between behaviors and threats, and absence of identified threats from the integrated model of functions and threat mitigations. This makes it possible to achieve a design that is provably resistant to the anticipated threats and thus reduce significant design-level vulnerabilities.

We present a model consisting of a swarm of unmanned, autonomous flying munitions to conduct a synchronized multi-point attack on a target. The unpiloted air vehicles (UAV) lack global communication or extensive battlefield intelligence, instead, relying on passive short-range sensors and simple, inter-agent communication. The multi-point synchronized attack is successfully demonstrated in a simulated battlefield environment. The simulation results indicate that the reactive, synchronized, multi-point attack is effective, robust and scalable. It is especially well suited for numerous, small, inexpensive, and expendable UAV.

In the vehicle routing problem (VRP), there is a collection of stops with known demands for service, and a fleet of vehicles with known capacities available to serve the stops. The problem is to assign the stops to vehicles, and specify routing sequences for each vehicle so that total distance is minimized. Many heuristic algorithms for the VRP have been developed over the last 25 years. Given a particular vehicle routing problem instance, we address here the issue of selecting which heuristic algorithm to apply to the problem. A modular system of neural networks is the knowledge base that is used to make the selection. Three types of multiple-layer neural networks are involved, and all are trained with the back-propagation learning paradigm. After training, the neural network system was applied to a collection of new problems not used in training. The system was very successful in identifying the optimal algorithm to apply to the new problems. We conclude that neural networks have considerable promise for use in vehicle routing model management systems. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.

In this paper a fully interactive software system(SAGIPIS), which carries out data analysis, parameter estimation and process generation is discussed.